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& Europe, Study GroupWill we look back at the last six months as the point when artificial intelligence broke through? The release of ChatGPT in late 2022 sparked a flurry of global headlines and debate. The dust had barely settled before the even more powerful GPT-4 was released in March 2023. The two tools represent a significant step forward in the emergence of AI, and they are a wake-up call for any organization – or individual – who doubted, or was oblivious to, the astonishing progress being made by tech developers. Past months have brought fresh urgency to the imperative for organizations to double down on digital transformation and engage in the process of building an AI-powered future.
Of course, AI and machine-learning have enormous potential. It’s easy to focus on the downsides: the potential to destroy once-lucrative business models, destroy jobs and widen social divisions. But these same technologies also have huge potential to improve human existence, helping to solve complex and previously intractable problems. This positive potential is the upside of AI, recognized by the authors of the open letter that urged a pause to development of AI more powerful than GPT-4. “Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable,” wrote the authors. “Let’s enjoy a long AI summer, not rush unprepared into a fall.”
The contradictions of AI are extreme. The quandaries that lie ahead will perhaps test leaders like no others in the modern era. And they are at the heart of the Focus articles in this issue of Dialogue, which takes stock of AI and the evolution of digital transformation more generally. What should be leaders’ next steps? Well, Ben Pring outlines six potential strategies in his AI survival guide (p16). Ryan McManus explains how AI drives speed and scale in unprecedented ways, and urges leaders to grasp the potential that lies in their organizational data (p20). Saša Pekec of the Fuqua School of Business provides a pertinent reminder
of the inherent limitations and biases of AI, and the value of human expertise and experience (p24). For organizations contemplating how best to use AI in their organizations, Mark McDonald reflects on the experiences of the last decade, observing that many leaders now perceive that the value they’ve created for customers through digital transformation has not been matched by increased value for their business. The prize now coming into view, he argues, is increased agency – the possibility for businesses of finding greater capacity for action to better determine their destiny, as change-makers not change-takers (p26).
Elsewhere, Maria Katsarou-Makin dissects the reality of modern teams, explaining why many attempts to change team behaviour fail, and what leaders can do to create the conditions for truly outstanding team performance (p44). Amy Bradley and Katherine Semler take a look at the prevalence of overwhelm and burnout, a real concern for many leaders in the wake of the pandemic (p48). Joe Perfetti shares the latest annual Duke Corporate Education financial cycle time rankings, and explains why capabilities are the key for organizational success (p60). And Marce Fernández takes issues with the orthodox view that leaders and organizations must move ever faster, arguing that a ‘middle way’ of thinking, allowing leaders space for reflection, is the right basis for making better decisions (p76).
As the AI revolution gathers pace, that is an idea that might have wider application. Enjoy the issue.
Patrick Woodman is editor of Dialogue
Past months have brought fresh urgency to the imperative to engage in building an AI-powered future
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55 Vivek Wadhwa on innovation The democratic world can triumph in tech if it works together. It’s time for a Nato for tech
56 Advantage, gamers Skills developed through gaming will give young leaders the edge in the future officeverse
16
Surviving AI Strategies for navigating a disrupted world
20
Atomic core How AI is accelerating change in the digital economy
24
The human touch For all AI’s power, it cannot replace human expertise and judgement
26
Lead with agency Taking back control in the post-digital world
30
Digital wealth Technology is creating new types of assets
34 Leading projects How will project management change in an AI-powered world?
80
News nation France wrestles with retirement reforms
82 Conference report Lead with Her
84
Big ideas Perry Timms on nested circles
86
Last word Sanyin Siang on invisible roles
MARKETING
59 Phil Young on finance Can AI mitigate human financial frailties? 60 FCT winners 2022 The latest rankings underscore the crucial importance of developing corporate capabilities
64 The bottom line When losses mean growth: it’s time for a financial reporting rethink
66
The money problem Financial services should put happiness at the heart of how they serve customers
69
Giles Lury on marketing Don’t be too hasty to ditch the old ways of doing things in the era of digital technology
70
Data downturn Retailers must focus on customers rather than cost-cutting when weathering the current downturn
72
Digital insight Data is no substitute for the creative state of mind that leads to great marketing insight
75
Rita Gunther McGrath on strategy Wasted time is not inevitable. Leaders need to free their people from the curse of useless work
76
decision
Mind your speed Leaders are under pressure to move at ever-greater pace. But a middle way of thinking could yield better decisions
When making complex decisions, a short period of unconscious thinking leads to a better
Marce Fernández, p76
Traditional banks have a future. But they must accept that they have a different future. If bank leaders fail to make radical changes, they will perish. The time for those changes is now.
In the face of fast-moving, low-cost disruptors, bank leaders must acquire the ability to balance the short- and longterm, to reconcile equally the need to exploit existing markets and experiment with new ones – banks and their leaders must become ambidextrous.
An IT futurist, author and professional thought leader on the cutting edge of business and technology, Pring is vice president at Gartner for General Managers. Named as one of the 30 leading management thinkers by Thinkers50 and one of the 10 leading influencers on the future of work by Onalytica, Pring is co-author of award-winning books including 2021's Monster: Taming the Machines that Rules our Lives, Jobs, and Future Focus p16
Distinguished vice president and fellow at Gartner Research, McDonald has more than 20 years’ experience working at the crossroads of business and technology. He is the author of several books and articles including The Digital Edge (Gartner Press) and The Social Organization (Harvard Business School Press). A well-regarded technology blogger, Mark received his PhD in technology policy management from TU Delft. Focus p26
A digital economist and university educator focusing on blockchain, the metaverse and Web 3.0. Yu is executive director of the Metaverse Industry Committee of the China Mobile Communications Federation, and has won industry awards including the Metaverse Chinese Leadership Award. He is co-author of The Rise of the Metaverse: How Web3 is Enabling Our New Digital World. Focus p30
An expert in corporate finance and strategy, Perfetti is an innovation fellow with Duke Corporate Education and teaches equity analysis at MBA and undergraduate level at the University of Maryland. He has delivered executive training to leading corporations including Google, Merck, Raytheon, McKinsey, Nokia, CVS, Union Pacific, and Citibank. Finance p60
Co-author with Dr Jianing Yu of The Rise of the Metaverse: How Web3 is Enabling Our New Digital World (LID Publishing, 2023), Sun is the founding partner of C² Ventures, an early-stage Web3 investment firm. She was previously heading of listing and blockchain investments at Huobi Global, and worked at Boston Consulting Group, Deloitte Consulting and Ernst & Young. Focus p30
A thought leader, author, practitioner, and professor in projects and strategy, recognized by Thinkers50, NietoRodriguez is the creator of concepts such as the Project Manifesto. His co-author, Ricardo Viana Vargas, is former director for infrastructure and project management at the UN. Focus p34
Organizations have struggled to create value through their digital investments, but they can still seize the prize of increased agency, writes Mark McDonald (p26). But beware AI’s biases, warns Saša Pekec (p24): leaders’ critical thinking skills are more important than ever.
The emergence of generative AI tools has injected fresh urgency to the discussion about how leaders can guide their businesses through digital transformation. Ben Pring outlines six potential strategies for thriving in this brave new world in his AI survival guide (p16), while Ryan McManus urges leaders not to approach data as a minefield full of dangers to be navigated, but as a key strategic asset to be maximized (p20).
Need to take team performance to the next level? Start by understanding that teams are dynamic systems, says Maria KatsarouMakin (p44). Harness the power of purpose, like Udit Batra at Waters (p52). And find the invisible roles, urges Sanyin Siang (p86).
As the latest Duke Corporate Education Financial Cycle Time rankings underline, speed is critical to business success – when paired with capability (p60). But speed carries risks too. One is personal. Increasing numbers of employees shows signs of overwhelm and burnout: how can leaders reduce the risks? (p48) Undue haste can also lead to sub-optimal decisions. Could leaders adopt a ‘middle way’ of thinking to improve their decision-making? (p76)
Gender equity must be integral to all parts of organizations
Where is the W in ESG? That was the question posed by a high-powered panel at Duke Corporate Education’s ‘Lead with Her’ event this spring. The W – as the name of the conference suggests – stands for women.
That there is a moral and social case for gender equity is not in question. Good business leaders would agree that inequitable companies are, like inequitable societies, undesirable. But should that mean that the W is encapsulated entirely by the S, considered exclusively part of the societal element of ESG? The evidence suggests otherwise.
I was struck by the comments of panellist Pauline Miller, chief equity officer at marketing giant Dentsu. “If we hold women back, we are holding back society and progress,” she said. “But we must recognize that it is not just one lens, not one single dimension – we must be much broader. The W is very powerful in the S of ESG. But it’s not the only place where we need to consider it.”
The arguments for a broader treatment of the W are many. The E – environment – has a strong case. Women constitute 70% of the world’s poor, according to the United Nations. Those in poverty rely more heavily on natural resources and are more likely than other groups to be exposed to extreme conditions resulting from climate change.
Businesses will increasingly be charged with finding solutions to global problems like global warming. Those solutions are more likely to emerge if the groups hit hardest by them are represented among senior decision-makers. “Women are disproportionately going to be affected by climate change,” Anna Stanley-Radière, director for climate transparency, World Business Council for Sustainable Development, told Lead with Her. “Women need to be part of the solution at all different levels – but we must also ensure that the leaders at the top that are making these decisions are much more female.”
EducationStanley-Radière’s testimony is therefore as much about governance as it is environment. Experience shows that businesses, charities – even governments – follow different paths if those at the levers of power are feminized. A female-run company, or one run by a mixed group, is likely to behave differently to a male-administered organization.
“The W is a business imperative,” said Stephanie Werner-Dietz, executive vice president and head of human resources at ArcelorMittal. “The research shows us that the more diverse teams we have and the more gender justice, the better the results. Women bring to the table different ways of thinking. There are some female characteristics –such as being more attuned to social responsibility – which mean questions are raised that would otherwise not be.”
It is crucial that the W pervades all elements of ESG, integral to all parts of the business. Siloing gender equity and female advancement in the S, as a purely social concern, is a narrow-minded mistake.
Brian Tippens, senior vice president and chief social impact officer at Cisco, has it right. “It’s important for ESG leaders to be core business leaders across the enterprise,” he told delegates at Lead with Her. “They must be able to lead up to their leadership, to the board of directors; to lead down, to all the employees in the enterprise – but also to be a trusted partner to other leaders in the business.”
The W isn’t yet everywhere. But with an integrated approach to ESG, we can make it so.
A female-run company, or one run by a mixed group, is likely to behave differently to a maleadministered one
DR MARIA KATSAROU-MAKIN is the founder of the Leadership Psychology Institute and has over 20 years of experience in organizational development and executive coaching. She is a Chartered Psychologist and has done extensive work and research in team dynamics.
RICHARD BOYATZIS
PhD, Distinguished University Professor, Case Western Reserve University, and co-author of bestselling Primal Leadership
Print edition: ISBN 978-1-912555-75-8 | E-book edition: ISBN 978-1-911671-26-8 Published by LID Publishing (www.lidpublishing.com)
“…an intellectual tour de force through many of the primary sources, theories and research about effective teams…[the author] even sensitively examines the dark side of teams and frequent pathology. It is guaranteed to spark ideas about how to lead and infect your teams”
Way back in the 1970s, the world’s biggest photographic company invented the future, then buried it. Kodak was then a giant, a global megabrand that was the pride of America. Its Japanese rival, Fujifilm, was named after a mountain but was a mere hillock in the shadow of its transpacific opponent.
Kodak engineer Steve Sasson brought his world-changing invention – the selfcontained digital camera – to Kodak’s executives as early as 1975. But the firm made most of its income from sales of film. Sasson recalls their reaction to his disruptive innovation: “It was filmless photography,” he told the New York Times “So, management’s reaction was, ‘that’s cute – but don’t tell anyone about it.’”
The rest is history. Kodak’s raison d’être collapsed with the advent of the digital camera – a device that Kodak had itself pioneered, but deliberately ignored, fearing it would destroy its existing revenues. By the late 1980s, rivals like Fujifilm realized the dream of digital photography themselves. Kodak’s core business was disrupted, then destroyed, when Sasson had given it the opportunity to do likewise to its competitors.
One of the greatest commercial mistakes in US history has lessons for leaders today. Kodak wanted to maximize returns from its current competency at the expense of developing a future capability. By denying its destiny, it came to jeopardize it.
The new hybrid leadership avoids such a fate. It is possible – indeed necessary – to maximize our current skills
while building new abilities that ready ourselves for where the world is going. This challenge for leaders – reconciling short-term exploitation with long-term exploration – is the new incarnation of hybrid. Leaders must prepare themselves for the next battle.
Shortly before, throughout, and briefly after the pandemic, hybridity focused on location. It was the result of a clash of cultures, each with persuasive arguments: “work isn’t a place you go, it’s a thing you do” vs “innovation comes from those water cooler moments
that happen only in the office”. Many companies have brokered a kind of peace: much work can be done, often more productively, at home; but there is value in colocation too – great ideas often emerge from in-person interaction. Probably, a targeted mix is best, hence hybrid leadership.
But that was then and this is now. The future of work is hybrid, but hybridity is no longer about place. Where once physical and remote were the poles that leaders had to resolve, now the opposites that must be reconciled are core vs edge; short-term vs long-term; exploitation vs exploration. Historically, leaders were measured on two metrics – speed (how fast could you do the task) and horsepower (raw intellect, either technical or formal). These are no longer sufficient. Today’s organizations are assessing leaders on a third scale: that of learning adaptability and agility.
“It is often from the margins and playful spaces that innovative ideas emerge,” says David Gann, pro-vicechancellor, development and external affairs, at the University of Oxford. “This happened with microwaves, Post-it notes and even Viagra... But it is an organization’s leadership that truly nurtures or stifles innovation – even when it brings new risks.”
Agility means being able to operate ambidextrously and handle those risks. Leaders must ensure that their organizations remain stable: core business provides a baseload revenue to allow innovation at the edge. Yet they must also prevent the demands of the present function from diminishing the exploration of the future. Nobody said the new hybrid leadership would be easy, but it is nevertheless essential. The alternative is denial, disruption and eventual destruction.
Today’s hybrid leaders are untroubled by place. Rather, their dimension is time: learn from the past; maximize the present; explore the future.
Vishal Patel is president of global markets at Duke Corporate EducationNobody said the new hybrid leadership would be easy, but it is nevertheless essential
The emergence of easily-accessible generative AI tools has sent shockwaves through business. It has made real the astonishing progress of digital technology, and brought home the potential impact on business models and wealth creation. Digital transformation has shifted up a gear.
Yet many organizations are still struggling to get traction on their own digital transformations. In this issue of Dialogue, we take a closer look at the implications of the rapidly-changing technological landscape for leaders. We consider the potential strategies for organizations to thrive in the new era. We look at what businesses need to do to improve how they manage data, the lifeblood of AI. We ask, what are the pitfalls of AI and the biases that leaders need to consider? How will AI change project management? We explore how organizations can secure greater agency in the wake of digital transformation. And we look at how the very nature of wealth is being changed.
Articles
16 The AI survival guide
20 The atomic unit of strategy
24 Think, critically
26 Leading with agency
30 The evolution of digital wealth
34 Leading projects in an AI-powered world
After ChatGPT and GPT-4, the disruptive potential of artificial intelligence is impossible to ignore. Here’s how to navigate the changes now under way
Writing Ben PringThe future is here and about to get much more evenly distributed. After years in the laboratory and on the movie lot, artificial intelligence is real, and ready for its close-up.
Unless you’ve been living under a rock, you have heard of ChatGPT and GPT-4. You have probably played around with it. Your kids certainly have. So, what now? Anybody can see that AI has become incredibly powerful. To imagine that it does not change everything is simply a failure of imagination. But how, precisely, is it going to impact our work, our lives, our world? And how can it be leveraged for positive outcomes?
We are on the cusp of a moment of momentous change. A period which will fill the history books – or perhaps the history downloads or chip implants – of the future. A period in which your future is unwritten but depends on what you, with your corporate and personal hats on, do next.
In 2017, I co-authored a book with Malcolm Frank and Paul Roehrig, called What to Do When Machines Do Everything, which set out a corporate playbook for executives looking to leverage the incredible power of the nascent machine-learning
techniques that were then just emerging. Now, six years later, with technology that has developed and is maturing fast, I o er this AI survival guide – a framework made up of six steps to help you and your organization (and your loved ones) think about how to navigate terra digitalis incognita
The territory is new and unknown and there are no published maps available, so you must create your own. Take a tip from the French in the Seven Years’ War and hire or commission scouts to head out into the woods and find what is there – what natural resources, what predators, what potential points of fortification. In 2023, that means establishing a handpicked task force of some of your best in-house technologists to explore the raft of AI technologies and products that are emerging daily (hourly, in fact), speaking with analysts and academics who have had early access to said tools, and contracting with consultants who understand your business processes and can align them against new relevant tools. It means feverishly reading everything from
It is incumbent upon you to understand what is going on with AI. Now. Not next quarter. Now.
the MIT Technology Review to the subreddit on machine learning (reddit.com/r/sml). Lastly, and most importantly, it means walking the via regia of AI, going to the kings of this new world. Leaders should be knocking on the door – metaphorically, or even better, literally – of 3180 18th Street, San Francisco, California, to understand what OpenAI can do for them.
It is incumbent upon you to understand what is going on with AI. Now. Not next quarter. Now. Without a map, you are – and have – lost.
“Whoever becomes the leader in this sphere will rule the world.” Vladimir Putin’s ominous 2017 words, spoken in the context of geopolitical turmoil, are –uncomfortable as this may be – entirely applicable as a description of the competitive AI battles that exist between commercial organizations. Whichever company becomes the leader in this sphere will rule the world.
However, while a small number of companies will undoubtedly have a leadership position in AI as it continues to develop (Google over recent years, Microsoft potentially in the next few), antimonopoly competition laws will likely prevent any one company from completely controlling AI. Rather, several companies will be dominant players. If it is at all possible, your company should be one of them. In every previous phase of technological development, the developers of the primo tool of the age have stood as Colossi of all they survey; Whitney and the cotton gin, Watt and the steam engine, Stephenson and the locomotive, Mercedes, Benz, Ford and the automobile, Gates and the graphical user interface Now.
The surest way to be a master of the coming universe is to be a developer of AI technology – be it directly yourselves, in partnership with others, in consortia, or through investment funding. The development of large language models (LLMs), the heart of AI, will continue to be the purview of a small number of very specialized software engineering firms for the foreseeable future, but the integration and customization of those LLMs with other component technologies and processes – ones your company may have expertise in –will allow your technology to be a component of the broader, more complex ‘engine’ that AI will become.
This possibility will be open to many companies in many di erent technology areas (including user interfaces, digital avatars, integration, hosting, managed services) and many di erent business domain areas (including AI for wealth management, for medical diagnostics,
AI has leapt from developers’ labs and the realm of sci- into the real world at breathtaking pace. ChatGPT and GPT-4 were the breakthrough technologies of early 2023, but even more powerful AIs will quickly follow. To imagine that AI will not change everything is a failure of imagination.
Start by Mapping the unfamiliar landscape. Explore routes for Developing the technology, and Mastering its use, to seize competitive advantage. Next, consider Zagging where others are zigging; assess the potential for Stopping AI, remembering that it remains within our gi to do so; or, if all else fails, think about Hiding.
for education, and so on.) The closer your organization can get to the source of proprietary leading-edge AI creation, the better.
To paraphrase Kevin Kelly, the founding editor of Wired, the future of your work is “X + AI,” where ‘X’ is whatever it is that you do, and ‘AI’ is, well, AI. That simple motto captures a profound insight – that adding AI to your job as a coder, a doctor, a teacher, an executive, a chief executive – and to your product or service, as a car manufacturer, a bank, an insurance company, an online gaming company – is the route to the next performance threshold available to you.
In a previous Dialogue article called ‘The Myth of Bad Robots’ (Dialogue, Q3 2018) I outlined how managing greater and greater density and complexity of data at faster and faster speeds was the key task ahead. Now, mastering that key task is mandatory, not elective. You personally, and your organization corporately, may not develop AI tools, technologies, or techniques yourselves, but deploying and optimizing them within the context of whatever it is you do is set to be crucial in the competitive game you are playing. The legal firm that can process huge volumes of information and provide legal insights faster than its competitors will become the go-to legal firm. The retailer that can deduce fickle fashion sentiment and adapt to market demand faster than its competitors will become the next sensation.
As has been frequently noted, AI itself will not destroy jobs and organizations, but people and organizations using AI will destroy the jobs of people and organizations not using AI.
Having been an AI enthusiast and evangelist for many years (my undergraduate dissertation was on ‘The Philosophy of AI’ – in 1983!) it is exciting to see AI finally break through into mainstream consciousness. But having been a Marxist contrarian – of the Groucho variety, not wanting to belong to a club that would have me as a member – for even longer, the explosion of interest sets my non-conformist alarm bells ringing. I am reminded of the Oscar Wilde quote: “Whenever people agree with me, I always feel I must be wrong.”
If everyone now thinks that the future is X + AI, it is probably not. The career and/or corporate manifestation of this impulse is to hedge against AI: to develop a job, product or service that is explicitly designed around what AI cannot do, currently or in the forecastable future. In essence, to zag when everyone else is zigging.
For instance, a hotel (and its employees) could double down on o ering non-technology mediated ‘experiences,’ perhaps including ‘digital detoxes’. A department store could double down on nontechnology mediated human-delivered customer service. A financial advisor could double down on the quality of its non-technology mediated advice and assurance.
Though AI will undoubtedly di use into more and more aspects of our work and lives over the next few years, we should not overlook that the AI software market – estimated to be worth $135 billion by 2025 – is a relatively small subset of the $4.5 trillion global IT industry, which itself is a subset of the entire $100 trillion global economy. There is still a lot of opportunity outside of the tech sphere, no matter how fast tech generically, and AI specifically, develop in the next few years.
There is something of a ‘manifest destiny’ quality to AI – that it is a natural, irreversible dynamic set to unfold no matter what any of us think or feel about it, individually or collectively. But the truth is that AI, as a human creation, is still subject to human control. And within this truth is the reality that though AI has its proponents, it also has its detractors – critics who, for a variety of reasons, believe that we should pause, stop or, at the very least, legislate how AI is developed and deployed. Sometimes these reasons are philosophical; the fear that AI could potentially overwhelm human control and lead us towards the ending of 2001: A Space Odyssey. (“I’m sorry, Dave. I’m afraid I can’t do that.”) Sometimes they are geopolitical;
see Step Two, and the thoughts of President Putin. And sometimes they are commercial; the concern that a dominant technology could create a dominant vendor with an unsurpassable monopoly position.
As I type, the campaign for technological disarmament – call it CTD – has broken into public view. The Italian government has banned ChatGPT and a raft of senior technologists, academics, politicians, and investors, including Elon Musk, Steve Wozniak and Andrew Yang, have released an open letter calling for a moratorium on AI development, stating that the challenges AI raises to humans “must not be delegated to unelected tech leaders”. Perhaps you or your organization has a reason to stop AI development. Aligning with this nascent campaign may strike you as a Luddite move, but in fact it will be entirely rational. Human agency is still our most profound quality. The power to shape the future is, and should be, still in human hands.
Sun Tzu’s advice on dealing with a stronger opponent was typically pithy: “If he is in superior strength, evade him.” For many organizations and people, the only real option will be to keep as far away from AI as possible. Stay small, stay analogue, stay o the grid, stay local, stay home, stay human. Though this thought may seem heretical from someone who has made a living in the tech industry for 40 years, it is born from the knowledge that many organizations and people simply will not be able to compete against machines, and resistance will be futile. Increasingly in my job I have the sense that I am a bad robot, and GPT-5, 6 or 7 will be able to do what I do, better than I do. Many people and companies will be able to leverage AI to augment their work – see Steps Two and Three – and reach a new promised land of productivity, fulfillment and wealth. But many will not.
A clear head will be required as to understanding the possibilities to ‘head out west’, or to stay put and make the best of where you are now. That map is going to come in handy.
Ben
The views expressed are those of the author and do not represent any official position held by Gartner Inc
As President Eisenhower once said, “Plans are useless, but planning is indispensable.” This is always good advice, but particularly at moments of existential change. Such is the moment now.
To survive – let alone thrive – in the age of AI will require agility, courage and good old fashioned human intelligence. Much is at stake. Bon chance, and bon voyage – and take this AI survival guide with you.
Pring is a research vice president at GartnerHuman agency is still our most profound quality. The power to shape the future is still in human hands
Artificial intelligence will accelerate change in every dimension of the digital economy
Writing Ryan McManusFor over ten years we have worked with boards, investors and senior leadership across corporations, governments and the military to help them understand the growing urgency of digital transformation and the need to rethink business models, investments and culture. Every discussion included the coming rise of AI, which was always predictable as a result of the explosive growth in data volumes and cloud-based computing power, and how AI would re-platform every element of the digital economy which preceded it. Early examples, such as Google’s Sidewalk Labs, demonstrated its potential several years ago.
Still, the emergence of generative AI, arriving with unprecedented speed, has caught many leaders by surprise. Leaders need to understand how AI will change their businesses, and grasp this change much faster than many did in the previous era of digital transformation. Speed and scale win in the digital economy, and AI drives both at supersonic levels. It’s very simple: AI enables organizations to deliver what was previously impossible. How should leaders respond? And what data foundations do businesses need to prioritize to stay relevant?
The golden age of AI
AI is already mission-critical in many sectors, and has also reached the point where it can startle. That is reflected in an accelerated uptake. Netflix, which launched in 1999, took 3.5 years to achieve one million users. Instagram, launched in 2010, took 2.5 months. When ChatGPT launched in late 2022, it took just five days to hit a million users –reaching 100 million within two months.
The rapid success of ChatGPT has highlighted the democratization of inexpensive access to advanced digital capabilities. While the content and image generation capabilities of ChatGPT, Dall-E and other companies are impressive, generative AI’s impact is rapidly expanding across sectors.
Take, for example, the July 2022 announcement by AlphaFold that its AI capability had solved
The emergence of generative AI has caught many leaders by surprise
the previously unsolvable problem of predicting protein structures. This historic accomplishment enabled researchers at the University of Toronto and Insilico Medicine, using the Pharma.AI platform, to create a new solution for the most common form of liver cancer, and to predict the patient survival rate. Time to solution? Only 30 days. Science went from a highly-complex, insolvable problem to new solutions in a matter of weeks.
AI enables teams to do things which were previously thought to be impossible. As similar examples rapidly proliferate across sectors, the challenge for leaders is to think differently about AI-driven competition, create a shared sense of urgency, and create new structures which allow their organization to keep pace.
Algorithms hold little value without significant data sets to power them. The lifeblood of AI is data. Yet it is often treated as tactical, rather than as a fundamental driver of competitive advantage and new capabilities. MIT Technology Review Insights and Databricks research shows that only 13% of companies are utilizing their data properly. Why are leaders ignoring this critical element of digital transformation? Gartner has identified the four levels of capability that data teams have typically focused on:
1 Descriptive What happened?
2 Diagnostic Why did this happen?
3 Predictive What might happen next?
4 Prescriptive What should we do next?
But a fifth level, enabled by generative AI, is by far the most exciting and transformative. This level asks: what can we build?
This level is only attainable with the most advanced data capabilities: organizations still struggling with rudimentary data management risk cannot compete at this level. The companies pioneering Level 5 are prospering: the median pre-money valuation of these generative AI startups has reached $90 million in 2023, up from $42.5 million in 2022, according to Pitchbook.
Even Level 1 data capabilities can upend entire industries when applied at scale. In the music industry, for example, the identification of emerging artists has changed forever as the amount of data has increased. Vasja Veber, co-founder of Viberate, the music analytics platform, says: “Nowadays the first step of finding hot artists is done with analytics, which wasn’t possible before streaming media and social media. We have 700,000 artists with verified profiles and can check who are emerging as the hottest artists.”
Traditionally, only major record labels offered advances to artists, based on their evaluations of the artists’ sales potential. In return, they owned the rights to the artists’ catalogues. But with the influx of data into the industry, artists can now directly calculate the potential value of their music (the predictive level), and either self-finance or take loans based on their expected value. Companies like Concord Music, Primary Wave and Hipgnosis have even used analytics to spend billions on acquiring song catalogues, using data to determine the future value of the music.
As a result, the economics of the music industry have been changed significantly. “Before streaming, artists were monetizing by selling mechanical media,” says Veber. “Once the CD was bought, that was the only revenue the artist received. With streaming, artists make money with every play, so the lifespan of a track can now be unlimited, revenue can be unlimited. It has enabled the whole industry. It’s basically fintech meets music,” he adds. As data enabled predictive capabilities, record labels lost much of their traditional advantage.
Tesla is also increasingly heralded – not only by Elon Musk, but by investors – for its AI leadership. Tesla captures an astronomical amount of data from its fleet of electric vehicles, its energy businesses, and its advanced robotics manufacturing processes. It captures so much data that it has its own AI chips and software platform to manage its data operations. This allows Tesla to develop AI solutions which may eventually be sold as a service across manufacturing, autonomous transport, and even personalized robot assistants –
Above Tesla captures an astronomical amount of data Left ChatGPT has highligted the democratization of access to advanced digital capabilities
rewriting business models across multiple sectors. Recognition of such growth opportunities gives Tesla a market cap multiple times larger than its competitors.
Explicitly valuing data allows leaders to highlight the importance of this foundational element of digital transformation to their organizations. David Bach, the chief executive and founder of Optios, the AI-powered neuro optimization company, is working to create the world’s largest database of brain data. “Data aggregation, management and optimization becomes the primary source of competitive advantage,” he explains. If you get it right, the value of data instantly soars. “Lots of companies have spent tons of money and gotten zero value. It’s because having data doesn’t do you any good, unless you figure out how to garner a competitive advantage from it,” says Bach.
Shelley Leibowitz, board director at Morgan Stanley, Elastic NV and several privately-held fintech and information security companies, also places an emphasis on using data correctly.
Speed and scale win in the digital economy, and AI drives both at supersonic levels
“It’s about ‘what do we do that’s unique for our customers? What do we do better than anyone else?’ And then, ‘what information do we have that supports those things?’” she says.
The amount of data has exploded in recent years, as has the advancement of the tools required to get the most out of that data. “The amount of data that’s available to us all today is thousands of times bigger than it was decades ago. Figuring out how to analyse it, and learn from it, gives you opportunities that were unimaginable years ago,” says Bach.
Speed is key. “If we used two-year-old or even six-month-old machine learning systems we would be so far behind the curve it would be embarrassing. If you are using technology from several years ago, you are exposing your company to a ton of risk,” he adds.
To address those concerns, companies – and specifically their chief executives – need to make data a priority at the highest level, says Bach. “Say that this is a huge strategic priority, and spend time talking to the people who work on it. Participate directly in sprint planning meetings and scrums. Have your data management leader report directly to the CEO, even if they are the least senior person in the company.”
The speed of progress in this field can seem daunting. Bach says the pace of change can “boggle the mind”, but it also comes with an upside. Keeping pace with emerging AI capabilities saves money. Bach describes the changing economics of AI: “Smaller dollars can yield larger benefits. Three or four people with current data can outperform a team of 50 with slightly older technology – AI has quintupled the productivity of software engineers.”
How do you ensure that your organization’s mindset is keeping pace with these changes?
Shelley Leibowitz says data and intelligence
“need to become actions”. Isolated data is irrelevant, and too often businesses are organized in a way that creates silos, meaning data can’t be orchestrated effectively.
It’s also important to treat data less as a minefield that needs to be navigated, and more as the underlying structure on which to build your business model. Many boards still view data as a risk to be managed, due to cybersecurity and other issues, but that’s a limited approach, says Leibowitz: “Very rarely is data something that is talked about in the boardroom from a strategy perspective.
“Leaders don’t talk enough about changing business models and allocation of capital to real investments in things like tech and data. It’s more
The seemingly sudden arrival of powerful generative AI tools such as ChatGPT and Dall-E has caught many leaders by surprise – but in fact, generative AI has been in the market for several years. Leaders need to adapt to AI far more quickly than many responded to previous phases of digital transformation.
In the digital economy, speed and scale are critical. AI drives both, to unprecedented levels. Generative AI also prompts leaders to ask a critical new question, “What can we build?” It demands advanced data capabilities, action to keep up with the speed of AI, and an AI strategy and mindset at the top of the business.
about strategy than risk management, a risk management context puts people in a defensive posture. What is the forum that is not just about risk management? It all comes back to capital allocation,” she adds.
Putting all this into practice can seem like a gargantuan task, but leaders can make an easy start by asking the following questions:
What is our level of data capability?
Which C-suite executive owns our data and AI strategy?
How do we value our data?
What risks and opportunities does AI pose to our value chain?
How do we know that we are not thinking too small?
How do we keep pace?
By addressing these areas, leaders can put data and AI at the heart of their business, but it does require an explicit strategic focus. “There are very few things that technology cannot do today,” explains Leibowitz. “The technology is all available, it’s about mindset and behaviour, and being able to envision something different which creates value for your markets.”
Ryan McManus is an educator for Duke Corporate Education, board director, and the founder and chief executive of TechtonicAI will continue to present significant challenges, not least around the ethics of its use, privacy and cybersecurity, all of which leaders will need to address. At the same time, leaders must begin to address the generational challenges represented by advancing data and AI capabilities. How does your strategy and leadership need to change when technology makes real what was previously considered impossible?
Treat data less as a minefield to be navigated, more as the underlying structure for your business model
AI has made jaw-dropping advances. But beware of its in-built biases and limitations – and remember the value of nuanced human expertise
Writing Saša PekecGenerative AI tools have burst into the public consciousness. For many of us, they have become part of our daily lives. OpenAI’s ChatGPT was reported to be the fastest-growing app ever, dwarfing the speed of adoption of most viral apps like TikTok.
The emergence of generative AI tools, which algorithmically generate new content by seamlessly aggregating, synthesizing and (re)presenting information in the desired tailored form, has underlined that we are, as yet, only scratching the surface of digital transformation processes. They will profoundly impact, not just businesses and our professional endeavours, but societal interactions and humanity as a whole.
It is widely accepted that generative AI has the potential to significantly improve many aspects of our lives. But it also creates enormous uncertainty due to the possibility of negative, even catastrophic, impacts on humanity. If we were to look for a comparison from history, the uncertainties of the still-nascent AI revolution are reminiscent of the gravity of uncertainties involved in the use (or misuse) of nuclear technology.
AI is poised to have critical and long-term impacts on our world – but these impacts are no longer distant or hypothetical. The unprecedented speed of adoption of generative AI means that uncertainty is here, and it is now. Leaders urgently need to assess both the opportunities and the threats created by the deployment of these powerful tools.
In the first instance, business has an opportunity to relegate a variety of mundane tasks to generative AI and other algorithmic tools. For example, AI has been used to draft tailored, personalized offers to customers. CarMax, the largest used-car retailer in the US, has reportedly been using AI to generate personalized listings for sellers, and utilizing OpenAI’s technology to aggregate relevant reviews and provide personalized recommendations to prospective buyers. Zillow, a real-estate platform, was providing algorithmically-generated binding offers to sellers as part of its house-flipping operation. However, the firm has since closed that operation, following heavy losses: it seems the accuracy of these valuations was insufficient to ensure the viability of the business model. Zillow’s example is a cautionary tale about the risks of overreliance on algorithmically-generated valuations.
Other examples are widespread. Chatbots are increasingly being used to handle mundane customer service tasks, slowly but surely making armies of customer-service agents obsolete: only if the issue mandates escalation does a human decision-maker enter the picture. In fact, most of us have relied on virtual assistants for some time. Apple’s Siri was launched back in 2010, and Amazon’s Alexa back in 2014. Today, the emerging generative AI tools massively enhance the usability of AI personal assistance, allowing it to go far beyond the well-established tasks of managing your personal schedule. Such tools can easily handle significant communication tasks, such as classifying the importance of communications and automatically generating and deploying personalized responses and messages. These AIgenerated messages could range from personalized performance-review videos from the chief executive, to hundreds or thousands of non-direct reports, to a personalized video message from a brand ambassador to targeted potential customers.
Another straightforward use case which gives a perspective on the usefulness and limitations of generative AI is in software development. Generative AI can readily provide blocks of code for executing well-defined known tasks, allowing developers to focus on creative aspects of developing software – which is important, because generative AI cannot reliably develop software for a novel use.
This is not unlike the breakthrough created by spreadsheet software four decades ago. It allowed decision-makers to organize and analyse large amounts of data with unprecedented ease, but it could not provide connections between digits in the spreadsheet and the real-life implications of decisions based on those numbers. Similarly, generative AI cannot provide solutions or answers
Generative AI is least reliable and brings least value precisely when decisions or actions hinge on information which is not clear-cut
for anything but what is already available, recorded, known, and/or solved in the datasets it has access to.
The risks of over-reliance
This underscores a principal shortcoming of (over) relying on generative AI. As an all-purpose tool, the outputs it generates are necessarily based on generic, context-independent rules. It is frequently impressive on topics that a user has no knowledge of, but appears disappointingly shallow – and often incorrect – when the user has even a shred of expertise or experience.
To verify this, experiment with one of the available tools. Ask its guidance on a topic from your area of expertise – ideally one that might not have commonly-known or obvious insights. Read what it produces carefully: an automated synthesis of the available (mis)information, with limited (or no) verification or quality assessment, is the prototypical setting for the ‘wisdom of crowds’ to fail. Generative AI can provide common wisdom on any topic in a palatable format, but it would be a fool’s errand to use it to replace one’s critical thinking or, worse, drive decisions.
Users also need to be aware that generative AI amplifies algorithmic bias by design. Its very purpose – creating content on demand – precludes the option of not creating content when there is uncertainty about the optimal output. Hence, if so prompted, generative AI tools will take a binary position, determined by how the available information is aggregated, regardless of nuance.
This further propagates the wisdom of (non-expert) crowds, based on prevailing (mis)information, and accentuates one of the critical pain-points and deficiencies of the digital revolution: the difficulty of determining the relevance, veracity or quality of available information. Just because content can be straightforwardly produced en masse does not mean the user can be confident that it is reliable.
Generative AI is least reliable, and brings least value, precisely when decisions or actions hinge on information which is not clear-cut.
If one’s value is based on an ability to complete mundane tasks, the technological progress currently exemplified by generative AI will probably bring that value to zero in the near future. On the other hand, the ability to make hard decisions and take actions that go against common wisdom – one of the distinguishing features of great leaders – is as important as ever. The ability to think critically, to parse relevant from irrelevant, to spot the importance of nuanced details, and so on, are even more valuable in a world in which humans are no match for machines’ ability to process vast amounts of data.
Alarmist perspectives on the catastrophic consequences of AI taking over might be premature, provided we respect the value of expertise and critical thinking. These are the advantages that humans still have over one-size-fitsall (mis)information aggregation algorithms.
As digital transformation matures, the ultimate prize for organizations is coming into view: increased agency
Writing Mark McDonaldDigital transformation has been high on the leadership agenda since 2011. Globally, companies are forecast to spend more than $3.4 trillion on digital transformation by 2026. These investments are on top of pandemicaccelerated investments. The cumulative effect is that many organizations are more advanced in their technology than in their business strategies or practices. This raises a crucial question: what are the leadership strategies for a digitally transformed business?
Customer centricity is synonymous with digital technology. The two fit each other perfectly: digital technologies enable deeper and more direct human interaction, and customer satisfaction is a driver of revenue. Customer centricity is a sound strategy when customers and companies benefit – yet this is not always the case in digital markets.
In different digital markets, digital solutions have created more customer value and utility than companies can recoup in revenue or margin. A 2017 McKinsey study projected that digital’s impact, creating new entrants and greater competition, would cause average revenues to decline by 12%,
with earnings declining 10% (McKinsey, ‘The Digital Effect’, 2017). By 2025, an estimated 90% of the Fortune 500 will become digital providers, according to the 2023 Global Interconnection Index produced by Equinix. Take three examples from different industries. In automobile insurance, data and digital solutions identify lower-risk drivers and charge them less. In the hospitality industry, holiday rental services have disrupted more than a quarter of the long-stay market. In media, account sharing for streaming services creates customer value while challenging company revenue.
Leaders can easily face a win/lose digital proposition. Customers win as companies meet their expectations; companies lose, unable to monetize that value. This appears to be the case in a 2022 survey of more than 1,300 companies, which reported that average-performing companies only achieved a median average of 31% of their revenue goals from digital transformation and 25% of their cost goals. The top digital performers in the study fared better, but still realized only 50% of revenue and 40% of cost goals (McKinsey, ‘Three new mandates for capturing a digital transformation’s full value’, 2022). Graphic 1 on page 28 illustrates these performance differences.
Leaders need to create new digital models and strategies that capture revenue, rather than raising the effectiveness of digital transformation projects. That starts with understanding the technical capabilities created by digital transformation.
Digital transformation involves systems and technologies that change an organization’s capabilities and competitiveness. Technically, a digitally transformed company has modernized API-based applications, highly available and consistent data, flexible infrastructures, greater insight, and new levels of operational automation.
The table on page 29 highlights changes in the pre-digital, digital transformation and potential post-digital world. As a firm digitally transforms, leaders gain the ability to know more, know faster and act at speed and scale in ways they could not in the past. It is not enough to use these capabilities to implement traditional strategy, planning and execution processes better, faster or cheaper. Leaders need to evolve the way they think about their business to achieve the best pairing with the capabilities of a digitally transformed company.
Leaders have choices in how they see and run the business. They can continue current themes related to customer centricity and utility. They could
Digital solutions have sometimes created more customer value and utility than companies can recoup in revenue or margin
become hyper-adaptive, agile and responsive to market changes. But these options do not resolve issues related to recapturing value, creating advantage and innovating business models. Addressing these issues requires that leaders increase their organization’s agency.
Agency is the degree to which you can control your actions and their consequences. Leaders have always had the ability to act, but in a fast paced, customer centric, highly competitive world, companies can easily become change takers, rather than change makers. Deciding which you will be is the first decision for post digital transformation leadership.
A change taker responds to and follows a trend. Companies with strategies that call for becoming the Amazon or Google of their industry are change takers, not change makers. Current customer centricity and experience strategies often lead to change-taking strategies. Change takers tend to give away utility in the face of customer expectations and competition. This places them on the back foot with customers and competitors.
Change makers have greater agency. They are more likely to incorporate their interests into strategies and set trends rather than follow them. Agency can apply internally, like Microsoft’s transformation to a cloud player, or externally, like Pfizer’s development of the Covid-19 vaccine. (Elon Musk and Twitter offer an example of agency run amok.) Firms with agency seem to ‘break the rules’ as much as they set new rules balancing customer, competitive, societal and company interests.
Agency is not the antithesis of customer centricity. It is centricity with direction. Apple has been a leader in this strategy, building products and services that customers do not ask for, but which create value for both. It is an example of a customer strategy based on advancing a direction for what you want customers to become, as Michael Schrage has put it.
Leaders’ need for agency increases as the purpose of a company broadens from shareholder to social responsibility. Effective strategies for realizing ESG, diversity, equity and inclusion, and other social goals requires taking deliberate actions. Worthington Industries, for instance, is a $2.1 billion manufacturing company that has exercised agency by incorporating internal and product innovations that go beyond meeting external standards and scores. Greater agency also gives leaders the power to break long-held practices. Accenture, the global consulting company, is one of several firms removing their college education requirement. Dropping such practices and requirements demonstrates agency.
Some simple questions can help test your company’s agency. Select a few decisions or strategies and ask yourself the following questions:
Why was this an issue?
What were our options?
Were we being proactive, or reactively following the market in our action?
Did these options advance our capacity to create value for customers, ourselves, or both?
The answers will tell you much about your current agency.
Agency accelerates digital transformation
Exercising greater agency is an important aspect of realizing value from digital transformation. The rate at which digital transformation fails to meet its original objectives ranges from 70% to 95%, according to a recent HBR article (Didier Bonnet, ‘3 Stages of a Successful Digital Transformation’, 2022).
As Kate Smaje has highlighted on the McKinsey Podcast, there is a common challenge associated with digital transformation. “What you typically see 12 months, 18 months, or two years into many transformations is this notion of, ‘I don’t feel I’m getting as much as I should be.’ The root cause of that is often a lack of alignment on where and how that value is going to be created.”
Actions for building greater agency
Leaders know that they need greater control of their direction and value creation in the face of continued digital commoditization, customer experience and accelerating competition. They build agency by leveraging the capabilities of post digital technology and leading the organization based on four key areas. 1
Knowing where they stand in terms of customers, competitors, and markets
New combinations of external, internal and AI
Companies with strategies that call for becoming the Amazon or Google of their industry are change takers, not change makers
Pre-digital
Markets Stable with well-defined industry boundaries and barriers
Customers Consuming available products and services
Competitive advantage
Based on size or clout, lowest cost, brand equity and control
Information Transaction data stored in disparate and isolated systems
Operations Oriented to adhere to business processes and rules
Technology Enabling business operations, cost and scale
Leadership approach Sales and operational efficiency, business process re-engineering
generated insight give them a perspective that goes beyond financial statements and budgets.
2 Having an ambition or direction This replaces mission and vision, which is often too high-level to drive operational choices. An ambition defines what the organization seeks to be in the future. Setting and communicating an ambition invites contributions and engagement.
Digital transformation
Experiential with customers setting expectations beyond industry boundaries
Demanding and expecting superior experiences
Based on customer experience, digital-first platforms
Customer and operational analytics that are brought together in data lakes
Creating customer experiences and service
Creating digital products, channels and platforms
Demand creation and customer centricity
Post digital transformation
Dynamic based on an accelerating pace of change and innovation
Realizing intentions across broader stakeholders
Based on fluidity and agility with advantage by acting with insight and technology
Insights created through AI with information from inside and outside the organization
Simultaneous innovation, optimization and agility
Innovating constantly with intelligence and productivity
Renewed agency to create and capture value
limiting performance and value creation. The leadership challenge is how to use these tools to their best effect. Leaders can use these capabilities to create a better version of their company without an evolution in their strategy, doubling down on change-taking approaches to customer centricity and internal efficiency. These leaders can expect to compete in markets characterized by increased pressures from new entrants, rising customer expectations and margin pressures.
3
Setting and updating the course of action at their own pace, based on the situation and ambition Composable and service-based applications facilitate constant changes and updates to realign and achieve the ambition.
4
Capturing a greater share of the customer value you create with experiences, products or services that create uniqueness through their insight and contextualization
Advances in generative AI (such as ChatGPT), automation technologies and experience technologies (augmented reality, virtual reality or the metaverse) need to create unique value, not just follow the leader.
Increasing company agency
Leaders have rightly welcomed the tools and abilities associated with digital. Knowing more with greater insight, coupled with the agility to act, removes many of the barriers and blind spots
Mark McDonald is distinguished vice president and fellow at Gartner Research, and author of several books on digital technology and business transformation
The opinions expressed in this article do not represent Gartner Research or its research positions
Alternatively, leaders who recognize that greater value comes from meaningful differentiation will use technology to increase their agency. These leaders use their heightened insight, flexibility and cost structures to act in ways that benefit customers, society and the company. Russell Reynolds estimates that 36% of leaders have these characteristics – a group they call Tech-First CEOs. The abilities attributed to such leaders stand as a description of what it takes to lead with agency.
Digital transformation is nearing maturity, with mixed results. At the same time, the limits of existing growth strategies are becoming apparent. The relationship between companies and their customers, their technology and their future, is being rebuilt. Will that relationship rest on responding to change, or on creating the agency to set and realize a distinctive direction? It is time for leaders to decide.
Agency is not the antithesis of customer centricity. It is centricity with direction
One of the most profound consequences of the fast-moving evolution of technology is its impact on the very nature of wealth. In the digital age, blockchain and smart contracts mean that digital assets can now be identified, circulated and secured in the metaverse. This opens up a new world of economic opportunities. Significant digital wealth can be accumulated through various new activities. Understanding the value, forms, attributes and allocation methods of digital wealth in the metaverse is crucial for leaders – and essential for identifying where old boundaries need to be broken to maximize future value.
The transition from the traditional internet to the metaverse represents a shift from an informationbased internet to a value-based internet. The core
change is the shift from an ‘open but untrusted’ internet to one that is ‘open and trusted’. The information-based internet relied on copy-pasting to facilitate the efficient exchange of information. However, the metaverse, blockchain-based internet, requires all information and data to be authenticated for ownership, enabling encrypted and secure information exchange. This represents a significant upgrade to the underlying value logic of the internet. Authenticated and encrypted information ensures that valuable data is not destroyed by copy-paste transmission.
As a result, the value of digital assets is undergoing a transformation in the metaverse, where data is becoming an essential asset. The emergence of blockchain technology offers a solution to the problem of data rights protection and assetization. By acting as an ownership confirmation machine, blockchain provides a low-cost data authentication service, enabling data transactions and value distribution through smart contracts, which are self-executing computer programs that automatically enforce the terms of a contract. This mechanism makes data a true asset for everyone, maximizing its value in the metaverse.
Axie Infinity – a blockchain game that became popular in Southeast Asia in 2020 – offers an example of data assetization in the metaverse. In this game, players are recognized as creators of the data assets they produce during the game, and their in-game items are authenticated on the blockchain, making them unique NFTs that players truly own.
Enabling users to truly own their data and benefit from its value is how blockchain technology provides a new solution to the problem of data rights protection and assetization. Governments and businesses must work together to develop a standardized system for managing data assets and protecting the privacy rights of users. Such a system would ensure that the metaverse can fully realize its potential as a new economic system, creating a better society where data is used for the benefit of all.
In 1997, financier Robert Greer published a paper titled, ‘What is an Asset Class, Anyway?’ in which he divided all assets into three classes: capital assets, consumable/transformable (C/T) assets, and stock of value (SOV) assets.
It is worth noting that a specific asset can have multiple attributes. For example, the main attribute of gold is its SOV asset characteristic, but it is also used in industry, for example as a raw material in the manufacturing of semiconductor devices. That means gold also has the attributes of a C/T asset. Or take real estate: it can generate cash-
The value of digital assets is undergoing a transformation in the metaverse
flow income when it is used for rental, giving it the attributes of capital assets – but at the same time, it is scarce, restricted by land supply, so it also has the attributes of an SOV asset.
Most assets only have one or two such attributes. However, some digital assets based in the metaverse may have all three attributes, forming a ‘super asset’ spanning the categories.
ETH, the token of Ethereum, is a prime example. First, the ETH has certain characteristics of C/T assets, like oil and natural gas. Following a 2021 upgrade, for example, a small amount of ETH is paid by users as part of handling fees and then ‘burned’ – destroyed and removed from circulation. Usage demand has also become a key factor – the greater the demand, the lower the circulation, which affects the value of the entire system.
Second, there are similarities to capital assets. When Ethereum upgraded from ‘proof-of-work’ (PoW) to a ‘proof-of-stake’ (PoS) validation system – a much more energy-efficient and cost-effective technology – holders were able to pledge ETH to the system’s betterment efforts, receiving digital asset rewards in return. In that way, ETH can bring a form of cash flow to its owners.
Third, there are similarities to SOV assets. Following the switch to the PoS mechanism, the annual ETH supply growth rate (like an inflation rate) may gradually decrease, and could even become negative, which would amount to deflation. Moreover, many decentralized finance (DeFi) platforms support ETH being locked in smart contracts as collateral to lend other digital assets or issue new ones as reserves, which shows that ETH has the function of asset derivation. In scenarios such as NFT trading, the ETH is
the main medium and it can be circulated on multiple blockchains through cross-chain bridges. In that respect, it has the attributes of a ‘universal equivalent.’ This is something like the position of gold in the world economy, which aligns with the definition of an SOV asset.
The emergence of Ethereum’s super asset marks a pivotal moment in the evolution of assets in the metaverse and signals the shift in value migration. Leaders should pay close attention to the distinct attributes and potential of diverse asset categories, as well as the transformative impact they can have on business. The rise of these assets opens up exciting possibilities for entrepreneurs to leverage new business models and create new types of wealth.
In the metaverse, the symbiotic relationship between content creators (that is, data contributors) and internet platforms is one of two-way empowerment. As the internet platform economy continues to develop, data contributors are becoming increasingly prevalent, and their numbers are growing. These contributors serve as critical nodes in the platform network and are responsible for creating the key value of the platform. However, they are often faced with limitations, including passive acceptance of platform rules, exclusion from platform governance, and inadequate participation in platform value distribution. Moreover, the profits they generate are increasingly absorbed by the platform.
While this conflict may appear to be a distribution issue, it is, in fact, a problem of governance, ownership and organizational structure. Such contradictions are commonplace in the era of the internet platform economy. The governance, distribution and organizational mechanisms of internet platforms do not align perfectly with their value-creation logic. Value creators are not being adequately rewarded. This is primarily due to the fact that while many internet companies are operating under a platform economy model, their organizational structure remains rooted in traditional company systems, which prioritize shareholder interests and rely heavily on capital. In this context, capital investment plays a decisive role in a company’s development and is often the key determinant of success.
However, this approach is no longer relevant in the digital age, where the source of value creation has shifted. In the platform economy era, success is the result of the collective efforts of all participants, including capital, entrepreneurs, employees and data contributors, who together
The emergence of Ethereum’s super asset marks a pivotal moment in the evolution of assets
form the overall ecosystem. For instance, the value of prominent internet platforms, such as Twitter and TikTok, is derived not only from capital investment and company management, but also from the contributions of content creators and users. However, these participants cannot share in the value they create, and are often excluded from the formulation and optimization of platform rules. Additionally, user data is frequently exploited by platforms, which can capture users’ browsing and search data and analyse it to deliver targeted content and advertising. While users provide data for free, platforms use the analysis results to generate profits for upstream traffic buyers and advertising sponsors, without sharing the profits with those data contributors.
By leveraging blockchain technology, users can maintain privacy while choosing to share browsing and other information with the platform and receive benefits according to the smart contract’s settings. For example, users can share their ‘attention’ to earn BAT (Basic Attention Token) rewards by using Brave Browser, a browser that is widely used around the world and based on the Web3 business model. This approach enables companies to create data value, protect content creators’ copyrights, and allow data contributors to maximize their personal data value, resulting in a win-win situation for all parties.
In the past, digital wealth was managed and distributed by central entities, such as companies or financial institutions. However, today, digital wealth is managed and distributed through new decentralized organizational forms, such as DAOs (decentralized autonomous organizations). A DAO is an organizational form that employs smart contracts on the blockchain to write community-updated operating and governance rules, enabling it to operate independently of third-party interference. Through intelligent management methods and corresponding token incentives, DAOs allow communities to achieve maximum self-operation, self-governance and self-evolution, thereby maximizing efficiency and value circulation. DAO management and decisionmaking are completed through token holder voting, which includes project founders, investors, or regular users. They decide the operation and management methods of DAOs, including project development direction, investment decisions, financial management, and more.
Through DAOs, a more equitable and efficient solution for the distribution of digital wealth has emerged. This method has already been tested through ‘yield farming’ – a real-time value distribution mechanism where users lock and stake
digital assets to provide liquidity for a platform, in exchange for digital assets issued by the platform through smart contracts. This process is similar to depositing money in a bank, but the bank does not just pay interest – it also rewards early customers with shares in the bank. For example, Compound, a distributed lending platform, uses yield farming to incentivize participants to deposit or lend more digital assets. Users are rewarded with tokens which they can hold for governance rights, use to propose and vote on updates to the project in the DAO, or sell for profit on the market.
Compared to traditional wealth distribution systems, yield farming offers several advantages. It uses new digital assets, such as governance tokens, to distribute both current profits and long-term value, creating a symbiotic relationship between data contributors and the platform. The allocation process is also transparent, fair and automatic.
In the future, DAO in the metaverse will become an essential economic form, where organizational goals will shift from maximizing shareholder value and company value to maximizing community ecological value. This shift will create a fairer, more inclusive, and more sustainable new paradigm for the digital economy.
These changes in digital wealth underscore the significance of data as one of the most valuable assets for businesses in the digital age. Not only is data a core competitive advantage for firms, but it is also a vital driver for shaping future business models and developing new products. For leaders, it is imperative to comprehend the importance of digital wealth in the metaverse and to adapt to the rapidly changing digital landscape.
To achieve this, leaders must incorporate data as a core asset, strengthen data security measures, improve data utilization efficiency, and ensure the security of data. In conducting business operations, management should respect and protect users’ data rights and return data ownership to data contributors in practice. Furthermore, data assetization should be promoted, to make data a genuine production factor for businesses.
The new collaborative organization model characterized by platformization, community orientation and online capabilities is gradually becoming the norm within the metaverse. Managers should re-evaluate the sources and importance of external digital contributors, carefully considering how they contribute critical resources to the company, and whether the way that value is allocated to them is reasonable. Leaders need to be ready to break boundaries as they attempt to construct a new benefit distribution system that can achieve maximum ecological value.
In the platform economy era, success is the result of the collective efforts of all participants
Technology has begun to transform how organizations deliver projects, and rapid change lies ahead. What role will leaders play when AI is deployed in project management?
Writing Antonio Nieto-Rodriguez & Ricardo Viana VargasWhile AI is not yet a standard tool in the world of projects and project management, there is no doubt that it will disrupt this discipline, and probably faster than we expect. The prospect of that transformation seems almost incredible: in most organizations the tools used to manage projects remain relatively basic compared to the sophisticated digital technology being deployed in other parts of business. Most projects are still managed with Microsoft Office tools, such as Excel and PowerPoint. Can you imagine running your business and operations with spreadsheets? Well, that reflects how little technology has evolved in project management.
Traditional project portfolio management (PPM) tools offer more advanced features, but they remain far from cutting edge. More recent applications enhance planning and team collaboration yet don’t bring automation or process improvements to any of the other critical
elements of projects. Radical change will only occur when the next generation of project management software emerges and becomes widely adopted. Based on personal research, we believe we will soon start seeing some tools that use algorithms to predict the success rates of projects, validate projects’ scope, and automatically create a welldefined project plan in just a few minutes.
The idea of automating a large portion of their current tasks may be daunting for project managers. Yet senior leaders in charge of projects may view the prospect quite differently. There are significant opportunities, as well as risks. Modern project managers will need to adapt and utilize these new tools to their advantage, shifting their focus from technical and planning aspects to more value-added activities. By doing so, they will improve project success rates.
The data challenge
AI and machine learning (ML) require large
For AI to deliver value to the organization, it is essential that data is available
amounts of data related to the projects to function effectively. Data is needed to train an algorithm. It has been estimated that as much as 80% of the time needed to create an ML algorithm is spent on data. For AI to deliver value to the organization, it essential that data is available and managed adequately – but many businesses have a lot of work to do.
Organizations have a large amount of project data that is stored in numerous documents from the past. It is important to ensure that this data is readily available and analysed to identify any anomalies or gaps. This may involve removing any irrelevant data or filling in any missing information. There are two main types of data: structured data, which is clearly defined with easily searchable patterns, and unstructured data, which lacks easily searchable patterns. The aim is to take raw and unstructured data and transform it into structured data that an ML algorithm can use to develop patterns that form the model. Project data
often comes in various formats, with missing data, fields that do not have a clear meaning, or data content that does not follow a consistent taxonomy. In most organizations, project data is scattered around different systems and rarely up to date.
Another consideration for project data is the variety of file formats. The project charter is usually in a Word document, presentation, or PDF format, while quality metrics may be held in a spreadsheet, and the schedule in any number of formats, such as Microsoft Project, Microsoft PowerBI, or Planisware. Natural language processing (NLP) must be used to convert words or phrases to usable data, which adds another layer of complexity. Fortunately, software tools and specialized vendors can scan databases and find unstructured data.
Data is at the heart of the transformation of projects that lies ahead. Therefore, before you rush to embrace new data applications, it is important to take into account several factors. First, it is essential to determine the amount of data available and its relevance. Additionally, considering the currency and validation of the data is important. The format in which the data is gathered is also pertinent, as is understanding how much of the data is generated internally, as opposed to by the supply chain. Identifying gaps in data collection and understanding the organization’s goals in relation to data is crucial.
It is also essential to keep in mind that AI applications need to be designed with a specific
purpose in mind. The speed of change in the data environment should be considered, and businesses must ensure they are keeping up. Finally, anticipating how access to data, analytics, and automation will impact the business is also important.
Uncertainty, inexperience, complexity and context are some factors that impact how projects are defined, planned and implemented. AI has the potential to help with them all. There is, as yet, no single tool that helps project managers systematically address these variables – but we do see a range of tools emerging that are beginning to have an impact.
Start with definition. Clearly defining a project requires knowing in advance the ‘what’: that is, the design, the requirements, or in project management terms, the scope. The more accurate the scope, the more precise our project estimates will be.
We are starting to see some technology startups assist with this task, such as ScopeMaster, which is an intelligent software requirements analyser. It reads requirements and user stories as if it were a human, and performs much of the time-consuming analysis usually done by the project manager and their team. It parses, interprets, tests, cross-references, and sizes and then reports on many aspects of the project scope. It will find potential problems such as ambiguities, duplicates, omissions, inconsistencies, and complexities. Such problems can account for 3060% of all requirements issues, which account for approximately 10% of all project defects.
Another interesting example is the project data consultancy Projecting Success. It has combined integrated bid and procurement data with feedback data for more than 10,000 projects, to identify over 1,000 parameters for an AI model. This enabled them to derive a wealth of insights, such as predicting the winning bidder in a given situation with up to 90% confidence, and developing bid and procurement strategies.
In addition to defining the scope, project planning, also known as scheduling, is another crucial aspect that demands significant effort during the initial stages of a project. Tools like Offolio are emerging that utilize project data and intelligent technology to simplify project planning procedures. They can generate detailed plans and estimate resource requirements, along with associated labour or non-labour expenses, in just a matter of minutes.
The energy technology company Baker Hughes provided a dataset to a data analytics hackathon, comprising 111 projects and 96,000 activities. Their
AI has the potential to impact the way projects are defined, planned and implemented
challenge was identifying areas requiring deeper investigation and developing a methodology for improving estimates in future schedules. A small team solved this challenge in just two days by deploying dashboards to identify focus areas, then applying feature engineering and AI to predict activity duration, saving weeks of effort.
Then there’s risk management. So far, it is one of the most advanced areas in project management in terms of automation. Sharktower and similar tools use big data and ML models to assist project managers and leaders in predicting potential risks that may not be apparent otherwise. These tools can provide suggestions for minimizing risks and may soon be able to modify plans automatically to prevent specific types of risks.
During a project’s execution, project managers have a crucial role to play in maintaining and reporting project-related information, which includes schedule, costs, and risks, among others, through formal project control/change processes. Reporting is a manual process that involves repetitive tasks like collecting and verifying project information, sending reminders, and generating customized reports for the project team, senior management, or steering committees. It is a timeconsuming task, and the information presented in these reports can often be outdated by a few weeks or more.
In the future, we can expect to witness the emergence of interactive visual tools that leverage ML models and real-time data to identify potential project issues before they escalate, offering objective insights on project status, benefits, potential delays, and team morale.
The role of project manager will be significantly impacted and disturbed by various changes over the coming years. Gartner estimates AI will manage around 80% of the current tasks related to project management by the year 2030. Project managers should not resist these changes. Instead, they should adopt new technologies to enhance the success rate of their projects.
The concept of cross-functional project teams may soon include a combination of humans and robots rather than just individuals. As a result, project leaders or managers in the future will need to possess important soft skills such as leadership, strategic thinking, business knowledge, and a strong grasp of technology. Some organizations are already building AI into educational and certification programmes. Northeastern University, for instance, is incorporating AI into its project management curriculum, teaching project managers how to use AI to automate and improve data sets and optimize investment value from projects.
AI and machine learning are set to revolutionize how projects are managed. The starting point is improving organization’s data on projects, which will be essential both for automating and streamlining time-consuming reporting and monitoring processes, and for building the machine learning models that will allow technology to perform more sophisticated tasks in future.
Uncertainty, inexperience, complexity and context are perpetual challenges in defining, planning and implementing projects. AI can help address them all. Software can already analyse project requirements, revealing ambiguities and inconsistencies. It can facilitate accelerated planning processes, and identification of resource needs. And it can identify potential risks and mitigating actions.
The fact that AI will be taking on project management tasks doesn’t imply that human project managers will become obsolete. Instead, the role of project managers will become even more important in the future, although their responsibilities will be different. In common with professionals in operations, sales, finance and other roles, we can expect a shift from tactical to strategic. For project managers, that means that while AI and automation are completing administrative work, the project manager will focus on ensuring that project results deliver the expected benefits and are aligned with strategic goals.
Antonio NietoRodriguez is the author of The Project Revolution (LID Publishing) and the Harvard Business Review Project Management Handbook Ricardo Viana Vargas is the former director for infrastructure and project management at the United Nations and author of Project Management Next Generation (Wiley)
While recognizing the potential advantages of AI for revolutionizing project management, we also have to recognize that there are challenges. Those include questions around ethics: current codes of ethics are written for individuals not algorithms, describe human values, and define standards of conduct for people working on projects. Can machines be held to account for their values or behaviour? The project management industry, in common with society as a whole, has work to do on this front.
But it is clear that the application of AI in project management will bring significant benefits. The automation of administrative and low-value tasks will enable project managers to shift from the tactical to a more strategic level where they can add greater value. And, crucially, it will help organizations, leaders, and project managers select, define, and implement projects more successfully.
When he was just 19 years of age, something happened to Antwan Lofton that would shape his whole career.
Lofton, newly appointed vicepresident for human resources at Duke University, remembers applying for an internship and travelling to New York to interview for the role. While he waited patiently for his turn, he chatted to the receptionist. “I had nowhere to sit and, being the extrovert I am, I just decided to spark up conversation with the lady at the front desk,” recalls Lofton. “She asked me, where did I see myself in five years? I was sharing with her my career goals and all the things that I wanted to do with my life. And we were laughing and talking – it must have
been 20 minutes or more – just having a great conversation while I waited for my turn.”
But Lofton’s turn never came. “A gentleman walked out of the boardroom and announced that they had made their selections for the internship, and they were not seeing any other people that day,” Lofton recalls. “So, there I was in New York and thinking, ‘Okay, well, there it is. I didn’t get it.’”
He brushed it off as best he could and continued his conversation with the receptionist, asking her the quickest route to the airport so he could catch a flight home. “Even more intently, she leaned in and wanted to learn and know more about me,” recalls Lofton. “I didn’t realize it then, but now it makes sense.”
As he went to leave, the receptionist called him back. She handed him a lunch ticket: “She said, ‘You came a long way. And there is a gentleman that will probably join you in the restaurant. Just go in. I’ve so enjoyed our conversation.’”
At that point, Lofton’s life changed. “Sure enough, at lunch, a gentleman walks over and sits down and shakes my hand. And we just start laughing, talking about life. I tell him my aspirations. Then, towards the end of the conversation, he says, ‘you got the position’.”
Lofton’s companion was the firm’s president. He had planned to have lunch with the receptionist, who was leaving the company, to thank her for her service. The president told Lofton: “She gave up her lunch with me because she saw something in you.”
By the time Lofton eventually emerged from his conversation with the president, the receptionist had gone. They never met again. “I’ve tried numerous times to find her,” he recalls, “to thank her for what she did.”
Unable to pass the thanks back, Lofton passes it forwards. “I made a vow to myself. Any door that I have been fortunate enough to walk through, I don’t close that door behind me,” he says. “I want to make sure that I leave that door ajar so someone else can walk through it. It may be a faceless person, a nameless person that I may never know. But if I create a shape or space that makes it easier for the next person to win an opportunity… that’s my way of saying thank you.”
Different vantage points
That word – opportunity – crops up a lot when you are speaking to Lofton. It seems to form his whole being. A career that began with that fairytale of New York, continued through years of service in the US health system, latterly into academia, with Howard University and now Duke. Throughout it all, he reveals, he has been studiously present: there to hear what employees are saying, building a three-dimensional image of the organization.
Any door that I have been fortunate enough to walk through, I don’t close that door behind me
“If I work in human resources, I must be an actual human resource,” he says. “If our people view me, or the offices that I represent, as solely transactional, they’re not going to come to me. I want to get to know everyone at every level, where they feel comfortable coming to me, even if it’s an area that’s not fully within my purview. People are often shocked: ‘What? Why did they go to you about that?’ The answer is because I make myself available for them to sit and to talk.
“I am always trying to figure out ways to best serve our people, as well as looking at ways to make everyone feel whole. If you’re going to make policies, if you’re going to update procedures, come up with a strategic plan, you need to position yourself so you understand how that plan is going to affect the capital, the fundraising efforts, the costs, but also consider how it is going to touch lives – patients, students, employees, faculty or staff. What is the implication of your plan going to have on all of those kinds of lives?”
Lofton recalls a 2008 film starring Dennis Quaid and Forest Whitaker called Vantage
mark. Live it. Fix it!
Point, in which an attempted assassination of the US President is told from the view of eight eyewitnesses. I hadn’t seen the picture, so streamed it the evening after I met Lofton. The movie uses a cinematographic technique called the Rashomon effect, which explores the known phenomenon of eyewitness inconsistency. The point of the screenplay is that it is impossible to build an accurate representation of an event without combining the experiences of multiple individuals.
“The entire movie centres around everyone telling the story as it relates to what they saw –but from where they were standing,” says Lofton. “And everyone has a totally different story, based upon their vantage point. I am always interested in bringing thought-leaders into the workforce that may not necessarily have the same lived experiences that I have.”
He makes himself available out of hours, whenever people want to speak to him. “I believe in doing impromptu surveys where you just go out and ask questions,” he says. “If there’s a town hall meeting, or a new announcement that was
We should not be afraid to say when we miss the
rolled out at 8am, by 11.30am I’m walking the halls asking people, ‘so how did that meeting go this morning?’ ‘That memo that went out from the president: how do you see your role playing a part in it?’ So people understand that they are a part of every decision that is made within the university or the health system. But here’s the other element. People working lates or nights shouldn’t be left out and asked to visit some non-existent waiting room where their opinions can theoretically be heard. I’ll show up on the weekend. I’ll show up at two o’clock in the morning and ask the staff working at night.”
Different people, different times, different vantage points: “I’ll say to the late shift, ‘did you hear about that announcement that went out this morning at 8am, because I realize you weren’t working at that time?’ And in many cases they’ll say, ‘yeah, I read that policy. However, it’s not applicable to us and this is why… boom, boom, boom…’ or, ‘we’ve seen several things rolled out that really only impact people who work during the day.’”
As the great economist John Maynard Keynes advised, when the evidence changes, Lofton changes his mind. “Make sure that when you hear those things you can say, ‘possibly we missed the mark,’” he says. “I have no problem admitting when I’m wrong. We should not be afraid to say when we miss the mark. Live it. Fix it!”
It is this multidimensional, agile approach to employee relations that has led Lofton to become a renowned expert in the field. He rejects my suggestion that he has some sort of ethereal gift for it, citing instead a formula of communication, accessibility, and endowment.
“I really wish there was this magical term that I could use to make it sound as if I had an enchanted touch or that what I do is somehow so special,” he says. I suggest he is downplaying his own abilities; underestimating his achievements: “I’m just successful at something that should be a very simplistic truth known by any leader,” he says. “And that is that everyone wants to feel seen, heard – and valued.”
The art of developing people Healthcare is heavily unionized. The cost-of-living crisis has triggered industrial action, both in his country and mine. Yet Lofton says that focusing solely on salaries is a mistake.
“If you are looking at the labour markets and how unions work, the number one reason that individuals give is that they need to be represented,” he says. “People automatically think it’s about wages. When people say, ‘I need someone to represent me’, what they are actually saying is, ‘I do not feel seen, I do not feel heard, therefore, I do
not feel valued – so I’m looking for someone – via a mediator; via a union – to come be my voice.’”
Lofton’s appointment at Duke represents something of a homecoming. He was born not at Duke University Hospital, but at the facility of its neighbour and archrival – the University of North Carolina Medical Center. “I was born under the lighter shade of blue!” he says, alluding to the colour associated with the university. But the hue swiftly changed. “I had difficulties breathing independently,” Lofton recalls. “And so, immediately after birth, I was rushed to this place with its darker shade of blue. It was Duke University Hospital that gave me the tools to breathe independently. I find it hilarious that I am back at the institution that gave me my second wind of life.”
I feel sure that he will maximize the opportunity, for himself and others. His approach to diversity is to increase the talent pool: ensure that the widest breadth of people and ideas come through that metaphorical door that was opened to him all those years ago in Manhattan. “It’s not all about changing who is hired, because we want the best candidate to be hired, that’s the number one,” he says. “But the goal is to widen that applicant pool, to make sure that it’s very diverse. Some people are shocked to hear this, but it’s the truth: there are certain career paths that are more driven by certain individuals. There are certain positions that are male-dominated; there are certain positions that are female-dominant. It’s also about educating our senior leaders and ensuring they are aware of what those paths look like.”
Lofton is so outgoing and determined, I wonder if he struggles to delegate. “That’s a very good question,” he says. “I do love to be able to see how a project is moving along. But I try not to micromanage, because while it may be easier to get involved – because it’s something that you’ve done for years, and you could just jump in and tell someone the best way to do it – sometimes the teachable moment comes from walking back and allowing them to figure it out. And then when they come to you and say, ‘this isn’t working’, then it’s at that point that the dialogue really helps.”
Maybe that’s an overlooked art of developing people. Timing. Lofton composes great teams because he lets people find their own way. He shudders at the idea of identikit recruitment.
“While I was listening to you phrase that statement, it instantly formed a question in my mind,” he says. “Could I imagine working with ten people that were identical to me?”
Ben Walker is editor-at-large of DialogueSo could he? “I don’t think so!” he says. “There’s so much value to being with someone that can introduce a new topic, hold a different opinion, or has lived a different experience to your own.”
Understanding the dynamic nature of teams is essential for leaders to thrive in a fast-changing environment
Writing Maria Katsarou-MakinHumans are deeply tribal. The need to belong is one of our fundamental needs after food and shelter. Being part of a group or a team has been part of our history – our evolution even – since we were sitting around campfires. Yet it is still an area of human behaviour that seems wrapped in mystery, as we continually search for new insights and techniques to answer that vital question of what makes a team effective.
Having worked with and in teams and groups – and researched the subject – for many years, I have seen that the key ingredients of effective team dynamics go well beyond the obvious, such as having a common purpose or running effective meetings. There are some important foundational points about teams that are particularly important for team leaders – indeed, for anyone working
with and in teams. These points are not necessarily interrelated; however, they are common issues for most teams. And if we understand how teams really work, we can begin to think more clearly about what great performance in teams really means, and how we can best pursue it.
A team does not operate in a vacuum. Instead, it is part of a larger system, and therefore interconnected. Most of the issues that exist in one area of the organization exist elsewhere as well. So if, for example, there is a lack of psychological safety within one team, that phenomenon is likely to be present within the whole department, and within the whole organization, including at headquarters. Teams are open systems that are adaptive and constantly process information in relation to their environment and context. Any efforts to shape team behaviour have to take account of their context within a wider system.
When it comes to influencing teams, leaders often have an underlying assumption that everyone wants to change, at an individual or team level. That is far from accurate. Often, teams do not want to disturb the status quo. They maintain existing behaviours because they are serving them in some way. That can seem dysfunctional to an outsider; however, on the inside, it might be that the team or organization simply chooses to work in this way. Ronald Heifetz, Alexander Grashow and Marty Linsky (2009) have called this the “illusion of the broken system.” The tendency is particularly common among people in authority and employees who have been in their post for a long time. In those cases, people are not resisting the change per se, but the potential loss of power, authority or identity. Such situations can be difficult for individuals to change on their own. An executive who attempts to rock the boat on their own is taking on a system that is larger and more powerful than them. Either the system will eventually push them out of the organization or the team, or they will be absorbed into the existing way of working.
When a basketball or football match is taking place, everything is happening quickly. Players must make decisions on the fly, foresee their opponents’ moves, and look at the whole game, including themselves and their teammates. Each team’s coach or manager is usually on the sidelines, observing and shouting out the odd comment.
Teams are open systems that are adaptive and constantly process information in relation to their environment
When the game is over and the teams review the game on replay, that is when reflection takes place. They can identify possible mistakes and learn from them for the next game.
In the fast-changing corporate environment however, teams seem to be doing less and less of this valuable reflection work. High-performance teams make this part of their daily routine and their way of working. They don’t have to be long, extensive sessions; they can be short, to-the-point reflections on what happened, what the team has learned and what can be done differently in the future. Such sessions should be held as close to the event as possible. In her 2012 study of teams, Amy Edmondson found that the teams that succeeded were the ones that constantly reflected on their observations and thoughts as a way of figuring out how to work more effectively. In my own experience, I have found that this process should be owned by all team members, not just the team leader or the HR professional. This is because team members all have equal responsibility for its effective functioning.
According to Daniel Goleman, self-regulation “liberates us from living like hostages to our impulses”. It is a competency of emotional intelligence (EQ) that involves being in command of our impulses and moods, and having the ability to respond (after some critical analysis) rather than react. At a team level, it takes the form of team members’ ability to observe their own emotional processes, identify dysfunctional patterns and work on those to become more effective without an external support.
For any change to be effective and long-lasting, executives have to be swayed both cognitively and emotionally; they have to involve both their head and heart to change behaviour. Very often, organizations’ interventions start at the middle level, with managers or leaders who report to the top team, without first exploring the top team’s own need for change. Yet the middle level usually
To better influence teams, leaders need to understand some critical aspects of how teams function. They include the fact that teams are part of a system, and that not all teams want to change. Leaders should also heed the role of reflection, self-regulation, time, psychological safety, and what is really happening when team members are labelled as problematic.
replicates the behavioural patterns and pathologies of the top team. Likewise, organizations often target just one or two individuals with coaching interventions when they’re actually facing a team issue. Careful examination is required to really understand what is happening and what the appropriate intervention might be.
I cannot stress it enough: a climate of psychological safety is important because it encourages people to speak up, enables clarity of thought, supports productive conflict, mitigates failure, promotes innovation, removes obstacles to the pursuit of performance goals, and increases accountability. Psychological safety is larger than (but includes) trust. Bart de Jong, Kurt Dirks and Nicole Gillespie (2016) conducted a large-scale study that involved cumulative evidence from 112 independent studies and included a large sample of 7,763 teams. They found that trust matters the most when team members are dependent on each other, in both short-term and ongoing teams. Trust is especially valuable for bringing a team together when under pressure to deliver results fast.
When I get called to work with a team, I am often told: “Even though the team is effective overall, there are a couple of people who don’t seem to be aligned with the rest.” Some members are perceived as problematic, not fitting in, or simply challenging. This view itself is problematic, however. From a systemic point of view, no individual exists in a vacuum. Therefore, I don’t espouse the term ‘problematic’; rather, I view each person’s behaviour as data. They are trying to say something and their way of doing this is their chosen behaviour. Each behaviour is the result of the rest of the team members’ behaviours – both conscious and unconscious. Yet organizations often place more weight on an individual’s personality and less on the interpersonal aspects of the context they are working in, such as how the other members of the team are behaving.
There are good reasons to challenge the typical view of high-performance teams. For one thing, the relentless pace of change today precludes teams from achieving a steady state of high-performance. Instead, leaders should focus on what leads to great performance in key moments, including understanding the emotional dimension of team dynamics.
For anyone engaged in studying teams or seeking to build effective teams, there is a big question that must eventually be confronted. Do high-performance teams actually exist?
Researchers and thinkers differ on this topic. Typically, high-performance teams can be described as those that produce outstanding results on an ongoing basis. There are as many definitions as there are authors, but they are typically seen as having characteristics such as a sense of purpose, shared values and beliefs, open communication, a culture of speaking up, trust and mutual respect, shared leadership, effective working procedures, the ability to build on differences, flexibility and adaptability, continuous learning, and selfregulation. I have come across well-functioning teams that satisfy those criteria to a certain degree, or that have had isolated moments when they truly excelled. But I am not sure that teams can be highperforming all of the time.
Indeed, an inherent problem with the concept of high performance is that it is premised on the notion of delivery on a continual basis. That unhelpfully implies a dichotomy between highperformance and non-high-performance teams, as Collins and Parker (2018) point out. The reality is more nuanced.
I also don’t believe that being a highperformance team is a fixed destination, simply because of how our work keeps changing and evolving. The average time that top executives spend in position has decreased over recent years. Korn Ferry research suggests that the average tenure of a chief executive dropped from eight years in 2016 to 6.9 years in 2021, and the same trend can be seen in other senior roles. I often encounter organizations where leaders stay for two years and then move on to the next assignment.
This trend – and other forms of ongoing change in organizational life – simply does not allow teams the breathing space needed to accept the new reality, digest it, and go through all the necessary processes to become high-performing. So, all teams will evolve over time. However, the ones that thrive, and don’t just survive, are those that tick off most of the high-performance team criteria.
Perhaps the key to high-performing teams is the willingness of leaders to take on one of their primary tasks, as Richard Boyatzis, Daniel Goleman and Annie McKee (2002) argue: to work with people’s emotions and the team’s emotional reality. This comes with the prerequisite that those leaders must first be able to process their own thoughts and feelings. That’s because emotions, it turns out, are more contagious than Covid-19.
Dr Maria Katsarou-Makin is author of Group Dyna-Mix: Investigating Team Dynamics, From Leaders to Corporate Gatekeepers (LID Publishing)
Neuroscience has provided us with valuable hard evidence about the effect that people have on each other when they work in teams. This makes it almost mandatory for leaders to know their biology, because whatever they do (or don’t do) and say (or don’t say), they are inadvertently having an impact on their teams.
As I explore in my book, there are several insights from neuroscience that are relevant to team leadership: even in brief, they provide a useful list of pointers for leaders to reflect on.
Leaders can have an emotional impact on their team without even realizing it, and that impact can be of great significance.
The human brain has the ability to continuously learn.
Emotions are contagious. They can have a ripple effect and be cascaded down an organization. Fear and stress in the workplace affect individuals’ abilities to analyse, innovate and even communicate at the optimum level. They are linked to the production of the hormones adrenaline and cortisol.
Humans are meaning-making creatures and, if they don’t have certain information, they will make it up. The human brain prefers predictability and structure to uncertainty. Fear is the enemy of initiative and creativity. People who are fearful will do as you say, but won’t be committed to the work.
Leaders need to continually gauge stress and engagement levels.
As leaders, practitioners, consultants and, above all, humans, we don’t exist in a vacuum. We are all part of a system or a unit, whether that’s our family, a club we belong to, the team or department we work for, and so on. We all contribute to each other’s behaviours – sometimes without being aware of it.
A team is a living organism, much larger than the sum of its individuals; it has a life of its own, and this is how group dynamics begin to unfold. As the word ‘dynamics’ implies, these are processes that take place throughout the life of the team, and they keep it in a state of constant motion and change.
I do not believe that high performance is a static state or a fixed destination; it is a fluid point in time. When a team achieves high performance, it has no choice but to keep working on it. The ability to help teams do that is crucial for leaders to thrive in our fast-changing, complex and unpredictable world.
Perhaps the key to highperforming teams is the willingness of leaders to work with peopleʼs emotions and the teamʼs emotional reality
Overwork and overwhelm have become ordinary. Leaders’ behaviours can create stress and contribute to burnout – or reshape workplace cultures to promote wellbeing and personal sustainability
Writing Amy Bradley & Katherine SemlerBurnout is one of the buzzwords of our times. Reports of chronic stress and burnout appear in the press every day, with people describing themselves working longer hours, facing higher workloads, and dealing with more demands at work and at home than they have ever known before. It seems that the pandemic has been a catalyst for a collective awakening when it comes to reassessing our relationship with work. Many leaders have realized that burnout is an issue, for their organizations, and for themselves as individuals – but few seem to know how to deal with it.
Burnout is a prolonged response to workrelated stress which manifests in three ways:
exhaustion, cynicism and ineffectiveness. Exhaustion relates to experiences of chronic stress over time. Cynicism involves becoming cold, detached and sceptical about our job or workplace; we experience ourselves as robotic and lose the human element when dealing with customers and colleagues, and even in our relationships at home. Ineffectiveness tends to manifest as a crisis of confidence, negative self-talk, and a sense of reduced personal accomplishment.
In their seminal work, Christina Maslach, Wilmar Schaufeli and Michael Leiter suggest that it is only when we experience all three states simultaneously that we are classed as burned out. It has been argued that burnout is too often used as a synonym for ‘tired,’ and that we are not in fact living through a burnout epidemic so much as a case of overdiagnosis. Yet as some of Maslach and Leiter’s most recent research has found, all three qualities of burnout are on the rise among the working population: according to a 2021 survey, more than 50% of workers in the US feel burned out. Many workers are experiencing feelings of being overextended, ineffective and disengaged. Over half of the working population may not yet be burnt out, but they are on the way. And leaders have a pivotal influence on whether they teeter over the edge – or can shift bank from the brink.
Leaders’ impact – for better or worse
Leaders play a critical role in setting the cultural tone with regard to overwhelm and burnout. Unfortunately, overwork has become a way of life in many organizations. In our experience, organizational cultures tend to see exhaustion as a status symbol and badge of honour, so employees
Many workers are experiencing feelings of being overextended, ineffective and disengaged
are implicitly rewarded for operating from this state. Yet there is also often stigma and shame attached to burnout, so people do not speak up when they are struggling, assuming that colleagues will think they are ‘weak’ and ‘not up to the job’.
Against that backdrop, leaders have enormous influence. They can help prevent burnout by building deep and trusting relationships with those around them, so that conversations about overwhelm can be surfaced without fear of judgement or reprisal. On the other hand, they can also promote burnout, through destructive leadership behaviours, such as blaming others, breaking promises and expressing anger.
Moreover, it is not just overtly negative leadership behaviours that drain energy, cause stress and contribute to burnout. Studies show that passive-avoidant leadership can be equally destructive. These behaviours include turning a blind eye to dysfunctional or damaging behaviours in organizations, regularly being unavailable or absent, and avoiding difficult conversations.
Consider Malcolm’s story, as told by his line manager (opposite). It illustrates how crucial our relationships at work are for spotting signs of overwhelm, which we know is a dashboard warning light on the road to burnout. When we are in overwhelm, our bodies speak to us through physical, mental and emotional pain. However, as is so often the case, Malcolm perceived that the demands of his job as a senior leader outweighed any compassion that he owed to himself, so his warning signs went unchecked.
Why is this so important? Because people who experience burnout almost always say they did not see it coming. Only with hindsight do they realize that all the signs were there; that they somehow ignored or suppressed them. Their inner voice was louder about the need to keep pushing on than when it was saying, “Slow down, take it easy, take care of yourself.”
So, what did you feel for Malcolm as you read the vignette? What do you think about his boss? Can you identify with their behaviours? Are we
As many as half of workers could be on the path to burnout, experiencing feelings of being overextended, ineffective and disengaged. In many organizational cultures, exhaustion is treated as a badge of honour – yet at the same time, burnout carries stigma and shame. That makes it hard for employees to speak up about their wellbeing.
becoming numb to our drive to overwork, or to the tendency for overwork in those around us? In Malcolm’s case, it appeared to be passive-avoidant behaviours that contributed to his burnout, with his boss appearing to encourage a culture of overwork. Leaders should ask themselves:
How might I be complicit in a culture of overwork?
To what extent do I turn a blind eye when it comes to unhealthy behaviours?
How do I personally role model in this regard?
Negative leadership behaviours – blaming others, breaking promises, expressing anger – can contribute to burnout, as can passive avoidant behaviour such as ignoring dysfunctional or damaging behaviour, being unavailable or avoiding difficult conversations. Leaders need to build deep and trusting relationships with those around them.
Malcolm was working for me when he broke. I still don’t really get it. He was a machine, you know, in a good way. Anything that came his way he would tackle full on and obtain incredible results. He worked tirelessly. I guess there were some signs, like one day he yelled at one of his team when there were other people, including me, within earshot. I mean, I do that sometimes – we have an assertive culture here – but it was unlike Malcolm.
That same week, I heard he lost his cool with a manager too, at a hotel we’d hired for our leadership summit. He was really stressed about the noise and construction going on during the CEO’s speech. We were supposed to record the speech and then use it in a companywide comms campaign. I guess they couldn’t edit out background noise and the CEO’s office had made it clear that the conditions needed to be absolutely perfect or they would not allow the video to be used. I think Malcolm stayed up several nights in a row leading up to the event. I told him, “Buddy, you should get some rest,” but I knew he wouldn’t let
anything drop for the sake of a few hours of sleep. And I was confident that in his hands everything would go smoothly. I mean, there wasn’t much the rest of us could do to help. He had it all in his head, and his team was good.
It was a two-hour drive home from the summit. Everything had gone perfectly. The CEO’s office was really happy and congratulated me. Malcolm seemed happy too, although he was quiet. He looked like he was forcing himself to smile when the MC thanked him and his team at the end. He was driving the van because it was rented in his name and at one point I looked over and saw that he was crying while he was driving. I thought maybe the late afternoon sun was bothering him, but he didn’t say anything and I didn’t want to make it worse. I guess all the tension must have got to him.
After we stopped for a break, one of his team members took over the driving and he seemed OK. It was the following week that he finally hit a wall and couldn’t come to work. Our HR business partner called me to say he was on medical leave and would be out for two weeks.
We acknowledge that this is a challenge, as leaders themselves often feel heightened pressure to perform. But the reprioritization of human connection, communication and care are the first steps towards creating a better work environment, for leaders and their teams alike.
We do not suggest that responsibility for creating a better work environment lies solely with individual leaders or the organization. To eradicate burnout, individuals, organizations, families and communities all need to play their part in moving us beyond self-interest and toward reciprocity and collective action, to create sustainable future workplaces for the benefit of all. To truly tackle burnout, not only do we need to challenge societal norms and expectations concerning work as the source of our fulfilment in life, we also need to pay attention to the organizational environments we find ourselves caught up in.
From the stories we gathered as part of our research, it is those people who act with tough compassion that are able to save their souls.
Dr Amy Bradley is a professor of leadership and management and author of The Human Moment
Dr Katherine Semler is a senior partner at Korn Ferry and adjunct faculty at Ashridge Hult. They are jointly authors of Running on Empty: Navigating the Dangers of Burnout at Work (LID Publishing)
Two weeks! That was like a whole summer holiday. I didn’t think it would take him that long to rest up and there was plenty of follow-up to be done from the summit, but he really did disappear. They took him to a special clinic and I hear he slept for most of the two weeks. He wasn’t even allowed to check his email and stay in touch. I thought it must have been driving him crazy to be so cut off after being the nerve centre for the whole thing, but apparently he needed it and they had just moved home. His career was on the rise, but he couldn’t have had much time for himself or his family. Maybe that’s what got him in the end.
If I’m honest, I need people like Malcolm on my team – people who really care and are able to push things to a new level. I need to oversee things and manage the politics, but the people on the ground, like Malcolm, have to be able to work at two levels. They need the intellectual power of a top leader and the drive of a front-line worker. I think Malcolm’s drive was too strong in the end. He was effective while it lasted, but he pushed himself too far.
Tough compassion means being able to spot and surface our own unhealthy behaviours – and those displayed by others – before it is too late. It means facing up to difficult conversations about the detrimental impact of organizations' work cultures, and it means living with clearer boundaries between work and non-work, in service of our long-term well-being.
If we are to make the changes required to tackle burnout at its roots, we must also demand different working conditions. Employees and employers need to co-create a shared vision of what it means to lead a healthy work life, and of how work fits into a life well lived.
To eradicate burnout, organizations need to be radically reimagined so that compassion for self and for others is prioritized – so that collective well-being is as much a priority as profit. Leaders must role model healthy behaviours by making personal sustainability one of their guiding leadership strengths; and we all, as individuals, must find ways of affirming that purpose also comes from life outside of work.
Waters’ chief executive Udit Batra shows why true purpose is built on shared authenticity – and great leadership
Writing Michael ChavezGrand statements often hide meagre aspirations. Yet the reverse can also be true: the most purposeful organizations can emerge without big words cast on brass plates in the lobby of a company’s HQ.
Waters is one such company. At Waters’ core, it uses science to improve human health and wellbeing. Waters enables scientists to ensure medicines and vaccines are safe; food and water is pure; car batteries don’t catch fire; and the materials used in products contribute to a sustainable future.
Two-and-a-half years ago, Udit Batra joined Waters as chief executive officer and president. Over that time, he has led a transformation that resulted in significant progress in regaining the company’s commercial momentum, strengthening the company’s leadership, revitalizing innovation and defining a long-term strategy.
At the start of the transformation, Batra’s tactics were to pave the path to growth. He brought together his leadership team and together they put all the facts on the table. Transparency about what was working – and what was not –enabled the team to have a shared understanding of the current state, and create a set of initiatives to get back on track.
“I said, ‘Let’s do the familiar first,’” says Batra. “And the familiar part was replacing instruments. We know how to do it. Then we got into the tactics: we built a spreadsheet, we looked at customer data. And I think what is lost very often is that there is a spiritual part of this: which is, ‘Hey, we can do it’.”
By focusing on regaining commercial momentum, Batra was able to invigorate the company’s indomitable spirit. In fact, ‘indomitable spirit’ became a rallying cry across the organization, reminding employees that when they approached challenges with focus, urgency and accountability, they could – and would – get back on top.
Commercial success followed more quickly than anyone had expected. “By the end of 2020, we were seeing the first signs of outperformance,” Batra recalls. “A year later, we had excellent momentum. And in 2022, the success continued. Not letting people get lost in the big picture, and just making sure that the actions were broken down into smaller pieces, was critical.”
This approach allowed Batra to not only deliver real change, but also to lay the foundations for something bigger. The groundwork for a higher purpose came from Batra’s efforts to revitalize Waters’ innovation and drive its long-term strategy.
Batra urges his people to identify what he calls the “intersection of purpose” – where their positive impact at work reinforces their positive impact at home
“When you are seeking collective purpose from your people, you must realize that the transition must occur organically so people start believing in themselves,” Batra says. “You can talk about purpose until the cows come home. But it won’t work unless you have built the necessary foundations. Get the first part right – the tactics of running a successful business – then you can change the narrative.
“In my mind, I had already said, ‘The first step is all these tactics’. And then, ‘Wouldn’t it be great if we could all become convinced that we are here to solve big problems.’ Did I invoke the essence of where we wanted to go, right at the beginning? The answer is no,” says Batra. “Our first purpose was the right to have a purpose.”
The recognition of this paradox – that promoting the big picture too early can actually inhibit individuals from connecting to the big picture –speaks to Batra’s brilliance. Instead, big-picture purpose is built stage-by-stage, as individuals embody the value in the essential tasks that they complete day-to-day.
I put it to Batra that this pivot – from practicalities to purpose – was the leadership equivalent of an elegant dance, using subtle cues and momentum to convert one dynamic into another. A simple cognition of the steps that were needed to bring the good times back led to an
embodied, but inferred, purpose: to use science to improve human health and well-being.
“You must feel it,” Batra insists. “If you feel it yourself, you don’t have to say it. When we talk about authenticity in behaviour, I believe it.
“I came into the healthcare industry to solve these big problems and work with people, and I’m not leaving until we’re done,” he reveals. “There’s no retirement in my mind. I want to work with people way smarter than me to be able to orchestrate something; to solve some of these challenges that we see in front of us.
“It costs $3 million to give gene therapy to a child with cerebral adrenoleukodystrophy (CALD),” Batra says. “If you fail to provide treatment in those first few years, you lose the child. Three million dollars! That’s a big problem that should bring purpose to everybody’s work.”
Yet Batra accepts that work is far from everything for people. Much individual purpose is found through families: the way we strive for the happiness and comfort of our loved ones. Batra’s understanding of this fundamental human truth informs much of his leadership. He urges his people to identify what he calls the “intersection of purpose” – where their positive impact at work reflects and reinforces their positive impact
at home. “Over time – if that intersection is compelling and powerful enough – people don’t leave just for a promotion,” he explains, “because they don’t believe that a promotion anywhere else will offer them that powerful intersection. But make no mistake, it’s an invitation. It’s not an obligation. It’s not a condition of employment.”
The invitation for Waters’ employees to consider the intersection of purpose is independent of the necessary elements of organizational success: performance management, structure, discipline. “The paradox is, how do you do performance management at the same time as the invitation?” says Batra. “But that’s the task of leadership.” Batra upholds standards while simultaneously trying to foster an emotional connection. “It can be done,” he says. “That is where the magic is.”
Under Batra’s leadership, Waters has harnessed that magic. By avoiding ‘big statement’ purpose –that is, purpose for its own sake – he has cultivated something far more potent: an innate, implicit, living and felt purpose narrative that has emerged organically, incrementally, and individually through the business.
It is purpose born of people, not plaques. Great leadership trumps signs on the wall.
“Richard Benjamins draws on his years of experience in the data journey to offer very practical advice for any company serious about becoming data-driven. This is a book you must read if you want to avoid the typical mistakes in this sort of transformation”
– DAVID DEL VAL , CEO of Telefonica R&D
“So many talk abstractly about Big Data and AI in large organizations. If you are interested in the nuts and bolts of being data-driven; if you care about success and all the things that really matter, read this book!”
– VIKTOR MAYER-SCHONBERGER , co-author of the bestselling Big Data
The democratic world can triumph in tech – if it works together
Believe the hype – even if you shouldn’t believe all the research. China is a global top dog in tech, leading in 37 of 44 technology segments – at least according to the Australian Strategic Policy Institute (Aspi). But China is not quite as dominant as that statistic suggests. Aspi bases its findings on the number of research papers published, which includes quasi-propaganda released purely to gain government incentives. Yet even accounting for rogue papers, China is undoubtedly up there with the US. It might even be ahead.
That the great emulator has become the almighty innovator is a trend well documented. Yet the US has been slow to respond to its rival’s progress. Finally recognizing China’s huge technological might, the US House of Representatives has formed the bipartisan Select Committee on the Strategic Competition Between the United States and the Chinese Communist Party. The committee focuses on manufacturing capability, trade policy and intellectual property rights protection – as well as human talent. It aims to increase investments in R&D and attract the world’s most able scientists and engineers to American shores.
The House committee’s work is necessary, but it is insufficient. At some point soon the US must realize that it is unable to cling to a global edge in tech while working alone. It is time for a North Atlantic Technology Organization. A new Nato, you might call it.
There are huge prizes on offer. I am on record as saying that my native India is an invaluable potential ally in healthtech – particular in the worldwide fight against cancer. It has the talent. And it is largely unimpeded by the need to protect industry profits. “Because India has no vested interests to protect and has a culture of giving and sharing, it can do what the West only dreams about,” says
Gary Reedy, the former chief executive of the American Cancer Society.
Yet international tech alliances are not fantasy, but reality. The European Council for Nuclear Research (Cern) was founded in 1954 by 12 European countries, including France, the UK, Italy and West Germany. The European G7 nations were concerned that progress in nuclear technology was overly reliant on facilities available only in the US and Soviet Union – where the focus was on the development of weapons, not energy.
Cern proved it is possible to resolve many of the diplomatic and economic challenges of multilateral organizations. It created a funding model and governance structure that gave a voice and role to each member state, whether it was a smaller player like Greece, or a major power like France. It achieved most of its goals. Indeed, its scientific influence reached beyond subatomic physics: it is credited with world-changing innovations such as the World Wide Web, the touchscreen and cancer-detection imaging. By contrast, techno-nationalism is an unwise play. Witness the refusal of China to participate in a global standard for the development of Covid vaccines. The result was the woefully underpowered Sinotec jab, which led to avoidable deaths and morbidity in China.
In a recent paper, professors Leonard Lynn of Case Western Reserve University and Hal Salzman of Rutgers University propose the development of new Science, Technology and Innovation (STI) Global Commons. By enhancing open access to global talent and following the democratic governance principles pioneered by Cern, new international collaborations on technology are possible. The potential rewards from a new Nato for tech are boundless. A partnership between the US and India is realistic. If the world can resist the false allure of techno-nationalism, early successes on the global challenges of climate change, cancer, cybersecurity and poverty could heave into view.
Vivek Wadhwa is author of The Immigrant Exodus: Why America Is Losing the Global Race to Capture Entrepreneurial TalentAt some point soon the US must realize that it is unable to cling to a global edge in tech while working alone
The skills developed through gaming will give many young leaders an advantage in the workplaces of the future. Here’s why
Writing Bob Johansen, Joseph Press & Christine Bullenthe puzzling world that’s all around us. Games can help us to connect with others in the processes of reconstructing the past or imagining a future, using verbal and visual language capabilities. Gamers fill these mental-made worlds with the fictional narratives they call identities. They play games of aspiration, decision, action and learning, expanding their connections with new stories. Well-designed games bubble with emotion and demand player attention, just like well-written stories. In a game, however, you get to be in the story.
Thinking ‘futureback’ – we recommend thinking ten years into the future and working back to the present – leaders will need a game designer’s heart if they wish to attract, engage and retain young people seeking meaningful work. Young people will be seeking harmony between themselves and their work. Expectations will be high. Leaders will need to provide opportunities for them to be in good company with others, through an increasingly wide range of digital media.
The future will be an incessant carnival of surprises that will be intensified by a new generation of gamers entering the ‘officeverse’ – the anytime, anyplace world of where we will work, when we will work, and how we will work.
As philosopher Marshall McLuhan said, “We shape our tools, and thereafter our tools shape us.” While many of today’s video games are overly violent and sexual, thinking futureback reveals that what we call video gaming today will become one of the most powerful learning mediums history has seen. Gaming will evolve from mostly recreational to a powerful medium for social engagement.
“It is better to be surprised by a simulation than blindsided by reality.”
Futurists Stuart Candy and Jake DunaganThe workplace is changing – and so too is the workforce. Many digital natives and cross reality (XR) natives – respectively, those aged 27 or younger and 17 or younger in 2023 – are already skilled in using the digital interfaces that are built into video-gaming platforms. When they play games, they create their own worlds and develop social networks. As they do so, they are preparing themselves for the office of the future.
These digital and XR natives will have a competitive advantage in the workplace, because gaming can be an excellent way to practise for the future in low-risk ways.
The power of games
Games are stories to help us make some sense of
The future officeverse will be an archipelago of places, spaces and possibilities
The mechanics and principles of games will be integrated in how we work, in multiple ways. Gameful cooperation will enable us to experiment with co-creating impossible futures. Accelerated by a new generation of gamers growing into leadership positions, gameful literacy – that is, fluency with gaming ideas – will influence ways of collaborating and organizing in every industry. Whether online or face-to-face, gaming will redefine how we connect and what we do together, which will redefine the future of an organization.
The player networks in the book and movie, Ready Player One, show how a complex and messy assembly of players can call gaming networks their social home. Whether in a massively multiplayer online roleplaying game like League of Legends, a multiplayer online battle arena like Fortnite, or a sandbox game without boundaries like Minecraft, these places force players to create squads, sports teams and parties that cooperate. Driven by an intent to win, such player networks increasingly resemble purpose-driven organizations.
In the world of gaming, agile cohorts can be built rapidly to create pop-up communities centred around core values. To encourage a positive culture, many gaming companies have codes of conduct that encourage positive behaviours and discourage bullying or destructive playing. Most have a stated goal of providing an inclusive gaming environment where players can have fun while feeling safe and respected. The parallels to organizations are clear.
The future officeverse will be an archipelago of places, spaces and possibilities. In the officeverse, technology will empower multiple identities and we will be able to write our own stories. Players will try out jobs and discover what they like and don’t like, learning how to be brave in low-risk ways. We can experience working for robots, like in the popular virtual reality (VR) game Job Simulator. Simulations and games allow people to be inside their scenarios, and to practise leadership.
Leaders can also use scenarios and gaming to probe impossible futures and focus on the importance of surprise. As you think futureback about offices and officing, ask: “How can we prepare ourselves to be surprised and hone our agility?” Scenarios, simulations and games
Bob Johansen, Joseph Press and Christine Bullen are all part of Institute for the Future and co-authors of Office Shock: Creating Better Futures for Working and Living (Berrett-Koehler)
allow us to prepare to be surprised – to think the unthinkable. They enable us to experience impossible futures before they become possible.
Think of the way that simulations are already being increasingly used for skills training and to encourage lifelong learning. VR simulations prepare members of fire and rescue services to safely fight fires and rescue endangered citizens, including learning resuscitation techniques. Cybersecurity simulation training is used to test how organizations would respond to cyberattacks. In Mountain View, California, the police department applies state-of-the-art neuroscience research to a combination of VR and biometric devices to give officers means to improve the ways that they respond to calls. We call this voluntary fear exposure, which allows you to practise handling simulated dangers in low-risk ways.
Gameful engagement will empower profound learning experiences. From prototyping store designs to troubleshooting industrial systems to training on-the-ground workers, engaging in this playground will trigger neuroplasticity at a scale never before possible. Gaming will be the preferred medium for building agile mindsets and organizations. And today’s young gamers will be more future-ready than the rest of us.
AI could one day protect banking from human frailties
loans with later rounds of venture-capital funding, rather than using the cashflow from present operations on which established companies rely.
Why should we care about these factors? As SVB matured, venture-capital activity slowed, leaving several of SVB’s fledgling borrowers without the liquidity to uphold their repayment schedule. Moreover, when interest rates rose, bond prices rose accordingly. Thus, to shore up its decreasing liquidity from the flight of customer deposits, SVB had to sell its bonds at a loss.
When it collapsed in March 2023 with $209 billion in assets, Silicon Valley Bank (SVB) became the second-largest bank failure in US history. Government officials and private finance professionals are just beginning the postmortem, yet it is possible that SVB’s failure risked triggering a financial crisis of 2008 proportions. Meeting the bank’s financial obligations has already cost the US government billions of dollars. When the news broke, perhaps many readers, like myself, thought: “Could AI have helped to prevent this from happening?”
In the few months since the launch of OpenAI’s ChatGPT in late 2022, we can already identify a wide range of activities where large language models (LLMs) can be applied. As a university professor, I have seen first-hand how the internet and search engines have changed the nature of teaching and learning: the first article I wrote for this journal was dubbed ‘Make Way for Professor Google’, eight years ago (Dialogue, September/October 2015 – bit.ly/profgooglephilyoung).
When I now read about how students are using ChatGPT to produce AIgenerated research papers and essays, I am impressed. Or, perhaps, depressed. If LLMs can help complete school assignments, compose music and write novels, imagine their potential in business, particularly banking and finance.
Yet, as reported in the Financial Times, the problems that led to the fall of SVB were more a result of human frailties than the lack of deep analysis that AI applications can provide. Allegedly, there
was evidence of weaknesses long before the run on the bank by its depositors. A conventional assessment of SVB’s balance sheet, including financial ratio analysis, indicated such risky factors as the large proportion of its loans made to startups, and the large amount of its investment assets held in long-term bonds.
Professionals with knowledge and experience should have seen these as part of a recipe for trouble – without the help of an LLM. Reportedly, SVB assumed that borrowers from startups could repay their
Lloyd Blankfein, who was chief executive of Goldman Sachs during the 2008 banking crisis, summarized the importance of the human element. “I generally don’t second-guess what someone should or shouldn’t have seen when I have the benefit of hindsight,” he told the Financial Times. “I’ll make an exception in this case, because the [problems] were very apparent.”
Every banking blunder is met with the traditional rounds of finger pointing, and SVB has been no different. One well-publicized argument has focused on the law passed by the US Congress in 2018 that weakened some of the key regulatory powers of the Dodd-Frank Act of 2008, which was passed in the hope of preventing future banking and financial meltdowns.
Like any transformative technology, the growth of AI applications will be fast and furious. AI in finance and banking is no exception. Its advent is already enhancing the customer user experience. It will likely also reduce the sector’s demand for labour: some predict that AI will reduce the jobs in finance by up to a quarter by eliminating the need for routine and repetitive work.
Could AI help finance decisionmakers overcome their human frailties in the making of good business decisions? We don’t yet have an app for that. But, someday soon, we might.
Phil Young is an MBA professor and corporate education consultant and instructorLike any transformative technology, the growth of AI will be fast and furious. AI in finance and banking is no exception
The latest research on financial cycle time underscores the crucial importance of developing corporate capabilities
Writing Joseph PerfettiIs it better to have a good strategy executed poorly, or a bad strategy executed well? It is a question posed by Richard Rumelt in his book, Good Strategy/Bad Strategy, and one I often ask at the start of a session with executives.
To answer, some choose the good strategy option, saying it is more important to have a good direction, even if you must struggle to get there. Others select implementation as the more important option, because they believe they can always pivot to a potentially better strategy later on. In all cases, though, the respondents realize this is a less-than-optimal trade-off – they are choosing between two bad options.
The better choice is to have both a good strategy and good execution. This answer is obvious. Yet many organizations build their strategies and assume execution. Key to understanding where companies go wrong – and how they can go right – is understanding the relationship between markets and core capabilities. That understanding is central to the success of the businesses who top this year’s financial cycle time rankings, the results of which are presented here.
In 1984, Michael Porter wrote his seminal book, Competitive Advantage, which introduced two enduring ideas. The first was that of competitive advantage. Porter described two: either you have cost leadership or you are a differentiated player. The other key idea was his ‘Five Forces’ framework for industry analysis, which helped executives determine the attractiveness of a given market. Studies since have shown that market conditions explain about 50% of companies’ performance, so selecting good markets is critical.
It is an insight echoed by Warren Buffet, the famed chairman and chief executive of Berkshire Hathaway. Buffet says that he does not invest in companies, but rather in industries, because they are more important. If he falls in love with a company in a bad industry, there is nothing they can do, he explains – whereas an average company in a good industry can still do well. His strategy is to first select an attractive and enduring industry and then select the companies within that industry that are going to win, in that order.
But it turns out that selecting attractive industries is not enough: plenty of firms have gone into attractive markets and lost lots of money. The consulting firm Bain looked at this problem. What they uncovered was the importance of capabilities. When a firm went into a market with capabilities, they were three times more likely to be financially successful than when they went into a market without capability. It goes back to Rumelt’s premise: firms need good strategy and good execution.
Amazon’s Jeff Bezos understood this completely. Recognizing that they were critical to his company’s growth, he controlled Amazon’s capabilities at a corporate level. He then identified vertical markets that were suited to these capabilities and used that as his means to grow. What are Amazon’s core capabilities? It is exceptionally good at the supply chain, enabling low-cost and fast delivery. It is also really good at data and digital analytics. Amazon Web Services is the secret sauce that powers Amazon (and it is why Walmart and others have not been able to keep up). Bezos applied these capabilities to eight trillion-dollar vertical markets that were suited to these capabilities. The result: Amazon grew from $281 billion in revenue in 2019 to $514 billion in 2022, and is expected to grow to over $800 billion over the next four years, passing Walmart as the largest retailer in the world.
Having a capability is not just owning an asset. It is often about a process that allows an organization to do something efficiently and repeatedly. We
The relationship between markets and a company’s core capabilities is central to financial success
have developed a model (p63) that outlines the six elements of a capability. To understand how to use the model, consider an example. A pharmaceutical company specializes in large molecule drugs (think infusions or injections), manufacturing them in a facility it owns. But its research and development arm has developed the company’s first small molecule drug (a pill). The company is deciding whether to make the pill at its manufacturing facility, and the question is whether it really can.
The pharma company’s leaders would need to answer a set of questions, reflecting the six arms of the diagram. Are the assets the same for making an injectable liquid and a pill? Is the technology the same? Can the same people make both? Is the knowledge required the same? Is the process the same? And is the required culture the same?
The culture might be the same, but the answer to the first five of these questions is clearly ‘No’. This company does not have the capability to make the new small molecule drug. If it pushed forward, telling itself “We manufacture drugs and this is just another drug”, it would run into severe challenges and have a low probability of success.
Above (clockwise from top left) Southwest Airlines, T-Mobile, Estée Lauder, Volvo, Nike, Novo Nordisk and Coca-Cola are among this year’s FCT gold award winners
In 2017, Duke Corporate Education published the first global rankings of financial cycle time (FCT). FCT measures how often a company can turn $1 of investment into $1 of collected cash from a customer. It is therefore a measure of how long cash is tied up. A faster cycle time suggests more efficiency and the ability to do things quicker. We present the latest annual rankings overleaf (p62).
Our gold medal winner in retail, Costco, had an average FCT of 35 days in 2022. Walmart was at 84 days and Target at 112 days. Think about that in financial terms. In the time it takes Walmart to sell and get paid for one product, Costco has sold two products and is working on the third. This is clearly a competitive advantage for Costco, and it is the result of its core capabilities.
In the airline industry, Southwest Airlines had a cycle time of 194 days, making it, once more, the fastest and most efficient airline. Southwest can turn around a plane – from pulling up at an arrival gate to pushing back for its next flight – in just 35 minutes. Its peers take about 50 minutes. Over the course of a day, given the short hops that Southwest
PCT: production cycle time represents the number of days it takes for a dollar of core invested capital to result in a dollar of sales. FCT: financial cycle time represents the number of days it takes to turn a dollar of operating investment, including leases, into a dollar of sales. Note that some companies are paid in advance and have a negative FCT.
1 Six elements of a capability
Process
Do you have the right work processes to produce the critical results?
Culture
Do you have the right culture/work environment to produce the results needed?
Knowledge
Do you have the data, knowledge, or intellectual property needed?
Assets
Do you have the right machinery, locations and soft assets (e.g. intellectual property)?
typically flies, it can get an extra segment on its Boeing 737s compared to the same plane being used by another airline. This gives Southwest a financial advantage.
To achieve this speed, Southwest has relentlessly focused on its core operating capabilities. For example, flying only 737s allows for crew and maintenance efficiencies. If a crew is delayed, another is available and trained to fly the plane. By contrast, if one of United Airlines’ Airbus A320s was delayed, a 737 crew could not take over. In addition, Southwest does not have assigned seating, which allows for faster boarding. And it flies to many secondary cities, with less airport congestion, reducing the potential for delays.
Above left Apple is a very efficient company, with FCT in 2022 of 15 days
To calculate FCT, we start with the total investment in operating assets and liabilities made by a company and divide by its annual revenue. This gives the percentage of a year that it takes to sell the investment. Multiply by 365 and you get financial cycle time (FCT) in days. Lower is faster.
As in previous years, we also calculate a related metric for each company, called production cycle time (PCT). To calculate PCT, we filter investment to take account of only working capital and net property, plant and equipment. Then we once again divide by annual revenue before multiplying by 365 to arrive at PCT.
People
Do you have the right number and type of people? Technology
Do you have the right technology, analytics, connectivity required?
Apple is another worthy gold medal winner, with FCT in 2022 of 15 days. Tim Cook, Apple’s chief executive, has built one of the most efficient supply chains in the world. Take its best-selling product, the iPhone. Apple pays its manufacturer, Foxconn, approximately $450 to make an iPhone Pro. They then sell this iPhone for $1,000 or more, resulting in an incredible profit margin. The genius is that Apple has very few assets and requires very little investment to make this sale. It is Foxconn, in China, that has hundreds of thousands of employees, that owns the production facilities, and that owns much of the inventory required to produce the iPhone. Apple only has about five days of inventory on hand worldwide. This model has given them a very fast FCT and an extraordinary operating return on investment of over 400% per year.
Finding attractive market opportunities is hugely important to an organization’s chances of success. But going into even the best market opportunities without capability reduces those chances of success dramatically. Organizations must have conversations that evaluate both market opportunity and capability – and as they develop capabilities, they must also use financial metrics to benchmark their progress. Speed is not the only measure that matters – safety, in particular, should not be compromised in pursuit of speed – but it is an undeniably important measure. Tracking FCT over time, and making comparisons against industry peers, is an important way of assessing performance, and ensuring that organizations move at the pace needed to thrive.
Applying 20th-century financial reporting rules to 21st-century businesses means that reported losses are not always losses. They might even indicate a growing firm
Writing Anup SrivastavaThe most important regulation in financial reporting, at least in the US capital markets, can be traced to the stock market crash of October 1929. Public confidence in the markets was shaken. Congress held hearings to identify the cause of the crash and to search for solutions. One of the solutions was the passing of The Securities Act of 1933, which requires public companies to “tell the truth about their business, the securities they are selling, and the risks involved in investing in those securities.” An integral part of this truth-telling exercise was the provision of an audited financial report by the firms, inclusive of an income statement, at least on an annual basis. Most companies didn’t report an income statement before, so this was the first time for many.
Income statements provide details of a firm’s performance over a year. Over time, earnings – the bottom line of an income statement – emerged as the most important output of a financial reporting
system. Share prices would react to earnings per share (EPS), chief executives’ compensation would be tied to profits, banks would give loans based on whether profits exceed debt servicing obligations, and suppliers would extend credit based on the company’s profitability. In this 20th-century world, the reporting of a loss would be catastrophic for the firm, as suppliers and banks might cut back on credit and the shareholders would dump the company’s stock. But this is no longer the case.
Today, almost 40% of firms listed on US stock exchanges report losses year after year, survive well, and even grow faster than the profit-making firms. They include household names like Twitter, Uber, and Airbnb. Amazon, now a trillion-dollar company, reported losses for almost a decade. In addition, numerous unicorns appear each year – companies with valuations exceeding a billion dollars – almost always reporting losses. What has changed? Why, in the 21st century, do losses no longer mean losses?
The reason is that earnings or profits are not a singular metric that could be recorded based on a single transaction. It is obtained by subtracting numerous expense line items from revenues, both of which are calculated after applying a diverse, and often inconsistent, set of accounting conventions.
Revenue recognition requires fulfilment of two conditions: an objective determination of the value of goods and services that have been delivered, and the customer payments being probable. These conditions, however well intended, cause the first point of departure for revenues from numerous events that create value for modern firms. These are events that could create a recurring stream of cash flows, but cannot be recognized as revenues –because no delivery has occurred. The signing of an exclusive partnership with a tech giant, the granting of a patent, approval of a blockbuster drug by the Food and Drug Administration (FDA), securing an influencer’s endorsement of a new product, or even a social media company signing up a million new subscribers: none can be recognized as revenues.
While this limitation applies to all companies, it is especially important for modern technology companies that build a probable future stream of cash flows through a series of serendipitous events that increase the value and marketability of their ideas. It is why we hear about pre-revenue companies with billion-dollar valuations –WhatsApp was purchased by Facebook for about $17 billion when it had never earned any revenues.
On the other side of the financial equation, expenses are calculated using numerous, inconsistent conventions. Most costs associated
Today, almost 40% of firms listed on US stock exchanges report losses year after year, grow fast and survive well
with the procurement and production of physical goods are initially capitalized and presented in an inventory account. These assets are then reduced and reported as expenses when the product is sold. A similar concept is applied to investments in property, plant and equipment (PP&E). Purchase, delivery and installation costs are initially capitalized in the PP&E account and then retired through a depreciation expense account over the expected period of use of PP&E. Thus, the costs related to physical assets are recognized as expenses in different periods from when they were purchased; that is, when those assets produce revenues.
Over the last 25 years, another class of outlays has emerged as the most important one for modern technology companies. These expenses are recognized immediately, and not necessarily when they produce revenues. They include: research and development (R&D) expenses, process improvement, information technology, software development, advertising, organizational strategy, acquisition of customers, brand building, and hiring and training personnel. To the extent that these investments are made in expectation of future benefits, the earnings – calculated as revenues minus expenses – become meaningless in assessing firms’ true profitability. The concept of profit margin becomes meaningless too, as it provides no indication of what future profit margins will look like. In that regard, tech companies are utterly different to businesses such as Walmart, where profit margins would be highly stable and predictive of future profit margins in a steady-state economy.
The non-correspondence between revenues and value-creating activities, and the immediate expensing of future-oriented investments, increasingly applies to firms listed in the last 30 years, which now constitute over 80% of all public firms in the US. As a result, newer cohorts’ profits and profit margins – especially when negative – offer few clues as to future profits. Investors start ignoring the so-called losses, firms start reporting what are known as non-GAAP numbers (see ‘Mind the GAAP’, Dialogue Q4 2022), and executive compensation is increasingly tied either to stock or stock options, or to a highly adjusted earnings number.
That is why reporting losses year after year is not catastrophic, as it used to be in the 20th century. On the contrary, it could be a sign of a growing firm. A modern technology firm has two aims. First, to create a library of intellectual properties and assets, such as subscriber network, so that it is an attractive acquisition target for another tech giant. Or second, to rapidly expand
Anup Srivastava is Canada research chair in accounting, decision-making and capital markets, and full professor at Haskayne School of Business, University of Calgary
its market and market share to become the sole supplier in the market, and earn winner-takes-all profits – consider how LinkedIn or Facebook have established themselves as the sole suppliers in their markets. As an investor or a stakeholder in a company, you are better off studying whether a firm can dominate the market it is trying to create, rather than focusing rigidly on its losses.
When it comes to money, what does ‘good’ look like? What does success mean when we think about our relationship to our finances?
One typical response will hinge upon the word ‘more’. Accumulating wealth, buying a bigger house, winning a promotion and a higher salary. Another response could be based around ‘less’. Lower bills, lower charges on financial products, less time spent thinking about personal finances.
But what if we applied a completely different success criteria? What if we judged our relationship with money by whether it makes us happy? To approach that question from a business perspective: what is the problem of money that the financial services industry is solving? Are products and services focused on more, or less – or on happy?
Many financial services companies attempt to help their customers manage their money through financial education. The term financial wellbeing is often used in this context, as a concept that
includes being better at managing finances and debt (which I would argue is better described as financial resilience). It also covers many other aspects of money, including our money beliefs, our behavioural biases, and money distractions.
Only when we understand the sources of happiness (short-term) and wellbeing (longer-term) can we really understand the role that money plays in helping to achieve these. We also begin to realize how financial education often starts in the wrong place. A wealth of research about human happiness helps us to better understand the problem of money, and the shortcomings of the financial services industry in helping to solve it.
Making great financial decisions is not something humans are built to do. In many ways, we have only needed to think about our financial futures for the last 40 years or so. In many parts of the world, life expectancy has boomed – but all those extra years are when we are not earning. Families have stopped living together all their lives, so income is needed beyond working age. We now need to make financial plans for the future that we are not equipped to make.
That goes to the very heart of how we think about money. Neuroscience research shows that money decisions are fearful decisions. We make them with our gut (so-called ‘System 1’ thinking, see p76-79) while knowing those decisions will have long-term ramifications. Other research shows that we find it difficult to think about our future selves, and therefore to plan for the future.
We can therefore see that the first part of the problem of money is that we are not equipped to solve it ourselves.
The second part of the problem relates to the role that money plays as a generator of joy. Of course, money can have a direct part to play in generating wellbeing. Being able to afford a holiday or to spend time with loved ones requires money. Improving financial resilience can reduce money worries. But research also tells us that the extent to which more money makes us happier gets smaller as we have more of it.
The sources of long-term wellbeing are relatively simple, it seems, including living a life with meaning and purpose, and social interactions. Similarly, short-term happiness comes from things that don’t cost money. Being kind to others, being outside, cuddles: none of these require wealth. And yet, one look at magazines, social media and advertising tells us that ‘more’ remains the mantra.
If the first part of our problem with money is that we are not built to make good financial
Making great financial decisions is not something humans are built to do
decisions, the second part is that our approach to money is often focused on its accumulation, not on using it to generate wellbeing.
We need help when it comes to our relationship with money. The help that financial services firms offer, however, tends to come in the form of information, not insight. This might be wealth managers who only talk about investments, or banks who provide education only on being ‘in control of your money’, or on how to take out loans. This is not solving the problem of money.
To help customers to be happier, not just wealthier, financial services need to address issues that relate to the sources of joy. Education on what those sources are would be a great start. Financial wellbeing – defined in the broadest terms – should be the starting point of financial education, not an add-on.
It is widely accepted that if we teach people about nutrition and its effect on health and energy levels, there is an increased chance that they will
eat healthier. It’s not a huge leap to think that a similar approach could work for our relationship to money. If we teach people that buying endless stuff only gives very short-term hits of joy, and that there are better sources of long-term wellbeing, they might manage their money better.
Similarly, if we help people to better connect with their future selves, they are surely more likely to put money into savings products. And if we help people to recognize that some of their money beliefs are not working in their best interests, they may make better financial decisions.
In this way, we could both equip people to make better financial decisions, and help them to understand that a better financial decision is one that is focused on their wellbeing.
If we make achieving wellbeing the success criteria for our relationship with money, we solve the problem of money, and the world will become a happier place. But it is a task that should not be left to us to tackle alone as individual consumers. We should have the full support of the financial services business that serve us.
PHILIP KOTLER
is known around the world as the “father of modern marketing” and has been a Professor at the Kellogg School of Management at Northwestern University for the past 50 years. He is the author of over 80 business and marketing books.
GIUSEPPE STIGLIANO is the Global CEO of Spring Studios, a leading communications agency in fashion, beauty, lifestyle and luxury. Prior to that, he was CEO of Wunderman Thompson Italy.
RICCARDO POZZOLI is an entrepreneur, advisor and investor, who has founded and advised a dozen startups in the past ten years, innovating within the fashion, media and food industries.
A HANDBOOK OF NEW RULES BY THE GURU OF MARKETING – PHILIP KOTLER –AND TWO LEADING PRACTITIONERS. Original contributions and insights from fashion leaders, including Domenico De Sole
(President of Tom Ford International), Leo Rongone (CEO of Bottega Veneta), Alfonso Dolce (CEO of Dolce&Gabbana), Remo Ruffini (CEO of Moncler), Jonathan Akeroyd (CEO of Versace) and Francesca Bellettini (CEO of Yves Saint Laurent).
Digital technology is changing the world, but don’t be too hasty to ditch the old ways of doing things
Iwas recently introduced to a new phrase that is supposedly catching on in the tech community: meatspace. It describes the physical world – the tangible counterpart to the virtual or digital world. To me, it sounds slightly derogatory, similar in tone to what I was once told was common parlance for passengers among airline staff, “self-loading freight.”
Now, I love much of the digital world and what it allows me – and billions of others – to do. I’m a heavy user of many of the generation of new brands it has created. However, as a sci-fi buff, I also have some sympathy with Stephen Hawking when he said, “Success in creating effective AI could be the biggest event in the history of our civilization. Or the worst.” The fact is we don’t how the digital world will change our world, as Hawking added. “We cannot know if we will be infinitely helped by AI, or ignored by it and sidelined, or conceivably destroyed by it.”
So, for now, it seems right to reflect on what we hold dear in the real world. To paraphrase Marc Anthony from Shakespeare’s Julius Caesar: “Friends, avatars and marketers, lend me your earbuds; I come not to bury the virtual world, but to praise the meatspace.”
Let me start with the benefits of real-world connection when working with other people. Teams, Zoom, Miro and all the other platforms can make working with colleagues near and far an effective experience – and one that is more environmentally-friendly than the travel-reliant business meetings of the past. However, it still doesn’t fully compare to meeting, talking, and working with other people physically.
In a creative industry like marketing, the opportunity to spark and build ideas together is more fruitful for many people if they have other ‘meat’ in the same room. Energy levels are higher, and people can’t pretend they are paying attention
while they’re actually doing something else, like answering the never-ending stream of emails.
On a more day-to-day basis, working remotely can be useful, although the jury seems to be split on whether or not it really yields increased productivity. Undeniably, though, it does improve numerous aspects of modern life. It does away with the daily commute – a double benefit of generating less pollution and saving time. Personally, my commute dropped from an hour each way, to a 30-second walk through my garden to my converted shed/workspace. It also gives people a bit more freedom to manage their work hours, which can help with things like the school run.
Surveys have suggested that many leaders still want to see employees spending more time in the office, often for reasons of communication and creativity, as well as for sustaining culture. My prediction is that, where feasible, many industries will move to a two or three-day office week, with the remainder spent working from home or remotely. The implications are enormous.
The final – and perhaps most important –reason to praise meatspace is, that like all humans, I am a social creature; in my case, one who cherishes interactions with the world in its many shapes and guises. I enjoy meeting people, whether old friends and family, or new people from different places, backgrounds and cultures. Simply put, I enjoy being in the real world.
Augmented and virtual reality will have a role in my future life. But I’m not prepared to give up my meatspace any time soon.
In a creative industry like marketing, the opportunity to spark ideas is more fruitful with other ‘meat’ in the room
When consumers are under pressure, retailers need to focus on their customers, rather than rushing to make across-the-board price cuts
Writing Doug KofoidThe global business landscape has been hit hard by inflation in the wake of Covid-19 and the war in Ukraine, and some economies are teetering on the edge of recession. Such uncertainties do not come with a handbook – no two downturns are exactly the
same – so business leaders must brace for a bumpy ride ahead. That often takes the form of cost-cutting and a highly cautious approach to new investment, particularly in retail, as leaders seek to buffer their businesses against the poor economic climate. Marketing and communicating to customers are often first under the knife.
Yet that may be a mistake. Thanks to digital technology, marketers now have the tools at hand to shift strategy away from indiscriminate costcutting, to more productive areas of focus. We can turn to data to better understand what matters most to our customers in tough times.
First, let’s examine decision-making during a recession. The margin for error is reduced as businesses cannot afford to make any mistakes, which there may be room for in a healthier, growing economy. This is when data granularity comes into play. Businesses need to collect data at a level of detail that allows them to understand the specific drivers of their business, and to track these drivers over time. By doing so, decision makers
can gain insights into which areas of their business are most vulnerable to economic downturns, and develop strategies to mitigate these risks.
For example, retailers that collect sales data at a high level of granularity (such as by SKU number or by store) can identify which products or locations are most impacted by economic trends. This information can then be used to make decisions about which products to discount, which locations to close, or where marketing spend can be allocated. Without this level of detail, businesses may make decisions based on incomplete or inaccurate information, which can lead to costly mistakes, or worse, missed opportunities.
Next, we need to look at how businesses treat their customers. As customers become more pricesensitive, businesses are competing for every penny. A common approach is discounting products across the board. However, this can prove shortsighted. It all comes down to how businesses are slicing up their data. Too often, we see businesses make decisions based on the average of a cohort of customers, rather than focusing on the journey of individual customers. Poorly performing products and services are hidden behind the average, and businesses miss opportunities to engage with their most high-value customers.
In the world of retail, the traditional approach to decision-making might have been to look at geographic segments, product lines or channels independently, asking questions like: “How is the London store doing?”, “Is the new range performing?” or “How are online sales doing vs store sales?” Today, the customer journey is not so simple. Customers are not restricted to a single channel or a single geographic region: a customer based in New York could visit a store in London while on holiday, physically try on a jacket, and then purchase it online when back home. When brands have the ability to track this journey and understand when and how a customer makes their purchases, they’ll be able to make more meaningful customer-centric decisions on when to apply discounts that matter, and which channels to use when communicating with consumers.
Investing in entering new markets during a recession may not seem like an obvious choice when times are tough. However, it is a strategy that can help businesses diversify their revenue streams, reduce their dependence on a single market and buffer against volatility in the global market. Of course, determining which new markets to enter is not a baseless decision. It’s prudent
to analyse market data and understand what’s happening locally to take advantage of pricing opportunities. Let’s look at cost-of-living vs cost-of-apparels as an example. The graph above (produced using Edited’s proprietary retail decision intelligence tools) details the average price of a full women’s outfit – a t-shirt, trousers, jacket, sneakers, underwear and a bag – on the mass market in two different regions. It’s plotted against Numbeo’s Cost-of-Living Index, which includes localized data on the cost of groceries, entertainment, transportation and accommodation for the most populous city in each market.
Such analysis can unlock key pricing opportunities. For example, products are most expensive on average in South Korea because of shipping costs and taxes of western brands. However, the average price of an outfit outstrips the Cost-of-Living Index. That suggests South Korean consumers may have more disposable income to spend on fashion and are more willing to pay full price compared to those in the US or UK. Brands entering this market may want to contemplate a higher pricing model than they would in their own region. It demonstrates that leaders should avoid a blinkered focus on reducing prices as the only option to hand.
Ultimately, businesses that are looking to thrive during a recession need to understand and stay closer to their customer than ever. A data-informed strategy that is focused on customer-centricity can help drive sales, and build customer loyalty and unlock new markets, despite a challenging economic environment.
Businesses that are looking to thrive during a recession need to understand and stay closer to their customer
insight in business is through the lens of Charles Darwin. Darwin’s theory of evolution was largely based on what was known as incrementalism: the gradual, linear accumulation of small changes over the long history of the evolutionary record and human change.
Digital technology offers marketers more data than ever about their customers, but it is no substitute for the creative state of mind that leads to great insight
Writing Anthony TasgalInsight is something that everyone wants, but hardly anyone understands. It is one of the most contentious topics in marketing, communications and research.
Everywhere you look in the business world, insight has taken on the aura of an elusive Holy Grail. Research departments have re-branded themselves as insight departments, and entire conferences dedicated to understanding and promulgating insight have sprung up, promising new generations of practitioners that they can uncover the magic formula of insight, and how to spot, discover and tame it.
There’s been an even greater focus on insight with the advent of big data. Shouldn’t that, in and of itself, feed our insight-addiction? Well, no. There’s simply no automatic process whereby data gives insight; no effortless shift from data to ‘ta-da!’ Too often the sheer quantity of data means that insight is drowned in the stormy seas of information as we mistake quantity for quality. Staring long and longingly at data dumps is not the answer.
So, why are intrepid insight-hunters still looking for this elusive vision – and how can they advance their search? Here are some ways to help cast insight in a new light, and provide a beacon for insight-explorers.
One way of looking at the transformative power of
We have to unlearn our obsession with dining at the ‘all the data you can eat’ buffet
A rival theory was that of ‘saltation,’ which suggested abrupt, non-linear changes in the fossil record. Language fans will spot the etymological links to sauter in French, saltar in Spanish and salire in Italian, all meaning to jump, leap or climb. It also reminds us of that well-known cornerstone of communication theory, ‘salience,’ or the ability for a brand or piece of messaging to jump out at us. Insight is about seeking a jump – or, as Douglas Hofstadter calls it, “jootsing”: finding something that ‘jumps out of the system’ at us.
From the artistic tenet of ‘breaking convention’ to the theory of deep-immersion ‘flow,’ there is an inherent element of creativity and subversion at work in insight.
What I call ‘insightment’ is a culture that creates insight and depends on the ability to perceive new and unexpected connections.
Let’s delve into some more etymology, beginning with the word ‘symbol.’ Its origins lie in the Greek word symbolon, with a meaning rooted in ‘to throw together.’ Symbolically, insight works in a similar way. When we can put two parts together to reveal a whole, there is an integration. We are rewarded with an ‘Aha!’ of completion and recognition.
As I like to put it, information is to be collected, but insight is to be connected. Yet, in a business world defined by pragmatic determinism, this creative urge often finds itself swept under the carpet of rationality and efficiency.
There are three key characteristics of the successful insight-hunter.
1Wandering One of the best ways of allowing your brain to make analogies is by wandering. I’ve written frequently about the etymology of ‘error’: the origins of the word have nothing to do with mistakes, failures or any other form of inadequacy. Instead, it comes from a root meaning ‘to wander.’
Too often, especially in brand comms, marketing and sales, we become prisoners of one market, one mindset. Wandering means that the brain can detect patterns, similarities, differences and commonalities that can create connections, which may prove valuable when it comes to originality and innovation. The searcher for insight
must ensure that they wander outside of the comfort of their own domain.
2Impertinence Another essential ingredient for insight is a sense of impertinence. Again, this gives us the opportunity to slip in a bit of linguistic or etymological chicanery. If something is pertinent, it is relevant and applicable to a particular matter or issue; it pertains. Jacob Bronowski, the brilliant Polish-born mathematician, historian of science and humanist, highlighted this play on words and ideas when defining science in The Ascent of Man, the landmark TV series and book. He put it this way: “That is the essence of science. Ask an impertinent question and you are on your way to the pertinent answer.”
Whether we’re talking about finding a new brand insight, hoping to win a pitch by finding a new angle for a client, or just finding a new point of view or direction, all of these can be initiated by applying some impertinence. 3
Storytelling As someone who has written two books on storytelling for business, you
Anthony ‘Tas’ Tasgal is a trainer, author and strategist. His latest book is The Insight Book (LID Publishing)
can’t be too surprised to find me suggesting this is an essential component of insight. Achieving excellence in insight is not just identifying it, but successfully transmitting it. I’ve witnessed many researchers, planners and clients trying to propose their insight to the higher-ups, but failing to gain traction. Why? Not because the insight itself wasn’t powerful and transformative. Rather, it was because they failed to create the necessary energy and persuasive power to make their case. This is where great storytelling is so essential.
When we’re trying to convince anyone of anything, we can never rely on the brute force of facts. Empathy is essential, so that at the human, emotional level, there’s a feeling of understanding that goes beyond objective assessment of facts. Storytelling is the ‘empathy engine’ par excellence.
We have to unlearn our obsession with dining at the ‘all the data you can eat’ buffet. We must appreciate that insight is a creative state of mind, rooted in seeing new links, and drawing on traits that can both be developed personally and shared among a company culture.
“[Simone Fenton-Jarvis] uses a wealth of personal experience and the latest psychology insights to rethink the purpose of the workplace and how we can create spaces that allow us to bring our best to every visit.”
ANTONY WILTSHIRE Director of Workplace, UK&I, Edelman
“
If you want to truly understand what it means to bring your full self to work, how the brain is both rational and emotional, what good leadership looks like, how to detect a supportive workplace culture and what roles space and technology play, this book is for you.”
DR
KERSTIN SAILER
Professor in the Sociology of Architecture, The Bartlett School of Architecture, University College London
When Jack Welch landed as chief executive of General Electric in 1980, the company had 411,000 employees. By 1985, the firm was down to 299,000 people, earning Welch the nickname Neutron Jack – because while the buildings were still standing, the people were all gone.
The business might have been leaner, but it was also meaner. Some of the very best people at GE started to decamp, crushed by heavy workloads and poor morale. Through a series of exit interviews, Welch learned that many employees regarded GE as an unbearable place to work. As one departee said: “The people are gone, but the work isn’t!”
Welch commissioned a study to determine how much of the work undertaken at GE added value to customers. The answer? Only 65%. Over a third of GE’s labour was essentially wasted. The study prompted GE’s Work Out initiative, one of the largest transformation projects of its kind in US history. Business schools were appointed to experiment with the 15 lines of business in which GE was operating, bringing academic rigour to the effort and enhancing Welch’s reputation as an innovative thinker to boot. The programme became a poster child for ridding organizations of useless work and bureaucracy. Humans hate wasting time and love saving it, so taking labour off people’s hands is one of the most inspiring things any leader can do.
I was in my doctoral programme for part of the Work Out process. Our team worked on one of GE’s least sexy divisions: distribution. Nonetheless, the leadership proved creative and inspiring.
Harry Stonecipher, the then head of the group, decided that nobody would take the change initiative seriously if leadership failed to demonstrate their own commitment to it. So, he took his team on a three-day retreat with the goal of tackling their own variant of useless work.
On the first day of the retreat, after being briefed on its purpose, every person in leadership was required to describe every meeting they had on a regular basis: who
was there, what decisions were made and how the meeting materially resulted in positive momentum. The outcome of Day 1? A list of the many meetings that were useless and would be abolished.
On the second day, attendees outlined all the approvals that had to come to them. The approval process followed a common pattern. At some point in the day, an underling would hand over a stack of papers to be approved, which the more senior person flipped through and signed without looking at the contents. The outcome of Day 2? A commitment to move approvals to the level at which the decision was being made.
The final day developed in a similar fashion. This time, everyone showed all the reports they received regularly and what information they gleaned. Reports took the form of a massive ream of computer printout. The section that highlighted the useful takeaways was tiny. The attendees resolved to eliminate many reports – and explore other ways in which necessary information could be shared.
When the executive group returned to the office, they held a town hall. They highlighted to the entire staff the commitments they had made, and said everyone needed to be prepared for similar pruning of useless work. And it worked – GE’s distribution division became a model for many of the practices that made the firm an iconic example of transformation during the Welch era.
Cutting red tape and eliminating waste might be an old lesson, yet it remains too rarely executed. I know of no organization that isn’t wrestling with the pain of meaningless work and excessive bureaucracy. Start by abolishing useless meetings, reports and approvals, and see how it improves your organization and inspires your people.
Rita Gunther McGrath is professor of management at Columbia Business School
Cutting red tape and eliminating waste might be an old lesson, yet it remains too rarely executedRITA GUNTHER MCGRATH ON STRATEGY
Haste often leads to wrong decisions. If you want to get things right, don’t rush
Writing Marce FernándezImagine you are the benefits manager in your company. You receive an offer from a local bakery to supply sugar-free plantbased pastries for consumption by your organization’s employees when they are in the office. You know that employees often reach for less-healthy snacks to kill their hunger, such as doughnuts or biscuits that contain high doses of sugar and saturated fats. What would be your reaction to the proposal?
Following the “dual theory of thinking” popularized by Nobel laureate Daniel Kahneman in his famous 2011 book, Thinking, Fast and Slow, you could take two alternative paths: follow
System 1 and respond quickly, or System 2, and respond slowly. Let’s look at the mechanics of each system as applied to the case.
What happens when you use System 1? Your mind makes a decision based on your previous similar experiences, the information available, your values and prejudices, and your personal situation at the time. You may have heard of another company that tried to innovate its employee benefits, with poor results. You may not know the nutritional composition of a typical doughnut compared with the proposed sugar-free plant-based pastry,
or the effect of excess saturated fat and sugar on employee performance. You may not follow the recommended patterns of healthy eating and living yourself. And you may feel under pressure to decide quickly, as your next meeting is about to start. So, when you receive the offer of these alternative products, you decide not to waste your valuable time analysing the pros and cons. Your decision is to reject the proposal without even considering its possible advantages.
What happened? In this case, heuristics took over the decision process. You preferred not to spend resources on studying the case and your mind identified some reasons that seemed
compelling. You felt confident enough to make a quick decision without needing to acquire more knowledge or devote more thought to the matter.
Let’s take the alternative approach: System 2. You consider that the bakery’s proposal deserves analysis because of its innovative nature and its possible benefits for employees’ health. You study the type of products that colleagues are accustomed to consuming in the office, the frequency with which they eat them, the best and worst ingredients for their performance, and evaluate the bakeries in the vicinity, as well as the range of healthy products available online. You also consult a nutritional advisor to get an expert point of view. You then go
When making complex decisions, a short period of unconscious thinking leads to a better decision
to your employee representatives and discuss with them the possibility of including healthy snacks in the company’s benefits programme. You also talk to your boss to inform him or her about your project. The problem is that while the staff representatives are willing to help you choose the best option, your boss does not seem at all happy with the initiative due to current budgetary constraints. The decision gets complicated.
What has happened now? You have assessed the decision as important and undertaken a thorough analysis process, including the involvement of other stakeholders. But you overlooked a critical factor that might have suggested it was not the right time to start the project: the resources available to fund the programme.
By using System 1, you invested no effort but missed out on the potential benefits of the proposal, while by following System 2, you have spent a considerable amount of time reaching a dead end. Could there be another way?
For my book The Wrong Manager, I conducted a survey of managers and executives. The first thing I asked them was to give an example of a management mistake they had witnessed. Two questions were particularly significant. One asked, “How do you think the decision in your example was made?” The most common answer, for 41% of respondents, was that the decision had been made “after a short period of reflection”. Beyond that group, 35% said that it happened “after a thorough process of analysis”, while 24% chose “quickly, once the decision maker understands the situation”.
In another question, I asked: “How do you think most of the important decisions of an organization are actually made?” Almost half, 49% of the respondents, answered that most of the important decisions are made “after a short period of reflection”. It was again the most common answer. Similarly, 36% picked “after a thorough
There are multiple solid reasons for making decisions more slowly. Time allows you to:
1 Reach a be er understanding of a problem or situation
2 Avoid falling into the trap of heuristics
3 Evaluate the objectives to be met by a decision
4 Consider the key elements necessary for a sound decision
5 Identify the possible reaction of the parties a ected
6 Have second thoughts
7 Evaluate the di erent alternatives more fairly
8 Design creative solutions to the problem
9 Visualize the implementation of the decision made
process of analysis” and 15% chose “quickly, once the decision maker understands the situation”.
The survey seems to confirm that the most frequent position from which a manager makes a decision is somewhere in between the two systems of Kahneman’s dual theory of thinking. I describe this as an “In-between System”. The table below shows how this intermediate decision-making system would be defined.
The In-between System is clearly related to the concept of “unconscious thinking” that Ap Dijksterhuis and some others have investigated. According to his experiments, when making complex decisions, a short period of unconscious thinking leads to a better decision. The human mind is not able to consciously manage a large amount of information in a short time.
However, through unconscious thinking each piece of information is associated and integrated with the rest, facilitating diagnosis and, consequently, leading to a better solution. Unconscious thinking allows decision-makers to dig deeper into the available information and work out new solutions other than the obvious ones that emerge as soon as a problem is presented.
In our example of healthy bakery goods, if the decision maker had let his or her mind run its course for a while, he or she would probably have achieved a better diagnosis of the problem, have found a way around the temporary budget constraints, and taken advantage of the healthyeating proposition made by the bakery – and all without the need for a time-consuming in-depth analysis of the matter.
In today’s fast-paced business environment, speed seems to be part of the essence. The pressure to be efficient is high and many leaders feel the need to move fast to remain competitive.
Speed in decision-making can lead to a dynamic organization that is able to adapt to changing market conditions, but it can also lead to hasty and ill-considered decisions. Leaders need to strike a balance between speed and thoughtfulness, and this is a real challenge.
The right approach requires taking into consideration the different kinds of decisions a manager faces. In The Wrong Manager, I propose a chart (right) to help sort out the relevant factors. The chart is based on two key variables.
Context can be certain or uncertain. A certain context would be when the problem can be solved by numerical computation so that the result is known with a high degree of probability. In the case of healthy cakes, if you could know the effects of unhealthy snacks on employee performance, you could compare it to the budget for healthy cakes, and assess if the costs would pay off. By contrast, the outcome of a decision in an uncertain context is unpredictable, which is the case with most management decisions. Complexity may be minor or major. This depends on the factors to be taken into account, the parties involved, the range of options, the sophistication of the problem conditions and the difficulty in foreseeing cause-effect relationships.
In a certain context, a decision-maker would have to try mathematical/statistical or financial tools to reach an objective evaluation. Applying heuristics to such decisions is clearly a lousy move, and following a thorough decision process would be a foolish waste of time. There should be no discussion here. But what happens in an uncertain context?
According to the chart, a complex decision in an uncertain context requires the tools and skills normally associated with management. Applying ‘management’ to a decision means defining an appropriate objective, establishing a set of reasonable alternatives, gathering the relevant information, and conducting an adequate analysis to reach a well-argued solution. If you were to apply heuristics to a managerial decision, the chances of making the right decision would be greatly diminished.
When an uncertain context and minor complexity come together, we can apply heuristics. This is a field widely explored by decision theories; it is where intuition and mindset play a key role. Heuristics are hugely valuable because they can
save managers lots of time and resources. But they can also lead to severe problems as a consequence of many factors, among which I would highlight cognitive biases.
The effect of cognitive biases on decisionmaking is widely known. They distort our perception of reality and influence our judgements. They can cause decisions to be based more on our subjective beliefs and past experiences than on accurate information, and often lead us to make erroneous assumptions and overlook important facts.
This is where the In-between System and use of unconscious thinking come into play, in place of pure heuristics. The recommendation is often simple: cool off, go on with other activities for a while, and come back to the decision later. If you can (and be honest: you usually can), wait a little longer and sleep on it, because tomorrow’s decision will most likely be better than the one you are about to make today. Pressure and haste are always bad counsellors when it comes to making any choice.
We have seen that rushing is not a good idea when it comes to minor decisions, let alone major ones. It seems obvious, but the belief that success belongs to those who move quickly and make decisions on the fly is common. Leaders should remember that the ‘rush to success’ mentality can lead to the wrong decisions. Taking the time to slow down and carefully consider all available options can yield a significant handful of benefits and, ultimately, greater success.
Missing an opportunity by being slow to decide can happen once in a lifetime; making a mistake by deciding too hastily can happen all the time.
Marce Fernández is author of The Wrong Manager: Management mistakes and how to avoid them (LID Publishing)
Leaders should remember that the ‘rush to success’ mentality can lead to the wrong decisions
As policymakers wrestle with the a ordability of state pensions for a growing old-age population, a wave of mass protests have sparked concerns about a crisis of democracy
Land area
643,801 sq km (247,270 sq mi)
Population
68.5 million
Capital
Paris (pop. 2.1 million)
GDP
US$3.128 trillion (2022)
Economic record
+2.6% (2022)
Forecast
+0.7% (2023 forecast, OECD, March 2023)
GNI per capita
$52,210 (2021)
Currency
Euro (EUR)
1 EUR = 1.09 USD (April 2023)
Unemployment
7.2%
Life expectancy
Women 83
Men 80
Official languages
French
68%
Popular opposition to Macron’s pension reforms (Elabe poll, 20 March 2023)
457
People arrested during protests on 23 March 2023
1.2m
Estimated number of people to have attended protests against pension age changes in March 2023
€13.5bn
Potential French pension deficit by 2030 without reform
903
Fires lit on Paris streets during the protests of 23 March 2023
Is this reform accepted? Obviously not. Despite months of talks, a consensus wasn’t found, and I regret that President Emmanuel Macron defends his pension reforms, April 2023
62 Previous state pension age
64
State pension age introduced by President Macron, coming into effect by 2030
28%
French pensioners’ projected population share in 2050. (Southern Europe 36%, Japan and South Korea 38%)
89.4m
Tourist arrivals to France annually, making it the world’s most-visited tourist destination (2018 data)
10%
Tourism’s share of France’s GDP
45,000
Potential visits lost through one day’s closure of the Louvre, Versailles and Musée d’Orsay in Paris due to safety concerns
€58bn
Spending by tourists in 2022
10,000
Tonnes of uncollected rubbish during the Paris protests over retirement reforms
The sporadic acts of violence of some protesters or other reprehensible acts… cannot justify excessive use of force by agents of the state
Dunja Mijatovic, commissioner for human rights, the Council of Europe
We are living through a serious democratic crisis
Laurent Berger, head of the CFDT union
What have men got to do with it? Rather a lot, as it turns out. That was the message from Julia Gillard, 27th prime minister of Australia turned chair of the Global Institute for Women’s Leadership – at Duke Corporate Education’s recent Lead with Her conference.
Gillard – the first and only female prime minister of Australia – used her keynote speech to call for men to mobilize alongside women in the fight against gender inequity.
“The research shows that if a man calls out a gendered problem – he points to a lack of gender equality – then something sticks,” Gillard told Lead with Her, which was staged in London, and online, this spring. “He will be more likely to be believed than if a woman calls it out.
“In some ways, I do find that a bit galling, but I think it springs from the fact that if a woman points to something that is gendered, the cynical voice in the back of our brains says to us, ‘Is she saying that because she really believes that? Or is
she saying that because she’s trying to get some form of personal advantage at work?’ People think about the conflict of interest.
“But if a man says it is, he is just believed, he seems to be calling it out with no conflict – he’s the sort of person who cares about his work colleagues and cares about points of principle.
“This is all upside for men. The more they get involved, the more they say, the more they do, the better it is for them. So, I would urge men to think about that – and to double down on what they’re doing now for gender equality.”
The quota dividend
Gillard’s call to arms – for men to be vocal allies in the global battle for gender equity – reflected another high-powered call for direct action: by former Lloyds of London chief executive Dame Inga Beale.
After returning from a sojourn in Australia, Dame Inga was offered a promotion because, she said, she was the only female candidate and the recruiting manager had to fulfil a quota. She initially refused, but eventually agreed to take the post: “It was only years later, when I got to a sufficiently senior level, that I realized there were targets.”
Dame Inga credits the quota system for her eventually reaching the top. “Still today we are debating it,” she said. “Why? If I had not happened to join that company, by being the only woman and therefore being promoted, I would never have later become the CEO of Lloyds of London, because, like every other company in the City, the behaviours, the biases, the societal pressure –nothing there was going to make it easy for any woman to make it.”
Indeed, Dame Inga became Lloyds of London’s first female chief executive in its then 328-year history in 2013. She stepped down in 2018.
Dame Inga’s was among a multitude of inspirational stories at the event. A panel on mentoring, hosted by event partner the International Women’s Forum (IWF), revealed the benefits for both sides of the exchange.
“The mentors and mentees learn from each other – which is why we refer to it as reciprocal mentoring,” IWF UK president Marty Rolle said. “One of our mentors said, ‘I gained more insight into how and to what extent the racial element influences a woman’s career development.’”
The research shows that if a man calls out a gendered problem… then something sticks
Julia Gillard, chair, Global Institute for Women’s Leadership
School of Business, reminded leaders that there was much work still to do. “There are exceptions. But, as a whole, we have been falling well short of greatness in building teams, for the simple reason that we have done a poor job of attracting, welcoming, retaining and promoting women,” Boulding said. “So, our teams are not as great as they could be. We have put an unnecessary cap on the potential of those teams.”
If Professor Boulding defined the battleground, Duke Corporate Education chief executive Sharmla Chetty issued the call to arms. “We are strong as sisters together, as friends, as allies,” she told delegates. “We have the power of our collective voices and the strength of shared experience that
Above Speakers at the event included former Lloyds of London chief executive Dame Inga Beale (centre) and Julia Gillard (centre right), 27th prime minister of Australia, and chair of the Global Institute for Women’s Leadership
we can use to help each other. Let us commit to this change. Let us speak out when we see injustice. Let us stand up for what is right, every single day.”
To access a full recording of the event and a highlight reel, please visit dukece.com/lead-with-herempowered-voices
It’s time to rethink how we construct our careers and manage our lives
Writing Patrick Woodman
Variety, we are told, is the spice of life. Yet how much of modern working life lends itself to that?
The dominant model for ‘getting on’ is still based on the ideal of fairly linear progression within an organization, or organizations, over time. But that model is breaking down. In its place Christina Wallace proposes a “portfolio life”, in which we combine diverse interests and talents.
Her analysis starts with the shortcomings of late-stage capitalism. If the Great Resignation meant anything, it was an attempt by millions to find a better place for work in their lives. But mere job-hopping may not be enough to find the better experiences we crave. Instead, she says, we need to change how we approach our work.
The watchwords here are identity, optionality, diversification and flexibility, and Wallace draws extensively on her own career, which has combined her love of the arts, technology and business. She outlines how to home in on the essential elements of your portfolio life, before exploring her model for a personal balanced scorecard, inspired by Clay Christensen’s call to apply business techniques to personal challenges.
The book has relatively little to say about how organizations might adapt to employees who seek a portfolio life, but that is perhaps a topic for another day.
Wallace does emphasize, however, her ardent belief that contrasting experiences enhance employees’ abilities. Eyecatching examples – like the NASA research scientist who switched to write a book on advanced origami, or the quantum physicist who is also a professional ballerina – underline the point.
Some may wonder if a portfolio life is truly for all; not everyone is fortunate enough to have skills that could sustain diversified income streams. Yet surely many more of us could think more ambitiously about the role work plays in a life welllived. If you’re asking questions about your next career move, this book could help.
The Portfolio Life: FutureProof Your Career and Cra a Life Worthy of You Christina Wallace (Ebury Edge)
BIG IDEAS PERRY TIMMS
One of the great early management theorists and practitioners, Henri Fayol (1841-1925), emphasized the importance of well-defined organizational structures. His ideas led to the organogram, which we might now call the org chart.
The typical org chart’s hierarchical boxes and lines of management control have endured over the last century. Many company adaptations are merely realignments of the org chart. Yet what the classic org chart only vaguely does is to show communication flow – which is omnidirectional – and things like innovation opportunities, or which people have social connectivity with others.
What if there were a di erent way to represent the complexities of the
21st-century organization? Enter nested circles. Common in self-managed, agile and holacratic organizations, such a representation can show the information flows – and the individual and collective accountabilities – that the org chart fails to capture.
As the name suggests, nested circles uses circular forms, nestling within each other. They are a much more e ective way to represent an organizational construct of delineated responsibilities (think sales, finance, legal), while showing that people are also present in non-hierarchical entities like projects, initiatives and experiments.
Tools such as Maptio use the principles of nested circles and make them
dynamic and easily updateable to create a real-time snapshot of our a liations and connectivity with others. This allows us to show how we, as individuals, intersect across work silos when we need to solve problems and get things done di erently.
From King Arthur’s round table to the seating arrangements of the politicians who negotiated Northern Ireland’s Good Friday Agreement 25 years ago, there is powerful symbolism in people being on the same level. The all-for-one, one-for-all ethos is more evident when we’re more naturally arced together, not mechanically separated. Breaking down silos? Take a look at nested circles.
It is the ‘other’ pandemic of the 21st century: the conspiracy theories, fake news and bogus stories that are transmitted via social media. Can society build immunity?
Deception or misinformation is everywhere: in nature, politics and warfare – and business too. Historically, tobacco companies used dirty tricks to undermine the credibility of research linking smoking to lung cancer. Today, greenwashing is widespread. Misinformation – the flipside of ‘knowledge is power’ – has been around
Van der Linden’s thesis is that misinformation is analogous to a biological virus and can be treated with comparable techniques, like vaccination
for centuries, but what’s new is its scale, reach and immediacy.
Due to social media, it is now possible to psychologically profile and ‘micro-target’ millions of individuals with manipulative messages tailored to their specific personality types. Such targeting is cheap, enabling non-state actors such as Isis (as well as state-backed groups) to become more powerful. And the technology of misinformation is evolving fast, as deep fake videos show. Misinformation has become much more dangerous, with the potential to undermine political stability, influence elections and erode institutions’ credibility. Sander van der Linden, a social psychology professor at the University of Cambridge, has advised the British and US governments on misinformation. In Foolproof: Why We Fall for Misinformation and How to Build Immunity, he sets out how online misinformation works and ways to combat it.
Van der Linden’s thesis is that misinformation is analogous to a biological virus and can be treated with comparable techniques, like vaccination. The book is heavily reliant on analogy as an analytical tool – perhaps overly so, yet it undoubtedly helps illustrate salient points. He sets out the common features shared by conspiracy theories, such as a belief in a group with nefarious intentions and the use of contradictory logic, and explains how their proponents deploy six manipulative techniques to confuse or mislead. They include quoting
fake authority figures or discrediting wellfounded research (both used by tobacco firms in the past), using polarizing messages and appealing to prejudices.
So how can society defend itself?
Governments can tackle part of the problem through regulation. For instance, mandatory ESG reporting rules will help tackle greenwashing by businesses. But what about everything that is not covered by regulation? Van der Linden o ers two options. ‘Pre-bunking’ can be applied to specific misinformation threats, by explaining in advance what your opponent’s argument is likely to be and providing a counterargument. But it is labour-intensive. Moreover, pre-bunking can be perceived as manipulative in itself. And if your counter-facts should turn out to be untrue, you risk undermining your own authority.
An alternative is educating people to recognize the manipulative techniques of misinformation, so they are forewarned. This is more e cient, possibly more e ective – and perhaps more ethically acceptable. This could be where social media and platform businesses, criticized so heavily for enabling conspiracies’ spread, lean in. Companies could provide far better online training and public information to help users spot manipulative messaging – a form of inoculation to build our collective immunity.
Foolproof is a stimulating and thoroughly-researched book about a topic that a ects us all. It is a must-read for those in the persuasion business –political, PR or marketing professionals – and deserves to be read much more widely too.
Foolproof: Why We Fall for Misinformation and How to Build Immunity
Sander van der Linden (4th Estate)
Piers Cain is a management consultant
Outstanding teams thrive thanks to unsung heroes. It’s time we recognized their contributions
Shane Battier is one of the great former US basketball players, but not by traditional metrics. In 2009, Michael Lewis of Moneyball fame dubbed Battier “The No-Stats AllStar”. Battier did not stand out for his personal numbers. But when he was on the court, revealed Lewis, his team fared “much much better” – and opponents did “much much worse”.
Not only did Battier typically defend the toughest opponents, he was a source of emotional cohesion and inspiration to his teammates. Among his ‘superpowers’, as I would describe them, was his emotional intelligence and the ability to communicate how his teammates and opponents relate to each other. Those qualities are not easily measured in box scores.
We have precisely the same blind spots in our organizations. To realize the potential of great teamwork, we need to look at factors beyond the current corporate box scores.
In my work with chief executives, teams and students, I have noticed a set of vital ‘invisible roles’. These roles are not found on organizational charts and they do not equate to the familiar posts of supervisors, managers, directors, officers and so on. Such jobs are clearly defined, structurally reinforced, and highly visible; invisible roles are the opposite. Often, they are not rewarded, incentivized, or even noticed – yet we keenly feel their absence. There are four invisible roles.
The Catalysts make us question our assumptions, reframe our challenges and deconstruct what has been. These individuals are thoughtful game-changers
who are always forward-thinking. They offer pushback, new ideas and can provide a healthy dose of scepticism. Catalysts help us to make a leap in our thinking, innovating beyond the current linear path that our project or organization may be on.
The Mentors are responsible for transferring knowledge and cultural norms. They are eager to listen, apprentice new team members, and ensure continuity between generations of leadership. They are emotionally generous, praising the accomplishments
In an era of disruption, organizations are struggling to survive. The contribution made by people is paramount
of others and helping team members set goals.
The Glue are individuals who, like Battier, promote team chemistry and create emotional bonds. They are energizing, focus on teambuilding, and increase joy capital. They keep morale up and ensure everyone works cohesively.
The Integrators are big-picture people. They excel at weaving ideas together and connecting people in a team. They spend time outside of their own department, building a diverse network, so they know how the company functions as a whole. They use their insights to help the organization fully leverage its assets. That includes diversity and inclusion: integrators help connect differing parts, making them greater than their sum.
These invisible roles can as easily be found in the executive assistant as they are in the chief executive. They are not found in job descriptions, but lie in how a person uses their relational or virtue superpowers. It’s an expression of what’s core to who they are, and what enlivens their work.
In an era of disruption, organizations are struggling to survive. Hundredyear-old powerhouses are on the brink of extinction; startups can flare out as suddenly as they arrive. Leaders have to ask: what do we need to not only survive, but to prevail? The focus is usually on the organizational architecture, processes and resources, or those in positions of power –the leadership team or the board.
But it is the contribution made by people – and the invisible roles they play – that are paramount. Such people are needed in every strata and department of our companies. If we can recognize these extraordinary superpowers in individuals, we can learn how to search for their qualities when hiring, promote them in our existing structures, and leverage the best of what our companies have to offer.
Sanyin Siang is a Pratt School of Engineering professor and leads the Fuqua/Coach K Center on Leadership & Ethics at Duke University
Better is the yardstick for management with agile, people-centric and dynamic features. As such, it turns management into a competitive advantage – one of the few advantages left in a time where they dissolve faster than ever before. Better Management gets work done, creates value; it is unique and hard to copy, it prevents short cuts and is deeply rooted in culture. That’s why it deserves the attention of every manager.
“Better management is badly needed. We learn about it daily from the media. Failures in management are often attributed to managers. Lukas Michel makes the case that theory and practice need an upgrade and offers six principles for the fix.”
We learn about it daily from the Lukas the ,
MICHAEL KÜHNER CEO, Strametz & Associates
“Lukas Michel’s new book provides every leader with compelling insights and tools and serves as a time-tested and validated blueprint that will help to shift an organization from activity-based leadership to true and sustainable organizational effectiveness.”
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