The 10 Most Intelligent Leaders in Data Science & Analytics 2022

EDITOR’S NOTE

Humans with AI: A FutureCentaurean

Iexcited about technologies like DALL-E and Midjourney that can create cool images given text as a prompt. Whatever you say about my drawing abilities, I have a good imagination and seeing it come to life as I write seemed pretty amazing to me.

have been a writer and an artist in the making, so I was pretty

Also, I remember when machines started winning chess matches against human grandmasters, and there was an undercurrent of worry in all news stories at that time, iterating, “ will machines overtake us everywhere?”

This worry seems to gain more weight when we start talking about the manufacturing industry and how automation is putting more and more people out of jobs. As a passionate enthusiasts of the scifi genre, I am guilty of looking toward books and movies for answers sometimes – are we going to be ruled by machines or are we going to gain tools that will propel the evolution of our society to new heights – in short, will it be an iRobot situation or a Real Steel

Probablysituation?neither,

looking at history for a better factual answer, when transportation evolved from an animal-based system to a fully motorized one, there were many jobs that did go out of existence, but dozens of new ones were created in its place. On the parallel lines, Society industrialized with every man, woman, and child owning some sort of vehicular system for travel. The same thing happened when technologies like phones and the internet were invented, and now it is happening again with artificial intelligence.

The 10 Most Intelligent Leaders in Data Science & Analytics 2022

As car racing became a beloved sport and computer-assisted humans 'centaurs' chess playing is becoming a thing, AI assistance is pushing the limits of humans' physical, cognitive, and creative capabilities. But from the outside, everything about AI can seem intimidating – 'am I too late to catch this train?' is the question that comes to one's mind.

It doesn't have to be. Like a writer dabbling in novice AI artistry– the bar for entry in this field has become quite low. The real question is how to reach the top of a field that seems to be inventing something new at a breakneck speed.

We at Insights Success set to find leaders who have been at the forefront of AI and Data Science & Analytics technologies that are rapidly proliferating in every sphere of life at a speed that seems to leave one's head spinning. In our latest edition, 'The 10 Most Intelligent Leaders in Data Science & Analytics' they talk about changes AI technology is set to bring in the future, how they keep pace with rapidly evolving tech, and what it takes to become a leader in this industry.

Dwell into such inspiring stories and make sure to read the insightful articles opined by our In-house editorial team.

Happy Reading! Shrivastava

Pooja M Bansal

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Featuring Person

BriefName

Harman International is a global leader in automotive technology, lifestyle innovations, design and analytics.

Ericsson is the leading provider of Information and Communication Technology (ICT) to service providers.

Mastercard is connecting and powering an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible.

IBM specializes in technology and infrastructure, software and consulting.

MYANIML is an AI powered early disease prediction and notification company.

Adient is a global leader in automotive seating.

ServiceNows's cloud-based platform and solutions help digitize and unify organizations for smarter, faster, better ways to make work flow.

GroupM is the world’s leading media investment company innovates, differentiates and generates sustained value for clients.

Dell Technologies provide the essential infrastructure for organizations to transform their digital futures.

Tesco is the leading retailer of consumer goods from food to fashion.

Joann

Paul

Shobhita

o you remember the famous cartoon featuring

DWile E. Coyote and the Road Runner, where the speedy bird is persistently chased by a hungry coyote who always came up with different ideas to catch the Road Runner?

Though the show brought smiles to millions of faces, what was most admirable was the sheer determination and grit of that coyote. Wile E. Coyote was never deterred by failure, he failed fast, was always learning, and continuously came up with unique ways to try and capture that bird. But what about the fact that he never caught his prey? It's irrelevant because we all know that would have ended the show. But we all admire Wile E Coyote's sheer grit and determination to keep learning; in short, this coyote's learning curve was always up.

When CIO LOOK set on a voyage to find “The 10 Most Intelligent Leaders in Data Science & Analytics,” we were looking for leaders who have a similar learning curve — that's when we found Paul Zikopoulos

A journey with an unquenchable thirst for knowledge (it comes from his parents, he tells us) has taken Paul through all kinds of roles at IBM. Something that really caught us off guard when we looked into his story? He joined IBM from business school and had no formal training in technology.

Today, Paul is the VP of IBM's Technology Sales Skills Vitality & Enablement group, where he oversees the strategic direction to develop deeper technical skills for IBM's entire sales force. For almost 30 years, Paul has spent his professional life acquiring knowledge and satisfying his massive appetite for learning. He advises all who will listen, “If you're not committed to being a lifelong learner, you're going to get stale in a hurry” When you look at his accomplishments, you quickly realize Paul's not interested in getting stale.

Paul credits IBM's culture of learning as an essential part of his growth path that's led him to write 21 technology books and hundreds of articles (remember, no formal training in technology). He was named a “Top 100 AI & Big Data Thought Leader” by Analytics Insight and to dozens of other “Thought Leader” and “People to Follow” lists, not to mention awards for his speaking and writing skills.

The Dog Years

Paul's journey has stops in Development, Product Management, and Sales — going back and forth, all the while spawning deep roots into technical communities and clients. He showed us some calendar entries that were a decade old and some just weeks old, they all had one thing in common: large blocks of his calendar were reserved for learning.

Paul began his career writing installation manuals and in user design, which instilled in him a 'teaching' capability. He broke down the complex stuff so that anyone could not only understand what he was talking about but follow his directions and learn themselves. This turned out to be one of his greatest strengths. Later he began to write data-focused magazine articles, and when the stars aligned, he answered the calling to become a book author, leading to name recognition as an expert in the field of data, analytics, and AI.

Paul told us how one inflection point in his career was when he made the decision to start focusing on other database technologies; he worked to get certified in Oracle and Microsoft SQL Server to complement his database expertise in IBM Db2. With this knowledge, he began to teach clients about things beyond what he was selling, which he says was “The gamechanger when it came to connecting with them.” When the analytics market shifted, and suddenly everyone wanted to talk

If you’re not committed to being a lifelong learner, you’re going to get stale in a hurry.

about Big Data and Hadoop, it raised Paul's curiosity, so he learned all he could and wrote the book “Hadoop for Dummies.”

Paul would rinse and repeat this process many times in domains such as Data Science, AI, and Cloud, writing books on all of these topics. He shares, “See the pattern?

My journey has had multiple jobs, but it's all built on a foundation of non-stop learning about something I originally knew nothing about.” He jokes as he reflects on the irony of it all, “I was the dummy that I was writing all those “for Dummies” books for!”

The Hurdled Path

Paul faced several career challenges on this journey, but he courageously shared with us that learning to believe

in himself was the biggest of them all. He mentions, “I have this picture I always look at: it has a blue chair in the middle and two yellow chairs on each side of the blue one. Over the blue chair is text with an arrow pointing to it — it says. “Here sat the leader that believed in me so much I started to believe in myself.”

Paul humbly reminisces about Bob Picciano, Alyse Dagehlian, Martin Wildberger, Rob Thomas, John Teltsch, Fred Gandolfi, Frank Luksic, and Mark Ryan, whom all shaped his journey, making a significant difference in his life.

One of Paul's biggest challenges early on in his career was the label he got for not being “technical enough”. His hiring manager gave him an opportunity to prove himself to the brilliant and accomplished minds that surrounded him.

Sharing his experience, he says, “Talk about not fitting in or feeling I wasn't good enough! It took time and grit, but I had lots of both. I remember the day I made a promise to myself to always be more technical than I was the day before. I still have this goal today! Remember this: compounding is the 8th wonder of the world; if you keep learning… you'll amaze many, including yourself, where you end up.”

Another challenge had some poor managers at times, but he is quick to note that he had way more good ones than bad — but this is the reality of big places. He shares with us some great advice if you find yourself in a similar spot: “Remind yourself that you're not a tree… you can move. I've been giving “Pick the boss, not the job” advice for years; trust me, it works.” he says Earlyconfidently.on,Paul

knew that the technical mountain he was aiming to climb was steep, and when taking into account the sheer size of IBM (at the time, ~400,000 people), he knew it would be easy to get lost in a crowd. Paul made a bet that putting focus on building his career outside of IBM would really boost his career inside of IBM. We admit it sounds strange when you first hear it, but it makes total sense as you listen to him speak. He noted how all the writing, public speaking, and client work he did over the years created a large following of customers and communities that got him recognized within IBM, and the rest took care of itself. He notes, “One sure-fire way to impress your bosses is to impress the client base and the community where your solutions get sold.”

The Learning Never Stops

Paul asked us, “If a personal trainer told you to workout with their program for the next two months and you would never have to work out for the rest of your life, what would you think?” We answer, “They're crazy.” He says, “Agreed. So why would anyone think work skills are any different?” If you want to be successful, the process of learning can never stop. The good news is that it's never been easier to learn, well, anything. There is something online for almost anything you need to get done, he reminds us. Paul also

let us in on his secret (which is really a Robert Heinlein quote): “When one teaches, two learn.” This is the reason Paul writes the books he does. He never starts as an expert in anything, but became knowledgeable by writing and teaching. He notes, “Everyone can take what they know really well and teach it in some way to someone else. I've made content creation a job… and that's my secret to learning.”

To emphasize the importance of learning, Paul shares some entertaining trivia that really got us thinking. “Let me really hit home how critical learning never ends is to success with a fun fact. I saw a movie called 'A Star is Born.' It stars two famous people: Lady Gaga and Bradley Cooper. The movie is about a drug and alcohol-addicted country singer (Cooper) and the discovery of a new star (Lady Gaga). As you can figure out by now, it's about music, and of course, Lady Gaga is world-famous as one of the most successful recording artists in history. I found something interesting. Lady Gaga demanded that Bradley Cooper perform everything live! He had to play his own instruments and sing live, too… no lip-synching or autotuning allowed! Cooper took singing and piano lessons to prepare for his role. When all was said and done, he spent three years of effort preparing to film the 'A Star is Born' movie.”

He reacts to the amusement on our faces while telling this story by asking rhetorically, “Why am I telling you this story? If one of Hollywood's leading actors spends three years preparing to film a movie remake, which has been done twice before, that took 42 days to film, how much time do you think you should be putting into learning for your own career?” He's right. We can all learn something from this story.

Diversity at Core

Diversity is critical to any successful organization. Paul states that every person deserves equitable opportunities; it doesn't matter your race, background, sexual orientation, or how you identify.

In his opinion, the world hasn't been doing as good a job as it should have been doing these last decades. He spends time being an ally to several different groups because it's the right thing to do for a better world. There's a nuance here that he's insistent you ponder because everyone talks about being an ally these days.

“When I say the word 'ally,' I'm talking about that word as a verb, not a noun,” explains Paul.

IBM has been a leader in diversity for decades; their lists of firsts are long and spread across many social justice issues the world is facing today (racial and religious lines, sexual discrimination, identity). Paul adds, “I'm so very proud I get to work for a company dedicated to something that means so much to me personally. Creating a culture of inclusion and voice is critical, and it's in so much of what goes on at IBM. I really must credit our CHRO for that, Nickle LaMoreaux; she's made it a personal mission to put actions behind announcements which has taken IBM in this space from the crowded domain of ‘cool to talk’ about to the less populated 'get stuff done' cohort.”

“I look across the teams I've assembled over the years; they've been so diverse. I've had representation across all age groups (into their 60s), races, religions, gender identification, educational backgrounds, sexual orientation, etc. It makes me so proud, and the culture at IBM helped me assemble those teams long before it was the discussion topic it has become today.”

Recognition and Beyond

Paul was the first-ever male to win the IBM Canada “Women in Technology Ally” award. He notes it as a “heart-touching experience in ways he never imagined.”

He shares, “I've been working in this diversity and inclusion space for a while, not because it's my direct job, because it's my direct culture. While IBM has their programs, they support and help employees get involved outside of IBM, too. I love that.”

Paul's work with Women in Technology began as an ally (verb) around an incident that went viral on social media, his words even made their way to “The View” TV show. Kate Brodock (CEO of Switch, formerly known as Women 2.0) took notice and approached Paul to join her advisory board. She insisted that the only way the world can move forward and overcome issues of gender representation, socialize mobilization, and change the digital activism landscape is to recruit #menasallies (and so the hashtag was born). From there, Paul became more and more involved by speaking at conferences, mentoring, and writing (he's amassed over 1 million views of his opinions in this space). Eventually, word got out, and Paul ended up with this award.

“The super humbling part of this award is I have no idea who nominated me and who voted to give it to me… I think that's what made it so special. The truth is, I don't want to know. It's not why I do the stuff I do… but it absolutely felt amazing to see that people noticed. But I thank you, whoever you all are!” says Paul.

The Impact of Artificial Intelligence

Paul often comes across questions asking for his take on AI and jobs… should we be scared? To which he answers, “In 1997, IBM's Deep Blue supercomputer beat Garry Kasparov in the now infamous man-versus-machine chess match. Kasparov decreed later that if he had had access to the corpus of chess game observations that Deep Blue had at its disposal during the match, and the ability to process the data as fast as a computer, he would have fared better. After all, if a computer could benefit from accessing a corpus of games played, why couldn't he? Good point!”

“Today, freestyle chess matches dominate the competitive chess landscape. Freestyle chess is like the mixed martial arts (MMA) of chess. You choose your techniques. You can play just using your own brain, enter a computer to play on its own, or enter yourself with a computer by your side — referred to as a Centaur Chess player. Last I checked, the best chess players alive are groups of humans with machines. When I last looked at the winning stats at these tournaments, sometimes the machines won independently, but Centaur Chess players won the most often. Do you know who never won? A human on their own! This is exactly what Kasparov was trying to say after he lost; while most people took it as 'sour grapes, it was a genius-level observation.”

Paul's takeaway is that AI isn't going to take all our jobs away; instead, he thinks AI will become a net job creator. However, some jobs will go away, but it's really going to be about the ability to adapt to change. “Don't get stale,” he reminds us. 'Roughnecks' on oil rigs will become 'RoughTechs' on oil rigs — but they will be the same people. He articulates this discussion so well when he says, “Look, I can't tell you what jobs will be here and what won't. I'm not a fortune teller. But I will make this promise to you: those who get comfortable using AI in their day-to-day jobs will replace those who don't.” He adds, “We're going to have to change our taxonomy for job classifications; it's no longer going to be about white-collar or blue-collar jobs; they will all be new-collar jobs.”

Then he gets candid about that part of AI that truly worries him. “What am I scared about when it comes to AI? I'm afraid of the data we're using to train our AI and a lack of algorithmic accountability and explainability. In a world where more and more AI can decide if you live, buy, die, or try, I'm more concerned about making automated decisions based on untrustworthy learnings that are not curated, than I am Ultron… that kind of AI is best left for the movies.” he says. (Ultron is the AI in the Avengers movie that was designed to keep peace in the world, but it quickly learned from the data that humans were the ones always disturbing the peace, so it concluded humans had to become extinct.)

His Head is in the Clouds

We ask Paul about cloud computing, and he reminisces about his time in IBM's development labs and the struggles he'd endure getting a test database server up and running. “Things have changed… a lot. Today, as-aservice models are for everyone and everything. Heck, I can now run workloads that took me weeks to enable in minutes for less than the price of a bad cup of coffee!” he chuckles before telling us he doesn't drink coffee, but he's pretty sure about his proclamation.

Paul talks about the cloud's future with more history, “If you've been around awhile, you remember people used to refer to the Internet, Intranet, and Extranet… but then communities rallied around a bunch of standards, and these domains converged. No one uses these words anymore; we just say Internet. Prefixes for the cloud? Private, Public, Hybrid, Multi, Distributed, Community… I'm sure there are more. But a bunch of technologies have come together (Linux, Kubernetes, and containers), and you're just going to

I’ve been giving, “Pick the boss, not the job” advice for years; trust me, it works.

He tells us that many are surprised to learn that cloud computing at most companies is still very much in its infancy. In fact, many companies who went all in on the cloud aren't getting the value they should be getting out of their cloud initiatives. Paul gives us an easy tip to remember that he promises will help organizations get up to 2.5x more value out of their cloud investments: “Cloud is a capability, not a destination.” Paul details how critically important it is to realize how a cloud as a destination mindset is an anchor to any value vessel; he goes on to detail how he's seen a number of customers repatriating some applications back to on-premises. He notes, “They didn't see the cost savings they expected (public cloud can save you money, but can also be responsible for skyrocketing costs), for some… regulations got in the way, others faced data gravity issues, and more. These companies started out thinking that the cloud was simply a destination. When I worked with them and shifted their thinking to cloud as an operational model, their company's (now) hybrid cloud initiatives suddenly were positioned to yield bigger and bigger returns. Think about it. Shouldn't agility, elastic computing, and flattening the time to value curve be beneficial everywhere? Just because your application benefits from data gravity or is under regulatory compliance doesn't mean it shouldn't benefit from the cloud. Use cloud everywhere: on-premises, on edge, and yes, with established hyper scalers too!”

There's another trap he's seeing with the rush to cloudnative applications (no matter where they're run). Most people don't realize that while agile and distributed components made life amazing for developers, it has created enormous issues for Site Reliability Engineers (SREs). He notes that, “You don't build applications today, you compose them. You stitch together discrete and distributed pieces of logic (microservices), and this approach gives you scale, availability, and agility. These apps have components that leverage function-as-aservice (FaaS) calls that can run in under a second. How do you monitor this? How do you figure out where a problem is coming from when the code runs in a second, and its runtime is ephemeral, and it runs on one of many cloud providers you're working with? It gets messier as more apps evolve into cloud native. Trying to figure out anything from a composed app's reliability perspective has become a nightmare.” What Paul's talking about has given rise to a higher order of application performance management (APM): observability.”

As we close out our cloud conversation, he notes how the over-allocation of resources in the cloud (which skyrockets costs) is also a big issue getting in the way of companies getting the full value out of the cloud. “Quite simply, infrastructure resource starvation and mis-sized resource allocations are the most frequent cause of application performance issues, leading to complexity, SLA violations, over-spending, and more. Welcome to the space of application resource management (ARM),” explains Paul.

Today's reactive and single resource monitoring tools do not understand the relationship between applications and infrastructure and therefore rely on manual interpretation and intervention to resolve resource congestion. When you bring APM and ARM together… you create powerful AIOPs solutions that can learn from past issues, alert to future ones, act in advance to prevent those issues from ever occurring, and over time get smarter and smarter along the way (reinforcement learning). He shocks us when he shares the investment dollars IBM has put into this space. We cheekily ask him (since we already know the answer), “Will AIOps replace IT support staff?” He responds as expected, “No. But IT staff that are comfortable using AIOps will replace IT support staff who aren't.”

Ready for the Next Chapter?

There are numerous lessons to be learned from Paul's journey, the knowledge he gained, the ladder he climbed, the books he wrote, and the experiences he shared. Everything ties into a continuous thread of learning. He finishes with one last piece of great advice. He tells us, “So many people tell me it's too late for them to start a transformation and upskill for today's hot technology job market.” He tells them that “technology years are like dog years… it's not about the head start. Society spends too much time recognizing the big moments and often misses the impact small daily improvements can make in your professional and personal lives. When it comes to technology, a newbie who never stops learning, in the long run, will far out skill the CompSci graduate who thought learning finished the day they got their degree.”

CIO LOOK curiously awaits to see how Paul weaves this thread and carries on his journey beyond the horizon.

Dr. Sunil Kumar Vuppala

When we asked Dr. Sunil Kumar Vuppala about what the next significant transition in the Managed Services sector could be, he answered, "Networks will evolve into global digital infrastructures, supporting a much more evolved digital society,"

Dr. Vuppala is currently the Director of Global Artificial Intelligence Accelerator (GAIA) at Ericsson, one of the leading providers of Information and Communication Technology (ICT) to service providers.

From visual intelligence of drone images to forecasting difficulties with underlying causes from terabytes of data for huge Telco operators throughout the world, Dr. Vuppala is solving challenging problems using AI.

CIO Look caught up with Dr. Vuppala to learn about his role and contribution in the Data Science sector for the edition , "The 10 Most Intelligent Leaders in Data Science & Analytics, 2022."

Below are the highlights of the interview:

Brief our audience about your journey as a business leader until your current position at Ericsson. What challenges have you had to overcome to reach where you are today?

My journey started as an applications engineer at Oracle after my Master of Technology from IIT Roorkee, India. Thereafter, I accepted the role of the researcher in Infosys R&D Labs and worked there for 11 years on cutting-edge technologies such as IoT, Automation, Artificial Intelligence (AI), and Data Science. I completed my Ph.D. at IIIT Bangalore as a working professional. Managing time for both work and

Ph.D. is a significant problem, even though the learnings from applied research are fantastic. Later as a principal scientist at Philips, I solved challenging problems in Afterhealthcare.completing

my senior management program at IIM Ahmedabad, I transformed from a core researcher to a business leader, as my overall perspective changed to think beyond technical to overall organizational business perspective. I was able to influence thousands of learners as a visiting faculty at premier institutes teaching data science, AI, and analytics. As a director –

We believe in a world where redefinesimprovesconnectivitylimitlesslives,business,andpioneersasustainablefuture.

of data science at Ericsson, my key focus areas include how to accelerate the AI adoption in the organization, Return on Investment, understanding the vision for AI in Telecom, setting the right expectations of stakeholders in terms of AI, and providing the right guidance to the team to deliver solutions.

Tell us something more about Ericsson and its mission and vision.

Ericsson is a leading ICT (Information and Communication Technology) provider to telecom service providers. The Sweden-based firm maximizes the value of connectivity by developing game-changing technology and services that are simple to use, adapt, and scale, ensuring our customers' success in an increasingly connected world. With its cutting-edge 5G technologies, Ericsson is leading the way in revolutionizing industry and society. 5G networks provide high throughput, ultra-reliability, low latency, and security, which are required for mission-critical services such as telemedicine, autonomous linked

vehicles, and smart factories that run on 5G networks. Our purpose is to create connections that make the unimaginable possible. We believe in a world where limitless connectivity improves lives, redefines business, and pioneers a sustainable future.

Enlighten us on how you have impacted IT Services and IT Consulting through your expertise in the market.

With my strong background in IT services and consulting experience from Infosys, I could contribute to how AI can impact the IT services in Ericsson. The contributions include proposing and executing strategic projects, various decisions on build vs. buy, building chatbots for the IT support teams, Cloud vs. Edge AI for the deployment, choosing the right business use cases with intelligent automation, optimizing the solutions beyond software, and how to leverage best out of available hardware by partnering with the hardware vendors. Development efficiency is a strategic theme for us at Ericsson Global AI Accelerator (GAIA).

Undeniably, technology is playing a significant role in almost every sector. How are you leveraging technological advancements to make your solutions resourceful?

I completely agree with you. Technology is changing very rapidly, and it is playing an important role in addressing business challenges. As a thought leader in data science, my role is to connect the dots in identifying the right technology to solve specific business problems. Building AI models which are fair, explainable, robust, trusted, secure, and ethical are the need of the hour using the latest technologies in the literature. We need to think of end-to-end model development, deployment, and maintenance of these solutions to make them resourceful. Our solutions focus on automation and standardization with MLOps and deployments in the hybrid cloud.

What, according to you, could be the next significant change in the Managed Services sector? How is Ericsson preparing to be a part of that change?

The next significant change in the managed services sector is in intent-based cognitive networks. Networks will evolve into global digital infrastructures, supporting a much more evolved digital society.

Because of the intricacy of running these networks,

cognitive networks will emerge. In evolving intentbased network operations, cognitive technologies combine large data with unique network domain expertise to enable unparalleled speed, scale, and accuracy. We are using AI in telecom to help us achieve our vision of future zero-touch networks by automatically determining which actions to take with minimal human intervention.

Where do you envision yourself to be in the long run, and what are your future goals for Ericsson?

In the long run, I envision that the penetration of AI and data science will be pervasive in telecom and other industrial sectors. I want to continue leading and building solutions with Trusted AI, Ethical AI, Green AI, and Metaverse for the adoption of AI in solving real business problems and building frameworks to democratize AI and data science. With my strong academic connections and being an active member of IEEE and ACM, I wish to contribute to bridging the gap between academia and industry.

The intelligent network platform will be redesigned to satisfy new requirements and to incorporate features

beyond connectivity. We aim to ensure that today's powerful 5G network foundation evolves into the 6G era, bringing new capabilities and the kind of extreme performance demanded by application areas such as the internet of things, intelligent machine communication, and the internet of senses.

What would be your advice to budding entrepreneurs who aspire to venture into the Network sector?

The Telecom network is a very complex domain. My advice to budding entrepreneurs is to check the gap which they wish to address in the network sector and make it their core business to solve the needs of the customers. It can be at any layer in the network. Having the right partnerships is another important aspect the entrepreneurs need to keep in mind due to the complexity involved in the network sector, eventually leading to delivering "cost-effective" solutions "in time" while meeting the quality requirements.

Has Humanity Reached Peak Intelligence?

e live in the age of innovations and

W technologies, where any task is at our fingertips, from purchasing products to getting education and finally getting jobs.

But one question that arises in the minds of many is whether we have reached the peak of intelligence. Let's begin with the exploration of the ancient origins of human intelligence. From the moment our ancestors learned to walk upright 3 million years ago, scans of fossil skulls suggest that the brains of our first apes were about 400 cubic cm, which is three times the size of today's modern humans.

There are numerous possible reasons for this brain boost, but it was the response to the increasing cognitive demands of group living. The larger social groups allowed members to share ideas and build on each other's inventions, resulting in inventing tools to improve the efficiency of hunting.

That's where humans developed the intelligence to observe and learn from others and provide one another a push for more incredible brainpower.

When our ancestors left Africa around 70,000 years ago, they were smart enough to adapt to any life in almost every corner of the planet. The astonishing cave arts clearly

showed this indication and were also capable of solving cosmological questions.

It was only a century back that scientists first invented IQ (Intelligence Quotient) to measure someone's intellectual potential. IQ is undoubtedly good at predicting academic success and to predict how quickly you pick up new skills in the workplace. In simple terms, they show a meaningful change in people's capacity to learn and process complex information.

th

The rise in IQ started in the early 20 century; when people take the test, their scores are transformed to ensure the median of the population remains 100. This allowed the researcher James Flynn to compare the scores between generations, and he found out that there has been a steady increase in IQ points. However, the Flynn theory is still a matter of debate due to multiple environmental factors. The best comparison is the change in our height; we are 5 inches thtaller today compared to the 19 century, which just means our overall health has changed. Another example can be taken from education – children lean on developing abstract thinking to cope with modern technology.

Whatever the cause of the Flynn theory, we have already reached the end of this era with the rise in IQ. For now, it looks like our culture is able to shape our minds in mysterious ways. While researchers continue to find more of these causes, it's worth questioning what these changes in IQ mean for society at large.

Necessary Answers

Today people are probably better at figuring out complex cell phones and technological innovations than they would that the turn of the 20 century. Moreover, as a society, higher IQs have not brought them solutions to any of the world's major problems – global poverty, climate change, violence, rising income disparities, and nuclear war, among others. That's not to mention, that we have relied on an intelligent workforce for the enormous benefits of scientific and technological advances.

Intelligence certainly has helped us to be more creative, but we do not see a rise in some individual creative thinking over time as our IQs increase. For our society, it can lead from medical errors and miscarriages of justice to global financial crises. It can also contribute to the spread of fake news and political polarisation on issues like climate change.

Looking at the future, the potential rise or drop in IQs should certainly cause us to take a look at the ways we are using our brains. We now know that this kind of thinking can be taught; these possibilities are an indication of what can be done if rationality and critical thinking are given the same respect as other cognitive abilities. We might even start to see a steep rise in rationality and wisdom in tandem with the Flynn effect.

By now, it is clear that you cannot conclude the rise and fall of IQ is just one piece of the puzzle, which will only get completed by answering the above world issues. IQ is just one piece of the puzzle – the cleverer side of the human being. There are many more things to life than having a higher IQ or higher score of cognitive ability.

Sibanjan

Finding himself between an offer to move to the United States and work as a consultant on a job that he didn't care for or to join an organization where he sees a huge opportunity to work on the things he appreciates the most. Sibanjan Das made a decision that, along the way, had a significant impact on his career, choosing the latter option. When he started in Data Science/Machine Learning, it was a relatively new area. But the journey since then has been equally challenging and rewarding.

Sibanjan shared his experiences to emphasize how crucial decision-making is in life. He says, "Few decisions worked well for me, and few didn't. But life is all about making choices, and once you choose, stay with it. There is no going back. Perseverance is the key."

Journey as a Leader in Data Science

Being a leader in the Data Science field has been a fun roller coaster ride for Sibanjan. He started as an engineer for ERP systems, then became a business analyst for the Order to cash processes. A few years later, he felt he was missing the other leg of Enterprise IT and transitioned into an analytics consultant role. He finally landed as a Data Scientist in 2013. But things never look that easy when you want to transition between different departments, as it takes effort, courage, sacrifice, and some hard decisions to make.

One of those decisions was Sibanjan quitting his job to study further in the area of Information systems and analytics when he was being offered to go United states as a consultant. He had decided to try the unknown,

and no lucrative offers could stop him. When he started in Data Science/Machine Learning, it was a relatively new area. His focus was always to work in the field of Analytics, and he tried to get into a functional analytics role. He landed up in the field of Machine Learning unintentionally. But the journey since then has been equally challenging and rewarding as well.

When Sibanjan started learning Machine learning, he always had thought about how to inject Machine Learning into the workflows in ERP systems. Oracle ERP was always his den, and he kept on trying and exploring things to make this a possibility.

Things didn't work out well until Sibanjan got a chance to work with Oracle on precisely what he wanted. He never wanted to miss this opportunity and gave in all to design that product. His previous business processes skills, Oracle ERP technical knowledge, and ML skillset all came in together to do some justice to the responsibility that the organization gave him.

The happiest moment was when he saw the modules that he designed and developed were released as a part of general availability and are mentioned in the product user guides. But during this time, he had already resigned, not because of Oracle, but for Analytics. He loves product development, but he wanted to be part of the enterprise analytics team for a long.

But, during this time, again, he was offered to move into Toshiba US as a Microsoft BI consultant. And yet, again, he didn't go to the United States even when he had an H1B visa and was already stamped for travel. This was the second time he had rejected the travel. His friends complained that he was killing his growth. It's not the case that he never wanted to go. But, for him, the work was more important than the location.

Today when he looks back then, he thinks he made the best decision. ServiceNow is a great organization to work with. The leadership there is terrific, with great people and enthusiastic teams. When Sibanjan joined ServiceNow, he joined as a business insight analyst within the Data and Analytics team. He believed this role was an apt role for him as this is an intersection of business and data science. But a few months after, he felt that the Data Science team within the same Data and Analytics team did the work he could do best.

Going the Extra Mile

During one of his conversations with his leader Brian Hoffman, Sibanjan expressed his interest in working with the Data Science team. He never said no, but he didn't commit to taking him on his team either because he didn't know him. So, he started testing him and asking him to solve some problems. He also challenged him with some more complex problems day after day.

Little did he know, Sibanjan had made up his mind about a do-or-die situation. He started working on two shifts – doing the work for Business insights during regular office hours and Data science work in the evenings. This continued consistently for a few months until one evening when Brian became tired and said, "Sibanjan, it's time for you to officially join the Data Science team." Five years later, when Brian and Sibanjan remember these events, they laugh thinking of those days.

Sibanjan also advises, "Try to focus on things you can control. Don't focus on something not in your control, as it will burn you out. Being an Indian, like the rest of India, I am a fan of cricket. In cricket, there are batsmen, bowlers, and fielders. If you are a bowler and start thinking much about the skillset of the batsman, you lose your focus, and he might hit your ball hard. Focus on your bowling. Don't think much about the batsman. He is there to bat and is thinking about how to hit your ball. Fielders are ready to save runs. Fielders might miss a catch, and you feel bad about it. But should you feel bad? Yes, but for yourself. Your aim should be to bowl him out, hitting the stumps directly. If you can't do that, don't blame the fielder or batsman. Do things that you can do, don't think about conditions beyond your control."

The Company's Impact

For Sibanjan, the impact is a magic word. He shares one of the many things that he likes about ServiceNow: people love creating solutions for complex problems and enjoy making them successful. The ServiceNow team likes solving challenging problems and always strives to improve yearly.

Sibanjan believes, "There are very few companies in the world who think about their growth and their customer's growth and success. ServiceNow is one of them, and they are at the forefront. And I am not saying this because I am a

ServiceNow employee. I have truly felt this in Service Now. ServiceNow always has a positive vibe and focuses on making customers, employees, and the community successful. There is always a "people" touch in everything they do at ServiceNow."

A Piece of Advice for Aspiring Professionals

Sibanjan believes that leadership is a generalized term. It's a responsibility to help grow your organization and support the team, which starts with you. If you have never made your own decisions and worked on your priorities, you might not be in a position to make decisions for your team and organization when you are a leader. Can someone make decisions that will andindividual’sorganizationimpactandlife,career,growthwhentheyhave

Secondly,themselves?Sibanjan

never decided for

talks about empathy. One needs to feel for their people and consider them as their own. He expresses, "My heart goes out to people who are loyal and strive to be a better version of themselves every day. When I say "loyal," it doesn't mean following orders but being dedicated to the commitments and things that they sign up for. Being a leader, we should try to make them successful and, more importantly, see them happy."

The third is trust. Sibanjan thinks trust is the thrust that keeps driving a team forward and achieving its goals. The great thing that he learned from ServiceNow is servant leadership.

Sibanjan clarifies, "Let me be honest here; I am not a leader yet. What I was speaking here is something I learned along the way and from our leadership team, who backs me up with the decisions I make. I am just someone working daily to see everyone happy – My family, colleagues, team, and organization. I try every possible way to have people around me happy and prosperous. I will consider myself successful as a leader only when I bring a positive impact on the world and community. ServiceNow provides me that platform, and so I am here driving our vision - doing work, work better for people, and creating a platform that makes work flow.”

riven by the life motto, "In a gentle way, you can

D shake the world," Somya Malviya is building up an ambitious career as a Data Analyst . She has incorporated Information Systems qualification with strong business acumen. She aspires to provide exceptional data analytics insights and technological transformations to make the world a better place.

The company she is assigned to, GroupM, is shaping the next era of media where advertising works better for people. It is the world's leading media investment company, responsible for more than $50B in annual media investment through agencies. The company aims to leverage all the benefits of scaling, innovating, differentiating, and generating sustained value for its business clients.

Continuously Pushing Boundaries

Somya has big ambitions for the broader industry. According to research, only 27% of female graduates opt for a career in technology. Looking beyond the statistics, she has first-hand experienced the struggles of getting into an industry typically dominated by men and workplaces that rarely provide opportunities to inexperienced individuals. Having encountered such circumstances in her journey from working in Supply Chain and Healthcare industries and eventually progressing towards the Data Analyst role at GroupM, she thrives on eliminating the notion of technology being competitive and non-inclusive. Somya's ambition is to progress into leadership positions where she can influence a wider network of people and help other women succeed, encouraging female graduates and interns to pursue Data and Technology.

GroupM's mission is to make advertising better for people, continually achieved by supporting its clients, partners, and internal teams in delivering ad effectiveness, optimizing media investments, and providing the platform to develop and deploy cutting-edge technological solutions. The amalgamation of all the different aspects of the business: Search, Social, Programmatic, and AI, acts as a powerhouse for three of the top five global media agencies: Mindshare, Mediacom, and Wavemaker. This is further driven by strong connections with its premium partners: Google, Amazon, Meta, and more. It constantly focuses on connecting technology with talent that allows it to grow and pivot into different opportunities and capabilities, enhancing scalability and interoperability within cross-functional diverse teams.

Somya Malviya Analyst

Somya tries her best to push the boundaries continuously and deliver ground-breaking projects working closely with several team members across Programmatic, Finance, and Operations. She has worked on several innovative solutions and navigated through uncharted waters to explore the media effectiveness capability of Data Clean Rooms like Amazon Marketing Cloud and Ads Data Hub to discover high-value audiences and measure holistic brand lift. Secondly, she has transformed the Pacing process into an automated dashboard, improving the efficiency with a performance uplift of 30% and saving GroupM $85,000 on manual and tedious processes. Additionally, Somya has created a Commercial Tracker that drove 35% savings in head hours, accounting for an overall savings of $2,000 each month.

Leaving a Mark in Media World

GroupM has always focused on bringing value to its clients and aims to touch many lives through global media

campaigns that give back to society by increasing ad effectiveness through data analytics and insight generation, media strategy, and investment optimization.

"The Go Give One campaign" in 2021 was one such instance to support World Health Organization's mission to vaccinate the world and utilize strategy building, big data, and technological advancements as the support system for campaigns that change the world. GroupM's mission to make advertising better for people, in turn, aims to play a key role in bringing this vision to life through leading and inspiring a team of media and data-centric individuals who build the backbone of effective work that has an impact on the world. GroupM has also implemented several initiatives like DE&I Talent Pipelines, Automation, TeamFlex, and Reconnect plans that allow its employees to work from home whilst visiting family across borders. It builds strategic partnerships that give new and different talent pipelines and eliminate mundane, monotonous tasks to decrease the staff attrition rate.

The ever-changing world of media and subsequent depreciation of cookies has left marketers grappling with privacy-first solutions that could measure return on marketing investment with higher accuracy. Somya shares, "My inquisitive nature and go-getter attitude enabled me to explore a new and innovative solution for a Pet Food client: Data Clean Rooms. My initial hypothesis for the first-ever use case for GroupM Australia was to create connections between platform and customer data, ensuring data compliance. However, I have dived deeper into several possible use cases to explore the ad effectiveness for cross-channel exposure and optimal frequency for different device types. Results generated were extraordinary, highlighting a promising use case where Amazon Sponsored Products along with Display ads led to an exponentially higher purchase rate. Almost 60% of total purchases can be attributed to customers targeted using both the channels, boosting purchase likelihood by ten times. Additionally, when multiple devices are used to target a customer, they are eight times more likely to drive conversions."

Data Visualization tools largely focus on creating a variety of charts and graphs; however, one of the most crucial parts of it is also the ability to generate complex insights and present those in support of the visuals. The storytelling feature of a dashboard is equally important, especially when it accounts for driving business decisions for stakeholders and clients. She has the vision to advance the Data Visualization dashboards to automate the generation of visuals from complex natural language processing questions. Somya explains, "I would also enable ways to display the Prescriptive analytical solutions that assist our clients in figuring out the solutions to the seemingly simple but biggest problems in media: Whom should I target? Where should I spend the biggest chunk of my budget? How many times should I serve an ad to a potential customer? Should this ad be served on Mobile, Desktop, Tablet, or TV?"

Cost-Effective Optimal Solutions

Somya believes that as Media Industry is stepping towards a cookie-less future, it is extremely pivotal to consider the revolutionized changes it is bound to bring within the analytics industry. This would shed light on the immense capabilities and importance of data owned by Walled Gardens like Google and Facebook and how it can be used to generate insights within a privacy-safe environment that guarantee no Personally identifiable information (PII) is shared across companies. Data Clean Rooms is just one

such solution. Several others focus on utilizing data pipelines, contextual targeting, and device fingerprinting to target the right set of users for an ad. According to this information, these use devices or website content to monitor user behaviour and target customers. GroupM is continuously collaborating with its partners like The Trade Desk, Xandr, Adobe, Google, and Amazon to explore solutions that maintain the highest level of privacy and improvise campaign delivery metrics and provide costeffective optimal solutions to its clients.

Somya concludes with a bit of advice to budding entrepreneurs, "If the world of media has taught me anything, it is the paramount importance that must be placed on the Total Addressable Market (TAM) for a specific business. This answers the simplest of questions but provides immense insights into your target market. In layman terms, any business that unlocks the door to know whom to target and how to build a product that solves their biggest roadblocks and appeals to their target audience wins it all.”

Venkat Raghavan

Powering organisations with analytics Venkat Raghavan

he crux of any business lies in identifying

Tcompelling problems and their most viable solutions. Gifted are those who have cracked the formula to run successful enterprises relying on this strategy. One such leader who has embarked on an enterprising journey across the globe, spanning multiple businesses, is Venkat Raghavan, an expert in analytics. He carries an impressive track record of successfully leading high-growth portfolios and believes that businesses grow by growing individuals and their thoughts.

Tesco Business Services (TBS) is the global services arm for Tesco, a 100+-year-old leading multi-national retailer with a well-established presence in Europe and the UK. As an Associate Director and Global HeadAnalytics, Tesco Business Services, Venkat has already proved his mettle as an expert in problem-solving with the power of data.

Let's dive in to find out the reasons behind Venkat's success in driving the power of analytics towards the continued success of Tesco as an organisation.

Opening the Gateways of the Mind

"Questions are more important than answers." Venkat started his career as a coder but understood early in his journey that he liked coding only if he understood where the code fits in the larger problem it is solving. This made him gravitate toward asking more business questions about how things are done and how they can be done differently. The desire to ask and understand the 'why' behind the 'what' got him into analytics early in his career, where questioning and hypothesising are the bedrocks to success.

Venkat's career can be divided into four parts; In the first part, he acted as an individual contributor and wanted to be the best-skilled employee and compete

with others in virtue of his skillset and content. In the second, where he had the opportunity to move to the USA to work directly with business stakeholders, he learned that content is only as important as the business context in which it is applied.

Midway through the journey, he started taking up roles with P&L responsibility, such as client partnering, where he realised that skill and context are only meaningful if it creates commercial value. Over the last five years, where he has played global leadership roles, he realised that content, context, and commerce are only a strategic advantage if they lead to sustainable cultural shift. He mentions “Real success of analytics should be measured by the tangible difference created for customers, colleagues and shareholders and not as a measure of scientific or technological greatness.” The challenge was to realise the need for a shift in thinking at different stages of his career. The mentors throughout his journey gave him the right nudges to evolve the mindset to look at a continuum of 4CsContent, Context, Commerce, Culture.

“ “

Appreciate problems, for they opportunitiesareindisguise.

Venkat Raghavan

Analytics - an Asset For Tesco

Tesco is a food retailer with over 100 years of heritage with an annual turnover of close to £55bn. As a leading multinational retailer with more than 345,000 colleagues, the company aims to serve customers daily with affordable, healthy, and sustainable food – to help them enjoy a better quality of life and an easier way of living. Tesco’s core purpose is to serve its customers, communities and planet a little better every day. Tesco has been using analytics and data science to find more opportunities to understand customers and increase Fromprofitability.ascience

standpoint, Venkat is optimistic about the tremendous scope for true AI to scale to understand customers and positively influence their behaviours. The team at Tesco has prioritised personalisation as one of its key strategic priorities to better understand the needs and expectations of its customers and engage with them through the offerings with high relevance and personalisation. He shares, "We are an extremely customer-centric company, therefore, we believe that if we get the pulse of our customers right, we can align our business operations to meet them, thereby unlocking value for our customers and our business. Having said this, the path to getting there is non-trivial – the global economy is going through a highly volatile phase, and our customers face many challenges" Therefore, in a world that is shifting continuously, analytics and science are needed to understand, anticipate, and act to win in the retail industry.

Evolution and Use of Analytics

Over the last 20 years, analytics has evolved from a support entity delivering reports and MIS dashboards to a core problem-solving entity that uses the power of Forecasting, Predictive Modeling, Machine learning, and AI. Today the industry is mature enough to impact the business outcomes directly. It is recommended to look at analytics as a commercial agenda, instead of as a cost centre to build future capabilities. This shift will enable a deeper and more meaningful partnership between business and analytics to deliver tangible results.

"Technology is the largest enabler for analytics and science to evolve." A lot of what analytics can achieve is supported by the foundation created by data and

technology teams. The core use cases where Venkat and his team leverage technology are to:

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Get more data signals about our customers, product, stores, online, and suppliers

Build the right analytics and science infrastructure that can make the petabytes of data accessible and get the right computing power to run large data queries as well as statistical and machine learning algorithms to solve complex problems

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Access to the best tools/technology options to build and visualize analytical solutions.

Automate and deploy the analytical solutions so that they deliver sustainable value

Retail is an early adopter of data and analytics. Since the invention of electronic Point of Sale (PoS) registers about four decades ago, retail has had the gift of harnessing and analysing data to find opportunities for better offerings, pricing, promotions, and customer engagement. One such example from his journey is the launching of one of the world’s largest loyalty programs with over 100 million members. The program created the possibility of understanding customer behaviors to offer better products, promotions, and customer service which resulted in a win-win equation for both the retailer and its customers.

Preparation for the "Next Chapter”

Analytics is a highly crowded market today. He advises young entrepreneurs, "Ensure you have a clear differentiation. For companies in the service industry, cost and quality of your work make a big difference." There are some companies in the product space where flexibility and scalability are pivotal.

For new-age SaaS product companies, it is imperative to understand where data sits – this is an important topic, especially in retail, where data protection and privacy are serious topics.

He adds, "Often, I get emails from organisations, including startups, where the differentiation is unclear. The other suggestion for startups, especially those targeting food retail as an industry, is that our margins are pretty thin. Therefore the ability to connect capability to true P&L impact is essential. Those startups that can establish this are celebrated more than those that don't."