Romanian Distribution Committee Magazine, Volume 11, Issue 3, Year 2020

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Romani an Di s t r i but i on Commi t t ee

VOL UME11 I SSUE3 2020

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Editorial: Industry-Wide Competition and Business-Model Disruptions, Disruptive Technology and Innovation, Seeing the Menace Posed by Changes, Deeply Reflecting and Agilely Acting

According to the latest McKinsey Global Survey on the economy – “The coronavirus effect on global economic sentiment, December 2020” – industry-wide competition and business-model disruptions are representing a couple of growing risks to respondents’ companies’ growth in 2021 - cited by 44% of respondents, compared to 34% before (McKinsey & Company, 2020). Also recently, one of the world’s leading futurists on global trends and disruptive innovation, Daniel Burrus, highlighted that a hard trend transforming business processes in every industry is the disruptive technology, being necessary to properly both use it in training, and educate companies’ employees to work better with it, of course without forgetting of considering honesty, integrity, and delivering on promises (Burrus, 2020). Far in the past (1983), Burus has “identified digital disruption as one of twenty technology-driven Hard Trends that would increasingly shape the future at an exponential rate, and at the same time drive economic value creation”, while five years ago highlighted the need of better understanding that digital disruption happens in waves, pledging for making digital disruption companies’ biggest competitive advantage (Burrus, 2015).

Also in 2015, OECD brought up the subject of disruptive innovations and their effect on competition for discussion, showing that the functioning of existing industries can be profoundly affected by the new technologies or business models (OECD, 2015). A year later, Dr. Martyn Taylor, a Partner in the Sydney office of global law firm Norton Rose Fulbright, approached the competition implications of the digital disruption, arguing why this concept (which is “blowing a Schumpeterian gale of creative destruction throughout the global economy”) can be viewed as a high technology ecosystem (Taylor, 2016). While two years ago, CX expert and New York Times bestselling author Shep Hyken stated: “When technology meets creativity, the opportunity to create convenience can disrupt competitors and even entire industries. Try adding convenience to your customer experience and see what a difference it can make” (Hyken, 2018).

Recently, Callander and Matouschek (2020) argued that: innovation is a matter of doing things both better, and differently; for the nature of the relevant market competition it also

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matters the choice of technology with which to innovate. And that within the context in which it is well-known the considerable attention received at the present time by the question of antitrust policy in innovative industries.

Without doubt, the speed at which innovation happens (both improving the existing products and services, and introducing new ones so as to capture the constantly evolving markets’ needs an organization operate in) is considered very important in today’s agile world (Nieminen, J., 2020). And in the name of innovation, creativity, strength, and endurance it is even permitted to fail (Peters, 2020).

As we underlined from the very beginning in our last issue, there is a real need of creativity in these times of interminable unpredictability, being obvious that there is both no going back to normal as we know it, one hand, and a true need for companies to take a faster pathway toward their digital transformation, on the other hand, while better defining the interplay between efficiency and resiliency.

Within this framework it is worth mentioning that a spontaneous exchange of ideas (which took place on December 2, 2020) at the level of the European Retail Academy network offered us the opportunity to instantly show appreciation for a great Friend: “Dear Professor Hallier, Very interesting approach of a “classical debate” (orderliness and freedom of speech... with regard to the lack of agreement on the start and end years of a wave cycle/the imprecise nature of the theory weakening its validity etc.). Yes indeed, there has been a lot of discussion about this (believed to result from technological innovation) “Kondratiev Wave” (Supercycle, with three phases: expansion, stagnation, recession), as suggested by Schumpeter (in “Business Cycles”), then Simiand (“Phase A” for the ascendant period of the cycle, and “Phase B” for the downward period of it) etc. Also interesting that it was expressed the belief of being in a sixth Kondratieff wave (which started around 2005), the cycle being fueled by advances in healthcare... (and properly handling healthcare issues – improving productivity – to can activate the economic growth). And right now, at the confluence of the new coronavirus crisis (as a Taleb’s “a Black Swan”) and the disruptive technologies (Industry 4.0) & Bostrom’s “Superintelligence” and “The Vulnerable World Hypothesis”, in full global work toward containing COVID-19, a real interesting challenge is launched by our great Friend Prof. Dr. Bernd Hallier, a challenge needing to be addressed smartly...”.

Theodor Valentin Purcărea Editor-in-Chief

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References Burrus, D., 2020. The Human Factor: Digital Connectivity Still Needs a Human Touch, Business Innovation, November 24. [online] Available at: <https://www.businessinnovationbrief.com/competition/disruption/industry/?> [Accessed 21 December 2020].

Burrus, D., 2015. Make Digital Disruption Your Biggest Competitive Advantage, August 26. [online] Available at: <https://www.burrus.com/2015/08/make-digital-disruption-your-biggest-competitive-advantage/> [Accessed 21 December 2020].

Callander, S., Matouschek, N., 2020. The Novelty of Innovation: Competition, Disruption, and Antitrust Policy. [pdf] Stanford University, October 13. [online] Available at: <https://sjc.people.stanford.edu/sites/g/files/sbiybj4051/f/innovation_13october2020.pdf> [Accessed 21 December 2020].

Hyken, C., 2018. Disrupt Your Competition, Business Innovation, October 1. [online] Available at: <https://www.businessinnovationbrief.com/competition/disruption/industry/?> [Accessed 21 December 2020].

McKinsey & Company, 2020. The coronavirus effect on global economic sentiment, Strategy & Corporate Finance Practice, December. [online] Available at: <https://www.mckinsey.com/business-functions/strategy-and-corporatefinance/our-insights/the-coronavirus-effect-on-global-economic-sentiment> [Accessed 19 December 2020].

Nieminen, J., 2020. Pace of Innovation – The Ultimate Competitive Advantage, Business Innovation, November 12, article originally published on Viima’s blog. [online] Available at: <https://www.businessinnovationbrief.com/competition/disruption/industry/?> [Accessed 21 December 2020].

OECD, 2015. Disruptive innovations and their effect on competition, Directorate for Financial and Enterprises Affairs (DAF). [online] Available at: <https://www.oecd.org/daf/competition/disruptive-innovations-andcompetition.htm> [Accessed 21 December 2020].

Peters, B., 2020. Freedom to Fail: Cultivating a Mindset of Innovation, Idea to Value, October 21. [online] Available at: <https://www.ideatovalue.com/insp/beaupeters/2020/10/freedom-to-fail-cultivating-a-mindset-ofinnovation/> [Accessed 21 December 2020].

Taylor, M., 2016. What are the competition implications of ‘digital disruption’? Norton Rose Fulbright, November. [online] Available at: <https://www.nortonrosefulbright.com/en/knowledge/publications/9574b9f5/what-are-thecompetition-implications-of-digital-disruption> [Accessed 21 December 2020].

The Magazine is the result of a true partnership, by bringing scientists and practitioners together proving the passionate pursuit of knowledge for wisdom, the real passion for acquiring and sharing this knowledge inviting the readers to maturing interdisciplinary dialogue and building a transparent culture network.

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Information and Communications Technology New Paradigm of Probabilistic Computing Could Inspire our Thinking through a Future World of Uncertainty -Part 2-

Prof. Eng. Ph.D. Victor GREU Abstract The paper presents the premises of probabilistic computing context evolution, as it is essentially linked with the challenge to maintain the pace of Information and Communications Technology (ICT) development, but providing a sustainable progress for Information society (IS) toward Knowledge Based Society (KBS) and generally for Earth environment. On the other hand, the ICT economic and social impact, including the humankind behaviour evolution, is complicate and difficult to analyse, because of the high level of complexity and uncertainty, when dynamically facing the diversity and the different levels of ICT products and services and applications. In addition, Covid-19 pandemy consequencies, far from being completely foreseen, will bring more and more uncertainity everywhere. One of the most complex and difficult challenge of such analyses is concerning the proper, responsible and opportune understanding of all ICT evolution consequences. Perhaps the most important care, for a sustainable progress of IS/KBS, is to have an efficient and efficacy response at the too fast changes induced by the ICT exponential evolutions, considering the states, organizations or people potential and will for complex and complicate analyses and eventually for expensive reactions/actions. This context could still provide benefic lessons for humankind, based on the ways ICT find new solutions to face the complexity and uncertainty which increase along with its products, services and applications. Such lessons could include more than the simple rules or habits to use ICT, but more than these, they eventually induce new and useful ways to think or approach the diversity of uncertainties that the fast pace and the complex evolutions of ICT and IS/KBS progressively induce in the real life and Earth ecosystem.

The paper first addressed the challenge to maintain the pace of ICT development, often linked with continuing Moore’s Law, considering to provide a sustainable progress for IS/KBS, which is, naturally, an everchanging condition, leading to probabilistic approaches for optimization. The analysis included, by relevant examples, the strategy of ICT leaders to adapt the goal of advancing performances to the new, more and more complex realities, by probabilistic approaches, aiming the highest performance of ICT, where the AI challenge is to further advance from the highest top of ICT in the more and more complex context of applications. The “highest performance” is actually linked with “autonomous systems”, i.e. the most challenging field of ICT applications, where we could find, along with the diversity of robots, self-driving cars. Here the importance of sensors and their precisions, although in a continuous spectacular progress, represent key factors for the sustainable development of applications fields. The inherent limits/errors of actual AI/sensors are mentioned and we consider that it is worth to notice that this is one of the main features of future ICT development, given by the fact that continuously increasing the technology performance level is inherently very complicate and difficult, in a World that complicates with a speed higher that the ICT speed, because of the complex impact at Earth scale and of humankind nature.

As a consequence of these limits, it is necessary to build, on actual levels (waves) of AI, the next wave, but actually we have to observe the essential link between the AI/ICT development and the “human beings“ needs. Here is included not only the fundamental rule of the sustainable development for AI/ICT/IS/KBS, i.e. de proper social need (command), but especially its specific evolution toward uncertainty, when “navigate the world” facing the technology errors risks. This conclusion is, by our opinion, fundamental for the sustainable development of AI/ICT/IS/KBS, because it is necessary to consider the risks of errors, as the humankind and all Earth ecosystem is tending to be too much depending on (mainly ICT) technology, especially when observing critical infrastructure like Internet, power grid, security, defence or … robots. From this point of view, we have to agree that this new

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paradigm of ICT leaders (i.e. probabilistic computing) is very opportune, realistic and responsible. On the other hand, the diversity of scenarios and the scientific/technical difficulties to implement this strategy will rise considerable problems for ICT applications involving probabilistic computing, although the idea is not very new, but the context, the aimed performance and the available technologies come with different challenges/benefits.

On this line, the role of modelling and programming/software is continuously increasing, as a flexible and efficient instrument for updating and improving systems performances when using the available hardware technology to implement.

The analysis also presents that probabilistic modelling and inference are the key factors in improving ML and further DL toward automatization of inference processes using Bayesian theory, in order to optimally cover the probabilistic scenarios of complex and dynamic context of AI applications. Here we noticed that correcting and re-orienting ML could make of it „the art of the possible”, i.e. having the potential to obtain remarkable improvements of AI applications. Toward such aim, it is pointed the intrinsic capacity of humans to make connections and generalize based on experience/memory and intuition, which are this way identified as desired features for AI, considering the inherent noise behaviour and operation that could provide the desired functionality and performance as the brain.

An important conclusion resulted as innovating both modelling/software and hardware structure of the AI systems could provide more advanced performances when facing uncertainty. The exemples confirmed the clear tendency and results toward using probabilistic computing AI/ICT for improvements when solving problems with high uncertainity data, approaching models which are inspired from human brain operational structure, but the way these advances could be useful for humans, beyond the main purpose of each application, is another, more complicate, issue. In fact, it is a complex ecosysytem of processes where the ICT/AI progress solutions could generate lessons to be learn beyond the areas and aims they are native implemented or designed. That is why it is very important, but also tough, to deeply analyse the balance and consequences of the complex and mutual dependencies in the processes inspired from humans and for humans. Going further from the ethical dilemma of these highest AI/ICT advances, we have to further analyze how such solutions issued from some humans thinking could influence all other humans thinking, especially facing life/Earth uncertainities.

Considering the mentioned noise as a generic or perturbation factor for decisions (of incumbents or individuals), when facing uncertainty data, we can go further and imagine that regardless the nature of noise/perturbation, it is necessary to have a strategy that optimally matches the process/case and this will be based on probabilistic approaches issued from the above elements and then extended to other areas. The supposed useful elements could include models and algorithms, but most concrete, each decision process will have to identify the probability distribution that better suits the context and the performance level. All these applications/contexts will gradually generate, along with AI/ICT devices and services, added value learned lessons to be used in a diversity of areas and scenarios, where we have to recall that imagination is the limit.

Consequently we have to consider again and again, the crucial importance of refining knowledge, as general model for IS/KBS, which generates such benefic „added value” in this complex ecosystem of Earth, where humans inspire ... humans, in processes that are distant in time, space and ... way of thinking.

As a final conclusion, due to their obvious difficulty, dynamic, levels and diversity of areas, such analyses needs further and timely continuation, for having efficacy results and useful conclusions in order to inspire people’s way of thinking in the World increasing uncertainty.

Keywords: probabilistic computing, quantum computing, artificial intelligence, machine learning, deep learning, qubit, probabilistic inference, neuronal network, information society, knowledge based society, human brain JEL Classification: L63; L86; M15; O31; O33

Ignorance gives one a large range of probabilities ― George Eliot

1. ICT is heading toward the third wave of AI by probabilistic computing Watching the amazing ways Information and Communications Technologies (ICT) influence our daily life, offering a fast changing picture of products and services, where the incredible technological advances pentrates all the activity fields, we simply could agree that ICT is a prominent factor of the progress of the Information society (IS) toward Knowledge Based Society (KBS).

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Even if we would consider only the benefic consequences of ICT exponential development, step by step the Earth complex realities prove that ... it is not enough!

Considering, for example, the prominent ICT advances, like Internet of Things (IoT), Artificial Intelligence (AI), Cloud, BIG DATA, 5G or the family of nanotechnologies, we have to observe that all their applications and associated processes at Earth scale, inherently will generate complex consequences and challenges.

Starting from this general approach, the principal challenge is to maintain the pace of ICT development, but providing a sustainable progress for IS/KBS and generally for Earth environment. Here we have to recall our repeated mentions [9] [6] of Earth challenges regarding climate changes, resources fading etc.

On the other hand, the ICT economic and social impact, including the humankind behaviour evolution, is complicate and difficult to analyse, because of the high level of complexity and uncertainty, when dynamically facing the diversity and the different levels of ICT products and services and applications. In addition, Covid-19 consequencies, far from being completely foreseen, will bring more and more uncertainity everywhere.

More than these, we have to emphasize one of the most complex and difficult issue, although sometimes not so evident, concerning the proper, responsible and opportune understanding of all these consequences and challenges of ICT evolution.

With other words, perhaps the most important care, for a sustainable progress of IS/KBS, is to have an efficient and efficacy response at the too fast changes induced by the ICT exponential evolutions, considering the states, organizations or people potential and will for complex and complicate analyses and eventually for expensive reactions/actions.

This way it is obvious that the timely analysis and knowledge refining, regarding ICT development and impact on IS/KBS is more than necessary, although difficult and inherently always far from being complete.

The benefits of such analyses could include, as our paper title emphasizes, important lessons for humankind, regarding the ways ICT find new solutions to face the complexity and uncertainty which increase along with its products, services and applications.

It is important to recall [3] [25], that such “lessons” could include more than the simple rules or habits to use ICT, but more than these, they eventually induce new and useful ways to think or approach the diversity of uncertainties that the fast pace and the complex evolutions of ICT and IS/KBS progressively induce in the real life and Earth environment.

In order to have a concrete expression of these challenges and preoccupations which could also bring the necessary confidence of their real importance, some relevant examples and references will be useful.

With a systemic approach, among the first we should address the challenge to maintain the pace of ICT development, often linked with continuing Moore’s Law [3][18][10][11][20], but now we should consider to provide a sustainable progress for IS/KBS and generally for Earth environment, which is, naturally, an ever-changing condition, leading to probabilistic approaches for optimization.

This way, we can understand the strategy of ICT leaders to adapt the goal of advancing performances to the new, more and more complex realities, by probabilistic approaches [1]: “Intel announced today that it is forming a strategic research alliance to take artificial intelligence to the next level. Autonomous systems don’t have good enough ways to respond to

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the uncertainties of the real world, and they don’t have a good enough way to understand how the uncertainties of their sensors should factor into the decisions they need to make. According to Intel CTO Mike Mayberry, the answer is “probabilistic computing,” which he says could be AI’s next wave.”

This Intel point of view is very relevant and brings together many sides of the analysed context, as it focused on the actual main ICT advanced field: AI. The relevance starts with the aim of highest performance of ICT, where the AI challenge is to further advance from the highest top of ICT in the more and more complex context of applications.

Perhaps less evident is the issue that, beyond a general pointing of AI, here we could observe that “highest performance” is actually linked with “autonomous systems”, i.e. the most challenging field of ICT applications, where we could find, along with the diversity of robots, self-driving cars.

Here the importance of sensors and their precisions, although in a continuous spectacular progress, represent key factors for the sustainable development of applications fields.

In a concrete manner, this context is suggested by the huge area of sensors that will enable unprecedented applications and performances, where the data they will provide could definitely influence the involved complex decision processes.

This way, step by step, the main idea of “probabilistic computing” is naturally found as “AI’s next wave”, but this is obviously just the start of a long and winding road toward the desired optimal models and solutions, from field to field of applications.

As we already mentioned [3] [21], the complexity and difficulty of optimizing ICT development is generally an “iceberg tip”, further detailed by Intel (one of the main players of ICT) as: “We’re trying to figure out what the next wave of AI is. The original wave of AI is based on logic and it’s based on writing down rules; it’s closest to what you’d call classical reasoning. The current wave of AI is around sensing and perception—using a convolutional neural net to scan an image and see if something of interest is there. Those two by themselves don’t add up to all the things that human beings do naturally as they navigate the world. An example of this would be where you are startled by something—let’s say a car siren. You’d automatically be thinking of different scenarios that would be consistent with the data you have and you would also be conscious of the data you don’t have. You would be inferring a probability. Maybe the probability is figuring out whether the siren is coming from ahead of you or behind you. Or whether it is going to make you late for a meeting. You automatically do things that machines have trouble with. We run into those situations all the time in real life, because there’s always uncertainty around what is the current situation.”

This is a very relevant analysis, made at Intel, due to the multiple sides it suddenly reveals, in order to create a clear picture of realities we have to face in spite of our unprecedented progress we benefit.

First, by a systemic approach, the inherent limits of actual AI/sensors are mentioned and we consider that it is worth to notice that this is one of the main features of future ICT development, given by the fact that continuously increasing the technology performance level is inherently very complicate and difficult, in a World that complicates with a speed

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higher that the ICT speed, because of the complex impact at Earth scale and of humankind nature.

After considering the limits, it is necessary to build, on actual levels (waves) of AI, the next wave, but here we have to observe the essential link between the AI/ICT development and the “human beings” needs.

In fact, this is the point where we can observe not only the fundamental rule of the sustainable development for AI/ICT/IS/KBS, i.e. de proper social need (command), but especially its specific evolution toward uncertainty, when “navigate the world”.

To understand the whole significations of this fundamental but complex reality, the simple but relevant example of the siren has the remarkable potential to realistically link the complex scenario/context (of traffic) with the main technological advances (autonomous cars/systems), starting from the human intelligence case, but clearly pointing the future design of AI case.

Quite from here we could observe the mutual relation, concerning the models and features, of the advanced AI or generally probabilistic computing, with the human brain.

With simpler words, the aim of probabilistic computing is to optimally solve the classes of problems AI systems could meet, in the complex environment of future World, with models and algorithms which could mimic the way human brain does.

As we have already mentioned [12][3][15], this strategy will change the paradigm of AI/ICT, i.e. using less data, because the Data Deluge could contain much uncertainty or ambiguity and on the other hand human brain has the capacity to take decisions from less data, even when containing incertitude.

A concrete expression of this limit of AI/ICT is also given, considering the actual typical case of machine learning applications: “Currently AI and deep-learning systems have been described as brittle. What we mean by that is they are overconfident in their answer. They’ll say with 99 percent certainty that there something in a picture that it thinks it recognizes. But in many cases the probability is incorrect; confidence is not as high as [the AI] thinks it is.”

This conclusion is, by our opinion, fundamental for the sustainable development of AI/ICT/IS/KBS, because, as we have already presented [18] [6] and here is confirmed, it is necessary to consider the risks of errors, as the humankind and all Earth ecosystem is tending to be too much depending on (mainly ICT) technology, especially when observing critical infrastructure like Internet, power grid, security, defence or … robots.

From this point of view, we have to agree that this new paradigm of ICT leaders (i.e. probabilistic computing) is very opportune, realistic and responsible.

On the other hand, the diversity of scenarios and the scientific/technical difficulties to implement this strategy will rise considerable problems for ICT applications involving probabilistic computing, although the idea is not very new, but the context, the aimed performance and the available technologies come with different challenges/benefits.

As above the challenges analysis was first considered, the benefits of the technology advances would, perhaps, complete the picture of probabilistic computing premises.

The role of modelling and programming/software is continuously increasing, as a flexible and efficient instrument for updating and improving systems performances when using the available hardware technology to implement [2]:

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“Let us start, as we always should, with first principles. Probabilistic models help us to draw population inferences – that is we create mathematical models to help us to understand or test a hypothesis about how a system or environment behaves. Probabilistic reasoning is a fundamental pillar of machine learning (ML), whereas deep learning (DL) can be distinguished from machine learning through its employment of gradient-based optimization algorithms.

Probabilistic programming languages are designed to describe probabilistic models and then perform inference in those models… As stated above, probabilistic programming languages and tools allow us to automate Bayesian inference. In other words, it allows us to code using probabilistic language-specific syntax to describe conditional probability distributions.”

Here we can observe that probabilistic modelling and inference are the key factors in improving ML and further DL toward automatization of inference processes using Bayesian theory, in order to optimally cover the probabilistic scenarios of complex and dynamic real context of AI applications.

As we already mentioned in [3], the hardware improvement is more difficult in the actual advanced stage of AI/ICT, but on the other hand, Moore’s Law foreseeable saturation has generated a deep research for revolutionary technologies, which will provide the highest performances required by AI progress.

More than these, quantum computing [4][13][16][17][19][23][24] proved to be very much linked with probabilistic computing , but here the progress is still very difficult and still slow, although the technology leaders (like Intel, NSF, IBM, AWS, M’soft) collaborate to advance faster [4]: “We obtain single-qubit control via electron spin resonance and readout using Pauli spin blockade. In addition, we show individual coherent control of two qubits and measure single-qubit fidelities of up to 99.3 per cent. We demonstrate the tunability of the exchange interaction between the two spins from 0.5 to 18 megahertz and use it to execute coherent twoqubit controlled rotations. The demonstration of ‘hot’ and universal quantum logic in a semiconductor platform paves the way for quantum integrated circuits that host both the quantum hardware and its control circuitry on the same chip, providing a scalable approach towards practical quantum information processing.”

One of the main problems encountered by the researchers is to extend the capacity of processing system to control more qubits (up to millions), which leads to complex control electronics circuitry, but Intel started to solve this issue by integrating qubits and control on the same chip: <<As Intel emphasized, “Applying quantum computing to practical problems hinges on the ability to scale to and control thousands – if not millions – of qubits at the same time with high levels of fidelity. However, current quantum systems designs are limited by overall system size, qubit fidelity and especially the complexity of control electronics required to manage the quantum at large scale. Having the control electronics and spin qubits integrated on the same chip greatly simplifies the interconnections between the two.”>>.

Of course, these examples are only tips of the icebergs involved in the technology advances, but it is important that they prove the importance and the dimensions of this new wave of AI we witnessing, with the confidence of unprecedented performances and the hope for a sustainable progress that could be extended from technology to our life benefit and even reasoning against uncertainties.

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2. Probabilistically modelling and thinking AI, inspired from humans and for humans With or without Moore’s Law, ICT and generally the technology in many fields of activity have to learn from nature’s research, as we repeatedely mentioned [18][3], but especially now, facing the challenges above presented, AI/ICT are truly involved in „mimicking” the human brain.

Obviously, this picture is changing as AI/ICT exponential evolution and performances are fast changing and also the ICT/IS/KBS in the Earth ecosystem is going more complex and difficult to optimize „sitting on top” technologies but facing challenges never encountered before.

On the other hand, the humankind evolution and behaviour is also changing, among other just due/because of the ICT benefits/consequences.

Last but not the least, entering the delicate field of „human thinking” changes, the averaged model to follow is more and more difficult to define.

With little words, these could be some prominent premises when analyzing how „probabilistically modelling and thinking AI” in the more general frame of probabilistic computing and AI/ICT performances increasing.

Without looking for references for all premises or involved factors, it is useful to observe, by some relevant examples, the ways this research, for higher performances and better efficacy/efficiency of future AI, could be achieved.

Although, generally, programming could be seen (by error) as a technical issue and having less potential for providing revolutionary improvements, now there are (partially above mentioned) prominent premises to reverse such opinion, as it is detailed demonstrated by [5]: „Today machine learning is rigid and requires massive amounts of data. But AI researchers are attempting to emulate the low-data fluidity and rich representations of human thinking. Give credit to Thomas Bayes....Two aspects of conceptual knowledge have eluded machine learning systems. First, for most natural categories (birds, fish, dogs, people) and artificial categories (man-made cars, boats, smartphones), people seem to be able to learn new concepts from one or a handful of examples. Standard machine learning algorithms, on the other hand, require large numbers of examples... Second, humans master richer representations of the categories than machines can, even for simple concepts; that is, they understand what inherent features make a bird a bird and a rock a rock. Humans learn these inherent features without careful study or instruction and can use them for a wide range of functions. Even when objects in a category are quite diverse, humans can create new “exemplars” — generalized concepts stored in memory — parse objects into parts, relate them to similar objects and develop new abstract categories. In contrast, the best machine classifiers fall behind when they attempt these additional functions, even with deeper analysis and specialized algorithms.”

Here we have to notice, before entering into details, that correcting and re-orienting ML could make of it „the art of the possible”, i.e. having the potential to obtain remarkable improvements of AI applications.

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Toward such aim, it is pointed the inherent capacity of humans to make conections and generalize based on experience/memory and intuition, which are this way identified as desired features for AI. In order to achieve such objectives, some introspections into human brain behaviour and operation structure are given: „A central challenge is to explain two characteristics of human conceptual learning: how people learn new concepts from just a few examples and how they generate such abstract, rich and flexible representations. An even greater challenge arises when you put the two together: How can machine learning use small amounts of data and produce rich representations? If this sounds paradoxical, it is, based on most current learning theories.

Nonetheless, people seem to navigate this trade-off with remarkable agility, learning rich concepts that generalize well from relatively sparse data. The answer may lie with a long-dead Presbyterian minister who had a deep interest in probabilities...”

The way AI could benefit from (theorem of Thomas Bayes, a Presbyterian minister) Bayesian probability and ... thinking, is very well pointed, considering simple examples from real life, where human brain operates in a simple manner: „This theorem is a means of updating beliefs in a hypothesis based on new evidence. It is rooted in probabilities: The more often you see the sun rise in the morning, the higher the probability that it will continue to happen in the future. The Bayesian approach captures a key aspect of how humans learn in an uncertain world. And although this learning can be quite complex, involving many hypotheses and multiple probabilities, it has led to a new form of AI that is improved by learning and inference.”

After suggesting how AI could achieve similar performances based on considering all relevant hypotheses and multiple probabilities, the improving of inference processes could come as: „More recent developments in high-performance computing and deep learning algorithms suggest that probabilistic computing is entering a new era. In the next few years, experts anticipate research to produce significant improvements in the reliability, security, serviceability and performance of AI systems, including hardware designed specifically for probabilistic computing. There are certainly strong incentives for developing machine learning approaches that are easier to use and less data-hungry. Machine learning currently requires a large, raw dataset, which typically needs humans to manually label it, clean it and reduce “noise” — that is, meaningless or random data. The actual learning takes place inside large data centers using many computer processors churning away in parallel for hours or days. In general, the time and cost associated with this are material.”

Finally, the essence of such approach is pointed and reveals the main mechanisms which allow to use less data, but provide higher efficiency and effective inference, this way nearing the human model: „Because Bayesian methods easily incorporate prior knowledge, effective inference can often be performed with a lot less data. This increases the efficiency of implementing new models and understanding data. Just as high-level programming languages transformed developer productivity by eliminating the need to deal with technical details of processors and memory architecture, probabilistic languages promise to free developers from the complexities of high-performance probabilistic inference. In short, BPS allows more efficient search to find

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the optimum possibility. The constraints are probabilistic, and the output is a probability distribution that can then be further refined.”

Although antecipated and very desirable, the reliability, security, serviceability and performance of AI systems, which could be obtained implementing brain models, need also to face the challenges that arose from the complex cortical processes to mimic [7]: „Probabilistic inference as a principle of brain function has attracted increasing attention over the past decades. In support of a sampling-based “Bayesian-brain hypothesis”, the high in-vivo response variability of cortical neurons observed in electrophysiological recordings is interpreted in the context of ongoing probabilistic computation. Simultaneously, it has been found that intrinsically stochastic neural networks are a suitable substrate for machine learning. These findings have led to the incorporation of noise into computational neuroscience models, in particular to give account for the mechanisms underlying stochastic computing such as sampling-based probabilistic inference in biological neuronal substrates.

Note that the term “stochastic computing” refers to the idea that the variability required for this form of computing can be mathematically described as (or replaced by) quasi-stochasticity without altering the functionality of the network. It does not imply that its implementation is relying on truly stochastic sources of noise, neither in natural nor synthetic neuronal substrates.”

Consequently, the AI models design have to consider and implement the inherent noise behaviour and operation that could provide the desired functionality and performance as the brain: „Neuronal network models of high-level brain functions such as memory recall and reasoning often rely on the presence of some form of noise. The majority of these models assumes that each neuron in the functional network is equipped with its own private source of randomness, often in the form of uncorrelated external noise. In vivo, synaptic background input has been suggested to serve as the main source of noise in biological neuronal networks.

However, the finiteness of the number of such noise sources constitutes a challenge to this idea.

Here, we show that shared-noise correlations resulting from a finite number of independent noise sources can substantially impair the performance of stochastic network models. We demonstrate that this problem is naturally overcome by replacing the ensemble of independent noise sources by a deterministic recurrent neuronal network. By virtue of inhibitory feedback, such networks can generate small residual spatial correlations in their activity which, counter to intuition, suppress the detrimental effect of shared input. We exploit this mechanism to show that a single recurrent network of a few hundred neurons can serve as a natural noise source for a large ensemble of functional networks performing probabilistic computations, each comprising thousands of units.”

Without other details we could notice that a very useful solution for these challenges is replacing the ensemble of independent noise sources by a deterministic recurrent neuronal network, which obviously has the advantage of an easier implementation, due to its simplified network along with performance increase.

Innovating both modelling/software and hardware structure of the AI systems could provide more advanced performances when facing uncertainty, as it is also confirmed by [8]: “Traditional computers often seem brilliant and simpleminded at the same time. On the one hand, they can perform billions of high-precision numerical operations per second with

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perfect repeatability. On the other hand, they fail catastrophically when their inputs are incomplete or ambiguous. These strengths and weaknesses flow from their mathematical foundations in deductive logic and deterministic functions. Navia Systems is working to change all this, by building the worldâ&#x20AC;&#x2122;s first natively probabilistic computers, designed from the ground up to handle ambiguity, make good guesses, and learn from their experience. Instead of logic and determinism, Naviaâ&#x20AC;&#x2122;s hardware and software are grounded in probability distributions and stochastic simulators, generalizing the mathematics of traditional computing to the probabilistic setting. The result is a technology as suited to making judgements in the presence of uncertainty as traditional computing technology is to large-scale record keeping.â&#x20AC;?

All these exemples confirm the clear tendency and results toward using probabilistic computing AI/ICT to improve performancies when solving problems with high uncertainity data, approaching models which are inspired from human brain operational structure, but the way these advances could be useful for humans, beyond the main purpose of each application, is a another, more complicate, issue [22].

In fact, it is a complex ecosysytem of processes where the ICT/AI progress solutions could generate lessons to be learn beyond the areas and aims they are native implemented or designed.

That is why it is very important, but also tough, to deeply analyse the balance and consequences of the complex and mutual dependencies in the processes inspired from humans and for humans.

Going further from the ethical dilemma of these highest AI/ICT advances (Who is worrying us most, the robots or the humans?), we have to see first how such solutions issued from some humans thinking could influence all other humans thinking, especially facing life/Earth uncertainities.

Although it could seem that we comeback to analysis starting point, now we have above presented elements/examples to observe what is new, or added value, when supposing to teach humans with lessons that apparently have been learned from ... humans.

To be more concrete, lets just consider the noise, as one of the most important sources of uncertainty/ambiguity for both machines and humans.

Here we have to recall, as a relevant example, from the above, that replacing the ensemble of independent noise sources by a deterministic recurrent neuronal network, which adresses the models of high-level brain functions such as memory recall and reasoning, is eventually an AI/ICT solution inspired from brain, but it could provide also better results in many areas of applications (including e-health), as a starting or way of thinking (idea).

If we consider noise as a generic or perturbation factor for decisions (of incumbents or individuals), when facing uncertainty data, we can go further and imagine that regardless the nature of noise/perturbation, it is necessary to have a strategy that optimally matches the process/case and this will be based on probabilistic approaches issued from the above elements and then extended to other areas.

The supposed useful elements could include models and algorithms, but most concrete, each decision process will have to identify the probability distribution that better suits the context and the performance level.

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All these applications/contexts will gradually generate, along with AI/ICT devices and services, added value learned lessons to be used in a diversity of areas and scenarios, where we have to recall that ... imagination is the limit.

In other words, we have to consider again and again, as we have already presented [12][15][21][24], the crucial importance of refining knowledge, as general model for IS/KBS, which generates such benefic „added value” in this complex ecosystem of Earth, where humans inspire ... humans, in processes that are distant in time, space and ... way of thinking.

Due to their obvious difficulty, dynamic, levels and diversity of areas, such analyses needs further and timely continuation, for having efficacy results and useful conclusions in order to inspire people’s way of thinking in the World increasing uncertainty.

3. Conclusions The analysis started from the premise that probabilistic computing context is essentially linked with the challenge to maintain the pace of ICT development, but providing a sustainable progress for IS/KBS and generally for Earth environment. On the other hand, the ICT economic and social impact, including the humankind behaviour evolution, is complicate and difficult to analyse, because of the high level of complexity and uncertainty, when dynamically facing the diversity and the different levels of ICT products and services and applications. In addition, Covid-19 consequencies, far from being completely foreseen, will bring more and more uncertainity everywhere. One of the most complex and difficult challenge of such analyses is concerning the proper, responsible and opportune understanding of all ICT evolution consequences. Perhaps the most important care, for a sustainable progress of IS/KBS, is to have an efficient and efficacy response at the too fast changes induced by the ICT exponential evolutions, considering the states, organizations or people potential and will for complex and complicate analyses and eventually for expensive reactions/actions.

This context could still provide benefic lessons for humankind, based on the ways ICT find new solutions to face the complexity and uncertainty which increase along with its products, services and applications. Such lessons could include more than the simple rules or habits to use ICT, but more than these, they eventually induce new and useful ways to think or approach the diversity of uncertainties that the fast pace and the complex evolutions of ICT and IS/KBS progressively induce in the real life and Earth ecosystem.

By a systemic approach, the paper first addressed the challenge to maintain the pace of ICT development, often linked with continuing Moore’s Law, considering to provide a sustainable progress for IS/KBS, which is, naturally, an ever-changing condition, leading to probabilistic approaches for optimization.

This way, the analysis included, by relevant examples, the strategy of ICT leaders to adapt the goal of advancing performances to the new, more and more complex realities, by probabilistic approaches, aiming the highest performance of ICT, where the AI challenge is to further advance from the highest top of ICT in the more and more complex context of applications.

The “highest performance” is actually linked with “autonomous systems”, i.e. the most challenging field of ICT applications, where we could find, along with the diversity of robots,

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self-driving cars. Here the importance of sensors and their precisions, although in a continuous spectacular progress, represent key factors for the sustainable development of applications fields. The inherent limits/errors of actual AI/sensors are mentioned and we consider that it is worth to notice that this is one of the main features of future ICT development, given by the fact that continuously increasing the technology performance level is inherently very complicate and difficult, in a World that complicates with a speed higher that the ICT speed, because of the complex impact at Earth scale and of humankind nature.

Considering these limits, it is necessary to build, on actual levels (waves) of AI, the next wave, but actually we have to observe the essential link between the AI/ICT development and the “human beings” needs. Here is included not only the fundamental rule of the sustainable development for AI/ICT/IS/KBS, i.e. de proper social need (command), but especially its specific evolution toward uncertainty, when “navigate the world” facing the technology errors risks.

This conclusion is, by our opinion, fundamental for the sustainable development of AI/ICT/IS/KBS, because it is necessary to consider the risks of errors, as the humankind and all Earth ecosystem is tending to be too much depending on (mainly ICT) technology, especially when observing critical infrastructure like Internet, power grid, security, defence or … robots. From this point of view, we have to agree that this new paradigm of ICT leaders (i.e. probabilistic computing) is very opportune, realistic and responsible.

On the other hand, the diversity of scenarios and the scientific/technical difficulties to implement this strategy will rise considerable problems for ICT applications involving probabilistic computing, although the idea is not very new, but the context, the aimed performance and the available technologies come with different challenges/benefits.

On this line, the role of modelling and programming/software is continuously increasing, as a flexible and efficient instrument for updating and improving systems performances when using the available hardware technology to implement.

The analysis presented that probabilistic modelling and inference are the key factors in improving ML and further DL toward automatization of inference processes using Bayesian theory, in order to optimally cover the probabilistic scenarios of complex and dynamic context of AI applications. Here we noticed that correcting and re-orienting ML could make of it „the art of the possible”, i.e. having the potential to obtain remarkable improvements of AI applications. Toward such aim, it is pointed the intrinsic capacity of humans to make connections and generalize based on experience/memory and intuition, which are this way identified as desired features for AI, considering the inherent noise behaviour and operation that could provide the desired functionality and performance as the brain.

An important conclusion resulted as innovating both modelling/software and hardware structure of the AI systems could provide more advanced performances when facing uncertainty. The exemples confirmed the clear tendency and results toward using probabilistic computing AI/ICT for improvements when solving problems with high uncertainity data, approaching models which are inspired from human brain operational structure, but the way these advances could be useful for humans, beyond the main purpose of each application, is another, more complicate, issue. In fact, it is a complex ecosysytem of processes where the ICT/AI progress solutions could generate lessons to be learn beyond the areas and aims they are native implemented or designed. That is why it is very important, but also tough, to deeply

24

analyse the balance and consequences of the complex and mutual dependencies in the processes inspired from humans and for humans.

Going further from the ethical dilemma of these highest AI/ICT advances, we have to further analyze how such solutions issued from some humans thinking could influence all other humans thinking, especially facing life/Earth uncertainities.

Considering the mentioned noise as a generic or perturbation factor for decisions (of incumbents or individuals), when facing uncertainty data, we can go further and imagine that regardless the nature of noise/perturbation, it is necessary to have a strategy that optimally matches the process/case and this will be based on probabilistic approaches issued from the above elements and then extended to other areas. The supposed useful elements could include models and algorithms, but most concrete, each decision process will have to identify the probability distribution that better suits the context and the performance level.

All these applications/contexts will gradually generate, along with AI/ICT devices and services, added value learned lessons to be used in a diversity of areas and scenarios, where we have to recall that imagination is the limit.

Consequently we have to consider again and again, as we have already presented [12][15][21][24], the crucial importance of refining knowledge, as general model for IS/KBS, which generates such benefic „added value” in this complex ecosystem of Earth, where humans inspire ... humans, in processes that are distant in time, space and ... way of thinking.

Finally, due to their obvious difficulty, dynamic, levels and diversity of areas, such analyses needs further and timely continuation, for having efficacy results and useful conclusions in order to inspire people’s way of thinking in the World increasing uncertainty.

REFERENCES [1]Samuel K.Moore, Intel Starts R&D Effort in Probabilistic Computing for AI Seeks ways to help selfdriving cars and autonomous robots deal with the uncertainty of the real world, IEEE Spectrum, May 2018.

[2]Jillur Quddus, The Future of Artificial Intelligence Part 1 - Probabilistic Programming Languages, APRIL 26, 2019|IN EMERGING TECHNOLOGY INSIGHT, https://methods.co.uk/blog/the-futureof-artificial-intelligence-part-1-probabilistic-programming-languages/ [3]Victor Greu, Information and Communications Technology new paradigm of probabilistic computing could inspire our thinking through a future World of uncertainty - (Part 1), Romanian Distribution Committee Magazine, Volume 11, Issue 2, Year 2020.

[4]John Russell, Quantum Bits: Intel Turns up the Heat; NSF, IBM, AWS, M’soft Collaborate; Q-CTRL Takes in Cash, April 15, 2020,https://www.hpcwire.com/2020/04/15/ quantum-bits-intel-turns-up-theheat-nsf-ibm-aws-msoft-collaborate-q-ctrl-takes-in-cash/ [5] Michael Kozlov, Ashish Kulkarni, Probabilistic programming and the art of the possible, May16, 2019, https://www.weareworldquant.com/en/thought-leadership/probabilistic-programming-and-theart-of-the-possible/ [6]Victor Greu, The information and communications technology is driving artificial intelligence to leverage refined knowledge for the World sustainable development – (Part 2), Romanian Distribution Committee Magazine, Volume 10, Issue 1, Year 2019.

[7]Jakob Jordan et al, Deterministic networks for probabilistic computing, December 2019, https://www.nature.com/articles/s41598-019-54137-7

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[8]Melih Bilgil, What is probabilistic computing?, 2018, Navia Systems, http://www.lonja.de/what-isprobabilistic-computing/ [9]Victor Greu, Searching the right tracks of new technologies in the earth race for a balance between progress and survival, Romanian Distribution Committee Magazine, Volume 3, Issue1, Year 2012.

[10]Katherine Derbyshire, How The Brain Saves Energy By Doing Less, March 15th, 2018, https://semiengineering.com/how-the-brain-saves-energy-by-doing-less/ [11]Will Knight, Intel’s New Chips Are More Brain-Like Than Ever, January 9, 2018, https://www.technologyreview.com /2018/01/09/67469/ intels-new-chips-are-more-brain-like-thanever/ [12]Florin Enache, Victor Greu, Petrică Ciotîrnae, Florin Popescu, Model and Algorithms for Optimizing a Human Computing System Oriented to Knowledge Extraction by Use of Crowdsourcing, 2020 13th International Conference on Communications (COMM), (Politehnica University of Bucharest, Military Technical Academy, IEEE Romania), https://ieeexplore.ieee.org/document/9141972 [13]Vikash K. Mansinghka, MIT Probabilistic Computing Project, 2020, http://probcomp.csail.mit.edu/ [14]***, Intel Scales Neuromorphic Research System to 100 Million Neurons, March 18, 2020, https://newsroom.intel.com/news/intel-scales-neuromorphic-research-system-100-millionneurons/#gs.8os7kd [15]Victor Greu et all, Human and artificial intelligence driven incentive-operation model and algorithms for a multi-purpose integrated crowdsensing-crowdsourcing scalable system, Proceedings of International Conference Communications 2018, (Politehnica University of Bucharest, Military Technical Academy, IEEE Romania), June 2018.

[16]Michael Irving, Intel's new neuron-based computer matches brain of a small mammal, March 19, 2020, https://newatlas.com/computers/intel-neuromorphic-computer-pohoiki-springs/ [17]John Russell, Is Is There a Probabilistic Computer in Your Future, September 23, 2019, https://www.hpcwire.com/2019/09/23/is-there-a-probabilistic-computer-in-your-future/ [18]Victor GREU, Information and Communications Technologies are Learning from Nature’s “Research” to Push the Performance Limits, Romanian Distribution Committee Magazine, Volume 5, Issue 1, Year 2014 [19]Sandeep Ravindran, Building a Silicon Brain, Computer chips based on biological neurons may help simulate larger and more-complex brain models, Apr 30, 2019, https://www.thescientist.com/features/building-a-silicon-brain-65738, [20]Robert W. Lucky, Back To The Elusive Future We looked back for inspiration on looking forward, IEEE Spectrum, Jan 2020.

[21]Victor Greu, Extending information and communications technologies’ impact on knowledge based society through artificial and collective intelligence – (Part 3), Romanian Distribution Committee Magazine, Volume 9, Issue 3, Year 2018.

[22]Joel Hruska, The human brain’s remarkably low power consumption, and how computers might mimic its efficiency, July 9, 2014, https://www.extremetech.com/extreme/185984-the-human-brainsremarkably-low-power-consumption-and-how-computers-might-mimic-its-efficiency [23]Will Knight, Intel’s New Chips Are More Brain-Like Than Ever, January 9, 2018, https://www.technologyreview.com /2018/01/09/67469/ intels-new-chips-are-more-brain-like-thanever/ [24]Victor Greu, The Exponential Development of the Information and Communications Technologies – A Complex Process Which is Generating Progress Knowledge from People to People, Romanian Distribution Committee Magazine, Volume 4, Issue2, Year 2013.

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THE ‘NEW NORMAL’ IN BUSINESS: HOW RETAILERS NEED TO EVOLVE IN 2020

Cosmin TĂNASE Abstract The retail world is reopening its doors to an uncertain and different future. No one knows exactly what the ‘new normal’ will look like and core retail sectors such as grocery, homewares or furniture and fashion are only now adjusting to the implications of an enforced shift online for consumers and to a whole season lost to lockdown respectively. The global COVID-19 pandemic has already had a profound and lasting impact on the retail industry. Seemingly overnight, may retailers closed physical stores, furloughed their employees, and rushed to activate (or develop) business continuity plans. As we enter the stabilization phase retail leaders may be tempted to wonder when things will get back to ‘normal.’ A better question to ask is: how can the organizations be better prepared to react quickly to a sudden change in market conditions?

Keywords: Digital Engagement, Payment Options, Forecasting, Planning, Customers, Competitive Advantage JEL Classification: L81, M31

Things are unlikely to return to ‘normal’ as they used to be, but is it likely that there will be future events, big and small, that will cause market shifts. Retailers who can react quickly, glean necessary insights, and translate those into making strategic adjustments will gain a competitive advantage. Likewise, an

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accelerated push to digitize will enable a new level of organizational agility, cost efficiency, and ability to engage customers in this new age of ‘no contact’ way of doing business. The current stay-at-home restrictions will end in many areas, but consumer sentiment may continue to be influenced by anxiety of public interaction and a preference to buy online. The following are key areas of any retailer’s business model that need to be evaluated with a strong bias for agility and digital enablement to successfully adapt to a new normal in retail.

Digital engagement. How can a company engage with its customers online? Many people are staying in their homes and are more plugged into their digital devices than ever looking for inspiration, connection, and entertainment. Their journey may not start with the intent of buying a product—retailers need to understand how their customers’ online experience may be changing and adapt the content and experience to engage customers in new ways.

• For retailers whose stores are closed, how can they bring the best of the store online? Many customers enjoy the benefits of a personal interaction with a stylist, the rich experience of feeling the fabric, or seeing how a beauty product looks when applied to skin. Innovative solutions from virtual showrooming, live video product demos, and AR solutions to visualize products at home, enable creating a richer and more interactive digital experience that fills the gap online.

• How can a company create a sense of community online? For digital native retailers this is a natural strategy, and many are well on their way in leveraging social and their own digital content to create virtual communities and interactive experiences. Retailers who’ve optimized for brick and mortar experiences need to change their focus and bring those experiences online. Consider live online cooking demos, make up tutorials, trunk shows, who wore it best contests with actual customers inviting an interactive experience.

Technology makes all of this possible and increases geographic reach. The employees know the customers, invite them to innovate and create interactive digital experience that engage and delight the customers accordingly.

• What does the company brand stand for? These are unprecedented times when communities are pulling ever closer together and supporting local businesses and companies that are investing in helping sustain communities. Many companies started campaigns to give products to health care professionals or manufacture in-demand equipment like face masks. Retailers should lead with their brand mission and highlight efforts to source locally, manufacture sustainably, and support local communities. While true for local brands, this is also an opportunity for global brands.

Flexible payment options. Uncertain economic and employment outlook is causing consumers to pull back on discretionary spending. Buy now & pay later, installment payment plans, and payment forgiveness insurance are some of the solutions retailers can offer to incentivize shoppers to buy now rather than waiting. Several flexible payment solution providers offer easy integrations directly into a retailer’s checkout path to support these flexible payment models.

• What type of payment options does the company offer to its customers online?

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• There is evidence that offering installment payment options or buy now pay later increases AOV as well as conversion. Buy now, pay later solutions have been in use for several years but were most popular abroad and among big retailers such as furniture and electronics but recently many fashion and consumer goods retailers started offering these solutions to draw in a wider demographic.

• The retailers should consider the target customer demographic and the average order value to determine if offering more flexible payment options is desirable and likely to drive additional conversion.

No contact delivery. ‘No contact’ has quickly entered the retail vernacular and retailers across sectors are rushing to design and deploy no contact curb side pick-up and delivery options. Customers will flex new muscles and learn new habits that will persist beyond the pandemic making no touch delivery and curb side pick up a trend that is here to stay.

• Do the retailers offer a buy online, pick up in store option for their customers? No contact curb side pickup is quickly emerging as the new version of BOPIS (buy online, pick up in store) for retailers with a brick and mortar presence. A working BOPIS solution can be easily adapted to meet the new no touch guidelines to minimize human contact by considering the physical logistics of the customer interaction during pick up. Map the no contact customer journey to fully understand how to mitigate the safety risks for customers and employees and ensure a positive and re- assuring customers experience. For retailers who have not invested yet in BOPIS, probably the time is now.

• No contact delivery is standard for some retail sectors. The package is delivered via a carrier and left on the customer’s door step or in a building lobby. For other sectors, such as grocery and take out dining the delivery model is changing to offer the customer options ranging from in person door delivery, no contact curb side delivery or no contact door drop off delivery. Enabling online payment at the time of order is an important step in enabling no contact delivery options.

• Another ‘no contact’ solution that’s worth considering especially for retailers who have stores and an idle workforce is last mile concierge services - leveraging store employees for just in time last mile delivery.

This could be especially relevant for product categories that require customization or tailoring services, or even to facilitate exchanges for a different size or color without the time consuming process of shipping something back and re-purchasing. Retailers that innovate and offer unique and personalized benefits are likely to inspire customer loyalty.

Buy planning & forecasting. Global markets have shifted significantly since the spread of COVID19 globally and will continue to shift for months to come. Buy and demand planning needs to be more responsive to fast changing consumer shopping patterns as well as the disruptions to the global supply chain.

• Does the cadence of buy and financial planning cycle enable a quick response to changing market conditions? How much of the planning is manual? A retailer should evaluate these processes, vendor contracts, and enabling technology and look for opportunities to automate. Even small investments in automation will save cost, reduce complexity, and most importantly increase both speed and flexibility in the planning cycle.

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• Does the retailer have the necessary data and analytics to pull in most current shopping/returns patterns as inputs into buy/plan decisions? Historical trends are not a good reference point for the current environment and not a sound predictor of the short to medium term consumer sentiment. Today’s ML and AI capabilities enable a view of changing consumer behavior that can enable predictive analytics capability to uncover changing trends in customers buying behavior and help forecast short to medium term demand.

• Diversification, is a retailer’s supply chain overly reliant on a single manufacturer, a single region, or a single distributor? The retailer should consider if it can source similar products more locally—consumer sentiment has been trending towards a ‘buy-local’ preference and in the wake of COVID-19 consumers are likely going to continue to want to support their local communities.

Product availability & fulfillment. Current market conditions are creating excess inventory scenarios for some product categories and shortages for others. Now more than ever, retailers need real time omnichannel inventory visibility and flexibility to fulfill from anywhere to anywhere to meet customers’ demand especially as distribution networks experience unusual bottlenecks and disruptions. Ability to fulfill customers’ orders quickly and safely is even more of a competitive advantage now and investment here will have a good ROI well beyond the COVID-19 pandemic.

• Many retailers allocate inventory to their online channel separated from store inventory and lack true Omni-channel visibility in real-time or ability to fulfill cross channels. A retailer should then question if it has true real-time inventory visibility across all physical and digital channels. Many modern distributed order management systems provide this capability natively—a technology assessment can help understand if the retailer has the right building blocks to unlock true real- time Omni-channel visibility.

• How automated is a retailer’s warehouse? Robotics for re-stocking and product picking have been the hype for a while, now may be the time to take a closer look. Robotic solutions provides a ‘no contact’ way of fulfilling online orders, giving retailers speed (robots can work 24/7/365) and the flexibility to supplement and ramp up / down a work force during demand spikes or unpredictable times such as a pandemic that impacts the safety of the workforce.

Returns. With the closure of stores, more customers will leverage a retailer’s online returns process. In the past retailers focused on making returns cost effective, but in today’s market more than ever a flexible and easy online returns process is a competitive advantage that will drive customer loyalty. There is mounting evidence that customers would not return to a retailer with a difficult returns process, but on the other hand many customers who had a positive returns experience would prompt them to visit the merchant again.

• A retailer should evaluate its return policy against its competitors. Many retailers don’t review their return policy or the return customer journey frequently and treat this as an afterthought. There is increasing evidence that customers prefer to buy from retailers who offer a no hassle return policy.

• Does the retailer require a customer to pay for shipping returns? Can a customer initiate a return online and print a label? With many stores closed and customers unable to drop off returns, making online returns easy will provide confidence with the customers removing friction from a buying decision.

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• The retailer should explore additional options to remove friction with returns. Understand the customer’s journey and consider offering helpful features: instant credit in customer’s accounts when returns are initiated, an ‘exchange’ option if a customer needs a different size or color of the same product removing the need for a refund/charge from the process. These features encourage customers to find a better option for what they need on the website rather than a competitor’s.

Conclusion Retail is going through a fundamental change as a result of the COVID-19 pandemic. While some sectors like grocery and fitness thrive, consumers have pulled back on many discretionary purchases and are learning new ways of interacting due to social distancing orders. It will be months before the economy and any normalcy begin to emerge out of this crisis. Many retailers have hit pause on investment and are focused solely on cost cutting measures to wait out the pandemic until they can open stores again and get back to normal. That strategy alone is shortsighted, retail as we know it will not get back to normal. Some retailers will see this as opportunity to innovate, automate, digitize, evolve their business models and capture new market share. Even small investments can make a difference in a retailer’s ability to emerge leaner and more competitive, for those that take the leap and use this crisis as an opportunity to truly transform the rewards will be much greater.

References [1] Kestenbaum, R. (2017). What are online marketplaces and what is their future? Forbes: Forbes Magazine. www.forbes.com/sites/richardkestenbaum/2017/04/26/what-are-onlinemarketplaces-and-what-is-their-future/#2e2312a73284.

[2] Da Gama, A. P. (2012), “Marketing audits: The forgotten side of management?”, Journal of Targeting, Measurement and Analysis for Marketing, Vol. 20, No. 3-5, pp. 212-222.

[3] Stokes R., The Minds of Quirk (2013), “eMarketing – the Essential Guide to Marketing in a Digital World”, 5th edition, Quirk Education (Pty) Ltd. [4] Nguyen, L. (2016). Standardization versus localization with impacts of cultural patterns on con- sumption in international marketing. European Journal of Business and Management, 8(35).

[5] Pymnts. (2017). Online marketplaces catch up to offline world. PYMNTS.com. www.pymnts.com/ news/retail/2017/online-marketplaces-catching-up-to-offline-world/.

[6] Rycharski, B. / Rupender, M. (2020). “Retail’s New Normal” – Slalom Consulting Analysis / slalom.com [7] TranslateMedia. (2015). Selling through international online marketplaces. www.translatemedia. com/us/blog-us/selling-through-international-online-marketplaces/.

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Digital transformation and the impact on e-commerce of the disruptive technologies which are the supporting structure of the Industry 4.0

Drd. Ioan Matei PURCÄ&#x201A;REA Abstract It is essential to obtain a clear picture of E2E value chain from the point of view of capturing the value from technology until the high-touch digital retailer performance, harmonizing technology and data on the challenging path of continuously improving CX, by implementing disrupting technology solutions in e-commerce business which has been made more agile by the new coronavirus crisis. There is a strong relationship between digital transformation, the novel economy and e-commerce. In the current times of disruption there is a key differentiator and a lantern for further action: experience design and innovation. It is obvious enterprisesâ&#x20AC;&#x2122; challenge of opening the window of the opportunity to create a culture of innovation and disruption in this novel economy, considering evolutions in e-commerce, AI, and mobile technology in retail. There is a powerful impact on e-commerce of the disruptive technologies which are the supporting structure of the Industry 4.0 concept, and the 5Cs marketing principles for it. It is also important to better understand digital transformation as a blending of process knowledge, intelligent automation, and data, valuing and mastering data and content through disruptive technologies. Automation is reaching the service sector, and a growing trend in e-commerce is a level of automatic customization called personalization.

The importance of robots enabling warehouses to scale operations in the e-commerce fulfilment market is increasing. We are witnessing the approach of specific needs of ecommerce packaging with the help of new robot technology. The new technologies are enabling the providing of the expected CX through seamless and integrated processing.

Keywords: Digital transformation; Disruptive technologies; Industry 4.0; e-commerce JEL Classification: D21; D80; L20; M21; M31; O31; O33

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Technology, a critical business capability, is changing people. The framed response considering disruption & core-technology transformation, being customer-focused based on business value and careful delivery at the front planned. Better understanding the importance of the technology forward model in driving successful digital transformations I have recently read a newspaper article in which it was expressed the concern about the technology’s potential consequences. And trying to reconstruct the overall design (both the author’s purpose, and the technique used; the way he expressed his attitude, his message about the topic), that made me also recall some quotes, such as: “The Web as I envisaged it, we have not seen it yet. The future is still so much bigger than the past” (according to Tim Berners-Lee, Inventor of the World Wide Web); “The internet is no longer a web that we connect to. Instead, it’s a computerized, networked, and interconnected world that we live in.

This is the future, and what we’re calling the Internet of Things” (according to Bruce Schneier, Security Technologist & Auth); “We want to build technology that everybody loves using, and that affects everyone. We want to create beautiful, intuitive services and technologies that are so incredibly useful that people use them twice a day. Like they use a toothbrush. There aren’t that many things people use twice a day” (according to Larry Page, Co-founder Google); “Mobile is the future, and there is no such thing as communication overloaded” (according to Eric Schmit, Former Executive Chairman & CEO, Google); “Technology is dominated by two types of people: those who understand what they do not manage and those who manage what they do not understand” (according to Archibald Putt, a pseudonym of the author, a reputed PhD, of the book “Putt’s Law and the Successful Technocrat: How to Win in the Information Age”); “Science and technology revolutionize our lives, but memory, tradition and myth frame our response” (according to Arthur Meier Schlesinger, American historian, Educator at Harvard University, and public official in J. F. Kennedy’s White House); “Technology feeds on itself. Technology makes more technology possible”; “The great growling engine of change – technology” (according to Alvin Toffler, the wel-known author of valuable books like “Future Shock”, “Third Wave”, “Powershift: Knowledge, Wealth, and Power at the Edge of the 21st Century”, “Creating a New Civilization” etc.); “The most important thing about a technology is how it changes people” (according to Jaron Zepel Lanier, considered a digital pioneer, a technology oracle, the father of virtual reality, an AI visionary; author of the books “You Are Not a Gadget”, “Who Owns the Future?”, “Dawn of the New Everything”, “Ten Arguments for Deleting Your Social Media Accounts Right Now”); “Once a new technology rolls over you, if you’re not part of the steamroller, you’re part of the road” (according to Stewart Brand, President of The Long Now Foundation, considered a legend in the technology, being the creator of the Whole Earth Catalog, The WELL, the Global Business Network, the Revive and Restore project etc.); “If you don’t innovate fast, disrupt your industry, disrupt yourself, you’ll be left behind” (according to John Chambers, CEO of Cisco); “Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence” (according to Ginni Rometty, CEO of IBM); “If you’re competitor-focused, you have to wait until there is a competitor doing something. Being customer-focused allows you to be more pioneering” (according to Jeff Bezos, Founder of Amazon).

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Fifteen years ago, the advances in technology have been seen by a 2005 Economist Intelligence Unit survey of CEOs and other senior executives as the single most important driver of change in the business environment. And with regard to (at that time) “tomorrow’s hot technologies” the findings have showed that business performance management technologies, security technology, mobile technology, converged and wireless networks, open source software, developments in autonomic technology (self-optimising, self-repairing IT systems) have been seen as the most important emerging technologies for the future. But beyond the remaining enthusiasm about new technology (considered to be an important lever for competitive advantage), it was considered more upsetting the need for many companies to properly manage risks and threats posed by new or disruptive technology (Economist Intelligence Unit, 2005).

In our last RDC Magazine issue we have reminded that Joseph Schumpeter (who coined the concept “creative destruction” in 1942) described the entrepreneurial process as one of “creative destruction” (Purcarea, 2020). It is also worth mentioning that in the last decade significant aspects have been highlighted in RDC Magazine issues, such as: “observing that the actual World is more and more difficult to rule (optimize)... in hard times, we all have to learn how the progress is still possible and especially how the miracle of switching from very low to high can be made... we will soon be almost total dependent on ICT products and services... we must think to a mature control of this dependence... the whole Earth is in a hurry and everybody is in “his race”, because we can not afford to forget that the Earth race is sure two-fold: to progress and to survival” (Greu, 2012); we need to become integrative thinkers “on the path to greater trust while going through a major transformation” (Purcarea, 2013), as confirmed, for instance, by both the Internet of Things (IoT) evolution within the context of the information and communications technologies (ICT) exponential development as the main factor of the information society transformation toward knowledge based society (Greu, 2015), one hand and the way in which ICT is driving Artificial Intelligence (AI) to leverage refined knowledge for the World Sustainable Development (Greu, 2019), on the other hand, and the last but not the least by the impact of digital transformation on the retailing value chain (Tanase, 2019).

Allow us to also remind that in the last years there were significant approaches with regard to disruption, digital transformation and digital disruption (managing digital disruption involving the use, for instance, of methods such as open innovation, co-creation and crowdsourcing), disruptive innovation (digitalization being a driver for it), and coretechnology transformation, such as: • The fact that enterprises must disrupt their products and processes in order to enable the next customer experiences (McQuivey, 2014); • “Big data” and the information technology are partners in disruption (Smith, 2015); • The changing customer demands, together with the new or changed competition and the technological advances, could be already considered a set triggers of this digital transformation (Wieberneit, 2016); • When it happens the digital disruption (when an existing industry faces a challenger

that offers greater value to the customer, and in a way in which existing enterprises cannot directly compete with (Rogers, 2016);

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• Enterprises need to reinvent themselves by digital transformation of the core (value proposition, people, processes, and technologies, all these representing the lifeblood of their business), and taking the proper decisions accordingly (Dahlström, Desmet and Singer, 2017); • Enterprises also need to better understand what is happening at the intersection of

innovation and disruption, people being at this intersection (Bova, 2017); • Enterprises must better understand the importance of technology in driving successful digital transformations, avoiding technology antipatterns as ineffective solutions for a problem, by paying special attention to technology choices, technology road map, technology management, and managing technologists, and urgently both identifying technology antipatterns and moving to address them. Reflecting and acting in this manner enterprises can make possible technology transformations to support the most highly praised three-part (faster customer-centric delivery, business growth, and happier employees) expected result of the digital transformation (Blumberg, Delaet and Swami, 2020).

• At the basis of the improved customer-focused solutions (from the point of view of efficiency, quality, and speed to market) there is a core-technology transformation (which involves time, effort, and investment), what presupposes a top-team mindset shift allowing the necessary match with enterprise’s context, fusion between technology and business outcomes, and methodical technology-tailored approach to execution. A successful technology transformation must be approached holistically, all happening across the three vectors (reimagining the role of technology, reinventing technology delivery, and futureproofing the foundation) highlighted by McKinsey’s representatives in the figure below (Carson, et al. 2020):

Figure no. 1: Technology transformation relies on three vectors Source: Carson, et al. 2020. Overcoming the core-technology transformation stalemate, McKinsey & Company, September (work cited)

• Within the new urgency into modernizing the technology function (the digitizing of end-user experience being ranked, for instance, as no. 1 type of transformation most likely to

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be pursued over next two years within the more focus upward along the technology stack), McKinsey Technology offered a valuable “tech forward” model which highlights the above mentioned three interconnected vectors (this model having inside ten specific domains of activity, as shown in the figure below) enabling advancing enterprise technology function so as to gain the capabilities needed to thrive, and not just survive, in challenging and constantly changing digital markets (Dhasarathy, et al. 2020).

Figure no. 2: Successful technology transformations span three vectors of activity, each consisting of a specific set of plays Source: Dhasarathy, et al. 2020. How to become ‘tech forward’: A technology-transformation approach that works. McKinsey Technology, November (work cited)

Within this framework, a special mention also needs to be made of the role of a new methodology brought onto the scene of tomorrow’s maintenance function (which will combine the strengths of lean and agile organizations) by the growth of Industry 4.0 and related digital technologies. And this given to enterprises’ challenges to achieve further performance improvements on the basis of digital solutions. According to the reputed McKinsey’s expertise, it is recommendable to better understand that in order to achieve better results it is necessary to properly combine the strengths of the lean and agile methods (which beyond their different terminology are both seeking to maximize the value delivered to enterprises’ customers, while safely minimizing the resources used to achieve the organization’s goal), considering the increasingly potential confirmed by the agile methods show the potential to address longstanding challenges in many organizations, breaking down silos between different functions or groups of technical specialists, and aiding the efficient allocation of resources in tasks with varying or intermittent workloads. (Heitz, et al. 2020).

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From capturing the value from technology until the high-touch digital retailer performance. Harmonizing technology and data on the challenging path of continuously improving CX, by implementing disrupting technology solutions in e-commerce business which has been made more agile by the new coronavirus crisis. Digital transformation, the novel economy and e-commerce A year ago, McKinsey’s representatives have underlined that if enterprises approach the transformations enabled by technology through a technology-focused lens can catch about 50% of the potential business value, but if they follow a two-step methodology (Assess: Building the strategic roadmap; Build and implement: Scaling the change) as shown in the figure below can translate their transformation priorities from strategy to action, and secure substantially more value. And this starting from the fact that enterprises’ operating mode can be fundamentally changed by the digital technologies (including analytics, IoT, AI and its subset Machine Learning), these technologies (technology and data representing the backbone) being harnessed by an End-to-End transformation, and allowing capturing this way the next level of value (Atluri, Baig and Rao, 2019). So, there are valuable lessons to learn for retail industry, too.

Figure no. 3: Industrial companies must follow a comprehensive transformation playbook to capture the value from technology Source: Atluri, Baig and Rao, 2019. Accelerating the impact from a tech-enabled transformation. McKinsey Digital, September (work cited)

An interesting discussion which took place within the framework of McKinsey’s “Inside the Strategy Room” (podcast) on the topic of rapidly and effectively developing a digital offering while facing the ongoing economic uncertainty revealed six archetypes of businesses likely to emerge in the post-COVID-19 era (see the figure below), one of them being the high-touch digital retailer. And in this case the identified challenge was starting

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from the way chosen to create curated retail experiences in the absence of the physical element (Barnes, et al. 2020).

Figure no. 4: Six archetypes for new businesses Source: Barnes, et al. 2020. Building a great digital business. McKinsey & Company, Strategy & Corporate Finance Practice, December (work cited)

On the webpage of the World Economic Forum it was clearly underlined that going digital is an urgent choice, the move towards digitalization being confirmed by the unprecedented growth in e-commerce businesses, e-commerce being a 20-year-old industry.

For the retail industry, this digital transformation (beyond automating and digitalizing the existing systems etc.) also showed the smart use of analytics, AR, VR, AI and facial recognition in order to provide in person, Omni channel and seamless CX. (Reddy and Morelix, 2020). We also noticed within this framework an inspired message for all ecommerce enterprises concerning some useful moving steps, as the core enterprise’s focus for a successful digital transformation, such as: identifying the digital transformation goals (see the digital transformation pyramid in the figure below), managing CX strategy (a four steps management process: • customer insight, customer relationship management strategies, integrated processes, customer acquisition strategy; • also considering Omni channel capabilities), implementing new technology solutions (including AI, IoT, cybersecurity, wearable technologies and cloud), executing the necessary today’s new journey to virtual platforms (VR/AR tools ensuring an improved interaction for customers), and being always ready for digital innovation within the context in which the highly virtualized and technology-enabled ecosystem of services are serving as basis for the future e-commerce platforms (Sharma, 2020).

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Figure no. 5: The digital transformation pyramid Source: Sharma, R., 2020. 5 Steps to Digital Transformation For E-Commerce Businesses, YourStory, 3rd Jul (work cited)

Recently, McKinseyâ&#x20AC;&#x2122;s representatives showed that CX and design inputs (as a significant domain which is defining user journeys and requirements based on humancentered design) are representing one of the ten domains (as shown in the figure below) across which enterprises need to have superior capabilities so as to ensure effective implementation of large technology programs in the digital era. And this within the context in which enterprises must accept the complexity, ensure the right capabilities (from the start) to act accordingly by: selecting agile methods; grounding the work in design thinking; using cloud-based services; using modular architecture to increase flexibility and vendor competition; getting people with large-program (ideally comparable) experience; being aggressive about necessary course corrections. Acting on this way enterprises can de-risk delivery by capitalizing on new digital techniques (Defossez, McMillan and Vuppala, 2020).

Figure no. 6: Effective implementation of large programs requires superior capabilities across ten domains Source: Defossez, McMillan and Vuppala, 2020. Managing large technology programs in the digital era, McKinsey Digital, November (work cited)

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There is no doubt that e-commerce has been made more agile by the new coronavirus crisis, this year being seen as a possible inflection point considering the acceleration signal of the upward projections of e-commerce penetration in the overall retail, as shown in the first figure below (Routley, 2020).

Figure no. 7: E-commerce penetration Source: Routley, N., (2020). 5 Big Picture Trends Being Accelerated by the Pandemic, Visual Capitalist, November 27 (work cited)

Figure no. 8: A breakdown of Amazonâ&#x20AC;&#x2122;s revenue model Source: Ang, 2020. Visualized: A Breakdown of Amazonâ&#x20AC;&#x2122;s Revenue Model, Visual Capitalist, October 14 (work cited)

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But beyond the above mentioned acceleration signal coming from the e-commerce, including at the level the e-commerce giant Amazon (but not only in its case) have been identified many other business segments fuelling its growing revenue, as shown in the above figure (Ang, 2020).

It is also worth underlining the following aspects: • In June this year, the reputed Brian Sollis, Global Innovation Evangelist at Salesforce, talked with TechRepublic’s Karen Roby about the impact of COVID-19 on digital transformation (which was itself digitally disrupted), starting from the importance of studying all of the trends happening in the market (going beyond making sense of them) and humanizing the next steps of both customers, and partners, ensuring moving forward by thinking about better operating (rebuilding, inventing and innovating) in the novel economy (described below in the next subchapter).

And as everything changed (including customers’ and employees’ behaviour), Sollis pledged for better understanding CX and optimizing productivity with the employee experience, happiness and wellness, and inventing accordingly based on new identified opportunities for growth, thinking differently about data with the help of AI and its subset Machine Learning, seeing technology as a revenue generator (within the so-called by him “bimodal digital transformation”), and optimizing infrastructure for operational excellence, and investing in business model innovation (also taking into account the current special time for human-centered innovation).

Sollis also made a special reference to e-commerce, considering some insights published by him on the basis of Salesforce’s global shopping index (which revealed both how online spending had, and how it was going to continue to shift), and highlighting the special position of e-commerce on this trajectory to become a huge percentage of total sales (Solis a, 2020); • What the recent Gartner’s 2020 Marketing Technology Survey revealed within the context of the disruptions triggered by the COVID-19 pandemic, namely more progress is being made on key actions improving marketing technology’s impact across the enterprise by the marketing technology teams which are apply agile methodologies to their technology roadmaps.

Compared with all others (as shown in the figure below) these marketing technology teams take more actions across the board, by integrating different types of marketing technology based on need, adding new functionality/enhancements to existing technologies, revising their roadmap due to changes in their business, adopting new technologies in response to changes in their market, changing aspects of marketing processes/operations to adapt to etc. (Bloom, Reid and McCune, 2020).

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Figure no. 9: Agile planners get more done Source: Bloom, Reid and, McCune, 2020. Gartner for Marketers. 2020 Marketing Technology Survey: Cost Pressures Force Martech Optimization and Innovation. Gartner, November, p. 25 (work cited)

In the current times of disruption there is a key differentiator and a lantern for further action: experience design and innovation. Enterprises’ challenge of opening the window of the opportunity to create a culture of innovation and disruption in the novel economy. E-commerce, AI, and mobile technology in retail

Technologies’ improvements are improving customer interactions’ value, the return on experience (ROE) confirming more and more its status of new return on investment (ROI), the entire E2E CX being orchestrated and personalized moment to moment, at scale, on any channel, and in real-time, the gap between the customers’ expected experiences and the channels where they live being better closed on the basis of the right Omni channel digital marketing approach (Martin, 2019). There are significant lessons to learn with regard to ROE (or ROX), enterprises needing: to better understand not only the correlation between different experiences, but also how CX and employee experiences affect each other; to avoid silothinking and sub-optimization when implementing ROE approach. (Hansen and Martinsen, 2019).

Coming back to the reputed Brian Sollis (who also pledges for attaching emotion to loyalty, customer lifetime value, growth) inspiring approach, it is worth mentioning his take on the role of innovation in both digital experience design, and measuring ROE, namely that in the current times of disruption experience design and innovation (which is pushing CX forward) is representing a key differentiator and a lantern for further action. According to Sollis:

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• Generation C (the incoming wave, before Covid-19, of connected consumers) was sharing behaviours (which are creating a new standard for CX), interests and expectations of everything to be not only tailored to their needs, but also to be delivered instantaneously (Solis b, 2020); • There are three key phases of the novel economy (coined by him, and expressing the rise of a new generation – “Generation N” – of both customers, and employees; the pillars of memorable brand experiences for this novel economy are shown in the figure below): stabilization (meaning to both survive and react to the new coronavirus crisis that changed the course of humanity and consumerism, and seek business continuity); to be alive (meaning to ensure transitions by both mastering the new normal, and starting exploring innovative ideas and business model opportunities); to thrive (in the next normal of business which could not only include improving operations, but also innovating and disrupting, considering new customer demands created by the collective pandemic experiences). In his opinion, the emergence of “Generation N” is a result of by pandemic caused new personal and societal constraints (such as: lifestyle and health traumas, mask-wearing and sudden work from home transitions etc.), Sollis using in defining this new unprecedented experience the term somatic marker (a theory hypothesizing that strong emotions is guiding behaviours and subsequent decision making) developed by Antonio Damasio (beginning with 1994) and other researchers (Jacoby, 2020).

Figure no. 10: The Pillars of Memorable Brand Experiences for The Novel Economy Source: Jacoby, P., 2020. The Rise of “Generation Novel” aka Gen N and the Novel Economy, Frost & Sullivan, Jul 13 (work cited)

There is a clear evidence that the coronavirus pandemic made AI adoption more urgent for retailers which are under pressure of transforming from cost structures to CX, AI (which offers lower cost-to-serve, more effective promotion and merchandising, and an elevated CX) going hand-in-hand with e-commerce (McKone and Madannavar, 2020).

Customers are more and more looking for answering their questions in real time, for having customized shipping rates, to benefit of product recommendations on their mobile apps or of

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a new sensory experience brought on by great digital displays showcasing great brands (Ginsberg, 2020) And as underlined recently by a mobile solutions architect at Stratix (the largest pure-play managed mobility service provider in North America) retailers: are achieving significant results by providing mobile sales tools for staff, and especially by deploying mobile point of sale (POS) – according to a research from IHL Group; are planning major foundational investments in mobile POS over the next two years – according to RIS News’ 30th Annual Retail Technology Study (Sciara, 2020).

And in the evolving environment of the payments industry there are three emergent data elements: TRID (the Token Requestor IDentifier, which is represented by a unique 11digit numeric value assigned by the TSP - Token Service Provider), WID (the Wallet Identifier, presented at the POS), and PAR (the Payment Account Reference, the unique identifier associated with a specific primary account number - PAN, regardless of device).

There are two advantages for retailers accepting this form of payment: to capitalise on the new data source and co-marketing opportunities to help grow business and improve business processes; to better serve customers using mobile wallets (Vanderhoof, 2020).

Instead of conclusions: The impact on e-commerce of the disruptive technologies which are the supporting structure of the Industry 4.0 concept, and the 5Cs marketing principles for it. Better understanding digital transformation as a blending of process knowledge, intelligent automation, and data. Valuing and mastering data and content through disruptive technologies. Automation is reaching the service sector, and a growing trend in e-commerce is a level of automatic customization called personalization. The importance of robots enabling warehouses to scale operations in the e-commerce fulfilment market.

Specific needs of e-commerce packaging approached with the help of new robot technology. The new technologies are enabling the providing of the expected CX through seamless and integrated processing We have seen above that there are valuable lessons to learn for retail industry within the context of the transformations enabled by technology, different approaches arguing for harmonizing technology and data (technology and data representing the backbone) on the challenging path of continuously improving CX (by implementing disrupting technology solutions in e-commerce business). On the other hand it is well-known the reputed Capgemini’s approach according to which brand positioning is reflected by the created CX aligned with the enterprise’s purpose thanks to the right content based on the right data, and acting and re-innovating accordingly in approaching digital transformation, with agility and responsiveness (Capgemini, 2020).

The Founder and Executive Chairman of the World Economic Forum, Professor Klaus Schwab, has argued in January 2016 that the Fourth Industrial Revolution (which is evolving at an exponential pace) is disrupting almost every industry in every country. He underlined from the very beginning the unlimited possibilities multiplied by emerging technology breakthroughs in significant fields (such as AI, robotics, IoT, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing), also expressing the conviction that the critical factor of production in the future will be represented by talent (more than capital). And approaching the impact of the disrupting technologies which are the supporting structure of this Fourth Industrial

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Revolution (Industry 4.0, as the digital transformation of production and related industries and value creation processes, shifting from simple digitization to innovation based on combinations of the disruptive technologies - also see the above Figure no. 5: The digital transformation pyramid) on business, Professor Schwab highlighted the four main effects: on customer expectations (customers being at the epicenter of the economy), on product enhancement, on collaborative innovation, and on organizational forms. He did not forget to mention the need of compassion, cooperation, privacy, and of redefining the moral and ethical boundaries, assuming the responsibility for guiding the evolution of both technology, and disruption (Schwab, 2016).

In November 2019, an article published in the “Engineering Management in Production and Services” scientific journal, a quarterly published by the Bialystok University of Technology Publishing House and The International Society for Manufacturing Service and Management Engineering (ISMSME), approached the challenging topic “Marketing principles for Industry 4.0 — a conceptual framework”. The authors, Katarzyna Nosalska and Grzegorz Mazurek, have identified a gap in the scientific research with regard to the impact of Industry 4.0 on marketing, and – taking into account the impact of both the new digital technologies, and the frequently growing number of new business models – were aiming to structure marketing changes by advancing a conceptual framework for marketing in Industry 4.0 (they used valuable sources: the qualitative method putted forward by Jabareen, 2009; the Design Principles of Industry 4.0 by Hermann, et al. 2016, and the Marketing 4.0 concept

by Kotler, Kartajaya, and Setiawan, 2016). The authors have gone beyond the usual scientific discourse on Industry 4.0 concept (which is focusing mainly on the technological aspects of the perceived occurring changes), and considering the holistic meaning of Industry 4.0 concept (which is suggesting a need for a multidisciplinary approach to identifying all the changes emerging in various areas of business operations; in other words, we may say now within the context of the unprecedented crisis, including both better understanding the customer’s perspective, and optimizing the customer journey), they have brought five identified main marketing principles for Industry 4.0 (as shown in the figure below): Cooperation, Conversation, Co-creation, Cognitivity, and Connectivity. According to the two authors the technologies are only enabling relationships’ development in the business ecosystems (facilitating communication between the participants on the relevant market), and enterprises must generate a strategic organisational change based on the synergistic effect resulting from the interaction between the new technologies and the innovative business solutions (Nosalska and Mazurek, 2019).

Figure no. 11: The 5Cs for the Fourth Industrial Revolution Source: Nosalska and Mazurek, 2019. Marketing principles for Industry 4.0 — a conceptual framework, Engineering Management in Production and Services, Volume 11: Issue 3, 19 Nov (work cited)

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In our opinion, this last approach, from November 2019, follows the above mentioned line suggested by the Professor Klaus Schwab in January 2016: “... billions of people connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge... Digital fabrication technologies, meanwhile, are interacting with the biological world on a daily basis. Engineers, designers, and architects are combining computational design, additive manufacturing, materials engineering, and synthetic biology to pioneer a symbiosis between microorganisms, our bodies, the products we consume, and even the buildings we inhabit... consumer engagement, and new patterns of consumer behavior (increasingly built upon access to mobile networks and data) force companies to adapt the way they design, market, and deliver products and services”. And here we see the linkage with the conceptual framework advanced by Nosalska and Mazurek and their conclusion concerning the opportunity of further enriching the existing scientific literature with new perspectives, the more so the COVID-19 pandemic has changed the way consumers use e-commerce, speeding up the shift towards an even more digital world compared to the last year.

This year, in August 2020, the Vice President of Marketing at 6 River Systems showed that the blending of the rise of e-commerce merchants and of the increased demand by consumers for just-in-time ordering determined a pressure for the fulfilment centers to deliver goods faster than ever, one of the questions necessary to be asked within this framework by the operators (revisiting their fundamental strategies and decisions about their supply chains) being how to merge e-commerce and retail fulfilment operations (Glinn, 2020). In September 2020, The Shared Services & Outsourcing Network (SSON) reminded us the importance of better understanding digital transformation as a coming together of process knowledge, intelligent automation, and data, within the context in which there is no doubt about what a robust data strategy requires: digitized & structured data at the point of ingestion, link to business context and strategy, and guidelines on data collection and management (SSON a, 2020). While a month later, at the beginning of October, the European Business Review stated that automation: becomes increasingly more viable and necessary within the context in which the new coronavirus crisis reshape the way we work (taking into account the ability for AI and robotics tools to improve transportation, consumer processes, and manufacturing); is reaching the service sector, AI being the new standard through chatbots, account security, and personalization (as a level of automatic customization made up of personalized ads and product recommendations created specifically for someone based on his personal data) in e-commerce (European Business Review, 2020).

In the last year’s summer we remarked “How Growing E-Commerce Demand is Driving Growth in Mobile Robotics”, context in which it was underlined that given this growing demand caused by increased e-commerce usage both humans, and robots are needed to meet it within the context in which in the e-commerce fulfilment market both flexibility, and efficiency have become primary differentiators (Britt, 2019). In May 2020, we find out that at a US start up from California, banking on fully automated warehouses for groceries (and not only), robots will do the shopping thanks to a new Home Delivery Service creating a touchless and robotics-powered retail model (aiming to cut out supermarkets as unnecessary intermediaries) to be launched in 2021 (The Jakarta Post, 2020).

Three days later Euronews has shown in an episode of Business Line entitled “The rise of robots, automation and e-commerce in the post-pandemic world” how within the realm

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of e-commerce many companies are finding new opportunities (Euronews, 2020). While in August 2020 Automation World trade magazine, a monthly publication covering the latest developments in automation, informed in an article entitled “Robotics Special Report: ECommerce Requires new Solutions”, about how the specific needs of e-commerce packaging are approached with the help of new robot technology (Mohan, A. M., 2020). Within this framework it was highlighted, among other aspects, that e-commerce represents one of the most significant consumer trends (at the end of Q1-2020 e-commerce sales have exploded) transforming the packaging landscape.

There is no doubt that digital transformation (which is going hand in hand with customer centricity, focusing on the customer journey) has become the imperative for maintaining an enterprise competitive advantage. Enterprises can transform their operating model via intelligent automation, driving improvements in both CX, and employee experience (and not only) on the basis of E2E process optimization (the necessary change depending on the process discovery, identifying automation opportunities across the process scope), the cultural transformation being considered key (SSON b, 2020). All the aspects above mentioned are confirming our November pledge (Purcarea, 2020) for better understanding both the new requirements of the Supply Chain 4.0 (applying Industry 4.0 innovations) & Value Chain 4.0 while implementing the ECR philosophy, and the fact that people and data are at the heart of the digital transformation which needs to be holistic.

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Blumberg, S., Delaet, T. and Swami, K., (2020). Ten ‘antipatterns’ that are derailing technology transformations. Shortsighted solutions to recurring problems—antipatterns—often sabotage a company’s transformation. [pdf] McKinsey & Company, July. Available at: <Ten-antipatterns-that-are-derailingtechnology-transformations.pdf> [Accessed 6 October 2020].

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Carson, B., Goldov, A., Kinet, L., Oakes, W., Giulio Romanelli, G. and Anand Swaminathan, A. (2020). [pdf] Overcoming the core-technology transformation stalemate, McKinsey & Company, September. Available at: <overcoming-core-technology-transformation-stalemate.pdf> [Accessed 12 October 2020].

Dahlström, P., Desmet, D. and Singer, M., 2017. The seven decisions that matter in a digital transformation: A CEO’s guide to reinvention. [online] McKinsey & Company, February. Available at:

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Game Changers, Asian Century, Early Leadership, Building a Second Brain, G-Global 2020, World Science Day, Respect and Trust, Going Hybrid Bernd HALLIER

Prof. Dr. Bernd Hallier, President of the European Retail Academy (ERA: http://www.european-retail-academy.org/), an Honorary Member of the Romanian Distribution Committee, and distinguished Member of both the Editorial Board of “Romanian Distribution Committee Magazine”, and the Editorial Board of RAU “Holistic Marketing Management” attracted our attention on great events happening in the last quarter of 2020, and allowed us to present them. It is also worth remembering that: immediately after visiting Romania for the first time on the occasion of the 24th International Congress of the International Association for the Distributive Trade (AIDA Brussels), Prof. Dr. Bernd Hallier sent us, in May 1998, a memorable letter we have referred initially in the Journal of the Romanian Marketing Association (AROMAR), no. 5/1998, and also later, in 2010, in the first issue of the Romanian Distribution Committee Magazine; the Romanian-American University (RAU) has awarded Prof. Dr. Bernd Hallier a “Diploma of Special Academic Merit”; the “Carol Davila” University of Medicine and Pharmacy, Bucharest, has awarded Prof. Dr. Bernd Hallier a “Diploma of Excellence”.

Game Changers Nikolai Kondratieff was the first who published in 1926 observations about innovations having long-term effects on macro-economic levels: 1939 called “Kondratieff-Cycles” by Joseph Schumpeter. A period of innovation driven by cotton/steam engine (1800) was followed by railways/steel production (1850), electrical engineering/chemistry (1900), petrochemical industry/automobiles (1950) and information-technology/revitalization of global trade networks

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for sourcing and distribution (2000). Prof. Dr. Bernd Hallier defines as the next KondratieffCycle the Lithium Production/Applications of Lithium/ Crypto-Currencies in a world of Smart Economies. Lithium production will replace the petroleum production in the impact of the geopolitical power-play according to Prof. Hallier. Taken the period of 1974-2018 measured in metric tonnes Australia leads by 123.206 units, followed by China (45.747), Zimbabwe ((34.604), Canada (22.097) and Chile (16.137). “South America is expected to increase its volume by roughly 200 percent in the next decade” Prof. Hallier expects.

Prof. Dr. Bernd Hallier mainly has registered himself for some decades the major disruptions of wholesale/retail since the year 1800: showing a permanent evolution in frogleaping jumps of 25 years: the last steps American Lifestyle/supermarkets (1950), hypermarkets/big boxes/shopping centers and Information Technology (1975), chiptechnology/RFID/tracing tracking and B2B/B2C internet (2000), mobile shopping, social media, cashless payment (2025), data-clouds, block-chain technology, the Internet of Things, Artificial Intelligence - new Retail Knowledge Consortia by mixed players having originally their competences in mass-data business, in process-optimization, in delivery-services (2050).

“COVID-19 is beaming its winners of the total supply chain as well as the traditional retail/wholesale institutional definitions as also the obsolete distinction of store types into the hybrid/digital world of the cycle 2050 already now. The new cycle will be dominated by players who we do not know yet as Retailers” Prof. Hallier claims. “COVID-19 is together with the new technologies a game-changer: like in Darwinism only those will survive who adapt quickly! The bottleneck between pilot-projects and the big impact 25 years later seems to be the delay in learning and behaviour” Prof. Hallier assumes reflecting the macro- as well as the sector- and micro-level studies about innovation reported in Applied Sciences. “Further on the personal mind-set needed for those changes will be different due to ethnological and historical developments in each country as well as dependant on financial resources available in poor/rich countries: disruptions very often widen the gap not only economically but also in respect to ecology or ethics", Prof. Hallier stated.

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Asian Century Already in 2019 Prof. Dr. Bernd Hallier stated after taking part in Chongging/China at the bi-annual Asian-Pacific Retailers’ Convent APREC: “After the Commonwealth Century and an American Life-Style Century now we are in an Asian Technology Century”. In 2020 Hallier welcomes the foundation of the multinational trade pack RCEP (Regional Comprehensive Economic Partnership) of 15 countries of the Asian Pacific area.

“Already since David Ricardo (1772 - 1823) we know that International Trade is promoting global wealth” he recalled Economic Theory and Observations of World Trade. “It is worth mentioning that Ricardo published in 1817 this extension of the research of work-division of Adam Smith - two years after the Vienna Congress where after the Napoleon War Europe was restructured and import/exports revitalized” Prof. Hallier recalls history. “The countries of RCEP accumulate about 30 percent of the present world population and will gain bigger GNPs than Europe till 2050 due to their different age-structure” Prof. Hallier added. “Regional multinational sub-systems may reactivate also WTO and by this stabilize World Peace.” Prof. Hallier has been travelled Asia since 1974 - being a part of lectures following for nearly two decades as a member of the Jury of Retail Asia the technical developments of the major players and having also taken part in the award-ceremony when the APREC-network got the Peace Circle

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Early Leadership In 1972 Prof. Dr. Bernd Hallier was as an AIESEC-exchange student in South Africa inspired by studies about developing countries. At the left-hand-side pic of the Collage he is discussing with his Stellenbosch- AIESEC counter-part Roger Chennells his visions - later during his three-months-stay also visiting Roger's parents in Zulu-Land (Eshowe) where Guy Chennells as a Liberal was already during the political Apartheid times a host for guests of different colours. Later in 2019 Roger was among the lawyer-team who bargained as an addition of the UN Nagoya Protocol a 1,5 percent royalty of the sales of Rooibos Tea for the local indigenous people.

All this Past came to Prof. Hallier’s mind at the G-Global hybrid Conference meeting in a Round Table with Ela Gandhi and Ndileka Mandela; Mahatma Ganhi having started to fight as a lawer in South Africa till 1915 for the rights of Indian people (before returning to India) - and Nelson Mandela fighting as a lawer for the rights of the coloured people in his country , becoming its first black President after years of imprisonment. He summarized for himself the Round Table: “I am totally impressed by the two Ladies: their joint message is that Spirituality and Intrusive Leadership are the factors for Global Peace. We have to teach our students not only content for their specialized subjects at universities - but we have to prepare them for leadership by holistic approaches and applied sciences to create visions for a global world with different cultural back-ground" is his conclusion. “G-Global should take a coordination function for a

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worldwide academic competition to promote ETHICAL VALUES. It was already El Farabi (872-951) - the second master after the Greek philosopher Aristotle - teaching at the Silk Road about the ideal society directed to true happiness” Hallier stated.

Building a Second Brain According to Prof. Dr. Bernd Hallier future managers and leaders in general have to build their own Second Brain to compete against the technical tools of AI. “The volume of data and information offered globally has increased within the last 25 years so much due to modern technology that the human brain has to be enlarged by outsourced capacities” he claimed about frights of replacement of human beings by robots (AI) in the development of distribution processes within retail and logistics. “Corona 2020 became a Super Innovation Driver for technology as can be seen by the dramatic increase of hybrid conferences, home-schooling and home-offices. Hand-written notes alone will not fit anymore to the competition of the XXI Century” he claimed in several digital conferences in November.

Photo credit to Building A Second Brain (BASB) His former ERA-trainee Dr .Alina Pukhovskaya (WebSite), who did PhD about Knowledge Management, discussed in her Newsletter some aspects of Personal Knowledge Management (Read More). Hallier believes the idea of a second brain and the basic

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technologies should be taught in the curricula of the first semester interdisciplinary. "I myself use the lockdown of Corona to file my archive and memories and to combine facts & personal emotions in a set not replicable by just algorithms" he added.

G-Global 2020 Like other organizations also G-Global decided for 2020 to go digitally! G-Global is headquartered in Astana/Nur-Sultan in Kazakhstan. The International Online Congress in 2020 is labelled “The world of the XXI century”. It will be supported among others by the UN Executive and Social Council, UN Conferences on Trade and Development, the Astana Club of Nobel Prize Laureates, the Eurasian Economic Club of Scientists, the National Academy of Natural Sciences of the Republic of Kazakhstan, the Astana Economic Forum, the International Silk Road Mayors Forum.

Prof. Dr. Bernd Hallier is attending actively the Astana Economic Forum for more than a decade (see also Interview: Link 1), he was with the Eurasian Youth Forum successful supporter of the claim to organize EXPO 2017, he is member of EECS and partner of the G-Global community and the Silk Road Mayors Forum. This time he will participate in the slot of the Online-Global Universities Congress (see more: Program below). “Having visited India and

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Africa many times it is wonderful to be together in one slot with Ela Gandhi and Ndileka Mandela” he stated in a comment about the G-Global Conference.

World Science Day Kazakhstan is the Co-Founder of the Silk Road Mayors’ Club; the (Link 1) shows the mayors of Nur-Sultan and Shymkent signing the contract in attendance of Prof. Dr. Bernd Hallier. Now the M. Auezov South Kazakhstan University in Shymkent will participate in the World Science Day “For Peace and Development” initiated by the United Nations. Due to Corona the Conference will be hybrid. Among the contributors will be Nobel Laureate Prof. Dr. Raekwong Chung and holders of other international prizes and awards in the field of science and economics. Invited from Germany is Prof. Dr. Bernd Hallier to speak about the topic “Corona as an Accelerator for Innovation”. More about the program see Link 2.

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“Corona became an accelerator for technical innovation in the distribution -, educationand even in the consumer/household sectors. The evolutionary traditional 25-years frog-leaping steps in the innovation cycles of the last two centuries are speeding up to revolutionary disruptions beaming everybody in future life-style-cycles expected to happen only in the period 2025-2050. Within each country but also internationally the competition will result in Darwinism: in winners and losers of our present challenges” Prof. Hallier stated announcing the Conference.

Respect and Trust “My first meeting in Moscow 1990 was with the still All-Sowjet Institute for Trade under the leadership of Prof. Dr. Tvildiani from Georgia; introduced by my East German counter-part flying with the East German Airline Interflug” Prof. Dr. Bernd Hallier remembers. “Today neither the Sovjet Union does exist anymore nor the East German DDR or Interflug, but within the last 30 years there are lots of friendships with personalities from Russia and beyond its borders which was formerly the SU.” Hallier added. “In our holistic political evaluation we have to see both: the history of those countries with ours as well as the eyes of our partners and the human beings who each have a bio with an impact of their own historical social environments”.

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See also: Interview January 2011 as a special guest of Radio Voice of Russia about the topic: How Germany has survived the economic crisis and what are the prospects of the unified Germany in the global system of relations: Link

“I met for example Prof. Dr. Nicolai D. Kolesov from the St. Petersburg State University, who was the youngest planner under Stalin and who even within the age of 90 years knew budget-figures of today’s Russia by heart; Juri Starovatikh, Honorary Member of the HeroCity of Volgograd who initiated the city partnership with the West-German city of Cologne heavily destroyed in World War II; Prof. Dr. Malyschkov from the Moscow Government being responsible for the distribution during the difficult transformation from Socialism towards the first steps of market economy; with Prof. Dr. Tabolin I was hunting in the North East at the Russian-Chinese border and with Prof. Dr. Kisselev I was driving fom Kemerowo to the city of Tomsk through the Taiga landscape; Prof. Dr. Leonid Strovskiy from Yekaterinburg in the Ural translating with his team my book Culture and History of Trade into the Russian language; Prof.

Dr. Oleg Oshkordin reported about his experiences as a young soldier in the German city of Dresden and both of us visited Dresden in 2011 to enjoy jointly the development after reunification; Prof. Dr. M. Fedorov from the USUE as my partner at the Youth Forum (at the photo with Nobel Laureate Prof. Dr. Aumann) - became also together with me driver for the EXPO 2017 in Astana/Kazakhstan; our Ukraine partners Prof. Dr. Lev Sarkisjan from Donestsk and Prof. Dr. Nina Ushakova from Kiev; never forgotten will be the emotional sailing-tours around the Skagerag in the Baltic Sea with the four-mast ship Padua/Kruzenshtern (today based at Kaliningrad/Koenigsberg) under the commanders Kolomenski, Sedov and Novikov who each due to their difference of age did have other styles of leadership - just to be mentioned as examples of the list of wonderful people from the ERA-network out of the former SU Academia.

This human layer then has to be connected with the background of the historic Russian Soul in literature, music and painting to get a feeling about why dialogues in our Civil Society are of utmost importance for global understanding and Peace Processes” Hallier summarized his point of view.

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Going Hybrid Due to Corona one of the big challenges for the educational sector is going hybrid Prof.

Dr. Bernd Hallier stated after the Magros Conference organized by the Konrad Adenauer Foundation and the magazin Suvremena trgovina/Croatia.

One of the pioneers of digital communication within the professors of the European Retail Academy is according to Hallier his friend Prof. Dr. Theodor Purcarea from the Romanian American University (RAU) in Bucharest. “Using Holistic Marketing Management already for years for the digital dialogue beyond borders also connected with tools of social media for further communication is a benchmark for European Academia” Hallier added. “RAU’s hybrid Opening Ceremony of the New Academic Year 2020/2021 shows how to link education and teaching with aspects of health in the new Corona-virus impacted times which might become a normal for us in the near future; Corona became an accelerator for technical innovation and change of consumer behaviour!” Hallier claimed (see also News Shymkent at Link).

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I SSN: 20690134