Measuring the Pace of Change in the Fourth Industrial Revolution

Technologies help us deliver on a business strategy.  Without a strategy, there is no rationale for deploying technologies.  In addition, there is no rationale for digital transformation, unless there is a need for business transformation.  If you believe this as we do, then strategy development will be a priority.  Strategies, however, are developed under the guidance of a doctrine.  The purpose of a doctrine is to create a high level understanding of what we we want to achieve with our strategy, and the concepts that must be employed to achieve it. An organization’s doctrine will guide strategy development, and the tactics needed to achieve a goal.

An example of a doctrine is, "We will be a fast follower, and excel at quickly manufacturing and delivering fashions proven to be in demand." With this doctrine, the company can now develop strategies that align with the doctrine.

Many executives consider digital transformation to be mostly an IT issue.  We, however, believe IT serves only one purpose – supporting the needs and strategies of the business.  If the business doesn’t have a strategy that requires digital transformation, then there is no transformation role for IT to play. 

In today's fast changing digital environment, the operational speed and agility of a business can mean the difference between winning and losing.  Speed and agility are not grass roots efforts, but the result of decisive and strong leadership with a clear vision.  Leaders must have an intimate understanding of the goals, doctrines and strategies of the organization, and the resources and levers of power available to achieve them.  They must have both the will and the clout to manuever the organization through the turbulence of change.  Grassroots efforts to transform an organization often takes too much time and the process of consensus building too slow to compete against engaged, focused leaders.  

In order to act fast, leaders must have an intimate understanding of fast changing customer behaviors. Leaders must know how much change is happening, and the technologies that are supporting these changes.  We watched consumers adopt and utilize the internet, mobile devices, search engines, online auctions, mobile retailer apps/websites, online classifieds, online markets and sharing economy platforms.  These changes required new business strategies and new digital strategies to support them.  

Fast changing business environments require us to measure and understand how fast buying habits and shopping behaviors are changing.  We must also understand where in the various steps of the path-to-purchase journey changes are taking place, and then understand how to attract and engage our markets in those new and mobile locations. None of this is easy.  Many new behaviors and trends are outside of traditional measurements. Leaders must measure the pace of market change, and align resources and priorities to ensure their organizations are changing, if not at the same pace, at least at a pace ahead of their competition.

What units of measure will capture the speed of change?  What data sources will provide the data necessary for analysis, and how do we capture the data?  Once we have a methodology in place for measuring the pace of market change, how do we then measure the pace of our own changes inside our organizations and in those of our competitors so we know how we are doing?  

Download my latest report, "How Digital Thinking Separates Retail Leaders from Laggards."

  1. How Digital Thinking Separates Retail Leaders from Laggards
  2. To Bot, or Not to Bot
  3. Oils, Bots, AI and Clogged Arteries
  4. Artificial Intelligence Out of Doors in the Kingdom of Robots
  5. How Digital Leaders are Different
  6. The Three Tsunamis of Digital Transformation - Be Prepared!
  7. Bots, AI and the Next 40 Months
  8. You Only Have 40 Months to Digitally Transform
  9. Digital Technologies and the Greater Good
  10. Video Report: 40 Months of Hyper-Digital Transformation
  11. Report: 40 Months of Hyper-Digital Transformation
  12. Virtual Moves to Real in with Sensors and Digital Transformation
  13. Technology Must Disappear in 2017
  14. Merging Humans with AI and Machine Learning Systems
  15. In Defense of the Human Experience in a Digital World
  16. Profits that Kill in the Age of Digital Transformation
  17. Competing in Future Time and Digital Transformation
  18. Digital Hope and Redemption in the Digital Age
  19. Digital Transformation and the Role of Faster
  20. Digital Transformation and the Law of Thermodynamics
  21. Jettison the Heavy Baggage and Digitally Transform
  22. Digital Transformation - The Dark Side
  23. Business is Not as Usual in Digital Transformation
  24. 15 Rules for Winning in Digital Transformation
  25. The End Goal of Digital Transformation
  26. Digital Transformation and the Ignorance Penalty
  27. Surviving the Three Ages of Digital Transformation
  28. The Advantages of an Advantage in Digital Transformation
  29. From Digital to Hyper-Transformation
  30. Believers, Non-Believers and Digital Transformation
  31. Forces Driving the Digital Transformation Era
  32. Digital Transformation Requires Agility and Energy Measurement
  33. A Doctrine for Digital Transformation is Required
  34. Digital Transformation and Its Role in Mobility and Competition
  35. Digital Transformation - A Revolution in Precision Through IoT, Analytics and Mobility
  36. Competing in Digital Transformation and Mobility
  37. Ambiguity and Digital Transformation
  38. Digital Transformation and Mobility - Macro-Forces and Timing
  39. Mobile and IoT Technologies are Inside the Curve of Human Time

Five Insights into Artificial Intelligence for Southeast Asia's Financial Services

The rise of artificial intelligence (AI) is the great story of our time, thanks to the ever-falling cost of computing and the increases in the availability and power of the machines. We are already surrounded by smart machines (from Alexa to Siri, Uber, and Netflix) that run on incredibly powerful and self-learning software platforms. This is just the beginning, as AI is transitioning from being our little daily helper to something much more powerful—not to mention disruptive—that is impacting every facet of our commercial lives. The banking and financial services sector is no exception. To understand how newly founded financial institutions are uniquely positioned to take advantage of AI, earlier this month we hosted an executive lunch briefing at the IDC Asian Financial Services Event in Singapore. Around 40 C-level executives participated in the discussion, in which we deliberated on the theme “Banking on AI.

It is safe to say that we had some eye-opening conversations. Below, I would like to share some key takeaways from our talks:

AI is here and now. It is crystal clear that AI is set to cause shockwaves in the banking and financial services industry, with almost every participant agreeing that it will fundamentally change the ways in which they interact with their customers and deliver products and services. In fact, our latest paper, The Work AHEAD in Banking and Financial Services, confirms that 58% of industry executives surveyed feel that the rise of the new machines will have a significant impact on their work, compared with the cross-industry average of 51%. There is no doubt that the future of work is the mirror image of the future of AI.

Chatbots are poised to take off. Southeast Asian banks are in the experimentation phase with Chatbots (many of their representatives mentioned doing POCs). Initial feedback from customers on this personalized ‘assistant’ has been very positive. Although Chatbots are still in their infancy, they will be ubiquitous within a few years and will have a game-changing impact on how customer support is conducted. For instance, a Singapore-based fintech startup,, is in discussions with 20+ banks in the Asia Pacific region to deploy its Chatbot platform and expects at least 10 of these to go live on their platform this year.

Robo Advisors are another segment that is gaining attention from organizations when it comes to redefining wealth management space. Startups like Smartly are in a prime position to target the Southeast Asian millennial market with their robo-advisory platform. My view is that, while we are still in the early days of robo-advisory services in the region, banks must get on board this ship before it sets sail. They should not just be thinking about using robo-advice as just another channel to sell products, but rather as a medium for delivering a consistent experience to customers.

AI localization will be the biggest challenge (and opportunity). The Digital Head of a large Thailand-based bank shared a practical challenge with us. His bank had recently implemented the Chatbot platform with the aim of securing deeper customer engagement. The platform was meant to understand and respond to queries in the English language. When it went live, people started typing Thai language words (in English) to ask questions. The system got confused as it could not understand many of the words. As a result, they had to take the system down within 24 hours of going live. This highlights the need for organizations to consider local and unique challenges when developing their technological capabilities.

The back-office is a wildly overlooked opportunity. Our research shows that banking and financial services companies have yet to unlock the true value of their back offices. Industry executives expect their costs to decrease by an average of 1.8% by 2018 as a result of going digital. We believe that AI-led automation will accelerate the pace of modernization in middle- and back-office operations, thereby truly digitizing the fundamental operational blocks. For instance, Blue Prism is applying bots to risk, fraud, claims processing, and loan management in banking to save millions. In fact, automation will dictate organizations’ subsequent enterprise AI initiatives. Our latest book, What to Do When Machines Do Everything, provides guidance on how leaders should pick their automation targets across their organization.

Regulations, ethics, and security issues are top-line concerns. Security, ethics, and the lack of AI-related regulatory frameworks are the main concerns that could throw a spanner in the works when it comes to the rapid adoption of AI solutions. For example, the regulatory squeamishness around cross-border investment in robo-advisors is something that has yet to be resolved. In addition, what if a bank’s algorithm finds a pattern of loan defaulters for a certain racial community and, based on that, rejects their loan applications? Legal regulations denote that customers cannot be discriminated against based on race. Such an outcome could cause a bank to face a potential legal suit, leading to a loss of reputation and business. Other questions include: how will an algorithm identify and verify the user before providing information or allowing for complex actions such as money transfers? Will over-reliance on AI incur unknown risks? These and many other questions were debated by our executives.

There is no doubt that AI is already among us; it just hasn’t been evenly distributed yet. In the timeline of the AI revolution, we have just fired the opening shot. While all the concerns raised by executives are valid and call for further debate, frankly they will not halt the cross-field uptake of AI-led innovations. Do you remember when the “information highway” opened back in the early 1990s, it caused a wave of fear over the erosion of data privacy and control, intrusion, and hacking? Despite all the concerns about companies tracking our information online, few swore off the Internet entirely. Instead, smartphones and social media have become permanent fixtures in many of our lives. Once AI is assimilated, we will stop focusing on its perceived downside. We are in the ‘fear phase’ right now; the trick is to avoid getting fixated on it.

We are in an era of perpetual change, with AI at the rudder. To put it in simple terms, AI equates to real value. The implications for business decision-makers are almost stratospheric in proportions, and their strategies and investments should reflect this. It’s time to move beyond trifling experiments and take a long hard look at AI and what it means to your business. Process by process, throughout your entire value chain, you should identify ways of applying AI to change how work is done and how customers engage with your business. It’s not an either/or choice, as the impact of AI on the industry could be even bigger than anticipated.

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Maslow's heirarchy moves into the Digital Age

I recently joined Cognizant’s Center for the Future of Work (CFOW), meaning that I now ... pretty much carry on doing what I used to do as an analyst: challenge organizations on their future journeys from a talent, process and platform perspective. Something that’s been on my mind over the last few weeks is the psychological impact of new digital technologies (AI, digital consumer interaction, big data, prescriptive analytics, etc.) on the workers of tomorrow.

I’m particularly interested in what work ahead will look like when intelligent systems perform more and more of our everyday, not-so-mundane tasks. What will motivate workers in this higher value world? And does humanity actually have a key role to play in continuously improving and refining this digitally led business environment of the future?

In a recent CFOW report, (People — Not Just Machines —Will Power Digital Innovation), we proposed the concept of “alloyed economies” that would blend talent, disciplines and technologies across industries to deliver compelling business outcomes. To an extent this is already happening – consider the recent IBM Watson/Salesforce partnership or Garmin’s dominance of the connected cycling world.

The coming of AI and true automation has widely been labeled the Fourth Industrial Revolution, the blending of the physical and digital worlds. Unreformed economist that I am, I can’t help but observe the impact that this revolution will have on our economy and society as a whole. Looking at the previous three industrial revolutions, it‘s apparent that society took a step forward in its basic needs and ambitions following the introduction of each one.

Observing the various stages of each against the backdrop of Maslow’s Hierarchy of Needs, parallels begin to emerge. Take the First Industrial Revolution: With the advent of mechanized agriculture and manufacturing, society could make more efficient use of resources, resulting in a greater abundance of food and products. This allowed society to move beyond subsistence living and progress up the hierarchy of needs to focus more on issues like security, safety and belonging.

If we take this thinking and fast forward to the Fourth Industrial Revolution, which is based on automation of tasks (payroll processing, driverless transport, etc.), a likely result will be a society that is better able to focus on areas outside of task fulfillment. In the next decade, we foresee individuals being freer to fully explore the needs of self-actualization and self-transcendence than at any time in human history. Recent policies being examined in governments around the world, such as the national wage proposed in Switzerland, point to the beginning of this stage. While it was rejected, the fact that it got as far as a referendum points to society that is overcoming the limits of the individual self and focusing more society’s wider ambiguities.

So, you might be thinking, “Great, but what does this mean for the future of business?” We see two potential impacts:

  • First, the worker of the future will be much more concerned with and driven by the need for self-expression, self-contemplation and creativity. This means businesses will need to drastically realign HR and working environment practices that allow workers to express themselves, their impact on an organization and their creativity. In an upcoming piece of research we are undertaking at CFOW that looks at how work and its physical environment will interact in the future, titled The Future of Space we will look to identify how space (cities and working environments) will adapt to foster productivity in this new age of self-awareness.
  • Second, this new sense of self-awareness and creativity feeds neatly into the future of work. Very soon, we won’t need “grunt” workers, and while many see this as the Armageddon of the job market, we see a new society of self-aware, creative workers emerging, bringing in a completely new set of jobs and skills. Roles such as virtual reality architects, smart home developers and talent explorers will become, dare I say it, commonplace. Workers with a greater need to express themselves creatively will be more suited to these roles.

Essentially, this Fourth Industrial Revolution will usher in a self-fulfilling prophecy: The very fact that mundane work is removed from our day-to-day lives, we, as a society, will be more able to imagine and develop the world of the future. And in that future – which will continue to utilize human talent -- our strategic and creative abilities will push us toward being the stewards, rather than simply the construction workers, of our future.

Just to end.

Within Cognizant’s CFOW, our Work AHEAD series of research is actively challenging business leaders to rethink their digital strategies and ready themselves for 2020. Our recent book, What to do when Machines do Everything, highlights the AHEAD model, this model provides a roadmap to follow in order to succeed in the business of the future underpinned by algorithms, AI, cloud and mobility.

In short, AHEAD outlines five key approaches for success with systems of intelligence, namely:

  • Automate: Outsource rote, computational work to the new machine.
  • Halo: Instrument products and people and leverage the data exhaust they generate through their connected and online behaviors (what we call Code Halos) to create new customer experiences and business models.
  • Enhance: View the computer as a colleague that can increase your job productivity and satisfaction.
  • Abundance: Use the new machine to open up vast new markets by dropping the price point of existing offers, much as Henry Ford did with automobiles.
  • Discovery: Leverage AI to convince entirely new products, new services, and entirely new industries.

The “meat” of this blog really deals with the “D” in this acronym, by looking to reimagine (or discover...) the worker and society of the future of business.