Kevin Benedict Ponders the Future

The 3 Tsunamis of Digital Transformation - Be Prepared

Change is hard, and many of us procrastinate, make excuses or lag behind. Today, we simply can’t. Digital technologies are no longer “nice-to-have” tools of the business – today they are the business. Digital laggards are already finding their markets disrupted and their abilities to compete overturned. As they desperately try to outrun the Darwinian effect of their slow responses, they are faced with not one but three periods – or ages – of digital transformation to navigate – disruptive transformation, hyper-digital transformation and ubiquitous transformation. Understanding these three ages, and when they will emerge, is critical for business success.

Some may argue digital transformation started 70 years ago with ENIAC, the first commercially available computer, while others argue it started with the Internet. Whenever the starting point actually was, we can all agree that the proliferation of digital over the last five years has brought unprecedented personal and business disruption.

The age of disruptive transformation introduced eight specific technologies that disrupted traditional business operations and IT infrastructures, and are having a “large to very large” business impact on at least one-quarter of the digital leaders in our survey:

Cybersecurity (59%) 
Big data/business analytics (54%)
Mobile technologies (40%) 
Cloud computing (32%)
Social media (31%)
Collaboration technologies (26%)
IoT/sensors (26%)
Biotechnology (25%)

These eight technologies are data-centric – they are all about producing, managing, analyzing, securing and storing data in new and innovative ways, and then acting on it. With the exception of biotechnology, these digital technologies are critical components of OILS, and profoundly impact business strategies, business processes and human interactions.

These digital technologies – which should already be implemented and scaling to have an impact on your organization – now serve as the foundation for the next two periods of digital transformation. If these top eight digital technologies are not already in place within your IT infrastructure, the current age of hyper-digital transformation will threaten your company’s very existence.

During the second period of digital-related change – the age of hyper-digital transformation – the pace of change and the business impact of digital technologies greatly accelerate. The eight top technologies from the previous era will rapidly increase their business impact by an average of 74% among digital leaders by 2020. This increase is a sign of the enormity of the forces at work, the size of investments needed, and the cadence at which organizations need to adapt to stay relevant and competitive.

In the age of hyper-digital transformation, nine additional, incremental digital technologies join the eight from the previous age. These nine start with a relatively low level of importance today but increase by an average of 145% among digital leaders by the year 2020. These nine additional digital technologies reach the threshold of having an “important to very important” business impact among at least one-fourth of digital leaders:

Telepresence (Skype, Google Hangouts, etc.) (49%)
Digital currency (49%)
Artificial intelligence (46%)
Robotic process automation (software) (41%)
Sharing economy platforms like Uber (39%)
Nanotechnologies (35%)
Robots (hardware) (33%)
Telematics (29%)
Wearables (28%)

When combined, these seventeen digital technologies increase their business impact among digital leaders by an average of 112% between 2016 and 2020. The predicted business impact of these digital technologies mean that the business and IT organizations you operate today will need to look very different by 2020 in order to keep up and compete successfully.

Retail is considered a canary in the coalmine for many other industries. As such, when retail giants begin to fail, it is important to pay attention and heed the warning signs. Retail giant Sports Authority led for bankruptcy in March 2016, and according to many analysts, this was due in large part to the company’s slow response to online and mobile competition. In May 2016, Aeropostale led for bankruptcy, and according to analysts, it couldn’t keep up with fast-changing consumer behaviors and the speed of emerging fashion trends at the same rate as their online competitors. Also in May2016, the UK-based BHS entered administration (i.e., led for bankruptcy), and according to reports, the company had fallen far behind its digital competitors and fast-changing consumer trends.

The consensus among retail analysts is these companies failed to digitally transform quickly enough, which resulted in lost ground to more tech-savvy competitors.

In the final period of the digital transformation trilogy – the age of ubiquitous transformation in the year 2025 – our research finds the business impact of the previous age slowing as companies work to digest the incredible change of the two previous ages. However, even in this more pedestrian age, respondents expect an impressive 35% increase in the business impact of digital technologies.

In this era, six new technologies mature and join the previous seventeen, all of which are now having a “large to very large” business impact on the organizations at the forefront of digital change:

Blockchain (43%)
Geospatial information systems (41%)
3-D printing (40%)
Virtual reality (39%)
Autonomous self-driving cars (34%)
Drones (33%).

Among digital leaders, these six digital technologies are expected to increase their business impact an average of 96% between 2020 and 2025.

These six additional data-driven technologies are at once foundational and revolutionary. They highlight dramatic changes to come in industries such as transportation, banking, finance and commerce and manufacturing, all made possible by the digital transformations that preceded them.

Timing is everything, and the correct sequencing of technology implementation and budgeting, from proof of concept through implementation of production-ready systems, is critical. Our list of 23 digital technologies, their maturity timeframes and projected business impact (posited by our respondents) are powerful tools to plan your organization’s digital transformation strategy.

Watch the 3-minute video:

Download the full report with charts and data sources here: https://www.cognizant.com/FoW/twa-hyper-digital-transformation-codex2478.pdf

Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant

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Follow me on Twitter @krbenedict

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***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

Robots, AI and the Next 40 Months

In a world that operates on billions of digits every day, humans are too slow and inattentive. To adapt, we must automate the processing of millions of complex transactions on a daily basis, at speeds fast enough to satisfy impatient digital users. This adaptation requires a massive level of digital transformation that can support operations, business processes and decision-making speeds faster than is humanly possible.

Historically, digital technologies get faster, cheaper, more powerful and smaller every couple of years. We humans, however, don’t. We operate in human time, a biological cadence influenced by the physical environment, our well-documented physical, mental and emotional limitations, and the universe that we live in. As digital interactions proliferate, so also does the volume of real-time data and required analysis. Most people are already at their limit of coping with the deluge of data, so we must now digitally augment our capabilities to handle the massive increases in the volume, speed and the complexity of it. These augmentations will involve OILS (optimized information logistics systems), supported by artificial intelligence (AI) and software for process automation.

Software robots (or “bots”) can be developed to analyze vast quantities of data without getting bored, make decisions based on codified decision trees that humans design, and then act in milliseconds. In our research, 18% of digital leaders report intelligent process automation via bots is already having a large to very large impact on their businesses, however, it jumps to 41% by 2020. This represents a dramatic increase of 128% in just 40 months.

We – humans – already at our limit, must find a way to digitally augment our capabilities to handle the massive increases in the volume, speed and the complexity of data with bots.

Slow service annoys us. We are immediately frustrated with people and brands incapable of supporting our digital habits and expectations. To achieve a real-time operational tempo, companies must evolve from "human time" to "digital time." When enterprises can support digital time, they can close process loops faster, harness immediate feedback on what’s happening within the process itself, and act on those insights nearly instantaneously. The result: smarter decisions that enable businesses to operate like never before.

One of the biggest challenges enterprises face today in designing, developing and deploying OILS is upgrading core IT systems that frequently comprise of legacy systems incapable of supporting digital time. Though this is hard work, it is the key to winning.

Our research clearly shows widespread consensus that AI is one of the most important emerging technologies that will help overcome many of these technology and human limitations. Our survey respondents predict AI will be the top digital technology, with the largest impact on their work, by 2020. Currently, only 15% of the respondents think AI is having a large impact on their business. In the next 40 months, however, 46% believe AI will be critical – that’s a 207% increase in pro-AI sentiment.

Digital interactions are often supported by AI systems dependent on real-time analytics to provide contextually relevant and personalized experiences. In addition, as the number of mobile and connected devices with billions of connected sensors increases, so also does the associated data in the ether that needs to be analyzed and turned into actionable intelligence that can be used by AI systems to deliver real-time business value. No wonder, then, that executives in our research forecast big data/business analytics will have the biggest impact of all technologies between the years 2020-2025.

Download the full report for free here.

Watch the report video here.

Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant

View my profile on LinkedIn

Follow me on Twitter @krbenedict

Subscribe to Kevin's YouTube Channel

Join the Linkedin Group Strategic Enterprise Mobility

Join the Google+ Community Mobile Enterprise Strategies

Digital Technology and the Greater Good

Adam Smith wrote about the concept of rational self-interest, which posits we work together for the greater good when it benefits ourselves. Does this concept have relevance in the context of robots, automation and employment? I think it does.

I believe most of us would agree that replacing large numbers of humans with machines that result in wide scale unemployment and suffering is not in our rational self-interest. Having massive numbers of jobs terminated by the Terminator does not result in a safer, healthier civilization or vibrant economy; therefore, it is not in our best interest.

Just because something is possible, does not mean it is good. A powerful king that takes all the food, property and means of production away from his people resulting in their suffering, quickly becomes a target of their wrath, and on a quick path to poverty.

Businesses that replace human workers with machines and software, out of self-interest, will over time find it increasingly difficult to sell their products to their unemployed or underemployed consumers. At what point do businesses seek to expand employment opportunities out of a rational self-interest rather than decrease them through automation? Is it a realistic option for profit maximizing businesses to seek the greater good?

In the short-term, factories hope to benefit from automation faster than their competition in order to gain advantages, while there are still sufficient numbers of consumers employed elsewhere to provide a market for their goods. In the mid-term, entire industries will automate and terminate large numbers of jobs, but hope other, slower-to-automate industries will employ their consumer base. In the long-term, however, when digital transformation has swept through all industries, who is left to employ the consumers and provide them living wages, and who is left with capital to buy goods?

As jobs that require little training or education diminish in numbers, we have two choices, 1) Increase education levels to equip our population for the digital future, or 2) subsidize the unemployed and underemployed with a sufficient income to survive and maintain their dignity. If there are still not enough jobs for those that work hard to increase their level of education, then we are reduced to one choice.

There are plenty of problems left on this planet to be solved. Solving these problems could employ many. Today, however, not all of these problems have economic values assigned to them. Fresh water sources, clean air, forestation, peace, better health, better education, etc., all of these have the potential to generate enormous economic benefits, but they need society to place a value on them and reward innovations and employment in these areas.

A vibrant economy, and a safe and secure society depend on healthy employment numbers, adequate wages, property ownership and rights, hope, peace and purpose. Digital transformation must foster these goals, or risks accelerating a break down in our society and economy – two things that can dampen a New Year’s celebration.

Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant

View my profile on LinkedIn

Follow me on Twitter @krbenedict

Subscribe to Kevin's YouTube Channel

Join the Linkedin Group Strategic Enterprise Mobility

Join the Google+ Community Mobile Enterprise Strategies

New Report: 40 Months of Hyper-Digital Transformation

Forty months is not a lot of time to design, develop and deliver something monumental. Consider that it took 182 years to build the Notre Dame Cathedral in Paris, 20 years to build the Great Pyramid of Giza and 10 years to build the Panama Canal. Executives from digital-leading companies, however, tell us that in just over three years – the year 2020 – 17 different digital technologies will dramatically impact the way they work, and transform the work that gets done, so we don't have much time.

This means that within the next 40 months the exponential growth of digitization and machine learning will fundamentally change how businesses create value, satisfy customers and outperform competitors. This also means that in this same time period, companies must take actions that position them for the next level of success. If they don’t embrace digital, for many it will be game over.

To better understand the strategies and technologies that digital transformation winners require, Cognizant’s Center for the Future of Work, in partnership with the renowned economist Nouriel Roubini, surveyed 2,000 executives, 500 managers, 150 MBA students and 50 futurists across 18 countries. What we found is that today’s and tomorrow’s winners will need to think differently, follow different strategies, deploy different technologies and make cybersecurity a top priority – all while realizing that time is slipping away.

Guiding a business through the turbulence and friction of digital transformation is perhaps the great challenge of our time. Just as John Ellis’s invention of high-temperature oils unleashed the power of railroads, industrialization and economic growth in the 19th century, data is the lubricant of today’s digital age. More to the point, today’s hyper-digital transformation will be driven by optimized information logistics systems (OILS) and IT infrastructures capable of facilitating real-time digital interactions.

Our research revealed several findings that we detail in the report:

Digital leaders think and act differently.
Digital leaders recognize that digital transformation is the key to their future relevance and success, and they act as though their lives depend on getting transformation right.
Recognition alone is not enough, though. Digital leaders also execute the right actions and technologies in the right sequences to successfully navigate resource constraints.
Digital technologies are the keys that unlock a golden door.

The 2,000-plus executives we surveyed have already generated $328.7 billion in total revenue through the strategic deployment of digital technologies in the last year. Respondents believe there’s much more to be had, though: We found businesses could unlock another $151.6 billion in value if they take full advantage of the digital opportunities at hand. Download and read the full report here https://www.cognizant.com/FoW/twa-hyper-digital-transformation-codex2478.pdf.

Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant Writer, Speaker and World Traveler

View my profile on LinkedIn

Follow me on Twitter @krbenedict

Subscribe to Kevin'sYouTube Channel

Join the Linkedin Group Strategic Enterprise Mobility

Join the Google+ Community Mobile Enterprise Strategies

Virtual Reality Moves to Real with Sensors and Digital Transformation

I was on a high-rise construction site 34-floors above the city. I was talking to the construction crew when a fight broke out. There was an explosion and the floor collapsed. I removed the virtual reality (VR) goggles and laughed. It was so real. The VR solutions provided an incredible experience, almost like being there. As good as my experience was, it was not reality. It was a controlled pre-programmed experience - a notional idea. Today, however, VR, sensors and sensory feedback technologies enable a notional idea to become reality – a Real-Reality.

IoT sensors extend our physical senses beyond our physical reach. Haptic feedback systems enable us to physically feel distant objects and experience events, digital odors can be collected, profiled, transmitted and recreated locally on odor printers, 3D infrared scanners can capture and scale physical shapes and environments and transmit them anywhere to be used by 3D printers or in digital scenes. We can visualize, sense, and mentally and emotionally experience events. These experiences, which are data centric and data heavy, go far beyond virtual reality, to Real-Reality (RR).

Wikipedia defines reality as, ”The state of things as they actually exist, rather than as they may appear or might be imagined.” With enough sensors collecting data, and with the right VR solutions and sensory feedback systems in place, we can step across the line from virtual to real reality. These technologies enable us to sense, feel, and experience actual events - potentially on the other side of the world. This is a big deal. This can enable experts to be anywhere on the planet, with maximum understanding of local situations.

Although many of these technologies are still in their infancy, they hint of a time very soon when the ability to bring distant realities into homes, industry and boardrooms are not only possible, but commonplace. The keys to making this future a reality, are measuring and collecting the right data, transmitting it, and optimizing the sensory experience.

How do we understand distant situations, activities, operations and events today? In many cases a human tries to capture and recreate the situation in words, and then forwards as an email or message. There are obvious limitations to this means of communication when fast moving and complex situations are involved. RR solutions with the required level of digital transformation implemented, including real-time sensors and sensory feedback systems, can communicate these experiences directly to our minds and bodies from anywhere in the world in real-time, thus bypassing the limitations of intermediary humans and written languages.

RR enables experts from anywhere in the world to conduct medical surgeries, repair specialized equipment, manage factories, farms and other kinds of operations from distant locations. The obstacles of the past that resulted in operational blind spots and incomplete information are quickly going away as RR becomes a reality - a real-reality.

Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant Writer, Speaker and World Traveler

View my profile on LinkedIn

Follow me on Twitter @krbenedict

Subscribe to Kevin's YouTube Channel

Join the Linkedin Group Strategic Enterprise Mobility

Join the Google+ Community Mobile Enterprise Strategies

How Good is Your Mind at Predicting?

My friend, Peter Rogers, who lives in the UK was wrong at predicting Brexit, but right at predicting Donald Trump would win. How did he get one wrong and the other right? Read about his experiences here.

Guest Blogger - Peter Rogers

Peter Rogers Predicted Donald Trump

I always thought I was particularly good at prediction as a result of me working as a technologist most of my life, but my world was turned upside down after Brexit. It took a long time for me to work out why I got Brexit so wrong, but eventually I brushed myself off and started to read a lot of material on Super-Forecasters.

It learned I had been misleading myself for many years. I thought I was good at non-technical decision-making. I recall looking at the Ladbrokes Swingometer for Brexit and being so sure of a "remain" vote, that I was going to place a large bet. I was however, wrong. I made the classic mistake of polluting the decision-maker-mindset.

In order to forecast accurately I needed to consider a wide range of diverse opinions without being overly drawn to any one particular source. This of course, is where social media makes fools of us all. We are typically drawn to a small group of close friends for inspiration, and these friends typically share our opinions. People rarely fact check on social media. We also read newspapers, which have an increasingly political bias, and a high percentage of us fail to fact check.

I decided if I was going to truly escape from newspapers and social media bias, then I was going to have to train myself to be able to forecast independently. As a first step, I built a website that enabled me to place forecasts and to track whether I was right or wrong. I added a scoring system so there was feedback for my predictions. This was important as most people don't keep track of their predictions and the results.

Every day I made forecasts on politics, sports, weather, finances, entertainment, and just about anything else I could think of. I thought anybody can make correct guesses in their own field of expertise, but how many people can make correct predictions outside of it? Even that prediction was wrong! In fact, it turns out that Subject Matter Experts (SMEs) are bad forecasters in their own field!

I learned there are two parts to being a good forecaster:

A good gut feel
Being able to show your "thought process." Show how you worked through an "Outside Model" that is refined by an "Inside Model."

I started out remarkably bad at forecasting. I soon learned to differentiate between the things I wasn’t so sure of, and mark these at a lesser percentage, from those that I was quite sure about, which I would place at a higher percentage. I also began regularly adjusting my prediction when new evidence became available. It actually started to feel a lot like betting, because I used a simple gamification hook with an avatar who gets weaker or stronger depending on my average score.

The bottom line, after 50 bets, I was actually able to predict with 95% accuracy that Donald Trump would be the next President many months before the actual election.

My goal now is to help other people improve their predictive powers as I did. The system still needs a lot of work. Today it helps people improve their gut instinct, which is an improvement as I went from 25% accuracy to to 75% in just three months of time. My plan now is to roll the system out to the general public as a beta. You can register by simply emailing peterzrogers@hotmail.com, and I will send you the website address and a secure login token.

I am also very interested in talking to people who would like to take the system forward because I strongly believe that digital systems to enhance forecasting are in demand.

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant Writer, Speaker and World Traveler

Kevin Benedict Ponders the Future

The 3 Tsunamis of Digital Transformation - Be Prepared

Robots, AI and the Next 40 Months

Digital Technology and the Greater Good

New Report: 40 Months of Hyper-Digital Transformation

Virtual Reality Moves to Real with Sensors and Digital Transformation

How Good is Your Mind at Predicting?

Interviews with Kevin Benedict

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