Kevin Benedict Ponders the Future

The Day Big Data Analytics Died

The Huffington Post gave Donald Trump a 2% chance of winning, The New York Times 15%. The best polls, prediction markets and analytics predicted a Hillary Clinton victory in the days before the election, yet they were all wrong. The national media’s predictive analytic systems failed catastrophically. Why?

Analytic systems require timely data on all the variables that impact a system and measure its performance. Analytics requires support from an optimized information logistics system (OILS), which describes the a system that manages the full lifecycle of data from collection, transmission, processing, analysis, reporting, data driven decision-making, action and archiving. An OILS is only as good as the data. It can only function correctly if it is collecting the necessary data inputs. For example the sensors in an Internet of Things (IoT) system must be attached to the right “things” that impact operations, to provide full system visibility and insight. The pre-election big data analytics systems used by pundits, media and prediction markets used incomplete data that resulted in operational blindness, a massive failure for those responsible.

A simple phone poll may not measure the degree of sentiment, neither does it measure those not on the phone. It appears from reports this morning that large numbers of folks whom rarely if ever voted - voted. This unmeasured, invisible group, that was an important data input, was not measured and analyzed in the OILS.

When I meet with business and IT strategy leaders and discuss data analytics and OILS, I always ask them, "What data are you NOT collecting that potentially could be important to your plans and operations?" Many have never considered this simple question. They look at their available data, but not their data gaps. Today in a world of hyper-connectivity, bots, real-time operational tempos and decision-making, having the right data at the right time is critical. What data are you not collecting?

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Kevin Benedict

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

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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.

Merging Humans with Enterprise AI and Machine Learning Systems

Artificial intelligence and machine learning systems are made up of code and algorithms, and as such, they work as fast as computers can process them. Often this means massive amounts of learning can be accomplished every second without stop 24x7x365. Code doesn't need to take weekends off, holidays, or sick time. Code doesn't get tired. It can recognize complex patterns, areas of potential improvement and problems in real-time (aka digital-time). Given these available computing capabilities and speeds, what are executives to do with AI and machine learning, when we live and operate in relatively slow human-time, and work within organizations that work at an even slower pace of organizational-time.

I believe the first step is to admit we have a problem - the problem is a difference in the speed that computers can operate and the speeds us humans can operate. The second is to understand what a solution might look like - how humans and computers can best integrate and operate together for business success, and the third is to have a strategy and plan.

Imagine a scenario where you arrive at your desk on a Monday morning and find hundreds of recommendations for business process improvements from your AI and machine learning systems. Each of the recommendations might take weeks to socialize across the organization and implement. Now, imagine that happens every day of the year. We humans would be completely overwhelmed! In this scenario, humans are the weak links in business process optimization.

How are we then to best utilize AI and machine learning in a manner that benefits humans, and human powered organizations? I propose the answer lies in developing a powerful AI and machine learning platform that understands our goals and aspirations, can filter findings, run and test simulations, and then present a few select prioritized recommendations to human decision-makers. Simply feeding leaders with unlimited numbers of recommendations may actually paralyze, rather than empower them. What are needed are systems that won’t overwhelm humans, but rather augment them.

In order for any of these AI and machine learning systems to actually work, the data that fuels these systems must first be available, accurate, normalized and timely - for many that is the essence of digital transformation. A digital transformation initiative often includes upgrading IT systems to become “optimized information logistics system” (OILS). Systems that ensure the right data is collected, available, analyzed and its meaning and context understood and utilized.

Once an organization has an OILS in place and the data available, then leaders must ensure their organizational structures and business processes are capable of responding at an operational tempo sufficient to capture the benefits and competitive advantages available from the insights derived from AI and machine learning. That is no small feat. It does no good, as we pointed out, to have recommendations that cannot be implemented.

Massive volumes of new data from sensors, mobile devices, embedded computers and online activities means there are enormous opportunities to learn and gain competitive advantages as a result of it, but only if our leaders, IT and business systems, and our organizations are capable of responding fast enough to capture the value. Understanding how to create OILS, how to utilize AI and machine learning to effectively augment our leaders, and then knowing how to create an organization able to respond fast enough to capture the competitive advantages in the data are the monumental tasks before us today.

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

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Mobile Expert Interviews: PowWow Mobile's CEO Kia Behnia

The enterprise mobility software vendor space has been around for more than a decade, but new start-ups continue to enter the market with ambitions to address unsolved problems and challenges. In this interview, I ask PowWow Mobile CEO Kia Behnia, why an enterprise mobility start-up now?

Kevin Benedict's latest video on mobile commerce trends and strategies: ************************************************************************

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

Profits that Kill in the Age of Digital Transformation

Presenting 40 Months of Hyper-Digital Transformation in Lisbon, PT

Digital transformation initiatives both increase revenue and decrease expenses according to our upcoming study titled Work AHEAD 2016 by Cognizant’s Center for the Future of Work. For this study we surveyed over 2,000 executives across 18 countries. The expected net business impact over the next 3 years of rapid digital transformation, i.e. hyper-transformation, is an increase in revenue of 11.4% (Revenue = 10.3%, Costs = -1.3%) amongst the companies in our study. These numbers represent the difference between success and failure in many industries.

To get the predicted revenue impact, companies expect to increase their spending on digital technologies from 11.3% of their revenue today, to 16.6% of revenue by 2020, while decreasing their non-digital investments.

In addition, our study reveals 64% of the futurists in our study, experts paid to study digital technology trends and to develop future strategies, believe digital transformation will boost revenues by 2020, 76% believe it will strengthen their competitive positioning, and 88% believe it will accelerate their speed to market. If you accept these predictions, then your organization should quickly transform itself and jettison the heavy baggage that accumulates as a result of decades of institutionalized methodologies developed and codified in an analog era - an era operating at a far slower operational tempo. The good news is that ROIs (return on investments) from digital transformation initiatives are compelling. Nearly 30% of the surveyed firms are receiving an ROI greater than 100%.

These revenue numbers have investors interested and asking about the digital transformation plans of companies they invest in, or are considering investing in today. We have all read about the list of companies that have failed this year due in part to their slow and/or inadequate response to digital technologies and changing competitive marketplaces. As a result investors today want to understand the speed and scale of their portfolio’s digital transformation initiatives, as these initiatives can be predictors of future value.

For executives, transforming an enterprise is difficult at any time, but when an enterprise is highly profitable - digital transformation is even harder. Why? The temptation to follow the maxim, “Don’t fix what isn’t broken,” is just too compelling. The challenge enterprises are faced with today, however, is that digital technologies are changing the competitive landscape faster and in different ways than executives have ever seen before.

Recently, we presented a workshop on digital transformation strategies to a highly profitable automotive parts and systems manufacturer. The company is filled with smart people using efficient long standing manufacturing systems and processes. The company is innovative in R&D, and forward thinking in the adoption of digital technologies and strategies for their products and services.

The challenge we all faced in the room is how do we justify digital transformation investments, when today the old systems and ways of thinking pay out in record profits? How do we articulate that sensors, artificial intelligence, digital platforms and real-time data are taking on a whole new level of importance? In fact, executives believe big data and business analytics will have the biggest business impact of all technologies on businesses from years 2020-2025.

We were able to demonstrate, through an intensive brainstorming workshop, how a sensor enabled digital platform connected to their physical parts and equipment, and integrated with external databases could provide enormous customer and business value. We were able to show them how their current list of physical products and services, could be expanded by adding a whole new list of new digital products and services on top of their current offerings. The data they had access to in their physical products and solutions was unique and could offer significant value and competitive advantages if they made it available on a digital platform as a service. Our mission was accomplished.

Today an enterprise’s system for collecting, analyzing, reporting and sharing data is mission critical, especially given the increasing importance of artificial intelligence, robotic process automation and machine learning to companies’ future success. The end-to-end system for managing this data we call the “optimized information logistics systems” or by its acronym, OILS. Having effective OILS is mandatory in order to become a digitally transformed enterprise (DTE). Digitally transformed enterprises place a premium on data collecting, analysis, situational awareness and real-time action and reaction. Executives see the value in OILS, as 63% believe analytics will have a very strong impact on work by 2020, and 62% predict OILS will significantly enhance decision-making over the next 5 years.

DTEs see where their resources are located, where they are needed and how best to manage them at all times to successfully and efficiently accomplish their mission. They see how customers are using their products and how they are holding up. Real-time connectivity combined with OILS enables organizations to think, act and compete in real-time, a capability never before possible. It enables products in the field to be intimately tied to R&D and the manufacturing floor. It is a whole new world, which in spite of profits today, must be anticipated and invested in for tomorrow, or the profits of today might lead to the death of them tomorrow.

Authors: Tim Hillison, Senior Director, Cognizant Digital Works, and Kevin Benedict, Senior Analyst, Cognizant's Center for the Future of Work

*Source The Work Ahead, 2016, Cognizant Center for the Future of Work

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

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In Defense of the Human Experience in Digital Transformation

Discussing Digital Strategies in Lisbon, PT

Last week, I was a keynote speaker at the Mobile Edge '16 conference in Lisbon, Portugal. Following the conference I met individually with many different companies. These companies represented a variety of industries, sizes and digital maturity levels. I was sharing my latest digital strategy report findings, and then answering questions and brainstorming about what the data meant to each of them.

At the hotel, following a long day of meetings, it occurred to me that the biggest value I was bringing to these businesses was the breadth of my experience - the kind of experience that has turned my hair gray.

The report I was sharing was titled, “40-Months of Hyper-Digital Transformation.” This report was the result of surveying 2,000 global executives across 18 countries on the current impact of digital technologies on their business, and their expectations for future impact. In this report I wrote a lot about artificial intelligence and software robots. I wrote about how robotic process automation will change the role of processes, employees and managers.

While pondering my day over a hot drink, it occurred to me that the report and the data I shared could have been presented by a junior employee with good communication skills. The value my gray hair brought to the table was the ability to understand the back-story, the history, how today is different, and analyze what needs to be done today to prepare for tomorrow. It was perspective, experience and wisdom gained from many years of accumulated successes and failures. It was my human baggage that was so valuable. It allowed me to listen to many disparate situations and challenges, understand them, and then see a unique path to success for each. It allowed me to see their challenges in abstraction and define steps to follow. I chuckled and sipped my coffee. Just try to do that, I challenged all the bots and artificial intelligence engines I had been writing and speaking about. Just try to do that.

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

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Join the Linkedin Group Strategic Enterprise Mobility

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Competing in Future Time and Digital Transformation

Digital Transformation is the process of transforming a business from one state to another - from a state where businesses operate in Human time, to a state that operates in Digital time and finally to Future time. Businesses today must digitally transform in order to compete in all three of these time continuums simultaneously.

Let’s first identify these different time continuums:

Human time – time governed by our physical, biological and mental limitations as humans
Digital time – time governed by computing, networking and data transmission speeds
Future time – time governed by predictive analytics, algorithms and artificial intelligence

Human time cannot compete with Digital time in a mobile and always connected world. Human time cannot deliver the real-time mobile and online commerce speeds that digital consumers require. For example, you can’t have a human responding to mobile search queries, or mobile payments, rather you need optimized information logistics systems (OILS) that are integrated with artificial intelligence (AI) enabled bots responding automatically in digital time.

Digital time refers to the speeds at which computer systems and networks operate. The goal being to reach speeds as close to real-time as possible by optimizing each connected system, component and process that touch data.

Future time is faster than real-time. It is the ability to anticipate needs, take actions and deliver content even before it is requested. It is the ability to automatically prepare for the future in a manner that adds value.

An OILS running in Future time, utilizes predictive analytics, algorithms and AI to provide an experience that anticipates the needs of the user in a manner that makes it nearly invisible to the user. For example turn-by-turn navigation supported by real-time traffic updates that route you around obstacles and problem areas. An OILS, running in Future time, can prepare personalized and contextually relevant experiences in advance.

I had the opportunity to work with a large global automotive system manufacturer this year. We explored extending traditional automotive systems to operate in Future time. They would integrate multiple external databases including traffic accident and insurance information, plus real-time weather and traffic information to automatically prepare the vehicle and driver for the road ahead. We were reaching into the future to provide additional value and a competitive advantage.

Future time delivers value from the future. It works in a time beyond “real-time.” This is the evolutionary nirvana for human to digital interactions. Businesses that have not digitally transformed in a manner that can harvest value from the future have no possibility of competing there.

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

Digital Hope and Redemption in the Digital Age

“You have a memory like an elephant,” is truly a compliment. Researchers document all kinds of remarkable examples of the recall power of elephants, and this is credited with their ability to survive harsh environments as noted in this Scientific American article http://www.scientificamerican.com/article/elephants-never-forget/.

Our human memory also helps us learn from past experiences and mistakes, avoid recognizable hazards and keep track of our very busy lives. Our memories for the most part have served us well, but the same might not always be said about digital memory in an always connected, real-time world.

One of the most valuable concepts known to man is hope. Hope is the belief that things can change and get better. It is the belief that one can turn the page and start a new life. It is the motivation that draws many to get out of bed each morning, recover from past mistakes, and go to work.

Bankruptcy laws were designed, in part, to give hope. The Supreme Court in 1934 describes it this way, “It gives to the honest but unfortunate debtor…a new opportunity in life and a clear field for future effort, unhampered by the pressure and discouragement of preexisting debt.” It gives debtors hope for a better future. Source: http://www.uscourts.gov/services-forms/bankruptcy/bankruptcy-basics/process-bankruptcy-basics

Today our second brains, the digital memory banks in the cloud controlled by programmed algorithms, don’t forget. Algorithms are programmed not to forget our histories, our bankruptcies, our youthful indiscretions, our convictions, DUIs, our vices, our former lives. They make it difficult to forget, transform into a better version and start fresh.

The more our lives, through digital interactions, are driven by and influenced by digital algorithms and second brains, the more important it becomes to consider the issue of digital forgiveness, digital redemption and digital hope. Hope that in the physical and digital world, you have the opportunity to start fresh, and change your life for the better, unencumbered by your plethora of mistakes, digitally remembered, biasing the future. Few of us, with the exception of Uncle Rico in Napoleon Dynamite, are the same person we were in our youth.

I can think of many scenarios where a person may want to change his/her life and leave the past behind, but algorithms and second brains won’t let them, unless somebody programs them to forget. If they are not programmed to forget, our digital interactions with websites, businesses, governments, police, search engines and match-making sites will hang-on to our past and use it to judge our present and future. Where is digital forgiveness in the digital era? Where is the ability to hope for a different and better life free from our past if algorithms are programmed to always reference, remember and judge based on our past?

Just because something is technically possible, does not automatically make it good or worthy. We as humans must define how we want digital technologies to support the world and society we desire. The Supreme Court in 1934 thought it was good and worthy to forgive and forget, to give people the “right to be forgotten,” in order to let a person start fresh. I believe it is time to let people be digitally redeemed in a similar manner.

The “right to be forgotten” concept has now been made into law in the EU, and variations of it have been implemented in other regions around the world. It was motivated by the desire for people to "determine the development of their own life in an autonomous way, without being perpetually or periodically stigmatized as a consequence of a specific action performed in the past.” Read more herehttps://en.wikipedia.org/wiki/Right_to_be_forgotten.

In Germany they have implemented a law titled the Federal Data Protection Act, or Bundesdatenschutzgesetz (BDSG). The law is designed to protect individuals' personal rights from being injured through the handling or mishandling of their personal information.

I believe the “right to be forgotten” is an important consideration and discussions. In a digital world fueled by data, capitalism is not a sufficient safeguard for our personal privacy and future. We must imagine the world as we want it, and make it so as a society.

Hope is a critically important concept to humanity, and it must not be allowed to be stamped out by unbridled digital algorithms and second brains. We must all recognize, in a digital age – that hope matters.

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

Kevin Benedict Ponders the Future

The Day Big Data Analytics Died

Merging Humans with Enterprise AI and Machine Learning Systems

Mobile Expert Interviews: PowWow Mobile's CEO Kia Behnia

Profits that Kill in the Age of Digital Transformation

In Defense of the Human Experience in Digital Transformation

Competing in Future Time and Digital Transformation

Digital Hope and Redemption in the Digital Age

Interviews with Kevin Benedict

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