Kevin Benedict Ponders the Future: IoT

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Sensors and AI in the Kingdom of Robots

Fingerspitzengefühl: Is a German word used to describe an ability to maintain attention to detail in an ever-changing operational and tactical environment by maintaining real-time situational awareness. The term is synonymous with the English expression of "keeping one's finger on the pulse". The problem with traditional fingerspitzengefühl, in addition to pronouncing it - is it is hard to scale. Today, however, in a world of sensors, GPS and mobile devices, having real-time situational awareness is far easier than ever before. In fact, today the challenge is not how to do it (answer: sensors), but what to do with all the information.

There are many dimensions of data that are available for work outside the four walls, which is mobile, remote and dynamic. We all know about 3 dimensional (longitude, latitude and altitude), but there are many more. We contrive:

Time
Start and stop tasks times
Travel times
Traffic conditions
Available workforces and associated costs
Available equipment
Activities
Events
Business process steps
Expenses
Security steps
Transactions
Compliance tasks
Performances against KPIs (key performance indicators)
Actors (customers, partners, suppliers, contractors, employees, etc.)
Relationships
Contract/Agreements
Supplies, materials and equipment tracking
Etc.

All of these data points can be bundled together as Performance Impact Variables (PIVs). PIVs are the data points that can be used as inputs to algorithms that can be used by AI systems to optimize and manage the performance of the business in real-time.

All of this data can be used as overlays to simple GPS coordinates on a map. Each of these additional layers of information exponentially increases the complexity, decision-making options and possible combinations. This enormous volume of data quickly overwhelms humans. That is why non-humans (AI/software robots) can be used to such great effect to maintain productive situational awareness and strategic advantages in complex environments demanding real-time decision-making and action.

During the period between WWI and WWII, Western countries all developed new tanks and military aircraft to support their infantry. The Germans, however, went three steps farther by developing strategic advantages in:

Radios and frequencies for communicating between forces (tanks, infantry and aircraft) in real-time
Strategies for coordinated actions between the three groups
Mission oriented command structures – Commanders define the mission “intent”, but the details of how to accomplish them were left to frontline officers.

In today’s world, companies seeking strategic advantages in field services operations can learn from these three additions.

The modern equivalent of “radios and communication networks” is OILS (optimized information logistics systems) that sense, collect, securely and wirelessly transmit data, analyze and report on it, and support artificial intelligence (AI) and automation.

The modern equivalent of “strategies for coordinated action” is the ability to collect and analyze vast quantities of real-time data to automatically and dynamically manage and adjust (using AI and software robots) a whole series of activities and events such as: schedules, tasks, jobs, orders, transactions, etc.

The modern equivalent of “mission oriented command structures” is an algorithm. Once the algorithm is developed, it can operate without human intervention.

When massive amounts of real-time data are automatically collected and analyzed, they can feed algorithms and AI systems to optimize real-time activities and events. The speed at which data can be processed through OILS and AI systems today far exceeds human decision-making capabilities – so automation that works in digital-time is required. This is where AI excels. AI can analyze all the inbound data in nanoseconds and instantly adjust and optimize operations.

AI does not just impact field services. It impacts many business processes by supporting:

New ways of selling
New business models
New ways of managing
New business processes
New ways of collaborating
New ways of making decisions
New ways of engaging customers
New ways of working with products
New marketing and growth strategies

My mantra is, "Digital technologies without digital strategies are wasted." Having digital technologies without a digital strategy is like having tanks, mobile infantry and aircraft, but no coherent plan for combined action. In a recent report, 40 Months of Hyper-Digital Transformation, digital laggards were found not to receive as good of return on investments (ROIs) on their digital investments as digital leaders do. The difference I believe is in their digital strategies, or lack thereof.

In the book, Stray Voltage, War in the Information Age, author Wayne Michael Hall defines two more PIVs - cyberspace and cerebral. "Information superiority is firmly connected to making decisions that are superior to an adversary's and combines information technology and intellectual power to create conditions with which to make better decisions…human beings will need to improve their thinking capabilities to cope with the increasing complexities of the world...people will depend more on visualization to help understand complexity quickly. Visualization will fuse data and information and display the result in a multimedia format. Visualization will allow the integration of data, information and knowledge from all sources and will allow for the integration of numerous contributors." Visualization, although helpful to humans, is far less relevant once algorithm-consuming AI systems take over.

Sensors, already powerful, are being developed with more capabilities to sense more things every month. Each year when I attend GSMA’s Mobile World Congress in Barcelona, I am astonished to see what additional capabilities sensors have added. Here are some examples:

Sensors able to identify and classify vegetation - natural and artificial
Sensors able to identify and pinpoint distressed crops
Sensors that can identify soil moisture content
Sensors that can detect heat sources and leaks
Sensors that can detect movements and changes in defined objects
Sensors that can detect the chemical make-up of make-up

Each of these sensors and their real-time data collection capabilities adds to decision-making complexity, but they can also be the very PIVs that give you the competitive advantage you need to win.

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

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Kevin Benedict

Senior Analyst, Center for the Future of Work, Cognizant

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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.

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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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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Join the Linkedin Group Strategic Enterprise Mobility

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Business is Not as Usual in the Age of Digital Transformation

Digital transformation typically begins as low cost POCs (proof of concepts), that evolve into mission critical corporate initiatives as positive results, consumer demands and market trends converge. Digital transformation becomes mission critical when consumers vote with their money to accept the digital replacements for physical products, services and processes.

Last month a regional retail book and entertainment chain, Hastings, filed for bankruptcy. CFO Duane Huesers blamed “a decline in the market for “physical media properties” like music, movies, books, games and media rentals.” Hastings joins chains like Blockbuster, Borders Group and Tower Records that went out of business as a result of not making the transition to digital fast enough. The strange part of this story is that Hastings never changed. Faced with overwhelming evidence, market trend data and their own sales data that showed consumers were moving to Netflix, Amazon and streaming music, they simply could not take the steps to change.

Enterprises must wake-up and transform themselves. They must jettison the heavy baggage that comes as a result of decades of institutionalized practices and methodologies developed and codified in an analog era - an era operating at a far slower operational tempo designed around the movement of physical objects. The good news is when enterprises choose to digitally transform, the ROIs (return on investments) are typically compelling. Nearly 30% of the firms we recenlty surveyed reported an ROI greater than 100%.

Where do enterprises start with digital transformation? Modern western militaries have been engaged in digital transformation for several decades now and we can learn a lot from their experiences. Their efforts involved rethinking strategies, tactics, doctrines and changing budget priorities, organizational structures, technologies and more. They recognized the need to change and become faster, agile, efficient and precise by embracing digital to succeed in their missions. They replaced mass with precision, and a reliance on physical (paper), with connected digital (mobile devices) equipment.

In the world of real-time precision introduced by mobile devices, IoT and sensors, data takes on a whole new level of importance. In fact, executives in our survey believe big data and business analytics will have the biggest business impact of all technologies on businesses from years 2020-2025. The winners in digital transformation will commit to developing in seven key areas at a pace sufficent to provide competitive advantages:

Becoming a data-centered business
Developing and implementing an OILS (optimized information logistics systems)
Achieving real-time business operational tempos
Implementing intelligent process automation using artificial intelligence and machine learning
Ensuring a shared situational awareness through the use of collaboration platforms
Utilizing real-time contextually relevant data to personalize digital experiences
Redesigning and re-architecting to become a digitally agile business

Mobile networks and devices are now ubiquitous in most regions of the world. Low costs mobile phones and service plans proliferate, and these are changing banking, commerce and global communications. They are even shaping global economies and politics. All of these activities are generating massive volumes of new data. Information is now available to people anywhere, and at anytime as long as they have connectivity to the Internet. Information can be searched for, saved in our second brains in the form of cloud storage, and monitored by our third eye, a digital eye that provides perception beyond ordinary sight in the form of alerts, news updates, notifications, tweets, messages etc., 24 hours a day. There is no such thing as business as usual in the age of digital transformation.

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

The Impact of Digital Transformation

Digital transformation is a revenue growth engine according to fifty futurists we surveyed. Many companies are already experiencing significant benefits and gaining competitive advantages. The futurists predicted the top five impacts of digital transformation on businesses by the year 2020 will be:

Speed to market
Competitive positioning
Revenue growth
Productivity
New distribution channels

Given the importance of these top-five on revenue growth and the future success of a business, who would not want to digitally transform their enterprise? Non-believers that's who. Non-believers, aka laggards, in our study of 2,000 executives don't believe in significant digital transformation now, or in the future. They don't demonstrate a sense of urgency or a recognition of the massive changes happening around them today. They seem blind to the fact companies are witnessing an increase in revenue already from their digital transformation investments.

Digital transformation-believers aka digital leaders, however, are investing significantly more now, and receiving positive ROIs on their investments already. As a result, they plan to invest greater amounts in the future, and predict higher ROIs in the future relative to non-believers.

Based on our survey data, believers and non-believers are seeing alternative realities. Non-believers, if they don't quickly become converts, are going to face increasing challenges staying competitive and relevant against digitally transformed competitors.

When we asked mid-level managers to list the top 10 mistakes companies are making regarding digital transformation today, they listed the following in order of rank:

Moving too slowly
Lack of clear digital strategy
Company has the wrong leadership for digital transformation
Investing too little in new technology
Not focusing enough on cyber-security
Culture that discourages innovation
Lack organizational structures to drive digital transformation
Ignoring fresh thinking from external sources
Not educating the entire organization on digital transformation
Neglecting to hire the right digital talent

This list describes the actions or non-actions we are seeing from non-believing companies.

Let's pull all our findings together and review once again:

Futurists see digital transformation as a revenue growth engine
Believers are already reporting positive ROIs, and as a result, plan even higher levels of investment and revenues in the future.
Non-believers are investing little today, seeing little ROI, and are planning relatively little investment in digital transformation in the future.
Mid-level managers report the biggest challenges are moving too slowly, a lack of a clear strategy, wrong leadership and too little investment in new technologies.
The revenue gap between what believers and non-believers predict in the future as a result of digital transformation is significant across all industries. Survey participants believe the bulk of the revenue gains will be achieved by the year 2020, with incremental gains continuing thereafter. That is only 3.5 years from now. Yikes! That reflects a view that more revenue is available now for fast movers. It also suggests a realization that a lot of work needs done quickly. Non-believers, because of inaction and/or a lack of investment, seem likely to miss out on these early revenue gains and will suffer competitively.

Businesses must invest the time and effort now to understand the impact of digital transformation on their industry, market and company. Once there is situational awareness achieved and a clear vision articulated, a digital transformation doctrine needs to be developed and socialized so strategies can be developed to achieve the vision set forth in the doctrine. What technologies should believers invest in over the next 3.5 years to achieve digital transformation? In the opinions of over 2,000 survey participants the largest business impacts will come from the following technologies:

Big data/business analytics
Cyber-security
Cloud
Collaboration technologies
Mobile technologies
IoT/sensors
Artificial intelligence
Digital currency
Sharing economy
Social Media

When asked for year 2025 predictions, survey participates anticipate a similar list, but with even higher business impacts from each.

It is interesting that core systems like ERPs, CRMs, HCMs and SCMs were not identified as driving high business impact. I am wondering if companies still view digital transformation as "add-on" technology? In my view, a business' ability to convert from "human-time" to "digital-time" and operate at a real-time operational tempo requires digital transformation across the entire ILS (information logistics system). The ILS is the master or umbrella system that manages and processes data across the entire organization to optimize business performance and customer interactions. This ILS system includes all the core systems that today, often involve legacy systems incapable of supporting the new world of digital-time. It is my analysis that many companies will ultimately be required to replace legacy core systems in order to accomplish true digital transformation.

If you find yourself sitting in IT and business meetings every week listening to how existing legacy IT systems will not permit new business processes, new business services, new business models and new innovations required to compete and win, then you should recognize those are red flags and things can get ugly, quickly.

When the New Year's ball drops at midnight and year 2020 comes around, will you be found among the believers? Stay tuned for my new report on digital transformation technologies and strategies.

Read more 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

Sensors and AI in the Kingdom of Robots

The Day Big Data Analytics Died

Merging Humans with Enterprise AI and Machine Learning Systems

Business is Not as Usual in the Age of Digital Transformation

The Impact of Digital Transformation

Interviews with Kevin Benedict

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