Sustaining industry averages and benchmarks are the antithesis of innovation and a great way to ensure average performance. Doing whatever everyone else is doing is a “paving the cow path" management mentality, lacking aspirational goals which are critical for organizations to fuel innovation and create customer and market differentiation. Which brings me to why I teach.

As my students and I work through their “Thinking Like a Data Scientist” exercises together, I always learn…

“If you buy a Tesla today, I believe you're buying an appreciating asset, not a depreciating asset.” – Elon Musk

Think about that statement for a second…you’re buying an appreciating asset, not a depreciating asset. And what is driving the appreciation of that asset?  It’s likely courtesy of Tesla’s FSD (Full Self-Driving) Deep…

There, I said it.  I said the “R” word.  And no, I’m not talking the political “R” word.  I’m talking about the potential of a… r-e-c-e-s-s-i-o-n.  There are many indicators pointing to the potential of a worldwide recession, and unfortunately during a recession, many organizations hunker down, cut spending, and try to ride it out – all the wrong things to do if you want to actually avoid a recession.…

One of the biggest threats to our world economy (outside of climate change, social inequality, unregulated proliferation of weapons and the rise of Terminators), is the retirement of the technician and engineering expertise that is necessary to keep our factories, hospitals, cities, trains, airports and other operational entities running effectively.  Deloitte’s 2018 skills gap in manufacturing study found that the skills gap may leave an estimated 2.4 million positions unfilled…

I continue to be infatuated with the potential of autonomous entities that self-monitor, self-diagnose, self-fix and self-learn without human intervention.  The vision of leveraging new digital technologies, growing reams of customer, product and operational data, and advanced analytics to create autonomous entities – farms, oil fields, factories, airports, theme parks, vehicles, ships, trains, etc. – seems like science fiction. 

Fortunately, the “3 Horizons of…

In the early 2000’s, IBM Deep Blue was on the lookout for its next Grand Challenge.  It had achieved an exhilarating win over chess grand master Garry Kasparov in 1997.  But that was a game with deterministic outcomes where superior processing power gave Deep Blue a significant advantage over even a human grand champion.  IBM needed a challenge commiserate with its Artificial Intelligence aspirations, and the wildly popular TV game show…

There seem to be countless articles projecting the incredible economic and social growth that will be driven by AI.  For example, PwC predicts that AI technologies and applications will increase global GDP by up to 14% between now and 2030 (see Figure 1).

Figure 1:…

As Kevin Lynch, CTO of The Information Lab in Dublin, was describing how his organization uses the Hypothesis Development Canvas, it occurred to me that Kevin was actually using the canvas to tell a story about how his organization uses data science to uncover new sources of value (see Figure 1).…

We live in a world driven by insights and decision making fueled by data and analytics. Information and technologies are so ubiquitous that no organization needs to be a digital titan (such as Amazon or Google) to compete in today’s world of business. Companies, large and small, are recognizing the need to utilize the full value of their…

Leverage AI to Create Autonomous Policies that Adapts without Human Intervention

Policies are the foundation for any successful organization.  Policies are the rules, or laws, of an organization.  Policies document the principles, best practices and compliance guidelines that aid decision-making in supporting the consistent and repeatable operations of the business. Heck, one could argue that an organization’s culture is better defined by its policies than it…

“It is hard to teach an old dog new tricks.  They’ve only been in business for 155 years.”

 – Anonymous

The Pullman Co (1867), Allied Corp (1920), Heinz (1869), Hughes Tool (1908), Ford Aerospace (1956), Motorola (1928), Bethlehem Steel (1857), Ralston Purina (1894), Compaq (1982), E.F. Hutton (1904), PaineWebber (1880), MCI (1983), Eastern Airlines (1926) and Pan Am Airlines (1927), Houston Natural Gas / Enron (1940), Arthur Andersen (1913),…

They say that the best ideas sometimes come to you while you are in the shower, and this idea of how to explain two important Neural Network concepts – Backpropagation and Stochastic Gradient Descent – actually did come to me as I was trying to set the perfect water temperature for my morning shower.

As I was struggling to adjust the two shower handles – one handle that controlled scolding hot and the other handle that controlled flash freezing – it occurred to me that I was a simple…

I hate it when I hear senior executives state that they want to become data-driven, as if somehow having data is value in of itself.  Now, one can hardly blame the unenlightened executive whose only perspectives on data are associated with statements like “Data is really the new oil” (Wall Street Journal) or “…

I grew up in a small manufacturing town in Northeast Iowa.  The factory in my hometown made tractors (no surprise given that it was Iowa), but eventually the economics of cheap foreign labor and an interconnected global economy caught up with that factory – as it did with many US-based manufacturers – and soon the factory closed, and many people were laid off.

But the technology world continues to evolve – especially with respect to IoT, Data Science and AI/ML – and so…

There is a phrase in baseball about pitchers “pitching through pain” that refers to pitchers taking the mound to pitch even though they have aches and pains – sore arms, stiff joints, blisters, strained muscles, etc. The idea is that these pitchers are so tough that they can pitch effectively even though they are not quite physically right. 

However, when the human system is asked to do…

This is the next blog in my random series on better understanding some of these advanced Artificial Intelligence and Deep Learning algorithms. This “episode” takes on Generative Adversarial Networks (GANs). Hope you enjoy my “Deep Learning” learning journey.

I originally wrote in “Transforming from Autonomous to Smart: Reinforcement Learning Basics” how…

Please join me in Las Vegas at Hitachi Vantara’s NEXT 2019 in October where I’ll be…

Imagine an advanced fighter aircraft is patrolling a hostile conflict area and a bogie suddenly appears on radar accelerating aggressively at them. The pilot, with the assistance of an Artificial Intelligence co-pilot, has a fraction of a second to decide what action to take – ignore, avoid, flee, bluff, or attack.  The costs associated with False Positive and False Negative are substantial – a wrong decision that could potentially provoke a war or lead to the death…

At first glance, data science and customer experience (CX) don’t have much in common.

Data scientists like me are typical left-brained thinkers: detail-oriented, logical and quantitative. We want to study, process and analyze data to extract insights from it. Customer experience experts, on the other hand, gravitate toward a more intuitive and creative…

What if you had a corporate asset that was never used?  Your first response might be that corporate asset obviously has no value.  And you’d probably be right. However, there are costs – acquisition costs, maintenance costs, storage costs, depreciation costs, salvage costs – associated with all assets. So, to incur all of those costs and then not do anything with that asset would be fiduciary negligence at its worse. 

Welcome to the world of dark…