In my previous blog “How DevOps Drives Analytics Operationalization and Monetization”, I discussed the critical and complementary role of DevOps to operationalize and monetize the analytics that came out of the Data Science development process. While the combination of Design Thinking and Data Science accelerate the creation of more effective, more…

I recently wrote a blog "Interweaving Design Thinking and Data Science to Unleash Economic Value of Data"  that discussed the power of interweaving Design Thinking and Data Science to make our analytic efforts more effective.  Our approach was validated by a recentMcKinsey article titled “Fusing data and…

Digital capabilities leverage customer, product and operational insights to digitally transform business models.  And nowhere is this more evident than the rush by industrial companies to digitally transform consumption models by transitioning from selling products to selling [capabilities]-as-a-service (thusly, Xaas).  For example:

• The key issue for the airlines is to maximize their core revenue generating mechanisms:flight scheduling and the hours…

Moo…

There is this very intriguing Enterprise Car Rental commercial on TV (I’m old school and still watch my commercials on a television) that shows a glimpse into future driving behaviors enabled by autonomous vehicles (see Figure 1).…

In many of my presentations and lectures, I have made the following declaration:

In Big Data, it isn’t the volume of data that’s interesting, it’s the granularity; it’s the ability to build detailed analytic or behavioral profiles on every human and every device that ultimately drives monetization.

Ever-larger volumes of aggregated data enable organizations to spot trends – what products are hot, what movies or TV shows are trendy, what restaurants or destinations are…

I had the great fortune to sit on an Ericsson-Wired Magazine panel with some outstanding thought leaders to debate the ramifications of the Fourth Industrial Revolution.  We debated whether the era was a revolution or just an evolution (I argued revolution because it will force organizations to think differently about their business and operational models) and whether IoT had failed so far (I said that to date it had “under-performed” from a business value…

Did you ever have a concept that you knew was right, but just couldn’t find the right words to articulate that concept?  Okay, well welcome to my nightmare.  I know that Data Science and Design Thinking share many common characteristics including the power of “might” (i.e., that “might” be a better predictor of performance), “learning through failing” (which is the only way to determine where the edges of the solution really reside), and the innovation liberation…

The Big Data craze caught fire with a provocative declaration that “Data is the New Oil”; that data will fuel the economic growth in the 21^stcentury in much the same way that oil fueled the economic growth of the 20^thcentury.  The “New Oil” analogy was a great way to contextualize the economic value of data; to give the Big Data conversation an easily recognizable face.  The Economist recently declared data “…

Describing the Data Science analytics development process has always been a struggle for me.  The corporate world is full of linear processes.  Major monolithic enterprise applications – ERP, MRP, SFA, CRM systems – have been architected to reduce operational complexity via a series of interlocking, heavily-engineered (and re-engineered) linear processes (though I suspect that anyone who has survived an SAP ERP implementation would take issue with my “reduce…

Nothing like a devastating catastrophe to bring a bit of reality into the world of IoT and data science.  The recent crashes of the new Boeing 737 Max have been attributed to a single point of failure – a sensor – in the design of the complex navigation system[1]. 

To summarize the situation:

• Boeing’s new 737 MAX included larger, more efficient engines than the previous generation and as such, the engines were…

Blog key points:

• Google open-sourced TensorFlow to gain tens of thousands of more users across hundreds (thousands) of new use cases to improve the predictive effectiveness of the platform that runs Google’s business.
• In the digital economy, the economies of learning are more powerful than the economies of scale.
• Organizations must avoid building orphaned analytics—one-off analytics developed to address a specific business need but are never “operationalized”…

Key points of this blog include:

• Digital Transformation sweeps aside traditional industry borders to create new sources of customer and operational value
• Unfortunately, Digital Transformation and “smart” initiatives are struggling, and organizations will need a more pragmatic approach to successful execution per Forrester research
• Organizations must define their “smart” initiatives from perspective of stakeholder…

I suck at the NCAA March Madness® bracket selection process.  I let my personal biases get in the way of making decisions based upon the numbers.  I over-rate the well-known Big Ten conference and under-rate the lesser-known Mid Majors and fall in love with the most recent team I saw on TV win their conference tournament.  You see, I fall prey to all the common decision-making traps – recency bias, over-confidence, anchoring, risk aversion, framing…

Key topics of this blog:

• Economies of scalehave historically given large enterprises unsurmountable market advantages through the exploitation of mass production, distribution and marketing.
• In Digital Transformation, “Economies of Learning”are more powerful than “Economies of Scale” because of the ability to learn and deploy those learnings within digital assets faster.
• Classic ERP “Big…

Why should companies care about Digital Transformation?  Yes, I know it appears as yet another technology-drunk buzzword, but what about Digital Transformation should make it EVERY organizations’ #1 strategic business initiative.  One word:  Economics. And your Digital Transformation initiative must start with understanding the fundamental differences in creating value or wealth from an accounting versus an economics…

This blog will cover the following “Future of Smart” initiative topics:

• Create a common definition or description of what it means to become “smart” and rally the organization around that definition. Confusion in definitions and terminology may be the #1 killer of organizational alignment and corporate innovation.
• Start with a customer-centric perspective by creating Customer Journey Maps to validate the points of customer, product,…

There are several technology and business forces in-play that are going to derive and drive new sources of customer, product and operational value. As a set up for this blog on the Economic Value of Data Science, let’s review some of those driving forces.

• Artificial Intelligence holds the economic potential to drastic drive industry and business model disruptions. But having AI technologies is not sufficient, especially when most AI technologies are open source and…

Professional athletes know the importance of developing opposing or complementary muscles (quadriceps and hamstrings, biceps and triceps).  These complementary muscles are sets of muscles that “work together” to move your body in the most efficient ways. If these muscles are strengthened together, it creates a balance that can lead to optimal performance.  However, if these muscles are not strengthened together, then one significantly increases the risk of…

“If” by Rudyard Kipling

If you can keep your head when all about you

     Are losing theirs and blaming it on you,  

If you can trust yourself when all men doubt you,

    But make allowance for their doubting too;  

If you can wait and not be tired by waiting,

    Or being lied about, don’t deal in lies,

Or being hated, don’t give way to…

In my most recent blog “Design Thinking Humanizes Data Science”, I discussed how Design Thinking and Data Science complement each other.  They are not just two sides of the same coin, but the same side of the same coin in their objectives to “diverge before converging” in driving business stakeholder collaboration with respect to identifying, brainstorming and…