Yelling analytics in a crowded theater


The USS Manley, ADP-1 (DD-74). My father-in-law, Aaron Cruise, served on this converted "four-stacker" destroyer in the Pacific theater

“To everything there is a season.” The last time I heard these words from Ecclesiastes was in the context of my late father-in-law’s WWII Navy veterans group, which had to shut down its activities in 2010 as its last surviving members began to join their shipmates lost during the war itself.  Nothing quite so dramatic for me, but the Value Alley has now enjoyed six of those seasons and the time has come for it, and me, to move on.

As I mentioned last time, I’m not going far – more like changing the channel than changing my address. For the foreseeable future I’ll be found over at SAS Voices, cranking out just as many marvelous meditations, inspirational insights and brilliant baloney as before  (My first post is already up: "Lifelong learning and analytics").

When asked why I chose to pursue this blogging endeavor, I answer with two reasons. The first was to use the blog as a safe place to try out new ideas and get comments and feedback, before committing them to more permanent status such as in a white paper or customer presentation.  A place I could make mistakes and learn from them. As I tell my colleagues considering getting into the blogging business, “It’s just a blog!”

And I have learned. A lot.  From many.  I thank you all.  I look back at some of my early stuff and just cringe, wishing I could delete it permanently, unfortunately not something the Internet permits.  More often, though, my opinions and approaches have evolved incrementally.  In fact, if over the course of six years they hadn’t, then something’s seriously wrong with my ego and my ability to adapt and grow.

burning man3The second and primary purpose of the blog, was, as today’s title says, to “yell analytics in a crowded theater”.  Six years ago both myself and the market were still waking up to analytics.  Data hadn’t gotten all that big yet, and the IoT was still mostly just the “I” part.  My primary audience was the Office of Finance, where building a spreadsheet qualified as doing analytics.  The business ops side was a bit more advanced, but as I was to discover, certain no-brainers like inventory and logistics optimization were still not mainstream.  The Value Alley was designed to build analytic awareness - and in my case, simultaneously emphasize the value.

How quickly things change. Lately, when I chair a conference, attend a trade show or speak with prospects, I’ve noticed that the question asked has shifted dramatically from, “What can analytics do for me?”, to “How do I get started?”  BI and analytics implementations are now the number three priority for CIOs, behind only cybersecurity and ERP.

There’s no need to yell any longer - the theater has cleared out. But they’ve not gone home, they’ve gone to work - to work on analytics.

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The Year of Ambiguity

I typically start off each new year with a more personal blog topic, something that’s occupied my thoughts over the holidays, but this year I instead opened with a couple of NASA-themed posts. This turned out to be fortunate in that it now allows me to get somewhat personal on this, my penultimate blog post for the Value Alley.  We’ll be retiring the Value Alley after my final, closing post next week, and I’ll be moving my analytical musings over to SAS Voices, our thought leadership focal point, where I'll join the rest of our talented staff addressing a broader analytics conversation to a wider audience. But until then, Leo still has a few remaining things on his mind.

keep rightThe title for this post comes from my oldest, Garik, who midway through his college experience decided that he wasn’t getting what he wanted and needed from the standard curriculum. He not only took it upon himself to call “time out” and rework his final two years, but he also decided to share his insights with his fellow students in a one-credit course he developed and taught, based somewhat on this TEDx talk he gave at NC State: “How LSD changed my life – Students taking responsibility for their own education”; “LSD” in this case standing for Life Style Design, the formal name of his course.

One of the class exercises consisted of reimagining the typical K-12 program, with a focus on “teaching to the problem rather than to the tool”, Read More »

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Neural networks demystified

You’ve likely heard the news that the Google DeepMind “AlphaGo” computer not only beat a human expert at the game of Go, defeating the European Go champion, Fan Hui in five straight games, but also beat the reigning world champion grandmaster, South Korea’s Lee Sedol, 4 games to 1.

Go is considered to be a significantly more difficult game for a computer to tackle than chess, if only because of the vastly greater number of possible moves over a much larger playing field. Chess has on the order of 1040 possible legal and realistic positions in a 40-move game; Go can have up to 10360, give or take a few tens of orders of magnitude (as a point of reference, there are approximately 1080 particles in the visible universe).

When Deep Blue beat world chess champion Gary Kasparov back in 1997, it did it with a brute force approach – a massively parallel computer that would typically search to a depth of between six and eight moves, and up to a maximum of about twenty moves in some situations. It was an Expert System (not AI), with separate programing modules/libraries for openings, end games, and middle game strategy and tactic evaluation. All the legal moves and rules had to be programmed into it, and it could not learn as it went (although its programmers made adjustments after each game).

AlphaGo, however, is a true AI machine, Read More »

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CyberCrime – What monsters are hiding under your bed?

Do you like a good horror story? Then may I suggest “Future Crimes” by Marc Goodman.  When it comes to this genre, Wes Craven, John Carpenter and Stephen King have got nothing on Goodman, primarily because Goodman’s story is non-fiction.

Scene 1: The present – Your workstation or data center

Whether it’s your personal or corporate data that’s at risk, the magnitude of that risk is far greater than the uninitiated are currently aware. We’ll skip right over the now mundane cyber threats of zero-day exploits, ransomware and spoofing, and get right to a few of the more vile and contemptable approaches currently on the crime market:

  • cyber cartoon“Girls Around Me”: a downloadable app that uses geolocation data from mobile devices and social apps – a favorite of stalkers.
  • “SpyEye”: A man-in-the-middle screen spoof that not only captures all your log-in credentials and drains your bank account, but records exactly how much was taken and adds that amount back into your fake current balance before presenting it to you, so as to buy enough time to clear the settlement period.
  • Mobile POS scanners, like the one carried by this guy on public transit, which, when pressed close to your wallet, will automatically charge your contactless debit card.
  • GPS signal spoofing that can redirect an 18-wheeler to the wrong warehouse or a cargo ship to the wrong berth, where the bad guys are ready and waiting to unload it.

Scene 2: The future – Rising action and danger

Cybercrime is a big business, run by professional looking organizations Read More »

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Artificial Intelligence: The Good, The Bad, and The Ugly

When the likes of Elon Musk and Stephen Hawking go on record warning about the dangers of AI, it’s probably prudent to take notice. However, before rushing off into full panic mode, some definitions and perspective would be in order.

Artificial_intelligenceThe type of artificial intelligence Musk and Hawking are referring to is known as Strong AI, or AGI (Artificial General Intelligence). This is the level at which a machine could readily pass itself off as indistinguishable from a human in cognitive, perceptual, learning, manipulative, planning, communication and creative functions - a thinking machine that can pass the Turing Test.  We’ll close with some perspectives on Strong AI, but first let’s take a look at Weak AI, also known as Applied AI or Enhanced Intelligence (EI). Read More »

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Houston, We have a solution: Data Virtualization

Like most boys my age at that time, I wanted to be an astronaut. Fate, however, intervened, in the form of nearsightedness, so I had to find an alternative occupation.  Coming to my rescue for the launch of Apollo 11 was my father, who presented me with a huge booklet that broke down the entire mission into each of its key components in great detail.  I had my answer – I was going to be a flight controller, and maybe even one day a flight director like Gene Kranz.  I had the entire Saturn V launch sequence memorized from the transfer to internal power at the T-minus fifteen minute mark down to liftoff, and would impress my father by beating the public affairs announcer to the punch by announcing, “initiating automatic sequence in 5, 4, 3 …”

ISS Mission Control, courtesy of NASA

ISS Mission Control, courtesy of NASA

A fascinating book came out last year called, “Go, Flight!: The Unsung Heroes of Mission Control".  In the process of telling the personal stories, recounting the heroic events, and describing the various roles in the mission control center (MCC), one recurring theme caught my attention – that of the communications (comms) loop.

The three primary roles in the MCC are: Read More »

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Objectives that drive strategy - A lesson in strategic planning from NASA and the Kennedy Space Center

Discussing strategy, and what we mean by it, can be a confusing and sometimes unproductive undertaking. Considering its different uses as a noun and an adjective, defining our terms is a good place to start:

  • Strategic thinking: Characterizing the environment, identifying and assessing risks, and developing and evaluating options.
  • Strategic goals: High level goals immediately derived from the organization’s vision and mission.
  • Strategy: The general approach to how a specific goal / objective is achieved, with consideration given to core values, vision and mission, boundaries and limits to action, and options.
  • Tactics: The specific actions taken to achieve the objective.
  • Strategic plan: The aggregate of the organization’s vision, mission, goals, objectives and strategies.
  • Vision: A roadmap to a projected future, what the organization wants to become.
  • Mission: What the organization does, its purpose, and its core competencies.

With this as a starting point, I’d like to relate the key points of a remarkable presentation that contributed greatly to the clarification and simplification of our conception of the strategic planning process. Read More »

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Automating bad decisions and the Ladder of Inference

There’s more than one way to make a poor decision.  Bad data, inappropriate assumptions and flawed logic are just three of the missteps you can take on your climb up the Ladder of Inference, a concept first developed by Chris Argyris, professor of business at Harvard, in 1974, and later popularized by Peter Senge in his 1990 book, “The Fifth Discipline”.  If we’re not mindful of these mental pitfalls, we’re likely to use our automated business processes to simply make bad decisions faster.

The Ladder of Inference, an oldie-but-goody, is likely familiar to you, although you may not have run across it in some time.  A quick summary of the ladder’s seven rungs would be (starting at the bottom):

  1. Ladder-of-inferenceObservation: The world of observable data and experience
  2. Filtering: The selection of a subset of this data for further processing
  3. Meaning: Assigning meaning / interpretation to the data, through semantics or culture
  4. Assumptions: Associated context, often from your Framework (below), of what you already know and the new meanings you’ve assigned
  5. Conclusions: Drawn based on the assumptions and meaning applied to the filtered data
  6. Framework: You alter, adjust or adapt your belief system / knowledge framework based on your conclusions
  7. Action: You take action based on the meaning of the data and your updated belief system


A simple example of the ladder in action might be: Read More »

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Tell me something I don’t know

What is information? The lack of a working definition plagued both science and the emerging telecommunications industry until the arrival of Claude Shannon and his famous 1948 paper, “A Mathematical Theory of Communication”, based on his cryptography work during WWII while at Bell Labs.  The landmark article is considered the founding work of the field of information theory, and would augment Shannon’s earlier groundbreaking research at MIT into the design of digital circuits and digital computers.

geo - CopyShannon interpreted his formal definition, H = -∑ pi log (pi), in a number of counterintuitive ways:

  • As a measure of entropy (the formula exactly mirrors Boltzmann’s definition of thermodynamic entropy)
  • As the resolution of uncertainty
  • As a measure of surprise

While that first definition has captured the attention of the likes of physicist Stephen Hawking and has implications for cosmology, black holes and a holographic universe, it’s the latter two that are of interest to us for the moment. Read More »

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How steep is your learning curve? On Analytics and Mentors ...

Having a mentor is the number one factor in increasing the steepness of your personal learning curve. So says my oldest, Garik, a Park Scholar at North Carolina State University (class of 2012), during a discussion he recently had with the incoming Park Scholar class of 2019.

learning-curveTo accept the value of mentoring first requires one to understand the centrality and importance of the learning curve. Garik asked the students to imagine plotting the characteristics of two people on a simple X-Y axis.  Person A comes to the game with only a moderate amount of resources at their disposal, but importantly, also a relatively steep learning curve, such that a plot of their capabilities has them crossing the Y-axis at an intercept of 1 and with a slope of one-half.  Person B, in contrast, has much greater resources at their current disposal:  time, talent, smarts, money, education, experience, etc …, but for whatever reason, has a shallower learning curve, such that their plot on the graph intercepts higher up the Y-axis at 2 but with a shallower slope of only one-quarter.

Unless you think you’re going to die before the two lines cross, you’d of course be better off as Person A. Based on his domestic and international experiences as an undergrad and grad student, as a researcher and an employee, and as part of two start-ups (so far), Garik’s conclusion is that, while there are several factors impacting the steepness of that learning curve, none is more important than that of having chosen good mentors.

Businesses can be said to have learning curves as well, and my discussion with my son got me to thinking about what factors would have the greatest bearing on organizational learning curve steepness. Read More »

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  • About this blog

    There are two sides to the Value equation: value creation and value extraction, and analytics has a role to play in both. Leo Sadovy, a former Vice President with 25+ years of strategy, finance and marketing experience at Fortune 50 companies, takes a bi-weekly trip down Value Alley to explore some of the innovation and operational insights that analytics can provide, from forecasting to segmentation to data visualization. The common currency of our digital economy is data, but it takes analytics to turn that data into information, into insights, and into value, both for your customers and for your stakeholders.
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