Death By a Thousand Analytics

knives.jpgDonald Farmer, now of Qliktech, offered to the Boulder BI Brain Trust (BBBT) last week that what we in “BI” do is better described as decision

knives.jpgDonald Farmer, now of Qliktech, offered to the Boulder BI Brain Trust (BBBT) last week that what we in “BI” do is better described as decision support rather than business intelligence.  The comment was greeted by a flurry of Tweets and Grunts of agreement.  It’s an observation I’ve also made, and for similar reasons.  In essence, BI tools support decision making; to attribute intelligence–business or otherwise–to software seems somewhat presumptuous.  And yet, there is a further problem with the term business intelligence.  It implies a level of rationality in decision making that is beyond the reality most of us encounter.  This implication is carried even further as various analysts and vendors begin to talk about business analytics as if it will be the ultimate solution to all business decision-making needs.

There are facts, we are told.  And if we have all the facts and we apply comprehensive analytics, we will discover the past, understand the present and predict the future.  We are told this is the scientific method; the truth is in the numbers.  Is this a valid way of interpreting the way the world works?  I would argue that it is so far from reality that we are in danger of creating a fantasy world worthy of Tolkien.

History, it is said, is named thus because it is “his story”.  History, they say, is written by the victors.  The implications are far reaching.  Yes, there are indeed facts, but it’s the stories we weave around the facts that are what really matter.  To quote Liz Greene(1): “Mehmet the Conqueror invaded Constantinople in 1453.  That is an historical fact.  But depending on which history book we read, Mehmet was either a redeemer or a cruel tyrant, a warrior for the True Faith or a vile heretic.”  In terms of the story we tell ourselves about this incident and its value as guide for the future, which part of the quote is more relevant – the historical fact or its interpretation?  And if you haven’t yet looked at the endnote for the source of this quote, do so now.  And be brutally honest with yourself.  Do your beliefs about astrology affect the weight you attach to the quote?  And when I tell you that Dr. Liz Greene is also a fully trained and qualified Jungian psychoanalyst, how does that cause you to re-evaluate your judgement.

Our current obsession with analytics is dangerous.  It’s based a number of simplifications, misconceptions and downright errors.  It is a simplification that business is an entirely rational, fact-driven process.  It is a misconception that given sufficient data you can predict the future.  It is a downright error to assume that in the future, business can be entirely (or even largely) driven by business analytics.

Does that mean we should abandon analytics?  Of course not.  There are facts to gather that have so far remained undetected.  These facts can influence our interpretations.  If they are indeed relevant to the story at hand.  And if we allow them to do so.  And if our business users can avoid statistical errors such as confusing correspondence with causality.  There are many examples already of significant benefits to be gained for businesses who adopt analytics.

The questions of relevance and abuse of statistics are ones of good analytic practice and education of users.  I have no doubt that, as we move beyond the hype phase, these issues will be addressed.  The issue of interpretation is much more difficult to tackle.  Because it is at the heart of how we imagine our decision makers behave.  Our focus on intelligence–rational and logical–obscures two other keys aspects of decision making:  intent and intuition.  Intent we ignore and intuition we dismiss.  All decision making includes the intent of the decision maker.  That intention drives everything from what data is gathered, through how it is evaluated, all the way to the final choice of action.  How many decisions are post-justified by careful data selection and evaluation?  If a decision maker is motivated by personal gain (and they do exist, you know), won’t analytics be enlisted to support that goal?  And regarding intuition, it is evident that not all decision contexts are wholly driven by measurable or predictable metrics.  Low prices may be important, but so too are ambience, history, ethos and personal relationships when customers choose where to shop.  Data measures for the latter are hard to define and capture.  The intuition of an experienced manager is needed in such circumstances.  Target’s decision to focus marketing of maternity products to women in the early stages of pregnancy was based on sound analytics according to a story in the New York Times, but the reaction of prospective customers was intuitively obvious.

The bottom line is that we focus exclusively on big data and analytics at our peril.  We need to move beyond traditional concepts of business intelligence and decision support.  I see our goal as supporting full-spectrum business insight.

(1) Greene, L., “Apollo’s Chariot – The Meaning of the Astrological Sun”, CPA Press, (2001)