Modern thinking is highly skeptical of such esoteric arts. Correctly so in the case of many practitioners. But it has far less reason, in my opinion, to dismiss much of the underlying rationale and value of these approaches. That, however, is a topic for another forum. My point here is that I did not believe the prediction; I didn’t want to. And that’s part of a rather gory truth of any predictive tool.
As we flip the calendar to 2014, it is clear that the audience for predicting people’s future behavior has grown far beyond the ragged ranks of lonely lovers. Marketers and advertisers, once content with psychological and sociological generalizations, have become increasingly besotted by big data and the promise it offers of knowing the customer so intimately that her individual and specific future behaviors can be predicted. And, probably of more value, influenced. This, of course, is the power and the glory of predictive analytics. But, as already noted, this blog’s title actually says “gory”. And here, in detail, is why.
While writing in Business unIntelligence: Insight and Innovation Beyond Analytics and Big Data about some of the uses of big data way back in February, 2012, I came across Charles Duhigg’s New York Times piece on Target’s ability to predict not only the pregnancy of female (obviously) customers but also their likely delivery dates. Over the New Year break, I finally found time to read Duhigg’s book, The Power of Habit, in which that story first appeared. My point in my own book, and in a related blog Death by a thousand analytics, was that using big data in this manner is both a clear invasion of privacy and likely to creep people out. But Duhigg’s book deals with a much broader topic–human habitual behavior and unconscious thought patterns–that has far deeper implications for predictive analytics and decision support in general.
The message of The Power of Habit is fairly easily summarized. A very significant proportion of our thinking, decision-making and action at personal, organizational and societal levels is entirely habitual. Given a particular cue (which can be anything from a thought to an action), a routine set of behaviors is immediately and automatically engaged, which provides an anticipated reward. Simply put: cue => routine => reward. This mechanism operates, both in its set up and execution, in one of the most primitive areas of the brain, the basal ganglia, a structure that derives in evolutionary terms from the earliest chordates. It is, in fact, a basic survival mechanism that enables us undertake a wide range of necessary life-preserving activities, from preparing food to getting home, with minimal expenditure of energy and attention. This, of course, initially freed the brain to deal with novel, life-threatening situations and more recently for higher-brain functions such as empathy and reasoning. However, as anyone who has ever tried to give up biting their nails or mid-afternoon snacking can testify, changing habitual patterns can be very difficult indeed, even those which are counterproductive or even downright dangerous.
This very primitive mental operation of cue-routine-reward has two (at least) important consequences for predictive analytics.
For marketing, the drive will be to move increasingly to an understanding of specific, individual habits and their cues, in order to create opportunities to influence behavior. This is more difficult than it sounds, as such cues are often difficult even for the individuals themselves to identify. Similarly, rewards are often far more subtle and diverse than might be imagined. The story of how Pepsodent toothpaste was sold to an American public famed for poor oral hygiene in the early 1900s has become a classic marketing exemplar of how to create a habit and a sales success. But, according to Duhigg, the actual cue and reward involved were long mistaken. Furthermore, although most Western people are by now inured to mass manipulation by advertising, the much more personal and private knowledge used for such individual influencing may raise resistance to such approaches. From the point of view of privacy, I am of the opinion that it most certainly should.
In the case of personal and organizational decision making support, habitual and other unconscious patterns are a serious impediment to efforts to become “data-driven”. My unfortunate lovelorn experience of disbelieving a predicted but undesired outcome is a basic behavior pattern well-recognized in psychology but seldom mentioned in business intelligence. Habitual beliefs and behaviors at an organizational level are so deeply embedded and invisible to participants that they stymie efforts even to recognize problems, never mind take effective action.
The bottom line is that no matter how much data you gather or how elaborate the models you generate, Business unIntelligence operates finally, in full glory or gory fullness, in the minds of your customers and business users.
