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What is Predictive Intelligence?
By Enid Brown

Why would you even care?
Well, you might not care at all… since it offers no great answers; it is hardly the promise of some Samurai consultants. Oh, and you can’t just say “we’ve implemented it in our company.” So obviously, it has its limitations in the slick world of marketing-hyped solutions.

Now, to encourage more readers to abandon this musing, we offer some prefacing comments. Predictive Intelligence is a method for inquiry -- that is most effective when approached with a tad of irreverence. Playfulness allows serious examination of interrelationships, unimagined linkages, and possibilities still unarticulated. We like to think of the process as "ragamuffinish" to dissipate any pretense of elitist strategy.

As a method of inquiry, Predictive Intelligence frames areas to explore beyond traditional questions. Rather than ask, “how can we solve a problem,” a broader framing could ask: “What might the data suggest in terms of patterns, cycles, trends - past, present and future? What range of variation might we expect in the manifestations of patterns, even those that may not be fully identified?”

Statistical projections may forecast projections, for example, for warranty problems for a certain vehicle model, part, or subsystem. A Predictive Intelligence approach would pursue further, by asking about the impact of warranty problems on consumer perceptions of a company, a high-profile executive’s persona, or how relationships with another supplier might evolve. Notice that the questions are not framed for cause-effect or blame determination. Patterns of problematic relationships with one company, for example, may reflect dysfunctional behaviors, expectations, and broader interrelationship issues beyond the corporate boundaries. An internal analysis may not show this. Missing this broader pattern could mean that entrenched problems could have a higher likelihood of repeating with another company - even one with an impeccable track record. If the pattern reflects a system-interface issue, analysis of each company separately would be ineffective.

Predictive Intelligence is not new at all. But its pragmatic application and growing emphasis is new. One example is an effort to look at vehicle safety from a broader, multidisciplinary perspective. Ricardo Martinez, M.D. and former Administrator of the United States National Highway Traffic Administration (NHTSA), began setting this shift in motion. He began funding what now includes nine Crash Injury Research and Engineering Network (CIREN) centers with support and participation from major automotive manufacturers. This program was a major focus at a recent global automotive safety conference, presented by the Society of Plastics Engineers. Compare a traditional verses a Predictive Intelligence approach.

A corollary in our justice system, is emerging in an arena traditionally rigid with an institutionally mantra of “solve the crime.” This is the same charge as “fix the problem” in automotive lingo. It is not one of building intelligence through methodical inquiry and learning about networks and interrelationships among possible criminal elements. The real world data suggests that perhaps many crimes are invisibly embedded within contexts of business relationships, philanthropy or simply dealmaking. (Another segment of readers may leave now, as the connection between the corporate arena and justice system begins to intersect more viscerally.) Please, there are no accusations intended.

Robert M. Bryant, former Deputy Director of the FBI, who currently heads the National Insurance Crime Bureau (NICB), argued for what he called a “sea change” regarding how the FBI had to shift its emphasis on tracking down criminals, to predicting and preventing criminal activity.

Forensic innovations such as DNA testing can provide evidence that was once elusive. Similarly, in the automotive world, telematics and other innovations in technology can use satellites to relay a host of data to analyze a situation. All are wonderful advancements, but no substitute for creating knowledge with transcendent value. Predictive Knowledge SM is the NICB’s process for collecting and analyzing information, turning the information into knowledge, then disseminating it so that customers, insurers and law enforcement agencies can prevent, detect and investigate crimes … and even project where future problems may likely erupt.

Collecting and manipulating data, and advancing technology are not enough. Predicting the future in concrete terms is delusional and counterproductive. However, predicting vulnerability and identifying future risks is integral to this art-and-science approach. A crystal ball just doesn’t cut it.

Predictive Intelligence does not predict per se.

The Western culture is attracted to the seductive nature of definitive predictions. Ego is involved. “I’m right and you’re wrong” helps distinguish those who made a hit from the others who struck-out. Unfortunately, by stressing their obsession with predictions, they can miss the more valuable learning aspects of an inquiry perspective. While many predictions may be legitimate when solid analysis determines that the variables are stable, often times the assumptions on which they are based become lost in the focus on “fortune-telling” or “fixing”. Yet, most assumptions are invariably riddled with variation. By focusing on the dynamical nature of these assumptions, and describing the various iterations of pattern after pattern, we can deepen our knowledge and build a sense of wisdom.

Reportedly, it is not uncommon for Japanese automotive engineers to go out to accident scenes to investigate real world vehicle dynamics. This helps them to design better. The broader system thinking assumes that data on crashes can be used to: determine cause, suggest avoidance strategies, and improve future vehicle design knowledge base. The essential difference is one method collects data and answers … while the other creates as system for collective learning for practical application.

Predictive Intelligence invites us to imagine multiple futures - from a scientific, yet playful mindset. Data and facts may be measured, but intelligence is not measurable by definition. Some cultures are comfortable with the more organic characteristics of inquiry. As any corporate anthropologist might note, it is significant when a culture expects “experts” to force-fit unmeasurables into quantified pretenses, to prognosticate and over justify its legitimacy. Corporate, government and media reports that assure us of their infallible crystal ball should flag suspicion. Predictably, horoscopes are right some of the time! Yet we can do better. Information reporting has its place. Event debriefing and analyses can be valuable. Let’s just keep sight of what we could be doing with a mindset that fully engages in a most natural human endeavor.

Predictive Intelligence is a way of exploring our world - by examining the past from multiple perspectives, experiencing the present with a dispassionate and purposeful engagement, while focusing on a future still receptive to improvement.

© Enid Brown 2001







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