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Decisions, decisions ... Competitive intelligence for predictive decision support and market risk management

This article appears in the issue November/December 2005 [Volume 14, Issue 10]

 "The clever combatant imposes his will on the enemy, but does not allow the enemy's will to be imposed on him." --Sun Tzu

 Success in business, as in life, really only depends on a series of good decisions. But the difference between good and bad decisions has always been more a matter of 20/20 hindsight than predictable outcomes, consequential contingencies and what-if scenarios. While consistency in quality decision making certainly counts to both shareholders and customers alike, mistakes large and small often happen without the losing firm being punished by the market for its inadequacy.

 In fact, markets have traditionally been forgiving--even kind--to mistakes made in their service, taking into consideration a firm's historical "average," the need for occasional injections of new management and generally downplaying most near-misses. After all, had we judged Apple (apple.com) by the Newton alone, the iPod would never have followed.

 But this forgiving environment has been transformed by a new ruthlessness in global competition, and never before have business leaders faced such intense competitive dynamics, both from the "usual suspects" and from emerging rivals offering substitute products or disruptively innovative business models. Even corporate superstars of more recent fast-growth markets like Blockbuster, Dell, HP, IBM, Intel, Kodak, Microsoft, Pfizer or even mighty Wal-Mart face competitive pressure when and where it's least expected.

 Or is it really all that unexpected after all? Many fall victim to their own past success and the momentum it generates. When opportunity knocks, it is the fleet of foot who turn to meet it. And the ways in which firms and their managers make decisions has become an area of intense study, as decision-making prowess is one of the few remaining differentiators in the field of modern management practice.

 Likewise, the clarion call to be innovative or first-to-market simply is not specific or meaningful enough to matter much to average frontline staffers trying to keep the business afloat day to day. Straining for tactical advantage amid bureaucratic red tape can slow them down sufficiently to be caught by nimbler competitors, or to misjudge the timing of new market investments so dramatically that first-to-market takes a back seat to making it to market at all.

 Competitive intelligence (CI) is finally becoming a modern strategic decision support tool. As the saying goes, the difference between first and second place in any market is a game of inches, and because timing so often makes all the difference, small but detectable indicators of market and industry change can have a dramatic influence on outcomes. Identifying and tracking tripwires involves considering not only past events and the lessons they compel us to learn, but also inferential patterns that can emerge from a sea of episodic market activity, as well as planning for high-impact, highly uncertain scenarios of the future, and predicting likely behavior by "gaming" comparative decision-making processes of other actors in a marketplace.

 But centralized, command-and-control CI practices have been called into question by the very theories driving modern decision science. CI must also adapt to new models and adopt the principles of instinctive as well as collective decision making in an era of ruthless, winner-take-all competitive pressure.

Sustainable competitive advantage and disruptive innovation

 In 1991, Jay Barney developed the Resource Based View (RBV) theory of the firm. That approach established four criteria that determine a firm's competitive capabilities in the marketplace:

 1. Is it valuable?

 2. Is it rare?

 3. Is it imperfectly imitable?

 4. Is it non-substitutable?

When all four of those criteria are met, a firm can be said to have a sustainable competitive advantage; more importantly, the firm will continue to enjoy an advantage in the marketplace that will last only as long as those four criteria are completely met. As a result, the firm will earn higher profits than other firms with which it competes.

 Fast forward to 2003 and the coalescence of Clayton Christensen's Disruptive Innovation theory, which explains that products "do jobs" for their buyers that would otherwise be hired out to specialized service providers unless and until a product emerges to automate the job. Consumer demand curves--not competitive innovators--decide winners and losers in the market.

 Christensen credits value chain evolution with the ability to predict the outcome of competitive battles in three important consumer-driven contexts:

 • Overshot consumers, who find current offerings too expensive or too complex, have a demand curve requiring specialist vendors with new business models to meet their lower-end needs more efficiently (Netflix, Dell and Wal-Mart).

 • Undershot consumers, for whom current offerings fail to meet their more sophisticated needs, have a demand curve requiring opportunities for "sustaining innovations" to improve existing products at a premium price to meet their leading-edge needs (Apple, Coach and Starbucks).

 • Finally, nonconsuming contexts exist for which there is no historical market, and truly new market disruptive innovation can reshuffle whole industries by meeting needs consumers didn't know they had (TiVo and RIM's BlackBerry).

 Which of those two seemingly contradictory approaches to strategic thinking—Resource Based View or Disruptive Innovation--is right? The answer? Both are.

 CI today must consider both dynamics in understanding how sustainable competitive advantage is reached and competitive outcomes predicted by seeking gaps in consumer demand curves unmet by current products, business models or vendors.

 TiVo, for instance, does not merely record television broadcasts so its customers can skip commercials; TiVo enables customers to shift time itself to suit their schedule--a job consumers did not know they needed until TiVo was introduced. However, rapid price commoditization followed because of the controversial patent leverage of TiVo's intellectual property that came as cable companies gobbled up the DVR idea, incorporated it into their services and decided to fight it out in the courts later. (TiVo appropriately is defending its patents on time shift as a process and concept, not the generation of technology that enables it.) Satellite companies, cable's traditional arch nemeses, are among TiVo's chief supporters. Enemy of the enemy is my friend.

Collective intuition and the element of surprise

 When considering decision making and how it impacts the strategic, operation and tactical questions of bringing products to market, we should look at the most recent thinking in the field.

 Recent books like Blink by Malcolm Gladwell and The Wisdom of Crowds by James Surowiecki have popularized the abstract world of decision science. Harmonizing seemingly opposing schools of thought has proven to be an amusing distraction for many of late, including the authors themselves.

 The debate revolves around whether individual, instinct-driven snap decisions yield better overall results than a collective consciousness where many minds pooled together reach consensus on the accurate depiction of risk, reward and reality. Both models of decision making challenge the "standard model" of organizational decision making in which centralized command and control is left to highly specialized, deliberate individuals who examine options, uncertainties and impacts, and formulate actionable recommendations.

 Blink is a book about the phenomenon Gladwell calls "thin-slicing," or "the ability of our unconscious to find patterns in situations and people based on very narrow 'slices' of experience." But it isn't just experts who thin-slice, we all do, all the time and with surprising success, so that "decisions made very quickly can be every bit as good as decisions made consciously and deliberately."

 But the notion that the snap judgments can be as good or reliable as those we reach after careful assimilation of lots of information seems counterintuitive. The longer and harder one thinks about something, we assume, the better one thinks about it.

 Most criticism of Gladwell's "rapid cognition" model centers on how reactions can be sabotaged by prejudice, stress, inexperience and complexity, so that intuition ends up being worse, not better, than deliberation. In situations where there's no time to think, we often fall back on simple rules of thumb that lead us astray. And if we don't know enough to begin with, there's no guarantee our instinctive reactions will be good ones. But while that may seem to mean that only experts should rely on rapid cognition, Gladwell argues "that our snap judgments and first impressions can be educated and controlled."

 Gladwell cites the example of Paul van Riper, a retired Marine who in 2002 played the role of enemy commander of Saddam Hussein's forces in a war game battling U.S. forces in the Persian Gulf. The Pentagon had anticipated that the United States, with superior intelligence-gathering capabilities, total informational superiority and carefully delineated leadership structures, would crush the enemy quickly. But van Riper outfoxed and devastated his U.S. opponents using surprise and low-tech solutions. Van Riper's strategy capitalized on keeping his side's "powers of rapid cognition" intact. Long story short, he sank half the U.S. Navy on the second day and won the war--not because of superior power or resource base, but because his side could act more quickly and because simpler, intuitive decision making has the power to trump analytical complexity.

 Competitive lesson: When timing is everything, the fastest decision will win.

 Still Van Riper seemed to draw a distinction in his own mind between those situations where rapid cognition works well and those situations where it doesn't. "When we talk about analytic vs. intuitive decision making, neither is good or bad. What is bad is if you use either of them in an inappropriate circumstance," he says. The real challenge is deciding which decisions can be made by rapid cognition and which are better made with a more analytical approach.

 In The Wisdom of Crowds, Surowiecki makes a series of observations that question the ongoing viability of the standard model and suggests that the collective wisdom of a crowd, more often than not, is superior in predicting outcomes than the individual decision making of an expert. He maintains that we're better off decentralizing decision making into the hands of the many, even if they lack expertise and their decision-making process is less deliberate. Collecting the opinions of novices who decide questions in anonymity and averaging their predicted outcomes without individualized consequences can free decision makers from self-interest and biases.

 Sometimes experts can have too much information, and the quantity of information not only makes analyzing it that much more difficult, its apparent completeness can make decision makers too sure of their analysis and predictions. Surowiecki cites the study of expert racetrack bettors who were given five equal bits of information about the horses in a race and asked to predict the outcome. By and large, the predictions tracked to the outcomes. But they were also asked how confident they were in their predictions. Then they were given, in succession, 10, 20 and 40 more pieces of information and asked to make similar predictions about the outcome. The additional information didn't make their forecasts any more accurate, but it did make them falsely more confident in the forecasts.

 Because it's so difficult to distinguish which information is central to the outcome of a decision and which is not, making such distinctions cannot be accomplished by rapid cognition alone. It requires the careful study of data to see what factors are and are not correlated. Much more important than a person's unique expertise are the hard-won lessons of experience; successful thin-slicing happens so quickly that it requires a keen sense of self-awareness and pattern recognition, usually driven by hindsight. People who are excellent at thin-slicing instantaneously screen out the irrelevant and filter for what matters.

 Paired with collective decision-making mechanisms such as betting markets, which allow individual investors to wager collectively on futures ranging from commodity prices to the presidential election to predict probable outcomes, the wisdom-of-the-crowd principle works because those tools articulate the instinct and intuition that individuals usually cannot. And for most decision makers, the combination of rapid cognition and individual decision making often makes it harder to spot potential pitfalls and to correct mistakes in time to make a difference in the risk equilibrium of probable outcomes.

 Business decisions happen across three contexts: the strategic, existential context of deciding which businesses to invest in and how; the operational, line-of-business context of optimizing cost structure and out-innovating traditional rivals while defending against emerging ones; and the tactical, frontline context of convincing customers every day that yours is the superior choice.

 But how do such principles of predictive decision making apply in the real business world where winner-take-all competitive dynamics have become the fundamental rules of the game?

Google vs. Microsoft: victims of past success

 As one of the most successful business enterprises in history, Microsoft (microsoft.com) is celebrating its 30th birthday by reorganizing to compete more nimbly with a new generation of competitors. At the same time, it's striving to reinforce the importance of Windows and Office in a market where the very nature of the desktop operating system has become less relevant as applications migrate to the Web. None other than Google (google.com) itself leads this new breed of competitive innovator, using its "Googleplex," the network infrastructure that enables the company to deliver rich, lightweight, browser-based applications from the world's largest supercomputer, to undermine the very idea of the desktop as the context of computing for the future.

As Microsoft has discovered, the ubiquity of its products has not only made the company the target of antitrust regulators worldwide, it has also made its products targets for hacking, phishing and other security-related attacks, thus diminishing their appeal to customers of all kinds. Likewise, perhaps the success of its own strategy is Google's greatest long-term threat. Probably the first litigious company forced out of the business of selling software or services that Google gives away for free will level charges of monopolistic, predatory and unfair competition on that once-humble enterprise whose strategy was, in the beginning, simply to avoid being evil.

As we see, the risks inherent in success itself as well as those brought about by more direct rivals must be considered, planned for and dealt with as companies make strategic, operational and tactical decisions every day. And only rapid, collective cognition across the enterprise can effectively plan for probable long-term consequences and their contingencies.


Arik Johnson is founder and chief executive of Aurora WDC (aurorawdc.com), a CI support bureau and systems consultancy. He writes a weblog about CI found at arik.johnson.com, and can also be reached by phone at 715-720-1616.


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