August 10, 2003

Calculating for Uncertainty

In today's economy, the only thing we know for certain is that more uncertainty lies ahead. Scenario-based planning could help you strategize for the unknown, plan technology investments — and even save your company

by Frank J. Bernhard

Hindsight is 20/20 — at least according to the old adage. But no one can say with certainty that the oracle is telling us the future. Given the clouds of doubt cast upon the technology landscape, can we do any better than listen to soothsayers? They tell us to continue to hedge our bets and wait for the next big wave in computing — and in business generally. But in competitive marketplaces, waiting isn't a viable strategy; instead, you need to sharpen your organization's ability to plan and execute through the fog of uncertainty.

Networks and systems grow in size and complexity, adding more and more data. Yet we hear constant worry about whether IT can manage this information volume toward a purposeful outcome. Before, the plea was simply to deliver information to the user. Now, the mandate is to transform this "tacit" data into kinetic knowledge. Only then can strategic decision makers probe the fog of uncertainty and allow a set of possible answers to materialize before it's too late — before a condition or event comes to the foreground. However, IT managers should not despair: The power of foresight is more attainable than you think.

Economists and business leaders have long subscribed to the notion of planning for the ebb and flow of business cycles. In that sense, the problems posed by today's protracted spending slump are no different from previous eras' — except for the new influence of information at our fingertips. Demand signals are tighter and more frequent. Data and its implications are communicated much more rapidly. The compressed intervals have us spinning to gain a sensibility about what reality is and isn't.

The fundamental application of mathematical and statistical modeling continues as it always has — but with one big change. The information deluge has vastly improved the accuracy of predicting the successive reaction chain, from customer behavior to the marginal benefits of deploying the technology to measure that behavior. By filling the models with enough real-time information, analysts can look into the future with unparalleled clarity. Decisions can be made with more authority.

The rationale for modeling uncertain outcomes dates back centuries, to the time when statistical science was taking shape as the heart of economic theory. As the practice of mathematics and statistics gained momentum, the biggest roadblock was lack of data. Without data, analysts couldn't derive a set of scenarios strong enough for reliable enterprise planning. Given the current expansion of real-time data, the calculation process is clearly more exact in hitting its desired target — and in generating insight.

Scenario-Based Planning

Challenging economic times force CIOs to measure technology investments in terms of explicit performance parameters and tangible business yields. Scarce resources compete with "limitless" project possibilities; choosing the right combination means finding the perfect match of current capabilities with foresight into demand, including that which is unaccounted for in the organization's current plan for growth. The result is an agonizing conflict between wants and needs in which the outcome always leaves some party unsatisfied.

• Privacy
• Your California Privacy Rights
• Copyright © 2008 United Business Media LLC