The Perils and Promise of Real-Time Data

As the demand for real-time data increases, as more and more information flows into the enterprise and its systems, the challenge of understanding and managing it grows proportionately. And sometimes, more is just too much.

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Real-Time Relativity

Like most terminology in the high-tech world, real-time means different things to different people in different industries. But what's common to most people's definition, says Royce Bell, CEO of Accenture's Information Management Services, is that the data is delivered "within an actionable time frame," whether that means within seconds or hours.

In the financial world, real-time data is, by necessity, defined as instantaneous. Traders, brokers and fund managers have to have information on global stock, equity and commodity markets delivered by the second. One can easily see why. In the financial services industry, downtime costs anywhere from $1.4 million to $6.5 million in lost revenue per hour, according to industry sources. A similar case can be made for systems in e-commerce companies such as Priceline.com, or in the airline industry (air-traffic controllers), utility industry (controllers monitoring electricity grids) and healthcare personnel (nurses monitoring patients), where even the smallest fluctuation in data is significant.

Step away from those segments, however, and the notion of what's instantaneous begins to slow down by minutes, hours or days, and the question of just how much, and just how often, becomes more uncertain. "Most organizations believe they need live data, but [in reality] they tend to consume things in a daily cycle," says John Hagerty, vice president and research fellow at AMR Research. "Daily is about as fast as they can do it."

Consequently, other terms closely related to real-time have appeared, including near-real-time data (anything updated more frequently than daily) and right-time data (updated any time of day or week that the company has determined to be most beneficial).

At Delta Apparel, a $270 million manufacturer and distributor of branded and private-label activewear, CIO Keith Smith describes his "two worlds." In one, subsecond real-time data informs decision making in Delta Apparel's manufacturing operations—from tracking when an order of polo shirts will be completed to figuring out which distribution center in the United States is best-suited to distribute those shirts in the shortest amount of time. "This is where real-time data is critical," he says. But in the other world—for sales information and budgeting—"real-time data totally falls apart," Smith says. It's just not practical or necessary.

Though Delta Apparel and Priceline were able to distinguish between the two worlds and adjust their data collection and delivery systems accordingly, many companies haven't been able to. And that's where real-time can get real dangerous.

Blinking at Real-Time

For the majority of 21st-century businesses, the possibilities of real-time data streams are endless and endlessly seductive: business activity dashboards on the PC, network monitoring alerts via e-mail, just-in-time manufacturing systems. The idea is to help people make better decisions.

But do they?

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