When a safety car appears in Formula One (F1) racing, it generally means there is some kind of hazard or debris on the track. Drivers must temporarily slow down, and F1 crews typically use the opportunity to bring their cars in for a pit stop. But when a safety car rolled out in the 25th lap of last year's Monaco

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nginx/1.14.0 (Ubuntu) Grand Prix, Team McLaren Mercedes made the counterintuitive decision to keep driver Kimi Raikkonen on the track. The ploy worked; Raikkonen won. But the decision wasn't made at trackside. It came from team leaders based at the McLaren Technology Centre in leafy Woking, south of London, who were using prediction software they've developed to help them make split-second tactical decisions in a sport where speed is king.

All F1 teams have their own versions of software that analyze thousands of variables — from weather and road conditions to fuel levels and competitors' likely actions — and how they may interact to affect a car's performance, before and during a race. The program spits out possible options, and assesses their chances of success. Now that racetrack technology is coming to the equally fast-paced world of business.

McLaren and its partner, British software company SmithBayes Ltd., are this week launching a business version of the team's "decision-engine" software. They believe that many companies, across a number of sectors, compete in environments not too dissimilar from F1 racing: countless variables and constant volatility. "Businesses make a lot of strategic decisions that involve uncertainties this software can track," says Simon Williams, ceo of SmithBayes.

The software's potential corporate uses are wide ranging. Companies can use it to measure the risks and rewards of moving into new markets, bringing out new products, or making capital investments. Myriad data and assumptions can be plugged in: possible new technologies, changes in government regulations, what rivals may do. The one constant most businesses can count on is churn. "If you know something to be true, it's already history," Williams says. A recent McKinsey & Company online survey and study found most executives are unhappy with their company's strategic planning. But it also found that corporate strategies often fail because managers are loath to admit they were wrong and make midcourse changes. Prediction software, Williams argues, makes it easier for executives to "accept uncertainty and move on."

It also helps companies practice "strategic agility," a popular management theory endorsed by Donald Sull, a management expert at the London Business School. He argues that chaotic working environments frequently harbor hidden opportunities. "You successfully compete by consistently identifying opportunities and threats and reacting before your rivals," Sull explains. Certainly the software lets executives react speedily; Team McLaren Mercedes, for example, had just 10 seconds to decide to keep Raikkonen's car on the track in Monaco.

A number of companies have been testing the software for SmithBayes, including one major European aerospace company. That's an industry whose products take years to develop and remain in the market for decades, but are loaded with electronic components that have the life span of gnats. That company has used the software to trim costs by figuring out the best time to replace many components across several product lines, while also introducing product upgrades. An executive with that company tells Time that his firm plans to make greater use of the SmithBayes software. Rival products, he says, can't factor in changes over time like SmithBayes': "Offering options over time is pretty unique to these guys."

SmithBayes put its own software to use when it picked a subscription-based business model, instead of licensing the technology or setting up a consultancy. Most clients start with an initial yearly package costing around $200,000. That's not cheap, but Williams calls it good value considering it helps clients place strategic bets worth millions. Sectors constantly affected by uncertainty and flux may find it most useful: think telecoms, oil companies, traders, insurers and betting companies. Firms that toil in steady environments may be less interested but, as Williams points out: "There seem to be fewer and fewer of those around."

• THOMAS K. GROSE | WOKING
• What can business learn from auto racing? Split-second decision making, says a British tech firm