The pros and cons of stretch goals

“The reasonable man adapts himself to the world,” wrote George Bernard Shaw. “The unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.”

They don’t come much more unreasonable than Elon Musk. The tycoon’s long-term goals (Humans on Mars! Brain implants! Humanoid robots!) are famously and wildly ambitious. Aggressive targets are also part of the day-to-day operating culture at his firms. “The Algorithm”, a new book by Jon McNeill, who was president of Tesla from 2015 to 2018, provides a window into what this looks like in practice. When Mr Musk appears in the narrative, as the carmaker grapples with an array of manufacturing and distribution problems, it’s usually to set a difficult target. He tells the team to increase e-commerce sales 20-fold. Buying a Tesla online took a tedious 64 clicks; he specifies a goal of ten.

The idea of setting ambitious targets, or stretch goals, has an allure that goes beyond Mr Musk. It sounds seductively simple: set an outlandish objective, apply pressure, make money. Stretch goals can galvanise an organisation: specific, difficult targets are much more effective at motivating people than general exhortations to do their best.

Seemingly impossible goals can also force firms to approach problems in entirely new ways. In the 1970s a young carrier called Southwest Airlines was struggling. It had to slash turnaround times for its planes to ten minutes so it could keep its small fleet in the air for longer. By borrowing techniques from pit-lane car-racing crews, it got the job done and helped change the industry.

But before you rush out and tell everyone to double revenue by Tuesday or colonise Jupiter, a few caveats. As ever, a poorly defined goal risks bringing about bad outcomes. In 1976 Continental Illinois, an unremarkable American bank, set itself a stretch target of becoming one of the country’s top three corporate lenders. With a relatively small amount of funding coming from retail deposits, it got there in part by borrowing on more volatile money markets. By 1984 it was big enough and overstretched enough to need a bail-out by the government.

The propensity for stretch goals to increase risk-taking was examined in an experiment by Michael Shayne Gary of the University of New South Wales and his co-authors. The researchers asked participants in an executive MBA course to take part in a computer simulation in which they played the role of chief executive of a startup airline, making decisions about aircraft orders, fares, employee hiring and more. Participants were randomly assigned a moderate goal, of a 22% compound annual growth rate in profits over ten years, or a stretchier one, of 38% annual growth.

The stretch goal was attainable but posed co-ordination problems: acquiring more planes and hiring more employees in the simulation risked lower service quality, which drove away passengers and generated financial losses. The results showed that tougher targets did lead to higher performance for a few firms, but that most participants either propelled their fictional airline into bankruptcy or, if things started to go wrong, changed their goals to focus on survival. There was less variability in the outcomes of the participants given more modest targets to hit; on a risk-adjusted basis, more achievable goals were associated with better performance.

Stretch goals involve trade-offs, in other words. The harder the target, the more likely it is to prompt a radical rethinking of how things are done. For Mr Musk, that is the point. The first and second steps in his algorithm for growth—the subject of Mr McNeill’s book—are “question every requirement” and “delete every possible step in a process”. This kind of reinvention is much less likely to happen if goals can be accomplished by doing the same thing as before, only better.

The stretchier the goal, however, the greater the likelihood of disruption to normal operations, and the more chance of demotivated employees if targets are always missed. And although greater variance in firm outcomes may suit the business model of venture capitalists, that is not the right goal in every environment; Mr Musk’s algorithm worked out less well when he tried to overhaul the American government, for example. The solution in most organisations is to have a blend of goals, some that must be hit and some that are more aspirational. If that sounds reasonable, it is. ■

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