Uncertainty begets opportunity

With the highest voter-turnout in the history of the Indian general elections and the victory of Prime Minister Narendra Modi, business leaders are optimistic that the business environment will continue to improve and economic growth will be strong. Still, with change comes uncertainty: No one knows how markets will play out or how regulations may shift. But this, too, is good news. Executives have only to benefit from embracing uncertainty: It opens the door to opportunity, in particular, to driving growth through innovation (DGTI).

Why does DGTI work? For starters, past experience can be limiting. Consider the case of W James McNerney, who became CEO of 3M — the nimble inventor of Scotchguard and Post-It notes — in 2001. Relying on his successful less-is-more strategy as an executive at General Electric, McNerney tightened budgets, cut thousands of workers, and implemented Six Sigma, to standardise processes and minimise variability. The result? Efficiency trumped innovation: Whereas in the past, one-third of sales had come from new products (released in the previous five years), by 2007 that figure had sunk to one-quarter. “Invention is by its very nature a disorderly process,” CEO replacement George Buckley told BusinessWeek’s Brian Hindo in a 2007 article, after he stepped in to undo the damage.

That disorderly process is driven by managerial vision. Innovation requires moving beyond past experience and intuition to experimentation. Indeed, experimentation and variation are the lifeblood of innovation. They enable companies to learn how to not just manage but grow from addressing sources of uncertainty across all company domains: R&D (will the product work?), production (can it be effectively manufactured?), customers (will it address needs?), and the business itself (does the opportunity warrant the investment?). No product or service can be a product or service without first having been an idea that was shaped through experimentation.

In a “perfect” business experiment, managers separate an independent variable (the “cause”) from a dependent variable (the “effect”), and manipulate the first to see changes in the second. However, the real world is rarely so tidy: Companies face changing environments, poorly understood relationships among variables, and uncertain/unknown variables. So managers must be prepared to iterate through experiments, as well as to know when to pause and observe or explore rather than act directly. New technologies — computer simulations, rapid prototyping—have changed the economics and the analytical time-line of experimentation. Thus, the process need not be daunting if companies match the level of uncertainty with the appropriate testing mechanism: Structured cause-and-effect experiments, informal trial-and-error experiments, or rigorous randomised field trials.

When managers know all relevant variables, they can use formal statistical techniques and protocols to develop and analyse the most efficient experimental designs to improve production processes and new products. Such structured experiments are now being used for incremental process optimisation and for studies investigating large solution spaces to find an optimal response of a process. Randomised field trials, modelled after drug-development trials, can pinpoint a specific change (say, a new layout for retail stores) and see if it leads to improved performance (increased sales). In medicine, the process entails randomly selecting two groups from a pool of people with the same disease.

One group receives treatment, the other (control) group a placebo. If the treated group does statistically better than the control, the treatment shows efficacy. Finally, to use experimentation successfully, companies must be willing to fail — to quickly drop bad ideas and pursue breakthrough ones. Google, for one, sees failure as part of doing business. In 2010, to test search-engine improvements, it investigated over 13,000 proposed changes, of which raters tested and evaluated 8,200. A subset of users evaluated 2,800 of those in a Google sandbox, and a committee analysed the results. In the end, just 516 were implemented. Google’s failure rate? Above 95 per cent. DGTI means applying these principles (and much more) to the entire organisation — when the market is up, and when it’s down, to keep the pipeline of new products, services, and business models flowing for when things turn around. It starts with executives making key decisions about strategy and resource allocation, and continues through strategy execution, process design, marketing, and operations — leveraging disruptive technologies and engaging customers as partners in the innovation process.

The writer is the faculty chair of the Harvard Business School Executive Education programme ‘Driving Growth Through Innovation, India’.

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