Rita McGrath is a best-selling author, sought-after speaker, and longtime professor at Columbia Business School. She is widely recognized as a premier expert on leading innovation and growth during times of uncertainty. Rita has received the #1 achievement award for strategy from the prestigious Thinkers50 and has been consistently named one of the world’s Top 10 management thinkers. Rita has also consulted CEOs of Fortune 500 companies worldwide.  

Rita has written five books, including Discovery Driven Growth, cited by Clayton Christensen as creating one of the most important management ideas ever developed.

Rita received her Ph.D. from the Wharton School and has degrees from Barnard College and the Columbia School of International and Public Affairs.

In this episode we discuss the following:

• At any given time, we’re in one of two situations: low uncertainty or high uncertainty. And the mistake we so often make is using the techniques we use for low uncertainty in the domain of high uncertainty.

• When we’re in an uncertain environment, where we’re making a lot of assumptions, we need to collect data to convert those assumptions to facts. Rita calls this Discovery Driven Planning.

• When planning for a conventional line of business, uncertainty is low, managers have good data, and people can accurately forecast the future with relative precision. But when launching an entirely new venture, uncertainty is high, so it doesn’t make sense to start off with a big team, ambitious goals, all the money upfront, and definite deadlines. Rather, we should do the opposite and start small, collect data, test assumptions, and iterate.

• When making decisions, we should first assess whether we’re in Situation 1 (low uncertainty) or Situation 2 (high uncertainty). And if we find ourselves in Situation 2, we should start small, collect data, test assumptions, and iterate.

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