How to Make a Decision--When You're Not Ready
BY Adam Vaccaro
You don't have data and you don't have time. Here's how to make a choice anyway.
In the era of big data, it is wise to wait for all the information before you make a big decision. But sometimes it's time to choose--and the information just isn't there yet.
So what to do? McKinsey & Company consultant Ameet Ranadive addresses this question in a recent post on Medium. Ranadive writes that he has encountered the problem throughout his career.
"During my time at McKinsey, we were often called on to advise a client to make an important decision without the benefit of a lot of data," he writes. "A good example was when a client asked us to evaluate whether it should move into an adjacent, but new, market. We often didn’t know how that market would grow over time, or what kind of market share our client would get in the new market."
Ranadive prescribes three-step process, anchoring them to that example. When you have to make a snap decision, ask yourself the following three questions.
1. What was your day one hypothesis? The idea here is if you put a premium on developing an early hypothesis, "you always have a decision that you can stand behind at any point in time," Ranadive writes. A smart organization puts a premium on how they go about creating this early hypothesis, Ranadive says, by reading whatever they can get their hands on or interviewing industry experts.
2. Do you at least know the general direction this decision will bring you? Along similar lines as point one, you might not know how much you stand to gain or lose by entering a market. But you should probably have a sense for whether you will stand to gain. If you can't make a pinpoint projection but can be what Radavine calls "directionally right," and if that's the only kind of benchmark you have, then you might as well act on it.
3. What do you have to believe for this to be the right choice? In other words, if you decide to go ahead with this idea and based on what you already know, does it have a reasonable chance of actually working out? As an example, Radavine says to suppose in the hypothesis phase you learned that the new market you want to enter has a $250 million market. The mandate, self-imposed or otherwise, that you're working with is that you must be able to capture $50 million within three years. Do the math, and that's 20 percent. Is it reasonable that you can capture 20 percent of this new market by then? If not--there might be other competitors in the space that make it impossible to tell, or you might not have experience entering new markets--you might have to shut this initiative down, at least until you have the data that can better inform your decision.