Page 61 - The McKinsey Mind
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02 (031-048B) chapter 2  1/29/02  4:49 PM  Page 39




                               Designing the Analysis                                      39


                               reach an answer of that level of precision very quickly, while
                               attaining spurious precision would take much longer.
                                   Also, if you can achieve some sort of satisfactory answer in a
                               short time, then you are much more likely to attempt the analysis
                               than you would if you had to get an answer to four decimal places.
                               As one of our alumni puts it:

                                   I find back-of-the-envelope analysis incredibly valuable
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                                   because it lets you know if you’re in the ballpark. A lot of the
                                   time, all I want to know is whether, say, a new product idea

                                   is going to be worth $5 million, $50 million, or $500 mil-
                                   lion. And some people find it very difficult to get comfort-
                                   able with that. They think,  “Oh, I’m going to say $50
                                   million; what if it’s really $75 million?” I don’t care! “But it’s
                                   50 percent off!” they say. I respond that it’s so much more
                                   valuable than not putting together a number at all.

                                   Just as some people want to do every analysis under the sun,
                               there are people who just have to get their answers correct to four
                               significant figures. Naras Eechambadi, founder and CEO of

                               Quaero, Inc., an information-based marketing consultancy, knows
                               all about that from the inside:
                                   I hire a lot of Ph.D.s and advanced-degree holders, and I

                                   almost have to force them not to look at every error pattern
                                   in the data. All that stuff your professors taught you is great
                                   if you’re talking about health care and you have to worry
                                   about people dying. But this is marketing; we’re just trying
                                   to make a buck. Let’s get the show on the road and stop wor-
                                   rying about all the nuances.
                                      You can spend a lot of time improving the precision of

                                   your models, but eventually you reach the point of dimin-
                                   ishing returns or you lose time to market. We don’t need to




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