Following the preceding list of elements in the analysis design,
we start by noting the issue to be analyzed and our hypothesis as to
the answer. We like to append our answer directly to the question,
although you could just as easily put it in a separate column. The
top-line issue goes (no surprise here) at the top. Beneath that,
indent and list the subissues, then do the same with sub-subissues
(not to mention sub-sub-subissues). Thus, the question “If it does
require special facilities, can we acquire them?” comes underneath
the question “Does the new process require special facilities?”
Next comes the list of analyses to be performed. In this exam-
ple, there aren’t many, but there could have been. For instance, it
might be useful to have a schematic diagram to go along with the
technical requirements for the new production process. Useful, yes,
even interesting, but not ultimately necessary, and someone would
have to take the time to put it together—time they wouldn’t spend
on actually proving or disproving the hypothesis. Therefore, doing
a schematic didn’t make the final cut, nor did a number of other
analyses that you might devise.
We’ll touch only briefly on the data and their sources, since
we will be covering that topic in detail in Chapter 3. Listing data
and sources helps you and your team cover all the bases so you will
be less likely to miss a rich source of information. Speaking of rich
sources of information, have you noticed how often interviews
come up? You’ll see a lot more about them in Chapter 3.
The description of the likely end product should be brief, as
in the example. These descriptions really serve as a departure point
for discussions within the team. At McKinsey, the EM takes each
team member through her part of the work plan and discusses her
expectations as to the end product. Sometimes, the EM will sketch
out a “ghost pack,” showing templates for each end product,
which can help guide the analytical process, especially for less-
experienced consultants.
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