STARTING WITH THE DATA

Starting with the data has a respectable history, dating back to the early days of consulting (1950s and 1960s). The profession was relatively new then, and consulting firms had not yet assembled extensive knowledge about industries and companies. Thus, the standard approach, regardless of the client's problem, was to begin a consulting engagement with a full company/industry analysis:

1. Identify the key factors for success in the industry, looking at

Market characteristics

Price-cost-investment characteristics

Technological demands

Industry structure and profitability

2. Assess the client's strengths and weaknesses, based on

Sales and market position

Technological position

Economic structure

Financial and cost results

3. Compare the client's performance against the key factors for success

4. Develop specific recommendations to capitalize on opportunities and solve problems.

The result was an overwhelming number of facts, from which it was difficult to draw meaningful conclusions. Indeed, a major consulting firm once estimated that fully 6CY/o of its fact-finding and analysis effort was wasted. Consultants produced too many "interesting" facts and exhibits, only marginally connected with what turned out to be the client's real problem. Often, much of the information was incomplete, so that in many cases there were little or no data to support major recommendations. This meant consultants were forced to find additional data at the very last minute, a process both costly and ulcer-inducing.

Even with complete data, organizing the thinking into a clear presentation of ideas for the final report required_ massive effort. The initial approach was to group the facts they’d gathered under headings like Operations, Marketing, Growth Projections, Issues, etc. But we know that, Summarizing Grouped Ideas, how difficult it is to draw clear conclusions from groupings like that.

In an effort to impose some structure for the reader most consulting finals resorted to presenting the information in the order in which they had gathered it, organizing around sections labeled Findings, Conclusions, and Recommendations. But these headings are no more helpful as a means to force the writer's thinking than are random topics. Either way, consultants spent vast amoms of time on the writing effort, and ended up with lengthy, not very interesting documents that only poorly reflected the insights inherent in their work.

Given both the increasing cost of the effort and the unsatisfactory results, firms began looking into the problem. Eventually they determined that what makes sense (and what the better consulting firms now do) is to structure the analysis of the problem before beginning to gather any data. To an extent they are replicating the classic scientific method, in which you:

- Generate alternative hypotheses

- Devise a crucial experiment (or several of them) with alternative possible outcomes, each of which will as nearly as possible exclude one or more of the hypotheses

- Carry out the experiment so as to get a clean result

- Plan remedial action accordingly.

In other words, they force themselves to think up the likely possible reasons to explain why the problem exists (a technique known as Abduction), and focus their data-gathering efforts on proving these reasons right or wrong. Confident that their conclusions about the causes of the problem are sound, they are then in a good position to be able to recommend creative solutions for eliminating them.

"Ah/' you say, " but how do I come up with the 'likely possible reasons.' I can't just pull them out of the air." No, you must get them by looking critically at the structure of the area within which the problem occurred-the Opening Scene or Starting Point of the Problem-Definition framework. To get at this structure in depth, you need to employ an appropriate diagnostic framework.

A number of diagnostic frameworks are available to aid analysis, as well as a number of nondiagnostic logic trees to help generate recommendations. Very often the difference between these two aids to analysis is not noted, and they are lumped together under the heading of "analytical techniques" or "Issue Analysis." It is useful, however, to note the difference so that you can use the right technique in the right place.