As consultants we are adept at identifying patterns quickly for action.
Sometimes the patterns are obvious from our experience, and we do data analysis to confirm the pattern (and not ignore other patterns). Sometimes we must analyze large volumes of data to discover the pattern (for example, the server capacity needs for one life insurance company tracked the NASDAQ index, with an unbelievable correlation of 1!)
Sometimes the answers are obvious and simply need confirmation. We once worked with a diversified manufacturing company, where the distribution included direct to retail and reseller. The mass market channel, representing 15% of total company sales, wanted the company to include an additional label on a pallet indicating the pallet contents. This was to speed receiving. Ironically, this company also made the printer and the software for producing the label, so internal costs were negligible. The director of the customer operations division wanted a detailed analysis of the costs for producing this label so “the company could decide whether to apply the label or not.” While we fully support completely understanding costs, making this “decision point” introduced consternation. The warehouse was fully prepared to apply the label, and Sales was demanding the customer request be made. It was hardly worth the meetings to determine if an additional cost of “about a buck” a pallet was worth the effort.
We see this time after time.
One client wanted to understand systems configurations and interdependencies in report format. Certainly the information is needed, and represents many of the foundational elements of a Configuration Management Database (CMDB.) The client acknowledged this would be best in a CMDB, nonetheless wanted reports of the data. Frankly, we question whether anyone printed or looked at a 400+ page report. This is a case where a database was the perfect solution, and would have increased the speed of the project (by having the most current data at the team’s fingertips.)
Another client wanted to do forecasting for certain data center capacities. The client executive wanted great specificity. Some of the project data for future years simply was an unknown. The budgets were not complete, and system designs were unknown. This is a case where using reasonable and thoughtful estimates is most appropriate. In this case, a great deal of time was expended querying technology teams for data they simply did not have.
In all of these cases, the argument can be made we were ineffective in making our positions known. I do believe reasonable people, when presented with the facts, will often come to the same answer.
What each of these cases share is an engaged manager who insists and demands more data regardless of the facts or data availability. These managers, in an attempt to get to the most accurate information possible, actually end up expending more time and resource than the analysis warrants (in our opinion.) In each case, the manager was a very bright and well intentioned person, with great passion for their work. We would submit they need to back away from an issue and look at it objectively determining if the extra investment is warranted.
Some might call this common sense or street smarts, and while I have sympathy with that perspective feel don’t want to discount the wisdom of the executive. In the end, a more rounded conversation is warranted between the consultant and the executive making sure the executive understands the cost of the analysis for the return. If the executive still chooses to make the investment, we are obligated to continue the work. Ultimately, we are a cost to the executive, and they need to understand the value of the analysis.
Do you have a story of analysis paralysis? Please share!