A useful and effective sales forecasting system is one of the Holy Grails of sales management. The components of such a beast will be topics of this post from time to time. But before we address any of those components in detail, I offer this fundamental truth about forecasting systems: A mediocre system thats used consistently is better than a perfect system that isn’t.

As profound as that statement may seem, its even deeper than that! Obviously, no forecasting system is credible unless every rep and manager whose input is required (the users) inputs reliably and consistently. Whats less obvious is this: Changes to the system, especially efforts to improve the system, can themselves have a significant impact on how reliably and consistently the system gets used. What if the changes you are considering will:

  • Make inputting more time-consuming? Virtually all significant changes to the system processes require the users to spend more time inputting data. Its a slippery slope: the basic system just asks for prospect name and deal size, the next iteration asks for sales cycle stage, then product line detail, then activity summaries, and so on and so forth.
  • Make inputting more complex? What if, for example, the proposed changes will require users to specify which of seven, rather than three, stages in the sales cycle each prospect is at? Or the changes mean inputting detailed product line information?
  • Require more judgment and subjectivity? For example, one approach to assigning probability of close is to tie a single specific probability to each stage (e.g., 100% for closed, 90% for in contract negotiation, 75% for user signed off, etc.). Another approach requires a sales manager to input his or her own probability assessment for each deal. Which approach produces the more reliable weighted average forecast?
  • Generate unwanted visibility? Additional detail in the system on each prospect is a two-edged sword. On the plus side, it enables company-wide collaboration to help close a deal, and provides valuable information. But from the sales forces perspective, that extra support may feel more like meddling, and an opportunity to be micromanaged.
  • Benefit those other than the systems users? For example, detailed product line information on all prospects might be much more valuable to marketing or engineering, than to the users who are just trying to close deals.

Some of the consequences of these improvements can include:

  • Input errors because the users just cant (or wont) devote sufficient time to inputting correctly,
  • Input errors because the input procedures are more complicated,
  • Inconsistent data in the system resulting from individual judgment and cultural differences,
  • Data simply not entered, because users are concerned that (a) others will meddle, or (b) that they wont personally benefit, through increased sales, from the significant additional effort thats being asked of them.

Theres no question that a good sales forecasting system is a living, breathing animal that is constantly evolving. But every time you consider enhancing the system with the objective of getting more accurate, more reliable forecasts, you need to ask yourself: When does better become the enemy of good?