• No prizes: The person who's best at forecasting very rarely receives recognition or reward. When's the last time someone was promoted to vice president of sales and marketing because they were the best forecaster?
• No penalties: Because everyone intuitively understands that forecasts, by their very nature, are imperfect and inaccurate, there is very little penalty for not forecasting better or being "the worst forecaster." When's the last time someone got fired, demoted, or otherwise penalized for not forecasting accurately? It's usually a slap on the wrist and "do better tomorrow." The real penalties come from not meeting sales quotas, and the real rewards come from beating them.
• Whose job is it anyway?: In many organizations it's
not truly clear who is responsible for the forecast. Even
where the responsibility is clearly documented, the lack
of tools, interest, rewards, and penalties effectively di
lutes the sense of responsibility to the point that it's
never taken seriously. This is then often compounded
by a lack of formal, consistent, clear measurement of
forecast accuracy. If it isn't obvious "how we're doing,"
veiy little attention goes into "doing better."
• "My real job is..." The responsibility for forecasting
is usually assigned to people having other sales and
marketing responsibilities, and inevitably they see fore
casting as the smallest, least important part of their job.
Given their aversion to doing it to begin with, and the
lack of reward for doing it better, it's always easy to put
off the forecast review and justify it with the explana
tion that "I had to talk to a customer, attend a market
ing conference, develop a new marketing program," etc.
• Tool confusion: With everything previously dis
cussed, it is tempting for the person responsible for fore
casting to hope that the best solution will be to
implement a new, highly automated, state-of-the-art
software tool that automatically generates the forecasts
with minimal human input and review. Software ven
dors eager to replace existing tools with their product,
have been known to make such promises.
Unfortunately, the statistical projections coming from these programs won't be significantly more accurate if the market forces driving demand changes in the future vary from the past. This then triggers the vicious cycle of picking new software, implementing it, running it, discovering that it's still not accurate, and then going to look for yet another software solution.
The real tools needed are much simpler and less sophisticated than what's typically offered. These are tools of comparison, aggregation, sorting, and display. They are tools that allow the analysis of data to be customized to a given situation and changed over time as factors in a given marketplace change. These are tools that make it easier for the analyst to identify trends over time and bias in the forecast, and to focus on the key or critical items that are causing most of the problems. They are tools that allow display of data in graphical format, easier for subjective review and analysis. The tools should help the analyst selectively focus on detailed information to find the true root causes of variation. They should include simple data display and reporting tools that every software vendor says are available, but which notoriously fall short of practical usability.
To Be Continued