How does this story fit into the context of the last entry about the usefulness of the metaphor of a Sales Pipeline for our list of known opportunities? Further development of the Leaking Sales Funnel Concept will eventually lead us to an alternative way of forecasting. So that later you can appreciate the benefits of a Funnel Based Forecasting Process, I want to first make you aware of flaws in forecasting process that can be observed today in the field. If you recognize similar behaviors in your organization this might also become the motivator for you to consider making your forecasting more efficient and effective with the proposed alternative process.
Believe it or not, I have seen Sales Executives whose desire to avoid hassles with their superiors was so big, that they not only shared the optimism of their sales people, they imposed optimism. They did not accept any deviation of the forecast from the business plan. Sales representatives, showing up with forecasts not meeting this requirement, were asked to add fictive opportunities to their forecast and were told “I am sure with a bit of effort you will be able to turn this fictive opportunity into a real one”.
Here is some anecdotal evidence and an illustration of the consequences of such behavior. Some times back, I was involved in a utilization study of a CRM system used by a well known IT-manufacturer. When I asked one of their sales people I had interviewed about his use of the system whether there is a last thing he would like me to know he said to me. “I just hope our production planning people do not do capacity planning based on my forecast.” When I asked why guess what the answer was? You are right he had a boss who imposed optimism just in the way described above. Worse though, the whole chain of command in the sales organizations seemed to adhere to the principle “the forecast has to meet the business plan”. I call this a form of Political Forecasting.
You might wonder why this sales person even thought about the production people in the context of his forecast. In his organization the forecast was not only done in monetary terms. The minute you actually entered an opportunity the system imposed an entry of at least one product code. I can guess what the original intention of this rule was. People in the supply chain wanted to impose coherence between the monetary and the product volume forecast from the very beginning of the existence of an opportunity. Due to the actual use of the system by the sales organization, this coherence, hoped to help reduce forecasting errors turned into a highly biased speculative volume forecast . This obviously did not go unnoticed within the organization of my client.
A few months after the utilization study, I was approached by a high ranking Product Line Manager of the same company asking me if I could help him with a forecast problem. He had made the observation, that only about 40% of the products shipped could also be found in the forecast of the sales organization. Based on my knowledge of the utilization study, I suggested to the manager that investigating if politics could be a root cause for this obviously very biased forecast might be a good starting point.
Once this amanager became aware that politics could be at play, his interest to improve the forecast vanished almost totally. He probably started to think of the taunting change management task needed to change the forecasting behavior of the sales organization. He probably also did not want to be the whistle blower initiating such a program.
Why is it worthwhile to look into such a thorny issue as forecasting? It is not for the satisfaction to increase forecast accuracy. Forecasts by nature are inaccurate otherwise they would not be forecasts anymore. We will obviously later have to look into the question what level of inaccuracy is tolerable for the organization and the enterprise as a whole. Right now I am more concerned that the time devoted to forecasting is well spent.
In their book Sales Forecasting Management –A Demand Management Approach, John T. Mentzer and Mark A. Moon give us an indication on how much time sales people in B2B sales organizations spend on forecasting. The average was 3 hours per month. If you are in this range you might not be so concerned about the efforts that go into forecasting. But if you are in the range of those 10% of the respondents who’s sales people spent 20 or more hours per month with forecasting, (this is the range where most of my clients are) this is a significant reduction in the time available to be spent in front of customers. You then have all interest that this time dedicated to forecasting is well spent. If the result of this effort is biased forecasts like the one described above, I doubt you can consider this time well spent. We will look at other root cause of biased forecasts in future entries.