John was recently promoted to assistant plant manager. He was provided with the production demand requirements for the next quarter. The leadtimes appear reasonable, and he is confident of the factory team’s ability to produce. Before his promotion, the factory had adopted a number of best practice manufacturing methods.
The problem is, John has never been held accountable for forecasting production output. While he is confident in the company's ability, this is the first time he has to present a forecast to the management team, and he wants to be accurate. In thinking about how to prepare his forecast, he considers who else forecasts regularly to management. Actually, all of the department managers forecast, but everyone seems to use a different method. Upon consideration, John realizes that the sales manager forecasts most often and has been successful at staying with the company for many years, so John decides that he should consider emulating the sales manager’s forecasting method.
The next day, John asks a production team member what his or her production status is. How many units do they have in-process at their workcenter? He asks each person what they think the probability is (in percentage terms) of completing their units in the relevant time frame. Based on the collection of that individual information, John builds an output prediction based on the weighted average of each of their probabilities.
This seems like a good idea, and sales uses it all the time. But when John meets with his boss, Steve, and explains his ideas on how to forecast, Steve isn’t happy with John’s forecasting method. When John says he copied it from the sales manager, Steve explains that sales cannot accurately forecast anything, and their methods prevent them from ever being able to do so. John explains to Steve that one of the things he learned from the sales manager was that while he was interviewing his people to get their forecasts of production, he could also motivate them to try to do better. In fact, the sales manager claimed to have great success at getting his people to commit to increased production during those motivation sessions. John says maybe he could get the shop to do even better by emulating that management method.
Steve suggests to John that if the sales manager were to emulate the plant’s forecasting and management methods, he might have more accurate forecasts, and more importantly, increased sales and operating efficiencies.
If sales were viewed as a flow, then lean thinking methods could be employed. Once a flow description of a sales process is in place, experimenting is possible by changing an activity in the selling process and monitoring the effects through feedback to determine how the change effects the outcome (sales). Anticipating what the sales manager would say about too many variables to accurately identify cause and effect, Steve reminds John of how, not that long ago, factory managers believed the same things about their complex processes. What production people learned is that the process works, and even more importantly, when the output changes, the flow model allows them to identify what was the intrinsic cause. The same is true in a sales flow model.
Further, the same management concepts, such as constraint theory, lean thinking and continuous improvement methods could probably be applied to manufacturing customers, if someone thought about it that way.
Steve points out to John that the sales department could view their sales reports in a whole new way. These new sales management reports could provide useful yield information from stage to stage as well as other in-process information such as throughput rate. Using these new process reports based on system yield and sales process rates, sales could provide much more accurate forecasts than the ones they currently provide. Further, sales management would be able to identify where to focus to improve sales performance rather than running month-end and quarter-end sales incentive programs.
