The Sales and Operations process is not well understood in many companies. The information collected by the Sales department is often inaccurate and incomplete, because, unfortunately, forecasting and gathering data is not the first priority of a sales department, but rather done as a necessary evil and an afterthought.
If not done well, and if the Operations personnel has little confidence in the data, various things will happen that denigrate the company’s ability to have the right quantity of the right stock at the right time. The following case study illustrates this point.
Our client had its distribution warehouse, production facility and Sales/Marketing operation in three different locations. They were having difficulty keeping the optimum amount of inventory in their distribution warehouse. This resulted in back orders and low customer fill rates.
The major issues revolved around their forecasting operation and how it provided information to the production facility, and in addition, their sales and operations process as a whole.
Analysis surfaced a disconnect between the forecast information and how that information was being used at the production facility. In addition, forecast error was not being measured correctly and management had a more optimistic view of the forecasting effort than was actually warranted. There was also “gaming” involved by the Sales team in that they added a certain percentage to the forecast to encourage the production facility to hit the target rates.
This resulted in an even bigger disconnect between Sales and Operations as the separate production entity could not have the required confidence in the forecasts and thus would “chase sales” rather than adhere to the forecast.
This was compounded by the fact that each entity had its own disparate system, each out of balance with the other two, despite IT’s efforts to interface them. There was always a timing difference between the systems, and even if this were only one day, it meant that people were always looking at different figures. This also adversely affected confidence.
The correction achieved was the removal of the forecast bias, along with the correct calculation and publication of the forecast error, which began to improve the forecasting techniques and give the production facility more confidence putting together its build schedules.
The second correction was to set up a formal Sales and Operations process that kept forecasts in line with production schedules and moved the responsibility for the inventory levels from Production to Sales/Marketing.
The third action was a complete analysis of their disparate systems situation so that management understood the cost in lack of visibility of not having a comprehensive Distributed Requirements Planning (DSP) and Enterprise Resource Planning (ERP) system.
In a 4-month time frame the company was able to significantly improve its back order situation and its customer fill rates. There was also a foundation in place for future improvements, as they now had a good forecasting method, accurate measurement, and, resulting from the Sales and Operations process improvements, a more cohesive alignment of production and forecasting.