Archive for December, 2009
Sales and Operations Planning: Are Executives Killing Collaboration?
Why do some executives feel inclined to make substantial forecast changes based solely on their own judgment? There’s no doubt the typical executive has keen insights into the business she directs. Yet, when that executive chooses to override other inputs, she undermines the integrity of the collaborative process.
“Why should I put any effort into creating a forecast when I know he will change it anyway?” This quote came from a client with whom I worked. The clear message was that their company’s collaborative forecasting process was not supported by the senior executive who had the final say in what the “consensus” plan would be. His actions unintentionally conveyed a message that the Sales and Operations Planning process which led to his desk had little merit in his eyes. The prevailing sentiment shared by S&OP participants was that their work was unimportant.
Opportunity lost! Executives must understand that S&OP can be successful only when they are engaged and supportive. Trumping the collaborative output sends a demoralizing signal. Empowered participants deliver superior results.
An effective S&OP process leverages inputs from across functional disciplines and at various levels of responsibility. Most decisions should be made prior to the Executive S&OP meeting. Executives should focus on setting policy, reviewing lower level decisions, breaking ties and making critical, strategic decisions.
Don’t kill collaboration. Empower participants and achieve better results.
By the way…the executive who applied his own final forecast values achieved forecast accuracy levels worse than if they had used the statistical forecast alone. Lots of analysis and meetings with nothing to show for it!
Sales and Operations Planning, Collaborative Demand Planning Depends on Bottom-up, Top-down and Statistical Forecasting
An effective S&OP program depends on solid, accurate demand forecasts. Best practice companies do three things well: statistical, top-down and bottom-up forecasting. Many companies are doing one or two of these, but few are doing all three well. Of course, some companies do none. Let’s just say these companies have a huge upside improvement potential.
A statistically generated forecast should use a “best fit” approach to select the mathematical algorithm that minimizes error (such as mean absolute percentage error (MAPE)). The statistical engine should select the best algorithm for each time-phased data series or set of regression data. The resulting forecast should serve as a starting point for bottom-up and top-down forecasts.
Bottom-up forecasts are accumulated from many contributors. A distributed sales force may have hundreds or thousands of contributors. Each contributor has a specific area of expertise such as a specific customer, product or geographic area. The contributor enters her forecasts for her specific area of responsibility. Forecasts from all contributors are summed to capture an overall bottom-up forecast.
Conversely, a top-down approach applies a more centralized view. A small number of forecasters will look at various inputs and generate forecasts. Influencing factors may include market data, economic indicators, and general product and customer trends. Here, too, the statistically generated forecast is a good number from which to start.
The beauty of top-down and bottom-up forecasts is their ability to look at the world from differing vantage points. The folks in the “ivory tower” know important information, but they don’t know everything. The folks in the field have keen insights into their unique areas, but they only see their small piece. The challenge is to capture the small pieces without tainting the field forecaster’s view. In other words, don’t tell the field forecasters the top-down targets. When field forecasters are told what their forecasts are expected to be, they tend to send back values right in line with the top-down values. Such tainted bottom-up forecasts miss the point of gathering field intelligence.
An effective marriage will capture top-down and bottom-up forecasts separately. A management by exception S&OP tool will make comparisons quickly to enable users to analyze critical differences and refine the ultimate consensus driven forecast.
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