Imagine you’re in the middle of the monthly S&OP meeting, and you’ve come to the point on the agenda that says: “review forecast accuracy KPIs”. You can already feel the Salespeople zoning out because they don’t have a clue what you’re about to talk about. And when we talk at length about MAPE and the like, can you blame them?
Salespeople are not familiar with forecast accuracy measures. They have no reason to be because it is not clear how these KPIs add value. They don’t help sell a product and they don’t make money in any obvious way. For me this is quite understandable and touches upon an important concept – that there has to be demonstrable monetary value in every step of the S&OP process. If our KPIs don’t reveal to other functions how S&OP makes the company money, then we’re not doing or jobs properly.
One way to get Commercial’s buy in into S&OP process is to show forecast accuracy as a cause-effect relationship
Show Forecast Accuracy As A Cause/Effect Relationship
One way to get Commercial’s buy in into S&OP process is to show forecast accuracy as a cause-effect relationship, showing predicted sales and actual sales, and the reasons for those particular numbers. What’s more, we need to demonstrate tangible KPIs like inventory, OTIF (On Time In Full) and SLOB (Slow moving and obsolete). These are far more real and relevant to the Salesperson than MAPE. You can easy explain how decreasing SLOB has a positive effect on bottom line, but are you going to convince Sales of the value of MAPE? Almost certainly not.
Often we lose track of this basic idea – that everything we do is designed to make money.
Measures like inventory level, OTIF, SLOB and write-offs have two main causes: forecast or supply. Tracking root causes behind performance of these measures is a standard activity and translating these into dollarized amounts will get peoples’ attention. Inventory, SLOB & write-off cost driven by forecast error is something everybody in monthly S&OP meeting should pay attention to.
In most companies you can trace the reasons for unfulfilled orders. Lost revenue due to forecast error is easy to identify – SLOB can easily be attributed to over-forecasting, for example. It’s easy to communicate and gets quite lot of interest from other functions at the meeting. The agenda for the monthly S&OP meeting should include presentation of KPIs, not only forecast accuracy but all financial KPIs affected by the forecast. Make sure to discuss the root causes.
Dollarize Your Forecast Accuracy
The main goal of S&OP is to increase profitability by fulfilling the highest level of customer orders whilst optimizing inventory. It is impossible to present the results of a Demand Planner’s work without referring to main these main principles. But often we lose track of this basic idea – that everything we do is designed to make money. In Forecasting and Demand Planning, there is not enough space dedicated to dollarizing forecast accuracy. Dr. Jain, Editor of the Journal of Business Forecasting, said in one of his interviews that “an average company can save $3.52 mil. for every one-percent improvement in the under-forecasting error, and $1.43 mil. in improving the over-forecasting error.” That speaks for itself and if you can put MAPE in these terms, that X increase in your forecast accuracy has delivered Y dollar amount, then Sales will immediately be more engaged.
Showing your forecast accuracy in this way, including historical data to show improvement, is a way of communicating the value of the S&OP process. This can help secure resources for the process like more staff. Not only that, making it clear to Sales that we as Demand Planners actually make money will make them more inclined to give us their time.
The key to success here is to show the impact of forecasts in dollarized amounts.
Evaluating Your S&OP With KPIs Is Very Important
A big topic of conversation in the Demand Planning community is how to make S&OP work and research shows that a lot of he time, it just doesn’t work at all. If S&OP isn’t working for your company, remember that a good process measures its outputs and evaluates itself. As S&OP is the process that all function are plugged into, all functions should be interested in how it’s performing. Forecast accuracy metrics are not always interesting for commercial functions because they are complicated or appear irrelevant. The mathematical calculation formulas might be off-putting for the less numerically inclined, but the good news is that the interpretation is quite easy and straightforward. The key to success here is to show the impact of forecasts in dollarized amounts.