Product portfolios are getting more diverse and therefore segmentation can help to provide focus on the part which needs most attention. Traditional 2×2 or 3×3 frameworks are widely used in many companies put categorization labels to products, such as AX, CZ, Mad Bull or Mule. However, in multinational companies with multiple business units, it is always a discussion on what aggregation level to perform the segmentation. Moreover, there often is a dispute between marketing or sales with supply chain what measure to use in the segmentation: volume, turnover or margin.
The following story shows you that dynamic segmentation can support every single business person in their own customized way to put focus at the right level and with use of the fit-for-purpose measure.
Forecast Value Add
Forecast accuracy has always been measured, but now it is becoming a key performance indicator (KPI) for many supply chains. But are we measuring the right thing? Most companies use forecasting performance metrics to determine how good the forecasts are, such as:
|Mean Absolute Percentage Error (MAPE)||R-Squared|
|Weighted MAPE||Root Mean Squared Logarithmic Error (RMSLE)|
|Mean Percentage Error (MPE)||Log loss|
|Mean Squared Error||Weighted Mean Absolute Error|
|Weighted Absolute Percentage Error||Root Mean Squared Percentage Error|
|Mean Absolute Error|
The problem with all of these metrics is that is does not explicitly say if the forecast was poor, mediocre, adequate or good. Therefore measuring forecast accuracy against a benchmark is better alternative.
A forecast process typically exists of multiple steps:
- Naive statistical forecast
- Advanced statistical forecast
- Demand Planner enrichment
- Marketing enrichments
- Financial enrichments
Why not take the previous step in the forecast process as a benchmark for the next forecast version? The following story shows you how visualization can help to evaluate the added value of each step in the forecasting process
Within FMCG promotions have a severe impact on business planning. If you’re able to forecast promotions overall predictability is easy! As the frequency and depth of promotions is steadily increasing in many different product categories, the need for a more professional promotion planning and forecasting is inevitable. A good starting point for this is to first get a better understanding of your promotions with the use of visualization. The following story guides you through several examples on how promotions insights can help you the get a better understanding of your promotions and can function as a starting point for creating more complex promotion forecast models.