How to Boost Your Forecast Accuracy
- Determine ABC Pareto analysis in terms of COGs.
- Assess the ‘forecastability’ of your product portfolio
- Classify your products based on the ‘forecastability’ rating of each SKU.
- Test the quality of your existing forecast in terms of accuracy, bias and nervousness
- Model, test and compare the quality of forecasts using of alternate forecasting algorithms.
- Tell you what you need to do to improve your forecasting performance and inventory outcomes.
Typical Benefit: ~ 4% – 5% forecast accuracy improvement.
Who is it for? Supply Chain and Demand Managers who ask themselves “How ‘good’ is our demand forecast?”
What you get? A customised report comparing the quality of your forecast (accuracy, bias and nervousness) to the statistical forecasting results using at least 5 different forecasting algorithms.
How good is your demand forecast? Can we beat it? In our Forecasting Benchmark analysis, we use your demand history to assess the ‘forecastability’ of your portfolio. We then simulate statistical forecasting, calculating 12 months of SKU forecasts using at least 5 different forecasting methods. After comparing these results with your own forecast we’ll recommend a forecast benchmark method and accuracy for your business.