MXI Tips to improve the Product/SKU level forecasting
We sell the market leading desktop SKU Forecasting Tool in Britain and Ireland. There are 3 versions of the product. 20,000 users world-wide including Toyota, Coca Cola, Amazon. MXI customers for Forecast PRO include Johnson & Johnson, Siemens Medical, Gowan Group, Irish Airports Authority (Aer RIANTA)
- Forecast PRO XE for 300 sku or less,
- Forecast Pro Unlimited to collaborate with colleagues handling 1000's of SKU.
- Forecast Pro TRAC. TRAC brings Forecast PRO into the realms of Sales and Operations level planning.
TIPS 1. Excel for forecasting.
Tempting, most people have Excel and a time series sheet of data that needs forecasting. However the Trend line feature in Excel is the least effective over 20 techniques for forecasting because of value it applies to older time series data ignoring the more valuable trending in recent data. Not ideal for managing the recession in consumer spending. Better to spend a little and use a proper exponential smoother.
2. Try Exponential Trending
Exponential smoothing recognises the value trend, extracts the surrounding noise in data can apply seasonality, trend and special events. Statistical results show exponential method to be one of the most reliable means of forecasting. Exponential smoother is also known to perform reasonably where there is limited historical data available.
3. Even Forecast/PRO Software can't deliver immediate results.
It takes time, trial and error is the best way forward in terms of planning. Once implemented take the time to learn your data and get to know the results. Be prepared to challenge the results. Consider separating data into 80 / 20 paretto analysis. Splitting some data into product/family (aggregating) levels and some at the SKU level can be effective.
4. Don't Automate too much.
Data needs checking all the time to improve relevancy. Even processes that are comfortably bedded need validation. Best practice and Industry leading performance can only be enhanced through regular monitoring.