Downloaded 16 times
Uploaded byWensheng Li
Demand forecasting
This document discusses demand forecasting and outlines several key points: 1) It distinguishes between stock and non-stock items, with stock items having high activity and low value, and non-stock items having low activity and high value. 2) For items with sporadic usage, it recommends maintaining stock based on a multiple of typical sales quantities or setting them up as non-stock. 3) When forecasting for items with recurring usage, it suggests considering past usage trends, internal trends, external factors like weather and economy, and collaborative forecasts from sales and promotions teams.
Demand forecasting
- 1.
- 2. Stock vs. Non-stock •Ranking products based percentage of total activity (number of hits) • Non stock items – Low activity and high value items • Stock items – High activity and low value items
- 3. Demand Forecasts andUsage • Products with sporadic usage – Maintain the stock based on multiple of the typical sales or usage quantity. – Roll up the usage to the central warehouse – Or set up as non-stock items? • Products with recurring usage
- 4. Forecast for itemswith recurring usage • Past usage • Internal trends • External trends – Weather, economy • Collaborative forecasts – Sales input – Special promotion • Forecast horizon
- 5. Past usage • Director drop shipments – Direct shipments should not be included. • Shipping an order from an alternate warehouse instead of the designated one – Usage should be recorded with the designated one. • Usage and substitute products • Record usage when a customer wanted the product – Required date vs. actual ship date? • Usage and transfers – Treating other warehouses as customers?
- 6. Utilizing Usage toForecast Demand • Seasonal products – Consider usage from the last year – Adjusting usage for unusual usage – Weighed average • 3x same month LY +2x next month + 1 following month – Use seasonal index – Applying trend factors • compare last year’s usage with this year’s usage
- 7. Determining the BestForecast Formula • Forecast error % = absolute value of (forecast –usage)/actual usage
- 8.