Inventory Management: Grab the Bull by Both Horns
Statistical Weekly Forecasting
Internet sales planning has two fundamental differences from catalog. One, the annual sales trends are more consistent over time, as there aren’t single mailing dates where millions of catalogs are released. Two, the planning time horizon is much shorter because product changes can be made in a matter of hours. This requires an approach to demand forecasting that’s better suited to evaluating the factors that drive sales on the Web site using statistical weekly forecasting.
Statistical weekly forecasting incorporates a blend of high automation with targeted controls. Actual sales information is evaluated within statistical forecasting methods, such as exponential smoothing or dynamic regression. When a business has enough sales data, extremely reliable forecasts can be derived from historic trends.
The base forecast is computer-generated, freeing up staff time to adjust forecasts to recognize ever-changing Internet marketing events, such as e-mails, homepage features and temporary promotions. With statistical weekly forecasting in place, users spend less time forecasting and more time making purchasing decisions.
Changing Your Approach
There’s no single right answer to an individual company’s forecasting technique. For most catalog-driven businesses, the best strategy is to apply offer-based forecasting to time periods, either calendar quarters or months. Because catalog mailings are still the dominant factor in sales trends, this technique most easily and accurately forecasts the impact of catalog plans on Internet sales time periods. Conversely, if a company has extremely stable catalog mailings with few product changes from year to year, the statistical forecasting technique may be best.
Since forecasting is only half the game, it’s equally important to have an inventory master-scheduling tool that incorporates future demand and on-hand and on-order inventory by week, along with estimated returns by week to calculate inventory level by SKU by week into the future.