
Accurate demand forecasting is the foundation for optimal inventory management. The more accurately you forecast your sales, the less buffer stock will be required, increasing your inventory profitability significantly. Thrive’s Demand Forecasting is a comprehensive demand forecasting system that will accurately forecast demand for your business. It utilizes proven science to generate automated ‘best fit’ demand forecasts for each of your items.
If your business needs a better way to forecast demand, these capabilities of Thrive's demand forecasting system will help you tremendously:Unlike other systems, Thrive Demand Forecasting automatically detects seasonal patterns where they exist and projects them in the forecast using proprietary harmonic smoothing science. This increases forecast accuracy and reduces required safety stock. With other demand forecasting systems, you have to manually review all your items every year to identify which ones are seasonal and which ones are not. This labor intensive process typically does not get done, resulting in inaccurate forecasts for seasonal items.
Demand Forecasting: Best Fit Forecast recast weekly for all itemsEvery week, Thrive Demand Forecasting analyzes the latest demand, applies several different forecasting models and applies the best fitting forecast to each item at each location. Most demand forecasting systems are engineered to only ‘revise’ or ‘smooth’ forecasts each week because they are inefficient, or were programmed many years ago when computing power is not what it is today. The problem with this is that the forecasts become inaccurate over time as demand inevitably changes for many items. Thus overstock and stockouts start to creep back in, and inventory performance suffers until the forecast is recast again.
Thrive Demand Forecasting is designed to leverage today’s computing power, efficiently crunching the math required to calculate fresh forecasts for all items weekly, utilizing up to 3 years of demand history and considering recent trends, events (such as promotions), lost sales, seasonal patterns, etc.
Users are alerted to changes in patterns of any item's demand forecast that would impact buying decisions (eg. Brand new items with rapid sell through). This ensures the most accurate demand forecasts possible at all times.