Demand forecasting could be the foundation of all data-driven decisions in some of your business processes. It optimises all sorts of aspects of the supply chain, including distribution planning, production scheduling, inventory management, and strategic staffing. It lowers costs, improves services and reduces CO2. Learn more about what demand forecasting exactly is, how it works and why you should have it.
Demand forecasting is the type of data analytics that use algorithms to predict future demand of items, sales, transactions or whatever drives the demand, using historical data, past events and trends such as seasonality, weather, events and/or the competition. Essentially, algorithms process large sets of (historical) data to build models that predict the future with a certain confidence level. With accurate forecasts, managers in all aspects of the supply chain can make well-informed business decisions for staffing, logistics, sales and inventory.
There are plenty of theories and methods available for forecasting different types of patterns. They have however one thing in common: they work well in one situation but not in others. Therefore, all algorithms are trained on the same data and the one best suited to that situation or type of demand is picked. By using actual data, accuracy can be monitored and the approach can be changed automatically if it would lead to more accurate forecasts.
One of the implementations of demand forecasting is in inventory management.
Accurate demand forecasting gives powerful insights on how much, when and which products should be stocked in inventory. Forecasting can then be utilised to better align sales and marketing efforts and reduce the risk of stock outs, resulting in lower holding costs and increased turnover rates.
Simultaneously, demand forecasting also allows operational alignment in terms of logistics and workforce. Knowing exactly what demand will be, allows planners to coordinate their logistics and distribution with the right amount of vehicles, optimise routes and streamlining their warehouse activities. This lowers logistic costs and maximises asset efficiency.
Another area where demand forecasting can be of great help is in workforce management. Demand forms the perfect base to build schedules on. Labour demand forecasting, as we call it, allows you to translate demand into required head count and opens up doors to optimised shift creation and shift filling opportunities. An example is slightly undercovering demand when costs have to be reduced and overcovering demand when high service to customers must be guaranteed. With labour demand forecasting, costs will decline and service levels will increase.
Demand forecasting has been around for a long time, but with the newest technologies demand forecastings are more accurate than ever. It has also been easier to generate these forecastings more frequently, tweak and tune them manually and to understand the results. They give a deeper understanding of the available demand data and form a powerful tool to start optimising operations across the entire supply chain.
Want to learn more about how this algorithm works and how it can improve your operations? Go to www.widgetbrain.com/demo.
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