The global predictive analytics market is set to be worth more than $12 billion USD by 2020, according to research by MarketsandMarkets, thanks to its ability to make accurate and real-time predictions and inform business strategy. How does it impact the world of warehouse planning and supply chain management?
The point of warehouse demand planning aims to help businesses understand future demand and plan buying needs accordingly. They make predictions so that they can keep their customers hwp-contenty by fulfilling their orders in their promised timeframes and yet not have large amounts of unsold stock go to waste.
Predictive analytics means accurate and up-to-the-minute forecasts that inform future buying strategy.
Where predictive analytics makes a difference is in saving valuable time while also providing more accurate forecasts. Predictive analytics as a term, encompasses a variety of statistical analysis and modelling techniques, machine learning and artificial intelligence to make predictions about the future. In warehouse demand planning, predictive analytics means accurate and up-to-the-minute forecasts that inform future buying strategy.
What makes predictive analytics key to modern warehouse demand planning?
Warehouse demand planning has to encompass seasonal fluctuation to understand how much stock is required at a given time of year. Predictive analytics combines historical sales data, recent demand and any number of other variables to create as accurate a forecast as possible. Being able to base predictions on such a large amount of data makes predictive analytics a powerful forecasting tool that supports other types of business planning.
The point of warehouse demand planning is to fulfill customer orders as quickly as possible without costing the company any more than necessary. In practice this means ordering new stock at just the right time to maintain supplies without having money tied up in unsold products. With older reporting, the data is only useful the second it was produced. However, predictive analytics is based on real-time data and machine learning that allows the system to identify the optimum time to re-order.
Predictive analytics is all about planning for the future, and every business needs to be forecasting ahead to ensure it remains competitive. Because predictive analytics keeps learning as new data becomes available, it can create predictions about future demand and shape warehouse operations and business buying strategy in years ahead. As each forecast season gets closer, predictions start to take into account smaller variables in the supply chain such as current lead times or weather-related delays that keep the financial planners up-to-date at all times.
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