Predictive Analytics will Improve the Supply Chain

Predictive analytics is the ability to use data to predict future activities. It enables real-time decision making and forethought on both strategy and performance. According to an interesting article by Gary Brooks at tdwi.com, predictive analytics is on the horizon for the supply-chain and the after-sales service industry. An industry, which he notes, that’s worth more than 9 billion dollars by the year 2020. Brooks proclaims that the predictive analytics predictive nature is what will make it the next big thing in supply-chain business intelligence.

In the article the author discusses three different main areas of opportunity that he predicts predictive analytics will take hold; Predictive Demand Forecast, Predictive Pricing and Predictive Maintenance. These three areas each focus on a different important element in the supply-chain structure.

Predictive Demand Forecast is a fundamental part of efficient supply-chain management. Predicting future demand for products and services based on past events and trends can improve manufacturers service and cost efficiency.

This area goes hand-in-hand with Predictive Pricing. With accurate predictive pricing manufactures can incorporate different factors that can affect sales, such as location, demand and seasonality. This can further lead to more easily adjusting prices based on the current market.

The old saying; “If it aint broke, don’t fix it” is nowadays outdated and misleading. The break-fix service model which the saying is based from are, according to Brooks, both too reactive and inefficient. He points to that over fifty percent of service attempts fail because the needed service was not available when needed. Which, he adds, leads to lost revenue and unhappy customers due to product downtime.

I recommend you read more about this interesting area here, where you can read the whole article.