How Machine Learning is Transforming the Demand Planning Process

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How Machine Learning is Transforming the Demand Planning Process

JDA research reveals that excess inventory is a growing problem for companies across all industries, and the associated costs of insufficient forecasting accuracy are staggering. “According to IHL Group, a research firm, in 2015 the cost to companies of overstocking was around $470 billion and of understocking $630 billion worldwide. Faced with growing supply chain complexity and demand volatility, improving forecast accuracy has become a top priority for many companies.”

JDA asserts that the availability of real-time digital signals has the potential to provide demand planners with new information about demand drivers and customer behavior. However, many companies have not had the technology or processing power they need to analyze hundreds of real-time data signals and derive insights from it.

This JDA white paper defines how new cognitive demand-planning capabilities make improving forecast accuracy a reality for many companies.

READ MORE FROM JDA

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By | 2019-10-08T15:37:27+00:00 October 8th, 2019|forecast, Uncategorized|0 Comments

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