10 to 20 gets you 2 to 3 to 5 - Revenue and Profitability

This webinar will explore how to realize a 10-20% increase in demand forecast accuracy using advanced machine and deep learning techniques to smooth out traditional demand forecasting approaches.

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Aging supply chain and inventory management practices, and technologies, pose a growing challenge to revenue lift, margin retention and growth, and cost of goods sold operational goals. Especially in a  global environment of increasing instability with continuous disruption. 

Continuing to plan and execute in operational silos, with disparate datasets and tools and attempting to integrate your way out of these silos will become increasingly challenging. Let alone the need to synchronize the integrated processes and datasets. Remaining in this operational state will continue to foster poor demand forecast accuracy, leading to lost revenue at point of sale, and higher inventory plus carry costs.

This webinar will explore how to realize a 10-20% increase in demand forecast accuracy using advanced machine and deep learning techniques to smooth out traditional demand forecasting approaches. It is not necessarily about replacing current approaches but making them better – improving master data decision making quality, reducing exogenous and internal process volatility and improving demand forecasting accuracy.  Doing so can result in a 2-3% revenue lift and a 5% inventory cost reduction in the network. 

An actual customer case will also be discussed.

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About the Author

Brian Straight, SCMR Editor in Chief
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Brian Straight is the Editor in Chief of Supply Chain Management Review. He has covered trucking, logistics and the broader supply chain for more than 15 years. He lives in Connecticut with his wife and two children. He can be reached at [email protected], @TruckingTalk, on LinkedIn, or by phone at 774-440-3870.

View Brian's author profile.

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