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Explore the significant impact of Machine Learning and Artificial Intelligence with your Forecasting and Demand Planning

About this White Paper:

Your skepticism about the hype surrounding machine learning and AI is justified. This is especially true when it comes to forecasting and demand planning, as these domains don’t fit the typical use cases proposed for these technologies.

By using the word “augmented” we propose that machine learning and other algorithms can assist demand planners in doing their job. We are not suggesting that AI and machine learning are going to replace demand planners. Rather, demand planners can rely on these technologies to help them do their jobs better.

In this white paper, you’ll learn how Machine Augmented Demand Planning (MADP) can help make planners more productive and achieve better demand planning performance.

What is Covered:

  • How MADP can help your Data Engineering with Anomaly detection, Aligning data from multiple sources, and imputing missing product attributes.
  • How MADP can help your Forecasting Models with improved accuracy on predictions, time series forecasting and stock-out predictions.
  • How MADP can help your Planner with value-added override decisions and planned risk assessments.

About The Author

Rob Stevens

Vice President, First Analytics

As part of the leadership team at First Analytics, Stevens helps companies develop and execute programs to cultivate their analytics competency. In his 25 years as an analytics professional, he has held consulting, product development, client service, technical and sales roles within software, consulting and market research firms such as IRI, Ernst & Young, Accenture and SAS. He has implemented analytics solutions in many domains within manufacturing companies, particularly in consumer products, including the areas of marketing, consumer insights, supply chain, human resources and plant operations.

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