Machine Learning 101 for Supply Chain Leaders Part 3: Prioritize Use Cases and Gauge ROI

Published: 05 February 2018 ID: G00349014


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Machine learning's potential to augment and automate decision making across the supply chain cannot be underestimated. This research provides supply chain leaders responsible for artificial intelligence and analytics with best practices in prioritizing ML use cases and gauging ROI.

Table of Contents

  • Analysis
    • Choose Supply Chain Use Cases That Increase the Likelihood of Machine Learning Success
    • Learn From Early Industry Experience With Machine Learning
    • Clarify Expected ROI From Machine Learning Investments
    • Clearly Identify Risks Associated With Short-Term ML Adoption
  • Gartner Recommended Reading
© 2018 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction and distribution of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartners research may discuss legal issues related to the information technology business, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice.

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