Story originally appeared in Modern Materials Handling on the Jan. 12, 2021. Excerpts from the story below. To see the full story visit MMH.com.
Today’s planning software makes use of artificial intelligence (AI) and machine learning in a way that constantly evolves as the software sees more data, in a way that “tunes” the planning engine so it can identify the trends that are here to stay as well as the outliers, explains Amanda Oelschlegel, pre-sales director at supply chain software provider Blue Yonder.
“While historical data is used for the initial machine learning ‘training,’ real-time data is constantly feeding the engine and corrections are being made,” says Oelschlegel. “Additionally, the longer you feed these engines, the more data aggregates and the ‘outlier demand’ becomes known. This allows for situations like crazy spikes in toilet paper to be reacted upon quickly, because the demand spike is being seen for long enough for the engine to realize it is not a blip on the radar.”
In The News
- Data Cloud Podcast: Building the World’s Largest Supply Chain Data Cloud with Duncan Angove, CEO at Blue Yonder
- Forbes: We’ll Never Fully Trust Artificial Intelligence With Our Businesses — And That’s Okay
- Automotive Industries: Blue Yonder accelerates automotive innovation with strategic flexis acquisition for supply chain transformation
- eCom Logistics Podcast: Modern Logistics Challenges: Strategies from Blue Yonder’s Ann Marie Jonkman at Modex 2024
- Logistics Viewpoints: How Can Your Supply Chain Become Even More Resilient?
Analyst Reports
- IDC ProductScape: Worldwide Warehouse Management Systems, 2024
- IDC’s Worldwide Retail Industry Spending Guide Taxonomy, 2024
- Gartner Critical Capabilities for Transportation Management Systems, 2024
- Gartner Magic Quadrant™ for Transportation Management Systems, 2024
- IDC Market Glance: European Supply Chain Planning, 1Q24
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480-308-3037
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Celeste White
Vice President, Global Analyst Relations
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