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
- iTWire (Australia): How Blue Yonder is Applying AI and Innovation To Solve Supply Chain Challenges
- Modern Materials Handling: Blue Yonder’s Logan Kluth on the Real Value of Cloud WMS
- SiliconANGLE: The Road to Intelligent Data Apps With Blue Yonder’s Chief Product Officer, Gurdip Singh
- FreightWaves Running On Ice: Prioritizing The Vaccine Supply Chain
- Sourcing Journal: Blue Yonder’s Sónia Peres On AI/ML’s Role in Fashion, Retail
Analyst Reports
- IDC Market Analysis Perspective: Worldwide Warehouse Management Systems, 2024
- Gartner Maximize the Value of AI in Supply Chains With “Whole Product” Use Cases
- IDC MarketScape: Worldwide Professional Services Providers for Retailers 2024 Vendor Assessment
- IDC Market Analysis Perspective: Worldwide Transportation and Logistics, 2024
- IDC Market Glance: Retail Last Mile, 3Q24
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