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Cracking the Code for AI in the DC

Logistics Viewpoints

There’s a new reason to optimize DC operations, and it’s bigger than the old reasons of productivity and efficiency gains. More and more companies are realizing that investing in their DCs and powering them with modern and sophisticated technologies like AI can lead to competitive advantages for the overall company. Dynamic Slotting.

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Probabilistic Forecasting Can Extend the Life of SAP APO

ToolsGroup

Since the beginning of time – OK, since the beginning of demand forecasting the standard approach has been a single number forecast that works relatively well with stable high volume demand. Traditional forecasting tools such as SAP APO, designed 25 years ago or more, generally hold their own in this environment. Under the Hood.

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Invest in These Capabilities to Drive Supply Chain Excellence

AIMMS

Use cases include analyzing the impact of Supplier and DC closures and shutdowns, planning for steep demand decreases and increases, evaluating potential reshoring, and assessing potential network investments with scenarios. The machine learning algorithm then continually fine tunes the forecast model through each forecasting cycle.

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A New Decade: Give Science A Chance

Supply Chain Shaman

The SAS forecasting system implemented in 2019 was not tested for model accuracy. An example for this client would be to use 2017 and 2018 history to forecast 2019. So, I asked the questions, “Is your data forecastable? Data at this level of variability is complicated to forecast.) The reason? The answer?

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Things Have Changed: What Do We Do NOW?

Supply Chain Shaman

This week I interviewed Robert Byrne, Founder of Terra Technology , on the results of their fourth benchmarking study on forecasting excellence. The work done by Terra Technology, in my opinion, is one of two accurate sources of benchmark data on forecasting in the industry. The other is Chainalytics demand benchmarking.

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Companies Improve their Supply Chains with Artificial Intelligence

Logistics Viewpoints

Machine Learning, a Form of Artifical Intelligence, Has Feedback Loops that Improve Forecasting. A supply chain planning model learns when the planning application takes an output, like a forecast, observes the accuracy of the output, and then updates its own model so that better outputs will occur in the future.

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Simplify Supply Chain Forecasting

Logility

Is 100% forecast accuracy attainable? Anyone that has ever had to forecast demand for products or services knows that obtaining a consistently high forecast accuracy is part science and part magic. Clearly, forecast accuracy is very important. Should it be? Wouldn’t that be called an order? Learn from your Peers.