Remove Case Study Remove Forecasting Remove Supply Chain Software
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Thoughts. Selecting Supply Chain Software

Supply Chain Shaman

I find that most companies’ understanding of supply chain planning is immature, and that next week, at the Gartner Supply Chain Summit in Orlando, that many will don their Mickey ears to discuss what I consider outdated supply chain planning models. How can I improve the process of software selection?

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How Technology Makes Continuous Innovation Possible: A Case Study with Unilever

Logistics Viewpoints

In the corridors of Unilever, a team of dedicated supply chain planners from demand to supply to transportation embarks on a daily journey. End-to-End Supply Chain Planning Platform The end-to-end process begins with data. The result is an end-to-end planning process operating on the highest quality data possible.

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Can Improving Forecast Accuracy Address Our Demand Planning Woes?

Logistics Viewpoints

If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? Artificial intelligence and machine learning ( AI/ML ) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves.

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Melitta: Collaborating for an Improved Forecasting Process

ToolsGroup

Melitta Sales Europe (MSE) embarked on an initiative to revamp existing planning and forecasting processes to increase efficiency and sustainability. With over 6,700 SKUs across various brands and locations, the team needed to modernize its sales and operations planning (S&OP) process with new technology. A Perfect Brew.

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We Should Not AI Stupid

Supply Chain Shaman

He shared that he worked for a freight forwarder providing supply chain planning services for a major retailer. The organization had little energy to test forecasting models. As a result, the project implemented by KPMG was primarily a technology implementation. The software was never tested.

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Supply Chain Forecasting with AI

ThroughPut

In the ever-evolving landscape of global commerce, businesses face a significant challenge: the pain of inaccurate forecasts and the relentless pace of market conditions. The agitation stems from the financial loss and operational inefficiencies accompanying these inaccurate forecasts. AI in supply chain forecasting is a game-changer.

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Supply Chain Forecasting with AI

ThroughPut

In the ever-evolving landscape of global commerce, businesses face a significant challenge: the pain of inaccurate forecasts and the relentless pace of market conditions. The agitation stems from the financial loss and operational inefficiencies accompanying these inaccurate forecasts. AI in supply chain forecasting is a game-changer.