Category: Demand

analytics

Case Study: A Scrappy Demand Management Approach

This study of Franklin Sports shines a light on the work that needs to be done at the sales account level to challenge a retail forecast, and also highlights the importance of a new technique for a forecast engine — reinforcement learning.

Artificial intelligence comes in many forms — large language models, generative AI, machine learning, unstructured text mining, deep learning, neural networks, reinforcement learning, agents, and agentics. While the industry is wigging out about agentics, I think reinforcement learning is a great step forward in the journey of Artificial Intelligence.

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analytics

If Only 2020 was 2020

The pandemic is in our rearview mirror. Many of the lessons from the pandemic that helped companies succeed are forgotten, but should not be.

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demand driven

Outside-in Process Q&A

On Friday, I presented an overview of outside-in planning to a consulting group. I love the questions when I present. The reason? The dialogue helps

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analytics

Driving An Octopus

My Quest To Redefine Planning The focus of many discussion threads on LinkedIn this week focused on building better engines for planning. The discussions included

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analytics

The S&OP Technology Quadry

Sales and Operations Planning (S&OP) is a business process. When the design is a supply chain-centric design, problems arise. I have tracked maturity levels in

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analytics

No Time Like the Present

In the face of disruption-after-disruption, now is the time to ask should be redefine supply chain planning and execution. Lora Cecere, Founder of Supply Chain Insights, says it is time. The value proposition is improving the time to make a good decision.

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