Supply chain planning, supply management, supply chain execution, network design, and transportation/logistics management operate in silos. Not much has changed over four decades. The connections flow back through transactional systems: order-to-cash and procure-to-pay. There is a myth that companies can buy an end-to-end supply chain management solution. This is largely a myth. Here we explain.
Supply chain is where the rubber hits the road. For a public company, over 40% of market capitalization is tied to the trade-offs between growth, operating margin, inventory management, and Return on Capital Employed.
The road for supply chain improvement is fraught with issues. Here we share some and offer some advice.
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.
When it comes to combining tech, 1+1+1 should equal more than 1. The impact should be exponential. Unfortunately, today, the answer is 0.
What do I mean? Let me explain.
I find that the supply chain technology market moves slowly along traditional technology lines. Conferences are usually focused on the use of technology, not on redefining work. This bothers me. I want it to bother you as well.
Here I share some insights to drive change.
An orbit chart is a powerful tool for understanding the “health” of a supply chain and its potential for improvement. The supply chain is a complex, non-linear system with limited trade-offs. The relationship between trade-offs varies by industry, region, and size. The orbit chart is a diagnostic we use in the Supply Chains to Admire work. Here I explain the use case.
Today, companies require industry-specific supply chain solutions. The performance of 82% of the industries–I term this industry potential–is going backward while companies are trying to
This post aims to shed light on a dark, automated world where supply chain leaders believe they have answers and are busy automating outdated processes but not driving value.
In the first quarter of 2026, the value of the companies offering Software-as-a-Service (SaaS) fell by 25-30%. The sell-off occurred as investors worried that Artificial
The supply chain is knotted. It is unruly. It is complex. It is growing more so. Current supply chain planning deployments often degrade value. This is
The industry need state requires the redefinition of the current taxonomy of planning based on first principles. This is in conflict with the current thrust to automate existing platforms using agents.
