Make the right call, when the forecast is wrong.
Analysis and insights for supply chain directors.
The perfect forecast doesn't exist (and that's good news)
The perfect forecast doesn't exist. Our manifesto: stop chasing accuracy, and invest in the decision at the moment the plan breaks.
Read the article→The hidden cost of supply chain disruptions
The hidden cost of supply chain disruptions gets lost in expedited freight, excess stock, stockouts and meetings that drag on. Added together, entire margin points disappear.
Read the article→Supply chain planning software: the 2026 comparison
ERP modules, APS suites, probabilistic, DDMRP: the four families of supply chain planning software compared, how to choose, and the limit they all share.
Read the article→Agentic AI in supply chain: definition, use cases and how it differs from predictive AI
Predictive AI tells you what is going to happen. Agentic AI acts on it. In supply chain, that shift changes how disruptions are handled. Here is what the term really covers.
Read the article→Your biggest losses come after the plan
Companies invest heavily in the quality of the plan, and almost nothing in the quality of the decisions made when that plan goes off the rails. Yet that is where margin is really won or lost.
Read the article→Decision capital: the memory that doesn't walk out the door with your experts
Decision capital is the memory of your supply chain's trade-offs: context, options, outcome. Why that memory is worth so much.
Read the article→You insure your trucks and your plants. Who insures your margins?
Companies insure their assets against rare accidents. They leave their margins exposed to everyday disruptions, which cost far more over a year. What is missing is insurance on what matters most.
Read the article→APS, ERP, decision tool: who does what in your supply chain
ERP, APS, decision tool: three building blocks that are often confused, and worth telling apart so you don't expect a tool to play a role that isn't its own. What each one does, and what it doesn't.
Read the article→S&OP, S&OE, MPS: who decides when the plan breaks?
S&OP builds the plan and the MPS breaks it down, but neither says who decides when reality drifts. That moment is called S&OE, and here is how to equip it.
Read the article→Supply chain control tower: definition and how it works
A supply chain control tower aggregates data from your systems to give a real-time view of flows, from the plant to the customer. How it works, the main families, maturity levels and selection criteria.
Read the article→APS software: definition, strengths and limits
APS software optimizes your production and supply plans: the main vendors, a six-criteria selection checklist and price ranges. Plus the limit few vendors admit to.
Read the article→Replanning production after disruptions: who decides?
Replanning production after a breakdown or a supplier delay: freeze rules, the role of the scheduler and the real cost of each trade-off. And the question that still has no tool: what gets sacrificed.
Read the article→S&OP software: what it does and how to choose
S&OP software aligns demand, production and finance every month on a common plan shared by every department. Here is what it changes, the families of tools, how to choose, and where it falls short.
Read the article→Comparing S&OP software: six criteria for choosing
Comparing S&OP software before you sign: a six-criteria scorecard to choose between APS suites, ERP modules, specialized tools and spreadsheets. And the limit no scorecard measures.
Read the article→S&OE software: managing the week that S&OP doesn't see
S&OE (sales and operations execution) software manages the gap between plan and reality week by week, where S&OP works month by month. Functions, tool families, criteria and the company size where it pays off.
Read the article→Demand forecasting software: how to choose
Comparing forecasting tools is useful. But none of them protects you on the day the forecast is wrong. Here are the selection criteria, and the lever nobody puts on the table.
Read the article→AI forecasting software: what machine learning changes
AI forecasting software improves demand forecasting in some cases thanks to machine learning, without making it infallible. Here is what it really brings, and how to evaluate it without getting caught out.
Read the article→Forecast accuracy: measuring error (MAPE, bias)
Forecast accuracy is measured with MAPE and bias: knowing your real error is the foundation of correctly sized inventory. Here are these indicators and how to read them.
Read the article→Finally put a number on what disruptions cost you every year.
Let's start by estimating what your disruptions really cost you. It's free, it takes 30 minutes, and you leave with a figure nobody in your company knows today.