Supply chain planning and control

Christian Kroschl Writing and reference models on how supply chains are actually steered.

On a typical material, a perfect forecast takes about 8% out of the buffer. A lead time you can rely on takes about 60%. Most transformation programmes are aimed at the first number.

Twenty years in pharma and manufacturing networks. The thinking here did not start with AI or APS. It started with variability, buffers, and who is allowed to decide. The recurring argument is that supply chain performance is set in the layer between the operating model and the running system: decision rights, decoupling points, time fences, planning parameters and the feedback path from execution back into the plan. That layer belongs to nobody in most organisations, which is why it is where the leverage sits. Planning is a control function, not a reporting function.

Interactive reference models

Each one isolates a single trade-off and lets you push it until it breaks. All figures are illustrative, all brands and systems are generic archetypes, nothing is uploaded or stored.

S&OP Simulation Suite One decision, three bills. The same call reads as volume to Commercial, as capital to Finance, as service to Supply Chain. six acts · narrated

Pattern Wheel Rhythm against reaction. A fixed rotation sequence set against reactive replanning, run day by day over a year. two-sided variability

Integrated Planning & Control The frame the others sit inside: six principles, a twelve step planning process, and the operating model around it. 32 KPIs

Safety Stock Synthesizer Which side of the formula is actually setting your buffer. Rarely the one the forecast debate assumes. forecast vs lead time

Lead Time Cascade One set of lead time components, two consequences: plan rigidity and inventory, moving together. one input, two effects

You are the agent Same data, three confident answers. The shortest version of the agentic AI argument: rules before tools. sixty seconds

Writing

Longer pieces on stabilisation, decoupling and synchronisation, dynamic planning parameters, S&OE as the execution control loop, master data ownership, and why neither an APS nor an AI layer stabilises a supply chain on its own.

Structure Before Tools The collected articles and simulators in one place, organised by theme. reading hub

LinkedIn Where the articles are published and argued about. /in/kroschl

Views here are personal and do not represent any employer or client. Nothing on this site describes a specific organisation.