Case Study
Production Demand Forecast & S&OP
Demand forecasting · S&OP planning · production capacity analysis
The Costco PO landed in week 32. Your co-packer found out in week 31. Every short-ship that followed was decided months earlier — by a planning process that runs on last month’s orders and somebody’s memory of the holidays.
Growing brands plan production by reflex: open orders plus a gut feel for seasonality, rationed by whoever shouts loudest when capacity runs out. It works until a major launch lands on top of existing demand. Then the brand short-ships its oldest accounts to feed its newest one — and the cost shows up downstream as OTIF fines, scorecard damage, and deauthorization risk. The fulfillment diagnostic on this site reconstructs that downstream cost: across the Cinderhaven book, short-shipping came to $32.8M across eight cost dimensions on $53M shipped over three years, with a deauthorization cliff at 90% fill. Most of it was a planning failure before it was a shipping failure.
The worked example is Cinderhaven Provisions — a synthetic $25M brand with 50 SKUs across 5 product lines and 6 contracted retailers. The data is invented so the methodology can be shown in full. The demand modeling, the capacity mapping, and the collision analysis are exactly what a real engagement produces.
What the diagnostic builds
Three things, joined: a demand model built from your actual signals — open orders, scan velocity, and seasonal patterns — instead of last month’s invoices; a capacity map of where the ceiling really is, by line, SKU, and period, including changeover and minimum-run constraints; and a collision analysis showing what the next launch or distribution expansion does to existing commitments, before you accept the PO.
The deliverable is a working S&OP view your team runs weekly without me: demand against capacity, four to six quarters out, updated as signals change.
See it worked through
Production demand forecast
Demand signals, capacity constraints, and seasonal patterns in one planning view. Built on the Cinderhaven dataset.
forecast.lailarallc.com →Fulfillment & OTIF diagnostic
The downstream cost of getting planning wrong: internal metrics reconciled against retailer scorecards, eight cost dimensions, the deauthorization cliff.
shortships.lailarallc.com →What you get
A demand forecast built from your signals, a capacity map of your real constraints, a collision analysis for whatever launch is coming, and an S&OP planning rhythm your team owns. Fixed fee, defined timeline.
Start with a conversation.
Thirty minutes. The first question is whether your fill-rate problem is a data problem or a capacity problem — the answer routes you here or to the Fulfillment & OTIF Diagnostic. No deck, no obligation.