Reduce stockouts. Cut excess inventory.

~100 contracts a year at a $260K average, sold through the website and a B2B sales team, with quoting, projects, inventory, accounting and email in five silos re-keyed by hand. Nobody had a number they could sell against, and reordering ran on memory. When we pulled their own stock file: 81 orders committed against stock that wasn't on hand, 107 order lines already past their promised ship date, and a quarter of all SKUs with no available-to-sell figure at all. Stock bought for a January order sat locked while a September customer was turned away.

AI-powered forecasting now turns 24 months of order history into one available-to-sell number, reorder points and buy-by dates per SKU. Sales quote against what exists, the January order is bought ahead instead of found short, and date changes reach the warehouse automatically.

$30M of car park work ran on spreadsheets and memory. Stock lived in people's heads, job kits were built from parts that existed nowhere so crews turned up short, and nobody knew what any job actually cost.

The demand planning foundation now runs on the software they already owned: every item counted across the warehouse and 20+ vehicles, with a reorder point on every item so nothing runs out before a job. Then we trained the team to run it without us.

Product data lived in 12 Excel workbooks with no central inventory view. Nobody could say what was sellable without opening three files, and the online store and the logistics side ran separately.

The demand planning foundation is one inventory view across store and warehouse, with the catalogue migrated, orders updating stock automatically, and logistics connected end to end.