Getting your data
to get to the point.

Handsets, audio and wearables lose value fast. Buying ran on supplier relationships and instinct, so cash kept getting locked into lines that were already depreciating. Over £180k of stock had been sitting past 90 days with no clear view of what to clear or when the next demand spike would land.

We built a SKU-level demand forecast and an inventory-at-risk dashboard: stock aged into buckets, margin tracked by category, and reorder points that factor in price erosion. One live page tells the buyer what to reorder, what to clear and how much cash is exposed.

In tech, timing is the whole game. Pairing a forward forecast with ageing turns a gut-feel purchase into a weekly buy list, and flags slow stock while it still holds value instead of after it has crashed.

Short shelf life punishes both directions. To avoid letting trade customers down, they over-ordered, then wrote off what did not sell. Roughly 9% of stock was going in the bin each week, with no daily, line-by-line view of what tomorrow actually needed.

We built a daily SKU-level demand forecast layered with day-of-week and weather signals, plus a waste and order-recommendation dashboard that balances service level against spoilage and hands the buyer a suggested order quantity each morning.

Perishables have a profit-maximising order quantity, not just a safe one. A tuned daily forecast finds the point where you protect the customer and stop paying to throw stock away, and it updates as patterns shift.

Demand swings hard with weather and project cycles. Cash sat in slow, heavy stock like timber and aggregates through winter, then peak lines ran out in summer. Thousands of long-tail SKUs went unreviewed, quietly tying up working capital with stock turning just 4.1 times a year.

We built a seasonal demand forecast by product family, a working-capital dashboard tracking stock turns and cash tied up, and a slow-mover rationalisation list so the team could see exactly which long-tail lines to cut and which to pre-buy before the season.

Matching stock to the season frees cash when trade is quiet and protects sales when it peaks. Reviewing the long tail stops money leaking into lines that turn once a year and puts it behind the ones that actually move.