The specialist retailers in Hawick managing knitwear and tweed lines are handling product data that most high-street shops never encounter: fibre composition, colourways, size runs, care instructions, export classifications for overseas buyers. That is before the allergen declarations and provenance statements that farm shops and artisan food producers need to maintain across a supplier base that often sends information in no consistent format at all. The outdoor kit and craft shops along the Tweed Valley are managing seasonal range changeovers on a small team with no admin support. In every case the data work comes home with the owner.

We build tools that read supplier price files and product information however they arrive, match them against the product master, flag changes and new lines, and produce imports ready for the EPOS and the website. Technical fields like fibre composition and allergen data are extracted from supplier documents automatically. The owner reviews before anything goes live. Most shops recover six to ten hours a week on the office side within the first month, and the product-data errors that used to surface at the shelf edge largely stop.

The Borders tourist season creates a version of the stock planning problem that is harder than a straightforward residential high street. The outdoor kit shops along the walking routes need to load up ahead of the spring and summer season knowing they cannot easily reorder at short notice if something sells through faster than expected. The market town shops in Kelso and Peebles have a more stable residential base but still carry a long tail of lines that overstay their welcome and have to be discounted before the next range arrives. A gift and lifestyle retailer in Melrose we spoke to had roughly a fifth of her working capital tied up in stock from the previous two seasons, and was still running out of the lines that her regulars came in for.

We build a forecasting set-up that sits alongside the EPOS rather than replacing it. It lines up the full sell-through history and produces a weekly reorder recommendation per SKU that accounts for supplier lead times and minimum order quantities. For shops with a hard visitor-season peak, the model weights the pre-season order against what actually sold last time rather than against an estimate of what might. The buyer stays in control and overrides wherever she knows something the model does not. Over a full season, waste on slow movers tends to fall. Availability on the top sellers goes up.

Independent owners across the Scottish Borders all run some version of the Monday morning trading review. What sold, what needs to be reordered, what has been sitting too long. Most of them are doing it on Sunday. The thinking takes twenty minutes. The data gathering takes two hours, because the EPOS and the website have to be reconciled by hand with no automatic way to bring the picture together. A Jedburgh retailer we talked to had been doing this every Sunday for three years, not because he liked it but because Monday morning was always too busy to catch up.

We build tools that pull the weekly trading picture together automatically overnight. The draft markdown or promotion plan is waiting in the owner's inbox on Monday morning, based on sell-through rate and stock age. He checks the flags, adjusts for anything the model could not know, and signs off. What was a Sunday afternoon commitment becomes around twenty minutes before opening. Markdown decisions tend to sharpen when they are made on the numbers at the start of the week.