Forecasting you delegate, not configure.
Tell Pinto what the business needs. It gathers the data, checks it, chooses the right method for every product and explains each number. Then it brings you only the forecasts it isn’t sure about.
Why forecasts go wrong
Stockouts hide demand
When a product sells out, sales history shows zero. Forecast from that and you order too little again.
One method can’t fit 12,000 products
Best sellers, seasonal lines and new launches behave differently. A single model gets most of them slightly wrong.
Decisions get lost between meetings
The campaign that moved or the line being dropped is agreed on Thursday and set up in the system days later, if at all.
What Pinto does in every forecast
Checks the data first
Finds missing sales, gaps in inventory snapshots and odd spikes. Fills small gaps where it’s safe, flags the rest, and skips products it can’t forecast safely.
Recovers lost demand
Uses inventory snapshots to estimate what would have sold while products were out of stock, so shortages don’t repeat.
Picks a method for each product
Tests several approaches against recent sales and keeps the one that is accurate and still captures seasonality and trend.
Forecasts new products
Products with no history are forecast from similar ones, based on their attributes, and Pinto shows which attributes it used.
Adds your business context
Promotions, launch and discontinue dates, growth targets and meeting decisions are built into the numbers.
Marks its confidence
Every forecast is rated high, medium or low confidence. The low ones come to you with the reason.
See how Pinto reasons.
Every recommendation comes with the facts behind it and a clear question for you.
- Forecast
- 2,300 units in the first 12 weeks
- Starting point
- No sales history, so Pinto forecast from three similar shoes
- Attributes used
- Trail running category 40% · $120–140 price band 35% · colorway family 25%
- Confidence
- Medium · launch data is thin
What Pinto always brings to you.
Pinto asks before it acts on
- Forecasts it has low confidence in
- Forecasts well above or below your targets
- Big changes from the last forecast with no clear cause
- Anything that would lean past the limit you set
Moved from spreadsheet forecasting to agent-led forecasting with automatic out-of-stock correction.
A multi-day buying cycle, now done in a single day.
Read the story →Related expertise.
Bring us a real inventory problem.
A forecast nobody trusts. A buy plan that takes a week. Stockouts you only find after the fact. Tell us what’s slowing your team down, and we’ll show you how Pinto would handle it.