Predictive Analytics
Predictive analytics
Forecasts for demand, churn, collections and stock — built on your own transaction history.
The problem
Every quarter your team makes a call on how much stock to hold, which customers are likely to pay late, and where demand will come from next month. That call is usually made by whoever has been in the role longest, using a combination of last year's numbers and experience. When they are right, nothing happens. When they are wrong, you either run out and lose the sale or you are sitting on stock when the season ends. A forecasting model makes the same call using the full pattern in your data — every transaction, every customer, every SKU — not just what one person can hold in their head.
Decisions about next month are made with a number, not a feeling.
Built for: Finance, operations and supply teams that plan ahead on incomplete information.
What we deliver
History audit before the build. A forecast is only as good as the history behind it. We look at your transaction data for gaps, seasonality, and whether you have enough consistent months to build from. Many businesses do not have enough clean history yet — and we would rather tell you that now than after you have paid for a model.
Festive-season handling. Indian demand patterns are tied to Diwali, Eid, financial year end and regional festivals. A model that does not account for these will be wrong every year at the moments that matter most.
Churn and collections signals. Which customers are likely to stop buying, and which invoices are likely to be paid late? Both are forecasting problems. Both can be modelled on the data most businesses already keep.
Outputs that connect to decisions. A forecast that sits in a dashboard nobody checks helps nobody. We build outputs that connect to the actual decision — a reorder trigger, a collections follow-up list, an account-at-risk flag.
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Frequently asked questions
- We only have two years of data. Is that enough?
- For some forecasting tasks, two years is workable. For seasonal businesses it is tight — you get two festive cycles to learn from, which is thin. We assess your specific data against the specific forecast you need, and give you an honest answer on whether it is enough or whether you should spend another season collecting before you build.
- How accurate will the forecast be?
- We measure accuracy on your held-out historical data before any model goes live, and we agree a minimum acceptable accuracy with you. We do not quote a number before seeing your data — that number would be made up.
- Can it use data from Tally or Zoho?
- Yes. We pull historical transaction data from your accounting or ERP system — Tally, Zoho Books, SAP, or an export — clean and structure it, and build from there. You do not need a data warehouse.