What a useful manufacturer MIS looks like
Most Indian manufacturers we meet have one of two MIS problems. Either no real MIS - the owner gets a gut-feel summary on a WhatsApp call every Monday and the books are reconciled at month-end. Or too much MIS - a 200-page deck the consultant built five years ago that nobody reads because it takes an analyst three days to refresh and the questions on the shop floor have moved on.
The middle ground is a small, sharp pack of five reports refreshed weekly with the discipline of a stand-up meeting. Each report answers one question, pulled from one or two systems, with a clear drill-down when the number looks off.
| Report | Question it answers | Source systems |
|---|---|---|
| Production vs plan | Are we making what we planned, by line and shift? | Shop-floor sheets, ERP production module, planner Excel |
| Sales vs production reconciliation | Is what we made clearing into dispatch, or building as FG? | ERP production, Tally sales, warehouse stock module |
| Raw material consumption variance | Is actual consumption tracking the standard BOM? | Stock issue records, BOM master, Tally purchase ledger |
| Vendor payment ageing | Which suppliers are about to choke our working capital? | Tally payables, supplier master, treasury Excel |
| Capacity and utilization | Are we using the machines we are paying interest on? | Shop-floor logs, machine OEE if available, ERP routing |
If the pack looks healthy, the operating team gets on with the week. If one of the five flags an issue, that is the meeting agenda. This is the discipline good plants run on, achievable for a 50 to 500-employee mid-market plant without hiring a data team.
Report one - production versus plan
Output by line by shift, against the production plan agreed on Monday. Surfaces process drift, machine downtime, and shift-level discipline issues before they show up in cost variance at month-end. The data lives in shop-floor sheets, a homegrown ERP, or sometimes an OEE system. The plan usually lives in an Excel maintained by the production planner.
The diagnostic question after looking at the report is almost always 'where did we lose the hours' - was it changeover, maintenance, material shortage, or quality rejection. A live MIS lets the production head pull up the breakdown by line and shift in seconds, instead of asking the supervisor to send the daily log by the following morning.
Report two - sales vs production reconciliation
Production output should clear into dispatch within an expected lag. When it does not, finished goods inventory builds and working capital quietly inflates. The sales versus production reconciliation surfaces this gap weekly, per SKU or per product family. Production booked in the ERP, sales booked in Tally, and finished goods stock in the warehouse module need to triangulate to the same number.
- Quality holds delaying dispatch. Lots completed and waiting on QC clearance, or rework loops that never get formally closed.
- Sales rejecting variants the line still produces. A SKU that is no longer in active demand keeps coming off the line because the planner did not get the memo.
- Booking discipline differing across systems. Production books the day the lot completes, sales books the day the invoice is raised, and a 4 to 8 day lag becomes structural FG inventory the owner is unknowingly financing.
Report three - raw material consumption variance
Actual raw material consumed versus the standard bill of materials, per product, per week. This is the report that catches yield slippage and vendor price changes early. Standard BOMs live in your ERP or in a master sheet. Actuals live in stock-issue records and Tally. Joining the two needs an item master that matches across systems, which is the everyday plumbing problem of Indian manufacturing MIS.
A consumption variance trending up by 1.5% week over week is a quiet ₹3 to ₹6 lakh leak per crore of revenue. Most plants discover it at quarter-end audit, by which time the loss is locked in. A weekly variance report compresses the discovery loop to seven days.
Report four - vendor payment ageing
Open vendor invoices by ageing bucket - 0 to 30, 31 to 60, 61 to 90, beyond 90 - with the cash impact of clearing each bucket. Indian manufacturers run on stretched supplier credit by necessity. The report tells the finance head which suppliers are about to stop dispatching, which early-payment discounts are still available, and which long-tail invoices have been disputed and forgotten.
Most owners do not track this and most CFOs have stopped chasing it because the data is messy. KolossusAI surfaces it as a standing number in the weekly pack so the finance head can route cash to the suppliers where the discount is largest relative to interest cost.
Report five - capacity and utilization
Machine-hour utilization by line, by shift, by product. The owner is paying interest on the machines and salary for the operators whether the line runs or not. The weekly view tells you which structural problem is dragging utilization below the 65% line on a high-cost machine.
- Product mix not designed for the line. Short runs of multiple variants on a machine optimised for long single-variant runs. Changeover eats the available hours.
- Planning discipline that leaves long changeovers. The schedule sequences SKUs without grouping by tooling or material, so every shift is a setup-heavy day.
- Material availability gaps. Raw material arrives 2 hours into the shift. The line was idle for 2 hours. Repeated weekly, that is 10% of available capacity gone.
Some plants extend this to a shift-wise OEE - availability times performance times quality - which is the standard industrial benchmark. Even without OEE, the simpler machine-hour utilization is a 10x improvement over the monthly capacity report most plants currently rely on.
Cost of quality and rework - the missed report
Most Indian manufacturer MIS packs ignore cost of quality entirely. Rework hours, scrap value, customer complaints and replacements, and the labour to investigate a quality escape are all real cost. They sit in production logs, warehouse records, and after-sales registers, and they rarely make it to a single number the owner can act on.
A weekly cost of quality view often surfaces the largest margin leak in the plant. A 3% rework rate on a ₹2 Cr weekly production is ₹6 L a week of throwaway labour and material. Most owners discover this only when a customer rejects a consignment. KolossusAI builds it as the sixth report when the data is available, which is most plants with a basic ERP and a quality log.
How to run these without a data team
Each of the five reports lives across two to four systems. Building them manually every week is a 12 to 20 hour job for an MIS analyst, and the analyst spends most of that time matching item names and customer names across systems. The reports drift the moment someone names an item differently or adds a new product variant.
The simpler path is an AI layer that reads all the source systems, maintains the cross-system mapping, and answers each of these reports on demand in plain English. See AI Analytics for Indian Manufacturers for the multi-system pattern, or AI for Tally users if Tally is your main system. The 14-day POC validates the numbers against your existing MIS row by row before you commit.