What We Do
Find the problem in days,not at quarter close.
Most operational problems are visible in the data days before anyone notices them in a report. Stock runs down, a process changes and compliance slips, a location quietly loses capacity. We build the monitors that surface those while there is still time to act, and we build them to be specific enough that you know where to look.
The problem
Monthly reporting findsmonthly problems.
Most operational failures are visible in the data days before anyone reads about them. Stock draws down faster than the reorder assumes. A process changes at head office and compliance quietly slips at every site. A location loses a room or a person and capacity drops without anyone recording it as a decision.
A monthly pack finds all of that eventually. By then the recovery costs more than the fix would have, and the conversation is about explaining rather than solving.
We build the daily monitors instead, and we build them specific enough to point at a cause rather than just raise a flag.
What we watch
The things that break quietly.
Days of supply
Units on hand against real consumption rather than a static reorder point, per item and per site. Anything already underwater is flagged, so a buyer finds out before a customer does.
Compliance and process adherence
Whatever your business is required to complete, tracked daily by location with a worklist attached. Regulated work is where a slow report costs the most.
Capacity and throughput
Booked against bookable, staffed hours against demand, and the gap between them by site and by day. The number that tells you whether a bad month was demand or staffing.
How we investigate
An alert is only usefulif it survives a challenge.
A number falling is not a finding. It might be a broken pipeline, a reporting lag that fills in later, or work that was booked and simply has not happened yet. Any one of those produces the same shape on a chart.
So the first thing we do with a drop is try to kill it. On one build a compliance rate fell hard over two weeks. It hit every location in the same week, which ruled out a single site having a bad month. The pipeline was healthy, the lag pattern did not match, and future bookings did not account for the gap. What was left pointed at a process change on a specific date.
That took days, not a quarter, and it arrived with the competing explanations already eliminated rather than as a question for somebody else to chase.
What changed
What it changed.
Caught in days, not at quarter close
A compliance number dropped sharply at every location in the same week. Hitting all of them at once ruled out any single site and pointed at a process change, so they knew in days instead of at quarter end.
Days of supply, per SKU
Units on hand measured against the pace they sell, with anything already underwater flagged. Buyers place the order before a stockout costs a sale, rather than after a customer finds the gap.
What else
This one rarely shows up alone.
What did you find out too late last quarter?
Most of it was probably visible in the data at the time.