Operational Analytics

Finalert builds the measurement on the processes you already run: order to delivery, invoice to cash, quote to job, hours to revenue. We take timestamps and volumes out of your operating systems, turn them into cycle times, throughput, utilisation and service levels, and put them next to the P&L lines they explain.

The useful part is the join. Cycle time on its own is an operations statistic. Cycle time placed beside working capital, or utilisation placed beside gross margin, becomes a finance conversation with a specific lever attached. We build both halves and the bridge between them, so a discussion about a margin point can end with a named process step rather than a shrug.

Operational analytics measures the running of the business rather than the recording of it. The raw material is operational events: when an order was placed, picked, packed, shipped and delivered; when an invoice was raised, sent, queried and paid; when a job was quoted, scheduled, started and signed off; when hours were logged and against what. Those events already exist in your order system, your field or project tools, your CRM and your accounting platform. They are rarely assembled into one timeline, which is why nobody can say with confidence where the days actually go.

Once the timeline exists, the questions get concrete. Order cycle time splits into its stages, and one stage is usually most of the total. On-time delivery stops being a single monthly percentage and becomes a distribution, which is where the late tail lives. Fulfilment accuracy, rework rates, first-time-fix and repeat visits all become countable. So does the queue: how much work is waiting, how old the oldest item is, and whether the backlog is growing faster than the team can clear it during a normal week.

Where the operating drivers meet the money

The invoice and collection process gets the same treatment as the warehouse. We measure the days between job completion and invoice issue, the proportion of invoices queried and why, the time a query sits with someone before it is resolved, and the gap between the due date and the actual payment date by customer segment. Those steps are usually treated as an accounting routine. They behave like a production line, they have the same throughput problems, and they respond to the same kind of measurement.

People and capacity are the other half. We build utilisation by person, team and location, separate billable from non-billable and both from unavailable time, and calculate recovery against standard rates where your business bills for time. Capacity is modelled against the demand actually arriving rather than against an annual assumption, so you can see the weeks where the schedule was full, the weeks where it was not, and what each of those cost you in overtime, subcontracting or work turned away.

Turning operating measures into financial answers

None of it is worth much until it is tied to the result. We build the bridge explicitly: a day removed from order cycle time expressed as a change in working capital; a point of utilisation expressed in revenue at your realised rates; a percentage of rework expressed as cost of poor quality; a day off collection time expressed in cash. The arithmetic is documented and agreed with your finance team so the link is a stated assumption that can be argued with, not a black box that quietly produces a number.

The reporting then runs on a cadence that matches the process, which usually means weekly or daily for operating measures and monthly for the financial bridge. Two limits are worth stating. We build and run the analysis; your operating and finance leadership own the decisions and the process changes that follow. And the analysis is only as good as the source data, so if your operating systems are not capturing reliable timestamps, fixing that capture comes before any reporting is worth trusting. We do not sign filings, issue audit or attest opinions, give legal advice or act as your accountant of record.