In a consumer goods order to invoice engagement, RE-ViVE reconstructed 2.47 million order lines and found the process running 294 distinct ways. None of those variants had been designed. All of them were being executed, every day, at volume.
Figures from a consumer goods order to invoice engagement. Read the case study.
1Why
At a few thousand orders a month you can feel the exceptions. At two and a half million order lines they disappear into the average, and the average looks fine.
A workaround invented once for a difficult customer gets reused, taught to the next hire, and within two years is standard practice in one region. Nothing was ever decided. The process simply drifted, and no document records it.
Wholesale, retail, e-commerce and marketplace all run the same order to invoice on paper. In execution each has its own credit rules, pricing exceptions, delivery patterns and billing corrections, multiplying the number of live paths.
An order edited three times before it invoices is still one order in every report. The three edits are the cost, and they are only visible when the order is reconstructed as a sequence rather than a row.
Execution variants by volume
294 variants across 2.47M order lines, carrying 9.69M days of rework. Every one of them was being executed; none of them was designed.
Headline figures are from a consumer goods order to invoice engagement. The distribution shape is illustrative; your own variant curve is measured from your data.
2Where
Order to invoice is usually where the variants are densest. The same reconstruction applies right through the supply and trade cycle.
Where margin, working capital and the customer promise are decided.
Where cost, supply reliability and compliance are decided.
3How
No new instrumentation, no data warehouse programme and no curation layer to build first. Four steps, from access to a live view.
Status histories, workflow logs and audit trails in the systems you already run. If a record carries a case identifier, an activity and a timestamp, it is enough.
Records from separate systems are linked back into one case — a single order followed across everything that touched it, in the order it happened.
The process as it was intended, set against every path it really ran. Variants, rework loops, waiting time and team differences are counted rather than estimated.
The view refreshes as the data does, so drift shows up as it happens instead of surfacing in the next review cycle.
4What
Not a score or a maturity rating. The actual behaviour of your order process, in units your commercial and supply chain teams already argue about.
How many distinct paths one designed process actually runs, and which handful of them carry most of the delay and cost.
Orders edited, re-priced, re-approved or re-issued before they invoiced — separated from orders that ran once.
The revenue sitting in orders that stalled, were rejected downstream, or invoiced later than they should have.
Where the distance between shipping the goods and collecting the cash is created, step by step.
The same order type compared across channels and markets, rather than averaged into one number that describes none of them.
How campaigns actually ran against how they were planned — pricing exceptions, late activations and manual corrections.
Pick the flow where variants cost you the most in margin or in cash. We will tell you, before any commitment, whether the data you already hold can reconstruct it.
