Fleet condition
The fleet comes with the business. So does the maintenance
$42K
In upfront costs to bring the fleet back to service condition.
Warehouse staff and technicians told us maintenance had been suspended for ten months before the sale. The fleet had 27 vehicles, roughly 30% with more than 250,000 miles. Tires and other maintenance were overdue.
Why it matters: Lower maintenance spending can make current results look better while leaving the next owner with the bill. We identified the work and cost the buyer needed to plan for.
Inventory and job costs
The parts left the shelf. The costs stayed behind
~$330K
In inventory costs not recorded over the twelve months examined.
Parts were being used and invoiced without the process reducing inventory and recording the corresponding cost. In this business, roughly 65% of inventory transactions lacked appropriate costing.
Why it matters: Inventory remained overstated and costs understated. The $330K covered one year; the process problem extended across years of records.
Backlog reliability
Some of the backlog had already become an invoice
~$3M reported. Under $1M remaining.
~3.5 months
reported
Fewer than 4 weeks
remaining
While mapping scheduling, we found a project manager’s local spreadsheet containing an accurate list of open work. Comparing it with the sales backlog exposed fully invoiced jobs still being counted, including individual projects worth $200K–$300K.
Why it matters: The reported backlog suggested roughly three and a half months of work. Fewer than four weeks actually remained. That is a different basis for staffing, sales priorities, and acquisition planning.
What that understanding makes possible
The work is done. The information hasn’t caught up
Technician notes carry the details the office needs to account for parts, schedule the next step, and send an invoice. When those details arrive late or incomplete, the office has to reconstruct the work.
Our work with MSI Data
We work with MSI to help reduce time to invoice (TTI) by mapping the process, locating the information, and identifying what their AI agents need to understand. You can’t move the right data if you don’t know where it is.
On one visit, a biller showed us how she prepares invoice notes. She had already built AI prompts that did the job well. To use them, she copied the information out for each invoice, ran the prompt, and pasted the result back in. The work was already being done, but every invoice took her a long string of manual steps. AI agents followed her workflow and reduce TTI.
Invoice timing and payment time
Published commercial-contractor data from BuildOps
Source: BuildOps. Observed industry averages, rounded. Not Solhver or MSI engagement results.
Working knowledge
The org chart missed someone rather important
10,000 POs a year. One undocumented dependency.
Following the inventory process, we kept hearing the same name. The accounts payable operation depended on a remote worker approaching retirement who appeared on neither the staff list nor the org chart. Their contacts and working instructions lived in a cheat sheet on a personal laptop.
We documented the cheat sheet and identified the dependency for leadership to address.
Why it matters: Leadership could see the knowledge it needed to preserve and the transition it needed to prepare for, rather than discovering the gap after the person left.
