Cost to collect is the unit economic that decides whether a billing company is profitable — the pressure is to keep it under roughly 10% of collections. But the inputs are split: payments live in the PM systems, labor and technology costs in payroll and your software bills, and throughput in nobody's report at all. This dashboard puts productivity and economics on one screen so the operation runs on its own numbers instead of gut feel.
What this dashboard answers
It answers how efficient the billing operation actually is: how much does each biller collect, what does it cost to collect a dollar, how many claims does a biller work per day, and how much rework does closing a claim take? The overview shows collections per FTE biller, cost to collect %, claims worked per biller-day, and total payments versus total operating cost, with collections and cost-to-collect cut by biller.
The metrics that matter
Cost to collect is the headline — it ties labor and tech spend directly to collections and is the number owners benchmark against the sub-10% target. Collections per FTE biller measures raw productivity, but touches per resolved claim is the quality signal underneath it: a biller who touches a claim five times to close it is fighting rework, usually from upstream denials or bad data. Reading throughput next to cost-to-collect separates the genuinely efficient billers from the busy-but-expensive ones.
Why the data is trapped across the systems
The pieces of cost to collect never live together. Payments post into the client PM systems; labor sits in payroll; technology cost is the sum of your athenahealth, clearinghouse, and tooling invoices; and biller throughput is buried in work-queue logs. Joining them into a single 'cost to collect by biller' figure means exporting from several systems and reconciling by hand — which is why most firms only estimate it.
How to read it
Start with cost to collect % against the ~10% line, then use the biller scatter — cost-to-collect versus collections — to find the outliers: low-cost high-collection billers are your model, high-cost low-collection ones need coaching or reassignment. Touches per resolved claim flags rework hot spots, and the activity-type stack (charge entry, payment posting, AR follow-up, appeals) shows whether the team's time is going to value-adding work or chasing denials. The sample uses entirely synthetic, anonymized biller names, so there is no real data.
Metrics it tracks
| Metric | What it means |
|---|---|
| Collections per FTE Biller $ | Total payments collected ÷ distinct billers — dollars collected per full-time biller. |
| Cost to Collect % | (Labor + tech cost) ÷ payments collected — operating cost as a share of what's collected. |
| Claims Worked per Biller-Day | Claims touched ÷ biller-days — daily throughput. |
| Total Payments Collected $ | Payments attributed to biller activity in the period. |
| Total Operating Cost $ | Labor plus technology cost across all billers. |
| Touches per Resolved Claim | Claims touched ÷ claims resolved — rework intensity to close a claim. |
Used by: RCM operations directors and billing-company owners
Frequently asked questions
What is a good cost-to-collect percentage for a billing company?
The common target is under roughly 10% of collections, with lean operations running lower. Cost to collect is labor plus technology cost divided by payments collected — the unit economic that decides margin. Watching it by biller and by client shows where the operation is efficient and where it's bleeding.
Why track touches per resolved claim?
Touches per resolved claim is rework intensity — how many times a biller handles a claim before it's closed. A high number means denials, bad data, or payer friction are forcing repeated work, which drives up cost to collect. It's the quality signal that explains why a busy biller can still have low net productivity.
Can I bring my own biller and cost data?
Yes. You combine collections from your PM systems with labor and technology costs and work-queue throughput, and the template models them into one productivity-and-economics view. The sample uses synthetic biller names and figures so you can see the finished report before bringing your own.
Build this report on your own data
Clone this RCM / billing companies template — describe it and we’ll generate sample data so you can try it free, or upload your own export. You get a fully modeled, branded Power BI project that opens in Power BI Desktop.
Use this as a template →