Most ops orgs report aggregate NPS or ticket volume. Almost none quantify the dollar value of preventable customer feedback (refunds, credits, handling cost, churn risk) coming from operational issues already mapped but not fixed upstream. This is the number you bring to the CFO conversation when the question is fix-it-now vs absorb-it-forever.
Operator preset
Pick the business shape closest to your stack. Each preset loads realistic volume and avg cost numbers, the fix economics, and (for marketplace) a populated category breakdown.
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Volume and cost per case
If you fill in the category breakdown below, those rows override these aggregate inputs. If you leave the category table empty, these drive the math.
Volume and preventable rate
/ mo
%
Avg cost per preventable case
$
$
$
Fix economics
$
$
%
How the cost-per-case math works
Each preventable case carries three costs that compound. The tool sums them into a single cost-per-case figure.
Refund or credit: dollar value of the refund, credit, or freebie issued to the complainant. Direct P&L hit.
Handling cost: agent time + escalation overhead + back-office reconciliation. Usually $5 to $25 per case depending on complexity.
Churn risk per case: not all complainants churn, but those who do take their LTV with them. Compute as (% complainants who churn) × (LTV impact). For repeat-purchase businesses this is often the largest piece.
Category breakdown optional, overrides aggregate when populated
If you have the issue taxonomy already mapped, fill the rows below. The tool will use category-level numbers and surface a Pareto chart of where the dollars actually leak.
Category
Monthly volumecases / mo
Avg cost per case$ / case
Monthly leak$ / mo
Outputs
Where the dollars leak
Pareto chart of the category breakdown ordered by $ leak. Top 3 categories highlighted: these are where you start. Anything below the top 3 is rounding error until the top 3 are fixed.
Sensitivity (annual leak)
If your volume estimate is off by 15% or 30% in either direction, or the avg cost per case is off by the same amount, how does the annual leak change? Use this to defend the headline number when the CFO pushes back on the assumptions.
Use cases I've seen this work
Patterns from operations I've run before. Adjust to your specific business, but the operating logic transfers.
Case 1: Self-service eligibility at a top-3 BR insurer
Inbound call center handling 1M+ contacts per quarter. Most calls were treated as fixed demand. Mapping calls by motive surfaced that 42% were self-service eligible. The user had a question or a request the IVR or app could handle without an agent if the flow existed.
How this maps: use the aggregate inputs with a 40-50% preventable share. The fix is not "reduce calls". It is build 3 missing channels (IVR menu, app self-service flow, WhatsApp bot for top 10 motives). The tool gives you the payback period before you go to engineering for the budget.
What shipped: calls dropped 42% in 9 months, retention up 9 points on the affected cohort. The fix paid back inside 4 months on the model the tool builds.
Case 2: Defect rate squad at a hypergrowth courier platform
Marketplace was treating NPS as a single number reported up to the C-level. The number told you the leak was getting worse, not where the leak was coming from. Building the NPS taxonomy (motive × sub-motive × root cause) was the unlock.
How this maps: use the category breakdown with rows for order delays, defects, address issues, refund processing, account errors. Numbers compound. The Pareto chart will surface two categories that hold 60-70% of the leak.
What shipped: two operating squads (defect rate squad + late delivery squad) with the taxonomy as the operating system. Defect rate moved from 6% to 3% and late delivery from 5.5% to 3.6% in 6 months. Per-order cost down meaningfully, NPS up 11 points.
Case 3: The fix-it vs absorb-it conversation with the CFO
You are running ops at a marketplace and you know the issue. Engineering is booked for the next two quarters. You have to defend the priority of your fix against the next 18 features in the backlog.
How this maps: switch to the CFO view. Run the analysis with conservative numbers. The annualized leak number is what you take to the meeting. The 12-month NPV and payback period are what close the conversation.
The play: CFOs do not greenlight ops fixes from anecdotes. They greenlight fixes from payback periods under 6 months and NPV above the cost of the engineer team. This tool gives you both.
Case 4: The renegotiation lever you forgot you had
Your CS BPO or your 3PL is the source of half the preventable feedback. Walking into the QBR without the dollar number means you negotiate on anecdote and lose.
How this maps: populate the category breakdown with the categories where the vendor is the upstream cause. Refund processing errors, late deliveries, account errors, billing, whichever maps to the vendor's scope.
The play: bring the annualized leak number plus the Pareto chart to the QBR. Vendors self-correct fast when their own data shows them as the line item. The conversation gets shorter and the credit terms get better.