Case study
Process mining missed the shadow work. Parable saw it — and scaled what already worked.
A Fortune 500 business-services enterprise deployed process mining and activity monitoring against a $68M past-due AR problem. Neither could see the Excel workarounds tenured agents had built — Parable surfaced them, unified the tooling, and scaled what the fastest agents already knew how to do.
At a glance
Industry
Business services
Use case
Accounts receivable & collections
Operation analyzed
69 collections agents
Engagement
Diagnostic + 3 targeted builds
Products used
Lorem ipsum
Results
56%
of agent time on prep & wrap — not customer calls
9.8M
data points analyzed across 69 agents
$13.7M
AR value preserved through 3 targeted builds
+19%
faster: tenured vs. junior agents
Where the agent day actually goes
Only 44% of the agent day reaches customers. The opportunity is to flip that ratio — less prep & wrap, more time on calls.
The challenge
A Fortune 500 business-services enterprise was facing a $68M past-due accounts receivable problem.
To understand it, the company had already invested in two categories of tooling — process mining and activity monitoring. Both were deployed specifically to find the root cause. Neither did.
56% of agent time never touched a customer.
The fastest agents had quietly built tools no system could see.
What they built
Parable analyzed 9.8 million data points across 69 agents and found that 56% of agent time was consumed by pre- and post-call work — preparation and wrap-up — not the customer calls themselves.
Parable also found that tenured agents were 19% faster than their junior peers because they had built personal, Excel-based shadow tools that no system had ever recorded. The organization had no way to see those workarounds, let alone standardize or scale them across the team.
Parable recommended an agentic solution to unify the shadow tooling so the whole team could work the way the most effective agents already did.
The results
The implementation preserved $13.7M in AR value through three targeted builds.
Customer stories