A Big 4 firm cuts 50,000+ hours a year out of its Contact-to-Cash workflow with RPA.
The situation
A Big 4 professional services firm runs a high-volume Contact-to-Cash process internally. Contact-to-Cash covers the full engagement-to-revenue lifecycle: setting up client engagements, tracking time on those engagements, capturing and approving expense claims, classifying expenses against the right cost categories, assembling and issuing client invoices, and applying cash when payment arrives. At Big 4 scale, the process touches tens of thousands of consultants, engagement managers, and finance staff every month.
The Firm's internal Strategy and Transformation Office identified Contact-to-Cash as a top efficiency target. The workflow carried significant manual effort across its lifecycle: pulling timesheet data, classifying expenses, routing items for approval, assembling invoices, and chasing exceptions. Each individual step was minor. Across the volume, the cumulative effort was substantial.
What we delivered
The work ran in two phases.
Streamlining first. Before automating anything, the team mapped the workflow as it actually operated, identified avoidable manual steps, and simplified the underlying process. Automation accelerates whatever it sits on top of. The value here came from cleaning up the workflow before any bot touched it.
RPA build. Once the simplified process was agreed, the team deployed RPA bots across the repeatable activities: data extraction from source systems, expense classification against the firm's chart of accounts, exception flagging for human review, invoice assembly from approved time and expense data, and routine reconciliation. Bots handled the repeatable work. Humans handled the judgment calls and the exceptions.
Our founder supported the Strategy and Transformation Office across both phases, contributing to workflow redesign, automation opportunity identification, and the business case behind the deployment.
The result
The automation removed over 50,000 hours of manual work from the operating model on an annual basis. The hours released across consultants, engagement managers, and finance staff translated directly into improved cost-effectiveness for the Firm.
The operating model holds regardless of the underlying technology. Whether the automation is RPA, an AI agent, or a combination, the work is the same: identify a high-volume manual workflow, simplify the process, automate the repeatable activities, and measure the time saved. The AI agents we build today are doing a broader version of the same job RPA did a few years ago, with more flexibility, more reach across unstructured data, and tighter audit trails.
Client name confidential by agreement.
Have a back-office process eating senior hours at scale? Book a scoping call. We will tell you whether RPA, AI agents, or a combination of the two is the right tool for your workflow — and where neither would help.