How to quantify ROI for RPA in our insurance brokerage operations?

[VioletR]

I'm an operations manager at a mid-sized insurance brokerage, and we're drowning in manual data entry between our CRM, policy management system, and email. I've been researching Robotic Process Automation to handle these repetitive tasks like client onboarding and claims intake. I've identified a few good candidate processes, but I'm struggling to build a business case that quantifies the ROI beyond just hours saved, and I'm unsure whether to start with an off-the-shelf tool or a custom build.

[Avery.H]

Nice area to optimize. I’d start with a small pilot on a high-volume, low-exception process like client onboarding or claims intake. Use it to quantify ROI beyond hours saved: cycle time, data accuracy, error rate, SLA adherence, and customer satisfaction. Keep the scope tight and document assumptions so you can defend the numbers to leadership.

[Mia99]

ROI framing tip: treat NPV/ROI as a combination of tangible and intangible gains. Tangibles: labor-cost savings (hours saved × loaded wage), reduced rework, faster processing. Intangibles: better compliance, auditability, customer experience. Use a simple calculator: annual benefits minus annual costs, divided by costs. You can present ranges to reflect uncertainty.

[Madison_M]

Off-the-shelf vs custom: if your processes are standard (CRM and email with common policy mgmt software), an off-the-shelf RPA suite with prebuilt connectors will get you value fast and with less risk. A custom build fits you if there are unique steps or heavy integration needs. My go-to approach is start with an off-the-shelf pilot on one process, then assess whether to expand or customize.

[Nora.G]

Pilot plan sketch (6 weeks): Week 1 map steps and collect baseline metrics; Week 2 choose tool and configure; Week 3 test with a small data sample; Week 4 run parallel vs live to compare; Week 5 measure ROI with defined KPIs; Week 6 decision and rollout plan. KPIs: cycle time, first-pass accuracy, number of manual clicks, post-automation error rate, user satisfaction.

[Madison_B]

Risk and compliance: insurance data is sensitive. Ensure vendor has SOC 2/ISO 27001, encryption at rest/in transit, RBAC, audit logs, and disaster recovery. Plan for data governance: where data is stored, who can access it, retention guidelines, and a process for prompt issue remediation.

[JackQP]

Change management: automation is a team effort. Involve ops and IT early; prepare for exceptions; build a lightweight governance to handle changes; provide training and a fallback plan when the automation trips. Align with compliance and risk teams early to avoid last-minute roadblocks.