When you have a smart Digital Workforce made up of bots that can capture and measure business data flowing through them, you can quickly become overwhelmed with all the information hitting you in real time. How can you make that influx of information actionable, easy to consume, and easy to act upon?
If you have an enterprise Robotic Process Automation (RPA) solution that features a robust analytics foundation, you can institute a simple three-step framework (measure, act, improve) wherein all data being recorded can be acted on to enhance business benefits and return on investment (ROI).
Let’s take a look at how this framework helps in the context of a healthcare payer.
What are we measuring?
For this example, lets take three crucial metrics related to insurance claims processing:
- Average cost per claim: How much is paid out on each claim to a customer?
Why it’s important: Analyzes average cost per claim by policy type to help drive proper policy pricing
- Average time to settle a claim: How long does it take on average to process and settle insurance claims?
Why it’s important: Claim settlement time impacts customer satisfaction
- Claims ratio: Compares number of claims over a period of time, with the premium earned during that period
Why it’s important: Helps detects fraud for high claim volumes or customer satisfaction issues for low claim volumes
How do we make this actionable?
The bots can be set up to deliver feedback on data produced in the interest of escalating action and properly directing resources to solve specific issues. Three examples of how information might be separated are:
- Good to know: All numbers are “green” and within their thresholds. <No action required>
- Seems interesting: The number seems better than expected and intrigues me to drill down further. <Invites a drill-down or ad hoc analysis action>
- Have to act upon it: Numbers are “red” and outside their thresholds. <Action needed immediately>
What are the business benefits of acting on this information?
Benefits of the above action framework can fall under three common buckets:
- Reduce cost of operations
- Increase throughput and process efficiency
- Increase business and sales volumes
The above framework can be applied to every RPA implementation across any business vertical (finance, insurance, healthcare, transportation, etc.) and helps make each such implementation very data-driven. The ROI derived from such implementations can then be quantified, which in turn can justify further expansion of the automation charter across more business groups within the enterprise.
The more you measure, the more you gain.