When you have a smart Digital Workforce made up of bots that can capture and measure business data flowing through them, you can be quickly 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 RPA solution that features a robust analytics foundation, you can institute a simple 3-step framework (measure --> act --> improve) wherein all data being recorded can be acted on to enhance business benefits and 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 3 very critical metrics related to the 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 & 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 drilldown or adhoc analysis action>
- Have to act upon it: Numbers are “red” and outside of their thresholds <Action needed immediately>
What are the business benefits of acting upon this information?
Benefits of the above action framework can fall under 3 common buckets:
- Reduce cost of operations
- Increase throughput & 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.
By Jay Bala, Senior Director of Products, Automation Anywhere
Jay’s extensive experience in big data analytics and two decades of high tech business leadership are integral to his role at Automation Anywhere where he leads the products team in building an analytics platform to measure the effectiveness of robotic process automation in large enterprises. Before joining Automation Anywhere, Jay was VP, Big Data Solutions and Information Management at Nexient, was co-founder of Claritics (later acquired by Nexient), and held product management leadership roles at companies such as Informatica, Influence, and Ramco Solutions. Jay has an MBA from the Indian Institute of Management, Calcutta, as well as a B.Tech from the Indian Institute of Technology, Madras.