Unlocking New Use Cases for Rules Engines
The Willis Towers Watson Story
Willis Towers Watson (NASDAQ: WLTW) is a leading global, advisory, broking, and solutions company that helps their clients turn risk into a path for growth. To stay competitive and to continue to meet the needs of their financial services customers, Willis Towers Watson embarked on an initiative to transform how they made decisions. Placing a priority on making more informed, data-driven decisions brought together their community of broking experts to ensure they could drive the best result for their customers.
As Willis Towers Watson looked to replace silos of data, manual processes, and custom applications that were difficult to maintain and test, they turned to Sparkling Logic SMARTS. SMARTS is a modern, agile, and easy to implement cloud-based rules engine and decision management platform that Willis Towers Watson is harnessing to drive their competitive edge.
When they started evaluating rules engine and decision management solutions, like most organizations, they wrote an RFP with very specific requirements. They were launching “Connected Broking” – a global placements platform and needed the rules engine to determine panel eligibility for insurance panels and they needed to automate decisions to channel the right risk to the right marketplace to better serve their customers.
However, once Willis Towers Watson selected SMARTS, they began to identify new use cases where the software could be applied to solve other business problems that were never even considered during the RFP phase. In some cases, the program management team saw uses for SMARTS that even their rules authoring lead and business analysts didn’t believe were a good fit for a rules engine.
The two new, not-so-obvious use cases that Willis Towers Watson considered were:
- Dynamic Data Capture
- Task Management
Let’s dive in a bit further:
Dynamic Data Capture
Willis Towers Watson identified an opportunity to apply business logic and rules to dynamically determine what types of data (and the sequence of that data) would need to be captured from an end customer so that the insurance carrier could make appropriate credit decisions and offer the best products and services. The team integrated SMARTS with a webform they developed to drive the data type and data sequence presented based on the application of business rules. Then, the webform was built to call back to SMARTS to validate the data that was entered. This solution is in production today.
Willis Towers Watson currently has plans in place to use the decision engine in an orchestration capacity. Specifically, they will use SMARTS in combination with a lightweight task management application that can trigger allocated tasks based on business events – getting the right task to the right person in the right application.
With each new use case discovered, Willis Towers Watson is looking to continue to harness and extend the value of SMARTS. It has been possible for the company to explore new use cases quickly due to the ease of implementing and managing SMARTS including the limited amount of developer and analyst resources required to author rules. As a result, the team has been able to devote time and resource to building the framework and integrations for both dynamic data capture and task management routing.
To learn more about how Willis Towers Watson achieved these results, read their case study.