Assess core transaction and customer tasks to determine which ones are potential candidates for autonomous processes based on frequency, business objectives, and feasibility (including, regulations, technology and line of business). Move thinking from task automation to process orchestration to help fuel this transition. ■ Work with business leaders to assess their digital roadmaps and identify how autonomous processing can help them support business outcomes around improving CX, driving operational efficiencies, and competing in the local market. ■ Demonstrate the value of automation to gain buy-in by applying metrics aligned to business outcomes for efficiency, operations, engagement, sustainability, services and revenue. Instill employee buy-in for automation by using employee engagement metrics, such as staff training on new skills and attrition across all automation initiatives, in addition to the desired business goal. ■
Recommended Reading:
Insurance Scenarios: Sense and Plan for Alternative Futures in an Era of Constant Change ■
3 New Customer Experience Requirements That Will Impact Digital Insurance in 2023 ■
Predicts 2023: What’s Next for Insurance CIOs Operating in an Era of Turbulence? ■
Data Fabric Back to Top
Analysis by: Kimberly Harris-Ferrante, James Ingham, Sharat Menon, Robin Schumacher and Alys Woodward
Description: A data fabric is an emerging data management design for attaining flexible, reusable and augmented data integration pipelines, services and semantics. A data fabric supports both operational and analytics use cases delivered across multiple deployment, plus orchestration platforms and processes. Data fabrics support a combination of different data integration styles and leverage active metadata, knowledge graphs, semantics and ML to augment data integration design and delivery.
Sample Vendors: Cambridge Semantics; Denodo; IBM; Informatica; Stratio
Gartner, Inc. | G00786204
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