Health Insurance: Drastically reduce your customer service workload

Context

The call center of a major health insurance company wanted to drastically reduce agent post-call work and find the best solution to obtain detailed information about the reasons for calls.

Challenge

Given the rapidly evolving health insurance market, this health insurance company wanted to leverage its data in ways that would create more business value. Specifically, it needed to:

• Move from traditional descriptive BI to a predictive, even prescriptive approach.
• Deploy an agile data environment to implement advanced analytics.
• Actively support business digitization and the new CRM approach. They also asked us to advise them on:
• How to transform the organization to support new ways of working with data.
• Choosing the technology best suited for traditional BI and new advanced analytics use cases.
• Defining an implementation roadmap, taking into account organizational and technical changes.
   

Method and Solution

We first examined the current organization (as-is) and the target organization (to-be) and issued a series of recommendations to establish the new team responsible for data and advanced analytics, redefine change, build and execution processes, and introduce a data governance approach within the organization.

In a second phase, we deployed the new Cloud-based data environment and quickly implemented a series of classic BI use cases (using an agile methodology) as well as new innovative AI and ML use cases, such as automating call center record processing using Speech-to-text and NLP technologies available on the Cloud environment.

Their new data platform is now rapidly scaling up and is a key element in significantly improving customer experience and implementing their digital transformation.