<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=458506188731710&amp;ev=PageView&amp;noscript=1">

Healthcare Payor

Major U.S. Healthcare Payor Drives Analytics Transformation Through Cloud Data Warehouse



About Client:

Dallas, TX
What Client Does:

Provides a full portfolio of healthcare insurance plans that tailor health coverage to their clients' specific needs

Solution Focus:
Utilizing Wherescape, Snowflake and Tableau to create a mature data pipeline and enhance visual analytics
Client's Unique Data Challenge

This Healthcare Payor Client had an issue with their "data silos" that hindered their ability to access and see their data accurately, causing lapses in data trust across different departments and the organization as a whole. They had important data residing in multiple systems and did not have a good way to create a single source of the truth. Additionally, several manual processes created inefficiencies that further perpetuated their problems with data quality.

They had three primary areas where they wanted to focus their efforts to build trust in their data within their organization:

Claims Data Analysis:

With claims data in multiple internal systems, coupled with third party processor data, the Client did not have a single source of truth to perform claims analysis.

Policy Lifecycle Analysis:

The Client wanted to better understand the data around their policy lifecycles.  Without an end-to-end view of the policy (sales to claim payout), they were not able to fully score the value of each policy.

Agent Hierarchy & Commission Payment:

The lack of a single source of truth that centered on agent hierarchy created internal conflict due to the use of different data sources by the sales teams and accounting departments. These disparate data sources also weakened the trust in commissions data across the organization.



Teknion's Approach

Teknion first gained an understanding of the Client's existing data landscape by interviewing members of different departments within the organization. Identifying all of their sources of information provided insight into the type of analysis they were performing with their data.

Teknion then recommended modifying existing data structures to follow best practices, migrating data to the cloud for improved access across the organization, and automating manual processes through a collection of tools that improve efficiency and increase data quality.

Lastly, Teknion devised and proposed a multi-phased project with detailed timelines and budgetary guidelines for each phase.

Delivered Solution

Before the Client could begin to rebuild trust in their data, Teknion assisted them with improving their data into an accurate and consumable format in several ways:

Leveraging Snowflake as a Cloud Data Warehouse:

By leveraging Snowflake, Teknion created a new cloud-based data warehouse that offered a modern approach to data architecture which provided the entire organization access to the same single source of high quality data.

New Data Architecture:

By utilizing Wherescape to restructure the data as it flowed into Snowflake, Teknion provided consistency across disparate data sources, elements of new metadata, and a mechanism to monitor and improve data quality.

Data Automation Tools:

By coupling WhereScape with Snowflake, Teknion enabled the Client to truly modernize their data platform by automating manual processes which in turn saved time and improved overall data quality dramatically.

Self-Service Visual Analytics Tools:

Through a side-by-side comparison of Power BI and Tableau, Teknion demonstrated to the Client how Tableau provides a better solution for putting insights into the hands of more employees to deliver their vision of self-service analytics.

Client's Wow Outcome

This engagement generated significant positive outcomes for the Client:

Claims Data Analysis:

  • Established a single source of truth for analyzing claims
  • Eliminated 520+ hours per year of manual processes
  • Provided new insight into claims processing backlog
  • Improved significant trust in data

Policy Lifecycle Analysis:

  • Provided end-to-end visibility of all policies
  • Eliminated double or triple counting of policy revenue
  • Enhanced forecasting insight
  • Improved policy risk assessment significantly
  • Increased trust in data significantly

Agent Hierarchy/Commission Payment:

  • Reflected real-time changes in agent hierarchy
  • Increased visibility in the productivity of agents, regions and divisions
  • Increased accuracy of commission payouts
  • Increased trust in data across sales, management, operations and accounting


 I would like to learn how Teknion can help me solve my organization's unique data challenge.