Abstract

A mid-size US-based Insurance company with a dominant market share in its home state in the professional liability market was faced with a declining market share, higher claims, and pressure on rates since 2007. In 2010, the Board of the company was presented with two alternative solutions to choose from. Both the solutions leveraged advanced analytical and data analysis tools, yet they followed a different approach toward finding the solution. The first approach, championed by the Chief Marketing Officer, looked at aggregated consumer data and suggested fixing the underwriting and pricing rigor. The other solution, championed by the Chief Executive Officer, looked at the existing performance monitoring tools and recommended substituting them with a tool that analyzed the data at a granular level and then creating a scorecard to monitor the performance at the lowest business denominator. The board had to consider the availability of data and analysis tools and their ease of implementation before deciding on one of the solutions. This case is meant for MBA/MS students as a part of the IT and Systems curriculum. It can also be used in a core Strategy curriculum, Operations Management curriculum, or a Marketing Management elective (for discussing the concepts of customer lifecycle management, segmentation, etc.). It is also suitable for use in Executive Education Programs involving practicing managers.

Learning Objectives

The case is structured to achieve the following Learning Objectives:

• Understand the application of advanced analytical tools and technology in creating a competitive advantage for companies in a highly competitive environment
• Appreciate the criticality of data granularity while analyzing business situations
• Appreciate the flexibility that data granularity offers in rolling up and having different views of data and the actionable insights that can be generated from such drill down views
• Evaluate the choices facing the board of VCare and debate the Board’s decision and the way ahead

Keywords

Data granularity, Granular data, Aggregated consumer data, Analytics, Segmentation, Pricing, Scorecard, Decision making, Business Intelligence, Customer lifecycle management, Advanced analytical and data analysis tools, Pricing Optimization