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Management Tools & Analytics

CIV believes that information (and the data that underpins it) is the foundation of sound managerial decision making. As a key component of our analytical framework, CIV has developed a set of tools to assist management in understanding the past, accurately measuring the present, and predicting what is likely to happen in the future, including:

  • Cycle Time Analysis
  • Volume & Capacity Metrics
  • Inventory Analysis
  • Staffing Models
  • Efficiency Analysis
  • Data Engineering
  • Behavior Trend Analysis
  • Operational Metrics

CIV has a unique ability to define what is most critical to the business, to quantify what may seem unquantifiable and to measure what was thought unknown. CIV’s analyses are probing and complex, but its conclusions are always clear and actionable. Thus, CIV’s clients gain a more profound understanding of their own business.

Case Studies

Transaction-based Staffing Model

Management in a major US Life Carrier asked CIV to examine their New Business Review Team, believing that the lack of clear productivity expectations was hindering capacity planning and driving up short term costs (through increased overtime expenditure.)

CIV built a transaction-based staffing model to calculate the number of reviews an associate should be able to perform in a regular shift, in effect setting their first productivity standard, which helped the management team communicate clearly and unambiguously to their staff.

CIV then worked with IT to develop a methodology for extracting actual completed review volumes per user from the workflow system. By reconciling these two numbers, CIV was able to create a tool for management to monitor performance going forward.

Underwriting Cost to Serve Model

A Top 10 Life Insurance Carrier primarily focused on high-end brokerage wanted to explore ways to reduce per application unit cost.

After assessing their operations, mix of business, submission volume, and placement/decline rates, CIV proposed a strategy of realigning the staffing based on the difficulty in processing incoming business. More skilled staff were aligned with the more difficult business, and less skilled (and less expensive) staff were aligned with the less difficult business. Improved processes were put in place for managing distribution relationships and assessing their value.