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Employee Master Data Management in a Private Insurance Company – Getting your Data Analytics Ready


Problem Statement and Analytics Objectives

The Business Problem

The employee master which consisted of @ 14000 headcount / employee records was riddled with unclean and dated data. This posed both serious compliance risk as well as communication challenges. Further, there was no automated / seamless mode of extracting data, cleaning the same and integrating the transformed data into their larger HCM platform. As a result the employee master data was never accurate and required periodic manual intervention to capture, clean, update and integrate into the larger system. This was a manual, cumbersome, inefficient process and prone to error. The Company incurred cost in three ways:


  • Loss of business due to poor data quality as any non-conformance would lead to client / customer penalties
  • Compliance risk leading to loss of reputation and brand image
  • High staffing cost due to additional staff deployed to manually collect, clean and audit the data.
Analytics Objectives

Data Diagnostics – Identifying Data Quality Gaps


Key Outcomes


Mobirise

Data Cleansing & Conversion – Dataset of @14000 with 52 Fields per record



Mobirise

Key Deliverables – Data Extract/Load/Merge/Collect/Transform/Clean/Audit


Mobirise


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