A global consortium of more than 70 pharma companies was struggling with delayed and inaccurate billing of IT configuration items (CI). They had a complex IT landscape in which the inventorying of Cis was being done manually. Adding to this challenge were multiple data sources from which CI information had to be collected. The manual, inconsistent and unorganized process resulted in several billing discrepancies and disputed internal charge-back process.

To resolve the issue we implemented DRYiCE ROAR in the client’s environment. ROAR is a robust computational engine that collates data from multiple sources and processes it to create a high quality, accurate data landscape. With ROAR the client was able to:

  • Reduce manual efforts
  • Improve data quality
  • Discover 50% more Cis as compared to original manual inventorying
  • Improve billing consolidation by 90%
  • Define clear ownership of Cis among the 70 member companies

 

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