Good data = Good Supply Chain

Our Customer’s Challenge

  • A leading pharmaceutical company, with global operations and delivering products in therapeutic domains such as virology, oncology, infectious diseases and cardiovascular diseases, asked us to help them with the way they organize data management. In a highly regulated industry such as pharma, as in many other industries, data volumes have exploded over the past decade.
  • Data management has become an important management concern. Regulatory compliance, product quality, but also operational success heavily depend on data quality. Our customer saw the potential of good data management as an enabler for operational efficiencies. They wanted us to help them use data in a better way, envisioning this would reduce supply chain lead times.
  • So the question was: how can we make and deliver the product quicker by bringing master data management to the next level ?  

Moore Stephens Expertise

  • Master data management
  • Change management
  • Supply Chain management


  • We started off by documenting the current use of data. As there was no detailed data flow architecture in place, we needed to take a deep dive in order to understand not just the general data flows, but also the details of those.  Which business processes are using which data elements?  Where is inconsistent data slowing down processes and where do we see supply chain bottlenecks because of data issues? But also, which IT systems have which data points in scope?  What is the level of overlap, duplication and inconsistency ?
  • With all of the above information, and with all of the insights we had gathered, we developed a master data governance model. Basically, drawing the future state of how data comes to existence, how it is used and how it is dispositioned at the end of its life-cycle. This meant, guiding our customer through the process of deciding which systems are leading for which data points, what is the source of each data point… Also, coming to an agreement on how data should ideally flow, and drawing a roadmap of changes to get there. Not just changes to system integrations, but also proposing changes to the heart of the business processes they support.
  • We also developed tools and practices to stimulate “Self Service Master Data Management” where possible. Business users were given as much ownership as possible on their data,  but we ensured we cut away all opportunities for error, backed up by Master Data Conventions which apply to the full system landscape.
  • Central Data Management was rolled out when we could not immediately implement all data conventions, or where cost to implement out-weighed the benefits.  


  • Self-service Master Data Management where possible, Central Data Management where needed.
  • Developed data conventions to improve consistency across systems & processes.
  • True data governance structure in place.
  • Improved data quality as an enabler for supply chain lead time reductions.

Want to know more? Contact us!

Joël Wijns
Partner Strategy & Operations | Supply Chain Services



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