Foundational Principles for Digital Transformation: Treat Data as An Asset

Adrian Gonzalez

Who owns data quality management?

Many operations people believe that IT is responsible for data quality, while IT points the finger back to operations and the countless trading partners (suppliers, customers, logistics service providers, and so on) that send them data. Simply put, the responsibility for data quality management is not clearly defined at most companies, or it’s assumed that data quality is everybody’s responsibility, but the required governance and accountability structures don’t exist.

Therefore, companies need to clearly define roles and responsibilities in this area. But before that, they need to view data as a corporate asset and assign value to it, just like they do to other assets like buildings, equipment, and intellectual property. Some frameworks already exist, such as the emerging field of Infonomics, which Gartner defines as “the theory, study and discipline of asserting economic significance to information. It strives to apply both economic and asset management principles and practices to the valuation, handling and deployment of information assets.”

Poor data quality results in poor supply chain visibility, which in turn results in lost sales (out-of stocks), higher transportation costs (expedited shipments), excess inventory, and reduced customer satisfaction (among other negative consequences). Putting a dollar figure on poor data quality and poor supply chain visibility, and how those costs break down, not only helps you gain upper management support to take corrective actions, but also helps you to prioritize those actions.

Assessment Questions

  • Who is responsible for data quality management at your company?
  • Do you actively measure supply chain data quality?
  • Do you have processes and systems in place, both internally and with suppliers and other trading partners, to improve supply chain data quality?
  • Are you able to quantify the financial impact of poor data quality?

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