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johnwernfeldt

Data Governance – Metrics​

Updated: 5 days ago

The Complexity of Data Governance ​

  • The three drivers of any Data Governance program are: Business processes, People (i.e. competence) and Tools (software).​
  • As such Data Governance becomes a complex system of many moving parts, that can be difficult to measure and follow up.​
  • However, not following up is the same as wishing for success and value (rarely a good idea).​

  • Metrics allows for monitoring, reporting and adjusting:​
¤ Identify software, business processes, or individual behavior needing changes​
¤ Highlight the program’s effectiveness in areas like regulatory compliance and Data Quality​
¤ Uncover areas needing improvement in the Data Governance program​
¤ Show the success of the Data Governance program to stakeholders​

Common Data Governance Metrics​
Common Data Governance Metrics

  • A common way is to take a fraction of the data and compare it to a “trusted” source and also to use tools to support the quality aspects of the data​

  • Depending on your specific use-case additional areas might be important to monitor and follow up:​
    ¤ Data encryption – applied correctly​
    ¤ Data breach incidents – should be low​
    ¤ User access monitoring – who have access (roles, people and situations)​
    ¤ Data access controls – how to ensure correct usage of data​
    ¤ Data retention – meet up to compliance, archiving and redundancy​

    The financial side of Data Governance​
  • As the Data and processes managing and using data matures and better quality arise is good and valuable, the effort put in also must correspond to better business outcomes.​
  • A well formulated and measured business case is also a valuable tool for the prioritization for the Data Governance program.​
  • Three categories:​
    ¤ Cost Savings from reduced manual work (IT and Business)​
    ¤ Productivity Gains trough self-service and single (trusted) source of the truth and automation of processes​
    ¤New Revenue Opportunities arise from the possibility of using advanced analytics and AI to analyze market and organization – thus finding new streams of revenue.​

  • There are many aspects of Data Governance that have a direct or in-direct effect on cost and/or profits, and the value it brings is unquestionable. However, without proper follow-up and measurements it is impossible to adjust (where needed) and to prove value for the organization!​
  • …and remember Data Governance is a business enabler and not an IT-project​




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