Non-Invasive Data Governance Explained

My first article on “Non-Invasive Data Governance”™ was published on TDAN.com almost two years ago even though I have been using the term “Non-Invasive Data Governance”™ for five years.  At first my approach to Data Governance was certainly non-invasive.

Now, … after implementing data governance and information governance programs in this fashion for more than 5 years, I can honestly say that the approach has become less and less-invasive over time.  Think about it … Your Data Governance program can be non-invasive (thus being less intrusive, less threatening, less expensive, but more effective) or invasive (about command and control – I call it the 2×4 approach).  You decide.

In the first article I tossed out the question, “How can you possibly implement a Data Governance Program in a Non-Invasive way?”  I still get this question a lot. All of my clients, and many of the people that attend my seminars and workshops across the globe tell me that the term “Non-Invasive Data Governance”™ is what attracts them to my approach.

In the first article I stated:

  • Most organizations view Data Governance as being over-and-above normal work efforts and threatening to the existing work culture of the organization.  And then I said … It does not have to be that way.
  • Most organizations have a difficult time getting people to adopt data governance best practices because of a common belief that data governance is about command-and-control.  I said … It does not have to be that way either.
  • While I firmly state that data governance is “the execution and enforcement of authority over the management of data”, nowhere in that definition does it say that Data Governance has to be invasive or threatening to the work, people and culture of the organization.  I said … It does not have to be that way either.

I went on to say that “Non-Invasive Data Governance”™ can be summed up in a few quick statements.

With “Non-Invasive Data Governance”:

  • Data steward responsibilities are identified and recognized, formalized and engaged according to their existing responsibility rather than being assigned or handed to people as more work.
  • The governance of data is applied to existing policies, standard operating procedures, practices, and methodologies … rather than being introduced or emphasized as new processes or methods.
  • The governance of data augments and supports all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives.
  • Specific attention is paid to assuring senior management’s understanding of a practical and non-threatening yet effective approach to governing data that will be taken to mediate ownership and promote stewarding of data as a cross-organization asset, rather than the traditional method of “you will do this”.
  • Best practices and key concepts of the non-threatening approach are communicated effectively, compared to existing practices to identify and leverage strengths and enable the ability to address opportunities to improve.

While I say that Data Governance is the “execution and enforcement of authority over the management of data and data-related assets”, several of my clients have tamed that definition to a more acceptable – and more in line with NIDG – sounding definition.  Let me share two of these definitions with you:

  • “Formalizing behavior around the definition, production and usage of data to manage risk and improve quality and usability of selected data.”
  • “Formalizing and guiding behavior over the definition, production and use of information and information-related assets.”

Notice that they both begin with “formalizing behavior”.  Formalizing behavior and holding people accountable are the two basic tenets of the “Non-Invasive Data Governance” Approach.  Formalizing behavior assumes that there is already some sense of data governance taking place (because there is).

To stay Non-Invasive:

  • Organizations should identify people that informally (and already) have a level of accountability for the data they are defining, producing and using to complete their job or function.  In order to do this, an organization must first design a Data Governance Operating Model of Roles & Responsibilities that aligns with the way your organization operates today.  A successful Operating Model does not require that you fit your organizational components into their model.  A successful Operating Model allows you to overlay the framework over your existing organizational components.
  • Organizations should identify existing escalation paths and decision making capabilities from both a positive (how and why is it working) and negative (why doesn’t it always work) perspecftive, and leverage what is working while addressing the opportunities to improve.
  • Organizations should recognize people for what they do with data, and help them formalize their behavior to the benefit of others potentially impacted by that behavior.  Often decisions are made in the heat of battle or in daily operations that result in consequences (positive and negative) for other people along that data lifecycle (reporting, integration, risk management).

As I summarized in the first article … Data Governance, by the mere inclusion of the term “governance”, requires the administration of something. In this case, Data Governance refers to the administering (formalizing) of discipline (behavior) around the management of data. Rather than making the discipline appear threatening and difficult, my suggestion is to follow a “Non-Invasive Data Governance”™ approach that focuses on formalizing what already exists and addressing opportunities to improve.

For more information on “Non-Invasive Data Governance”™, please read these articles:

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Robert S. Seiner

Robert S. Seiner

Robert (Bob) S. Seiner is the President and Principal of KIK Consulting & Educational Services and the Publisher Emeritus of The Data Administration Newsletter. Seiner is a thought-leader in the fields of data governance and metadata management. KIK (which stands for “knowledge is king”) offers consulting, mentoring and educational services focused on Non-Invasive Data Governance, data stewardship, data management and metadata management solutions. Seiner is the author of the industry’s top selling book on data governance – Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success (Technics Publications 2014) and the followup book - Non-Invasive Data Governance Strikes Again: Gaining Experience and Perspective (Technics 2023), and has hosted the popular monthly webinar series on data governance called Real-World Data Governance (w Dataversity) since 2012. Seiner holds the position of Adjunct Faculty and Instructor for the Carnegie Mellon University Heinz College Chief Data Officer Executive Education program.

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