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When putting together a governance framework, in my view, one of the key things to implement should be a RACI model. This ensures that when things go wrong with the data, the correct people are held Responsible and Accountable. When changes are made to the data, the correct people are also Consulted and Informed.

Is there any other non-governing-body controls/additions that can be made to ensure those on the responsible and accountable lists are living up to their promises?

Tags: Accountability, RACI, Responsibility

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A great discussion theme, I agree completely - RACI and the similar DACI (Driver, Approver, Contributor, Informed) models are extremely valuable tools in the data governance best practices toolkit.  The question I'm often asked thought, is when and where to implement these models.  In my opinion, we want to define a new RACI or DACI every time there's a new business initiative or opportunity that needs to be addressed.  

Here's my reasoning: To define a roles and responsibilities model at too high a level (e.g., all customer data-related business issues) likely assigns incorrect ownership and expertise to the specific issues and process that need to be addressed.   To define RACI/DACI too granular (e.g., customer data attribute data capture rules) would make it way too complex - requiring too many subteams of decision makers to practically get anything done.  

I think the DACI/RACI should be defined at the business opportunity level -for example (e.g., reduce average handle time in call center; improve delivery and trustworthiness of quarterly financial reporting, reduce number of order exceptions, etc).  This 'level' of definition will put the right business process owners with the right subject matter experts to deliver the best data definitions, rules and policies to support the effort.  

Any other opinions on how to manage responsibility and accountability on data governance efforts?   

When building and implementing new organizational capabilities, I fall back to leadership training instilled into my thick skull by Uncle Sam. Ill translate the following from Milspeak to (civilSpeak).

Mission capability packages include:
Organizational structure (what does the organizational structure look like? Roles and responsibilities, data stewards, data executives, executive sponsor).
Mission parameters (what is the Data Management Scope?)
Command and control (organization reporting structure, governance or steering committee for status reporting, funding and budget approval)
• Allocation of decision rights;
• Patterns of interaction among the actors; and
• Distribution of information.


In my opinion, defining and allocating of decision making best supports the RACI model.
Clearly there are architectural, hardware, software, storage, and integration decision that IT should own, but consult with the business on; just as there are business decisions, data definition, distribution, and frequency, decisions that the business owns, but should consult with IT.

Companies that invest in a matrixed data management organization can harmonize collaboration where IT becomes a competitive weapon that fuels rapid business growth, compliance, operational efficiencies, while controlling costs.

Thanks John, great comments. I am particularly keen on the 'accountability' part of the equation. In my experience, few are prepared to accept accountability. 


John said:

When building and implementing new organizational capabilities, I fall back to leadership training instilled into my thick skull by Uncle Sam. Ill translate the following from Milspeak to (civilSpeak).

Mission capability packages include:
Organizational structure (what does the organizational structure look like? Roles and responsibilities, data stewards, data executives, executive sponsor).
Mission parameters (what is the Data Management Scope?)
Command and control (organization reporting structure, governance or steering committee for status reporting, funding and budget approval)
• Allocation of decision rights;
• Patterns of interaction among the actors; and
• Distribution of information.


In my opinion, defining and allocating of decision making best supports the RACI model.
Clearly there are architectural, hardware, software, storage, and integration decision that IT should own, but consult with the business on; just as there are business decisions, data definition, distribution, and frequency, decisions that the business owns, but should consult with IT.

Companies that invest in a matrixed data management organization can harmonize collaboration where IT becomes a competitive weapon that fuels rapid business growth, compliance, operational efficiencies, while controlling costs.
Richard
Spot on.
This speaks to the value of executive sponsorship who authorizes the data management organization and mandate. This authorization holds the data management organization responsible for and accountable to data management.
Much better to have assigned responsibilities and accountabilities, in lieu of the alternative- plausible deniability and the omnipotent finger pointing blame game.

Someone once said (maybe it was me?) that "Accountability is taken, not granted."  In other words, you can give someone responsibility for something, but accountability is how they take ownership.  Some people take accountability naturally, others need to be encouraged. The best way I know to encourage it is to use a Lean technique, visual controls, and to remove fear from the culture. In other words, shine a light on responsibility (e.g. by publishing the list of data and system owners), make the data quality scorecards very visible,  and create a culture of problem solving (not searching for the guilty) when something goes wrong.

I recently wrote several blog articles about this:

  1. How Do You Know If Your Data Has Integrity?
  2. So You Want One Version Of The Truth?

I'd be interested to hear what others think.

John

Interesting thoughts, John. thanks for your input.

From my perspective, it's not about blaming people, it's about ensuring someone approves the work from their budget. I have found that a lack of accountability often leads to inadequate resources (financial and human) allocated to remediation. Ownership and accountability go hand-in-hand, otherwise you get a scenario where no one wants to use their budget to fix problems.

Rich 

John said:

Someone once said (maybe it was me?) that "Accountability is taken, not granted."  In other words, you can give someone responsibility for something, but accountability is how they take ownership.  Some people take accountability naturally, others need to be encouraged. The best way I know to encourage it is to use a Lean technique, visual controls, and to remove fear from the culture. In other words, shine a light on responsibility (e.g. by publishing the list of data and system owners), make the data quality scorecards very visible,  and create a culture of problem solving (not searching for the guilty) when something goes wrong.

I recently wrote several blog articles about this:

  1. How Do You Know If Your Data Has Integrity?
  2. So You Want One Version Of The Truth?

I'd be interested to hear what others think.

John

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