Just read Julie Hunt’s blog on the connections between business process and data governance. Interesting. http://preview.tinyurl.com/proc1hunt. In it, she quotes Rob Karel of Forrester from a blog entry last December, saying “Data governance is not – and should never have been – about the data.”
Rob has reiterated this in a bunch of thought-provoking appearances since publication, and a buncha people have asked me to comment on whether I agree. So here it is:
YES… and no.
“Big G” Governance is all about PEOPLE and RULES: Mostly Decision Rights (Who gets to make what kind of decisions according to what criteria) and which data policies, standards, and high-level control objectives should be prioritized, under what circumstances.
“little g” governance is all CONTROLS (process/technology/hybrid) that are inserted into processes, projects, systems, datastores, and practices to make the DATA meet expectations.
In between is an (often-underappreciated) “alignment layer” where tough decisions are made about how to convert policy to practice. In this layer, managers, SMEs, architects, data advocates, and others work separately, in matrix environments, and/or in roundtable settings. They make choices needed to deal with data – and the people who work with. Outputs may be project plans, architectural requirements, control objectives or specifications, and ACCOUNTABILITIES for data-related controls along their lifecycles and across horizontal efforts such as BUSINESS PROCESSES.
In short: Controls are put in place to govern data. In some environments, data control work can ultimately be fairly routine. Effective controls require aligned architecture and management. This alignment- and the Big G Governance rule-making that informs it – requires humans to interact with each other. So yeah, it’s all about PEOPLE, RULES, and PROCESS.
So what are the A-B-C value statements for the three layers of Data Governance?
- If we effectively govern data through controls, then the data will be more likely to meet expectations, and our business processes and analytics will benefit as they work to meet our organization’s missions.
- If we pull representatives together into an alignment organization such as a Data Stewardship Council, then they can each bring a piece of data-related puzzles to the table, with a result of more aligned decisions, controls, plans, and risk-management activities.
- If we provide input to these councils through Big G Governance activities and outputs such as policies, priorities, and other rulings, then they all have a common understand of leadership’s intent, which will make it more likely that they make decisions which will serve that intent.
What Rob said: (source http://tinyurl.com/calltoarmsKarel)
I’ve discussed this concept of process-led data management often over the past few years, and went into detail in my July blog post, “Data Governance Remains Immature: Increase Focus On Business Process To Build Momentum,” where I offered a critical call to arms that all MDM, data quality, and data governance evangelists must embrace:
Data governance is not – and should never have been – about the data. High-quality and trustworthy data sitting in some repository somewhere does not in fact increase revenue, reduce risk, improve operational efficiencies, or strategically differentiate any organization from its competitors. It’s only when this trusted data can be delivered and consumed within the most critical business processes and decisions that run your business that these business outcomes can become reality. So what is data governance all about? It’s all about business process, of course.
