Data Governance Maturity? Or Immaturity?


A sneak peak at the results from the Kalido Data Governance Maturity Assessment

Winston Chen

This autumn, we launched an online tool for assessing data governance maturity. Based on our Data Governance Maturity Model, we wanted to provide a means for people to determine how their organization ranks in terms of the business process for defining, implementing and enforcing data policies. We broke it out into people, process, technology and overall maturity so that companies can understand where they stand and pinpoint where they may be lagging behind.  We never intended for the tool to be a formal survey, but since approximately 100 companies have taken it to date, we’ve collected a good amount of data. Let’s take a peek!

Not surprisingly, Financial Services (21.4%), Manufacturing (11.9%) and Government (7.1%) are the dominant industries, as is Retail (10.7%), and Director/Manager of Data Governance (22.5%) and Data Architect (17.0%) are the dominant titles. However, a healthy 39% of respondents were from business roles. Consistent with other surveys such as the recent Information Difference survey, about 40% of organizations say they have data governance programs up and running, more than a quarter are currently putting programs in place, and the last quarter have neither programs nor any future plans.

In overall maturity, 21.4% are in the Application Centric stage – the least mature — while a full 2/3 are in the Enterprise Repository Centric stage and 11.9% are in the Policy Centric stage. No company is in the most mature stage: Fully Governed.

Drilling down to organization, process and technology maturity, what we see is that companies are in fact more mature in people and process than technology. (See chart.) This is interesting. For decades, experts have been scolding companies for buying tools before thinking about people and process. It seems that in this area at least, technology is lagging behind.

In Organization maturity, 27% have data governance councils with business representation and formal data stewardship, just more than half of the 45% who say they have a Data Governance program in place. If you don’t have a council and stewardship, do you really have a data governance program? On the other hand, I was glad to see that more than a third of all companies reportedly have documented accountability for data quality. This is great.

For Process, a surprising 57% have no performance management for data management activities. Another 25% have metrics related to IT operations only, like system up-time, etc. This is clearly an area that needs to be addressed. Data management ought to be no less a rigorous set of business process than HR or Finance. It’s one of the few business functions that suffer from lack of performance management. Communication of data policies also shows up particularly poor. A full 57% of companies report that data policy communication occurs only in response to a crisis, and it takes time and determination to even find the latest official policies. A surprisingly large portion, one-quarter, don’t have a concept of data policies at all.

Data governance technology falls behind people and process in maturity. Of the companies that have clearly defining data governance processes in place, 81.2% use office applications such as Email and Excel, or SharePoint for workflow. Data quality is another technical area that has not caught up. 40% report that data quality is not measured – not even the occasional profiling.

What can we learn from this data? I know better than to be suspicious of data, and to be aware of my personal biases when interpreting data. We also know that the people who took the Assessment are a self-selecting group – they have some interest in and awareness of data governance, otherwise they wouldn’t take the survey. The general population of organizations is probably even less mature than what we have found so far. But I think we can safely conclude the following two things:

First, data governance is being adopted, but it lacks discipline, ranging from what makes a data governance program to getting it operationalized. As many of us in the industry suspect, there’s a lot of “kick-off and cold-cuts” as Jill Dyché likes to say. A lunch meeting of stakeholders means there’s now data governance.

Second, technology lags behind people and process. In most business processes where this happens, you end up having low efficiency and sometimes low effectiveness. This means implementing a robust policy management solution rather than using Word or Excel, and automating the process using workflow and doing routine data quality monitoring.

You can download the whitepaper on the Kalido Data Governance Maturity Model, and you can access the online maturity assessment yourself to see how you compare. We provide everyone who takes the survey a customized, detailed report outlining where you stand, how to get to the next step and where you compare against others who have taken the assessment.

Meanwhile, I hope you’ll sign up for my upcoming webinar, “Defining and Developing Data Policies: Step 1 on the Road to Data Governance” (Tuesday, November 16 at 11:30 EST), where we’ll talk about how the role data policies play in a data governance program.

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