You heard me, stop trying to govern your data, it isn’t trying to get away!
Data is inert, it is just a representation of objects, activities and behaviors that will sit wherever you put it until or unless someone does something to it. Like cash or commodities, only time and the behavior of others will impact its value. Therefore, you’re not governing data, you’re really governing people’s behavior. Even at the technology level, bad things happen to data because people choose to do things like copying, changing, deleting and adjusting it with little regard for others.
Don’t blame them, they are only doing what they think is necessary to answer their business questions. Instead, consider focusing on people and their behaviors. Since behaviors reflect a complex set of people’s expectations, skills, needs and values, we need to think about the best approach to improve those behaviors over time.
You could use a compliance-based approach to drive actions without changing ongoing behaviors, something like a “golden clipboard” of checklists for policy compliance. However, a policy-based approach is self-limiting and very difficult to sustain because it doesn’t really change behaviors or expectations.
A golden clipboard approach pushes policy directives across an organization without a clear sense of how compliance adds value. When the value is not clear to both the people trying to comply and to the enterprise, the effort is usually seen as just another corporate drill. No lasting changes in behavior will occur without providing a clear answer to why these changes are needed, much less support for understanding how to make those changes. “All carrot, no stick” means that people do the minimum amount of work then wait it out with a “this too shall pass” mentality.
Everyone will dutifully use the clipboard to fill in the assessment but they will continue to do whatever is required to stay out of trouble and complete the exercise. You’ll have nice survey results and some cool charts, but your data will not change because behaviors have not changed. As with many policy programs such as government policy or corporate policy, a policy-first approach makes data governance the end, not the means, to better control people’s behavior with data. Perhaps we should start treating the people who produce, manage or handle and consume important data as participants and look at how we can engage them in a more proactive way.
The better option is to focus on a value based approach. We want all our data participants to value our data and protect its value for everyone’s benefit. That means providing participants with a clear, solid reason for protecting and even improving data. Answering the “why” question with real, targeted benefits goes a long way toward engaging participants’ energy in positive ways. Targeting real benefits can be as simple as understanding the challenges data participants have today. They spend too much time getting, revalidating cleaning and otherwise controlling data before they can use it.
Data assurance has become the norm for businesspeople who really just need to review, analyze and make decisions or take actions based upon the data. The work of sourcing and assuring its basic integrity for their use has overtaken their analytic and execution mandate. This over-emphasis on data sourcing and assurance undermines their performance and limits their career potential since they cannot shine based on analysis and execution alone, as they should. Relieving them of most of this burden by offering a much smaller comparative burden of controlling data as it is produced and consumed becomes a very attractive option, especially if it takes much less time and everyone involved is committed to this effort. The result is much more useful data “on tap” that reduced business time spent sourcing and assuring its utility.
So, what focus do we need to provide for our business data governance approach? The central goals of governance are visibility, control and improvement. We generate visibility to the data that matters most to the enterprise and its condition by standing up controls to determine and then improve its quality. This is a simple progression that provides real value through sustainable competitive improvement and performance. Anything less is simply too expensive for this level of effort. Improved governance should result in improved efficiency since we waste much less time in preventing chaos then we do in cleaning it up. Ultimately, this will lead to improvements in corporate performance.
Recognizing the behavioral component of data governance means deeply engaging people with options that result in better behaviors and outcomes. For example, urban planners understand that traffic jams are not caused by cars alone. Regardless of the number of traffic lights or speed limit signs, if drivers are unwilling to change their behaviors or have not been trained, there will be chaos. Without proper preparation, adding cars to a legacy mix of pedestrian and bicycle traffic leads to wasted effort and broad confusion and dissatisfaction.
When data governance leaders ask people to travel the data governance road, the leaders know it is a new road. New technology for finding, accumulating, changing and distributing data, just like the transition from a bicycle to a car, takes time and mentoring. Just as a car is often viewed as a means to get from one point to another, for many people, data management is just another task -- not the focus of their job or career. Very few people had exposure to data handling and management methods during their college classes or corporate career.
Improving behavior around the use of data also requires a willingness to provide better options. Many people are stuck copying and changing data to suit their needs with little understanding of the nature, sources or issues in that data. They need helpful options. In addition to answering the “why” question, you need to answer the “how” question. You’ll need to establish a firm case for both local and enterprise improvement and provide a clear way to work with data more effectively. When people know the “how,” they can confidently perform their policy assessments. With the confidence that their assessment answers will be used to enhance a proven, documented methodology, they are much more willing to engage.
Success is established over time as behaviors change. Behaviors change because better options are provided and supported. Giving people options requires that we provide methods, guidelines, training and examples. Only this deeper level of engagement can lead to improvement in data capabilities. This makes governance a means to a better end - an improved set of enterprise data and decisioning outcomes.
You’ll know you’ve done a great job when the people you’ve helped are improving and adding to their own methods. You’ll also know because you’ll find yourself mentoring and supporting rather than training and orienting. Whether you are trying to provide an enterprise governance program or working in a business line, the transition will occur as your participants take ownership of the process. You’ve turned the corner when your stewards are challenging you to broaden the data horizons they are addressing, looking for more ways to solve vexing problems and reaching out to each other to solve shared challenges.
Of course, you could continue to govern data and not bother empowering “self-governed” behaviors that actually improve data, decisions and outcomes. But you can only do this as long as your competitors follow suit or your executive team fails to see the link between their data, their people and their profitability. How long will that last?
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