Herding cats. Lack of management support. Not my job. A distraction.
So much governance behavior can be described as a “people problem,” where disagreement and distraction are blamed for the failure to achieve the levels of data quality that are purported to matter to the business. Certainly compliance issues should be less thorny when employees have sufficient education, supervisory support (and compassion), and an attitude aligned with business priorities. But here’s the thing: When governance activities are perceived as hard, or not valuable, the people problem isn’t solvable.
In some cases, people are simply unfamiliar with the process. A company may have many talented subject matter experts, but it’s very unlikely that any of these experts have taken a course in data governance. It’s important to let them know what data governance is. Although data governance done properly is hard work, it is not something that’s out of reach, given some understanding of the concepts and explanation of the methods.
Then there is the matter of interest. A scientist developing an innovative power source would much rather focus the next breakthrough than decide on what metadata to apply to a report about the project. Someone developing an ad campaign will be much more interested in testing the effectiveness of two different ads than in ensuring they use the same format for the product name as the salesperson who is selling the product. Data governance is not their core capability, nor do they necessarily see it as part of their job.
In order to get a diverse cast of characters on board, it is necessary to explain at a meaningful level why data governance is valuable and change is necessary, while keeping in mind the employees’ perspective. There are many ways of promoting the culture change needed to encourage people to adopt a new vision for how to manage data, but the process is usually slow. People need to understand what a data-driven culture is, and how the free flow of information throughout the enterprise is vital to achieving it. Information cannot flow freely if every department has a different way of identifying a customer or describing products.
Once these inter-dependencies are described clearly, convincing people that everyone has an important role in implementing policies of good data governance becomes easier. For example, the role of governance in maintaining information security and reducing the risk of violating privacy regulations becomes more evident. In addition, employees can come to understand that the analytics used to measure corporate performance can only be carried out when data quality is maintained. Compliance requirements are becoming progressively more stringent, and data governance is therefore becoming progressively more important.
One helpful approach is to actually make it difficult for your employees to go wrong when they are doing their part. Make the job as easy as possible. Just as you can reduce head-on vehicle collisions by converting two-way streets into one-way streets, you can prevent human-caused “data accidents” using any number of semi-automatic error-avoidance techniques.
Input validation, for example, prevents the system from accepting data that is not formatted correctly (“please enter a valid date”). Using controlled vocabularies allows for multiple versions of a term to be turned into a single preferred term, thereby unifying the terminology used throughout the enterprise. With auto-classification, unstructured data can be analyzed and then, based on either a set of rules or statistical results, the contents can be automatically assigned to categories. All three of these techniques can make it easier for your employees to be in compliance with data governance policies, reducing the risk of going astray, and reducing the stress on your employees at the same time.
Governance lies at the root of any successful digital transformation. Our ebook: Data Governance and Digital Transformation provides insights on how to develop the strategic, tactical, and advisory layers of a governance framework.