“We have the data,” people tell us. “But we can’t use it because of our organisation’s strict data governance rules.”
After all, this is the era of big data, machine learning and digital marketing. With the rules of the game having been rewritten these past few years, it is no longer about “if we had the data, we could…” Organizations today have the data. They also have the technology to process that data and churn out reports, generating massive amounts of insight for its leaders at each and every level.
But if there’s one department that usually has reason to complain when its organisation has a robust data governance policy in effect, it is the marketing team. For people in the marketing team, it is understandably frustrating to have all the data they need in the system without actually being able to use it meaningfully. It’s a classic case of being so near, yet so far, with data governance consigned to the role of the villain in the story.
Is data governance the villain, though?
In a perfect world, data governance is a guarantee of protection, not protectionism. A well-designed data governance framework keeps data secure, but without obstructing its use — within all legal and ethical boundaries — towards maximising gain for the organisation.
In response to measures like GDPR and data localisation laws, organisations have tended to err on the side of caution. Unfortunate, because these laws are intended to protect the rights of the individual from unauthorised, unethical use of personal data. Organizations can use the data they legitimately procure, with the subject’s approval, to serve them better. But in many cases, the data is locked up so tightly that only Big Data applications can access them – leaving marketing tools starved for the information that they need for creating more personalised pitches.
Finding the golden mean: How much DG is the right amount?
A strict data governance policy might reduce legal risks for the firm, but it might also be akin to throwing all your data into a black hole, never to be seen in its granular form again. On the other hand, a lax data governance policy does no one any good – you might as well not go to the trouble of formulating one at all. Finding the golden mean is a process that requires patience, and willingness to experiment and to be proven wrong.
Begin by involving all stakeholders. The creation and proliferation of a data governance policy involves a lot of stakeholders in the process. Even someone on the periphery, such as the store clerk who actually keys in demographic details that go into the analytics engine, should be consulted on the depth of information that can be mined from a customer without turning them off. There is no point in forcing your frontline teams to collect information that is never used — not only is it a waste of their time and effort, but also does it create a false expectation in the customer’s mind that you are setting up a more personalised experience for them.
The marketing team should definitely be a part of such conversations, and, where possible, be a part of data stewardship. They need to be aware of the information that can be made available to them, and they need to share how they will use such information in a way that data governance guidelines are adhered to. For instance, if you’d like to use customers’ buying patterns to send a regular mailer with customised offerings, you need to have the data and the corresponding access for your marketing tools.
But remember, your data isn’t static. Your data governance shouldn’t be either. While the core of any data governance policy — such as the vision, the security controls, the guarantees made to customers and other third parties — should remain as constant as possible, the rest of it is and should be considered as a constantly-evolving entity. After all, we are living in a world that’s characterised as VUCA — volatile, uncertain, chaotic and ambiguous — and it makes no sense to be committed to a course of action that might very well turn counter-productive overnight.
Therefore, let the ability to change and adapt be a part of your data governance policy’s DNA itself. Build in frequent, periodic reviews. Assess new requests to data on merit, legal-ethical compliance and organisational need. And avoid guidelines that are impossible to roll back.
Data governance is what data governance does. It can be as enabling or as obstructive as you design it to be. To know how to design or improve your data governance policy so that it enables your marketing team, do reach out to us for a quick consult.