6 Key Steps to Develop a Data Governance Strategy | 7wData

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data governance at one time was typically the concern of IT managers, database administrators and other data management professionals. That scenario has changed dramatically.

A combination of serious data leaks causing reputational damage to major corporations, a public outcry about the need for better data privacy protections and a strong response from government regulators in Europe and the U.S. have helped to place data governance on the C-suite agenda.

Why you need a data governance strategy Make no mistake, a data governance strategy is imperative. Ungoverned, the increasingly large volumes of data collected and used for more and more purposes in modern business operations can create a legal, technical or reputational morass. With good governance, enterprise data can be more consistent even across divisional boundaries, more accessible and easier to use, enabling better informed business decisions. Data governance policies don't restrict innovation. Quite the opposite. By creating a more reliable data foundation and reducing the risk of misused data, good governance enables new ideas to flourish. It can be tempting for IT leaders and business executives to purchase a governance strategy by contracting a consultancy or software vendor that promises a more-or-less packaged set of policies and tools. But this approach can be disruptive and counterproductive. Existing governance processes may break down when a new strategy is introduced, and busy end users will often ignore it in the rush to get their work done. Amid more sophisticated cyber threats and mounting regulations, every data-centric enterprise needs a data governance strategy that reduces risk and advances corporate goals. The best data governance strategy is developed organically in-house to harmonize with business operations. Following are six undramatic but entirely practical steps to develop an effective data governance strategy.

1. Document where you are now with data governance For many enterprises, just getting started with data governance can be a big, burdensome step that requires a budget. But the simple truth is, your company is probably already doing some level of data governance that can be developed into a strategy. The data governance may not yet have been documented as a policy, but people are already in place to manage corporate data, including a database administrator who sets permissions for access, IT staff that diligently back up and restore data and a network manager who checks that the business intelligence tools are licensed properly. From there, a directory of the company's data assets and a list of those who exercise any responsibilities for that data and their direct reports should be created. And don't be surprised if some sobering, if not shocking, oversights and gaps in coverage are revealed that need quick attention. This informal approach may reflect the messy reality of your company's current governance processes, but the result will be a simplified catalog of assets, roles and accountabilities. Once completed, it's time to get more strategic.

Much of the daily work of data governance occurs close to the data itself. The tasks that emerge from the governance strategy will often be in the hands of engineers, developers and administrators. But in too many organizations, these roles operate in silos separated by departmental or technical boundaries. To develop and apply a governance strategy that can consistently work across boundaries, some top-down influence is required. How can you win executive support for an initiative that may not show a clear advantage to the bottom line? One method, usually chosen by default, is to promote fear, uncertainty and doubt. Horror stories of fines for breaching the EU's GDPR law on data privacy and protection might keep business leaders awake at night.