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Avoiding the most common mistakes in data governance

More channels have led to the availability of more data than ever before. New and pending regulations mean that businesses are finding it increasingly important to manage the data they hold, to ensure it’s as up-to-date, accurate and relevant as possible.

It’s perhaps unsurprising, therefore, that there’s currently a lot of talk about ‘data governance’, a term which will mean different things to different people, depending on the way they use their data.

By way of illustration, a Google search will return a number of definitions that range from simply boring to downright confusing.

The most clear and succinct definition of data governance I can offer is “pro-actively managing your data to support your business”.

It isn't about data protection, data privacy or data security. Neither is it about data retention or records management, and it has no relation whatsoever to Big Brother.

Without understanding what data governance is and what it isn't, it’s easy for businesses to make mistakes during its implementation. Here are a few examples of such mistakes, along with suggestions as to how they can be avoided.

IT shouldn't be in the lead

For data governance to succeed, an organisation’s stakeholders needs to be persuaded to take ownership of the data and lead the initiative. In most cases, however, the IT team will take the lead. After all, while they don’t own the data, the IT team will understand better than anyone the implications of not managing it effectively, and will often be the first to recognise the need for proper data governance.

However, while this approach may appear logical, it could prove problematic. IT-led initiatives will generally focus on the tools needed for tasks such as cleansing data, while the actual quality of the data will only really improve if changes are made to it at its point of entry.

Businesses need to take full ownership of the policies and procedures relating to the creation and management of their data for a data governance initiative to be truly effective.

Don’t view it as a project

Implementing data governance can often be viewed as an internal project, but it won’t be successful if it’s simplified to a list of tasks.

Once an organisation’s stakeholders have given the go-ahead to the implementation, the next challenge is winning over the hearts and minds of the wider business. However, this need for a change in attitudes, behaviours - and sometimes even culture - can be overlooked if the success of an initiative is measured by deliverables that can be ticked off on a check-list.

It will prove difficult to implement a data governance framework without full commitment from everyone within an organisation, and practically impossible to achieve in the future should the first attempt be perceived as a failure.

The secret to ensuring the whole company embraces the implementation lies in communicating the time-frame of the transition from the current situation to one of data governance as a standard procedure.

It’s not about ticking the boxes

When the need to implement data governance comes as a result of pressure to satisfy a regulator, it can often be tempting for an organisation to do as little as is required to keep that regulator happy.

Doing so, however, can often lead to more work for the business than if it had implemented a data governance framework from the start.

In using a check-list showing only what needs to be accomplished and the consequences of not doing so, people will simply go through the motions, doing only what they’re expected to and seeing no obvious day-to-day benefit. Such an approach will make embedding a data governance framework within a company almost impossible.

And it’s worth considering how often regulators will move the goalposts. Without a data governance framework already embedded then, whenever the regulations change and the check-list updated, there’ll be a new set of boxes to tick and the organisation will be back to square one.

By adopting a principle of good data governance and thinking about what’s needed to meet regulatory requirements as well as delivering business benefits, an organisation should be able to comply with whatever a regulator asks for. Making the amendments needed for ongoing compliance will be a bi-product of an ongoing process and the organisation will avoid the need to start again from scratch each time.

Data governance is concerned with how an organisation manages its data, and the appropriate level of control that’s applied to its use.

Its implementation should be seen as an ongoing process, rather than a series of boxes to be ticked, and requires buy-in from the whole organisation. By taking this approach, and by aligning the data governance with wider strategic objectives, businesses will soon enjoy benefits that far outweigh simply satisfying the regulators.

Nicola Askham, The Data Governance Coach, on behalf of Stibo Systems

Image Credit: Shutterstock/alexskopje