Understanding data governance and avoiding the most common mistakes

By Simon Judges | 11 December 2015

An increasing number of channels means there is more data available to businesses than ever before. New, more stringent regulations mean that many organisations, particularly those in the financial sector, are finding that they are required to manage the data they hold to ensure it’s as accurate, up-to-date and useful as possible.

As a result, there is currently a lot of talk about “data governance” although, with different businesses using data for different reasons, it will often mean different things to different people.

The clearest and most succinct description I can suggest is “proactively managing your data to support your business”.

But Googling the phrase will result in a number of definitions that range from the boring to the downright confusing. Data governance isn’t about data protection, data privacy or data security. It’s not about data retention or records management, and it has no relation whatsoever to Big Brother.

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

Data governance shouldn’t be led by IT

Successful data governance relies on persuading stakeholders to take ownership of their company’s data and leading any initiative from the start. Typically, however, the lead will be taken by a company’s IT team.

This is unsurprising as, although they don’t own the data, the IT team will understand better than anyone the implications of not managing it effectively. They will therefore often be the first within the business to recognise the need for proper data governance.

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

If data governance is to be truly effective, businesses need to take full ownership of the policies and procedures relating to the creation and management of their data.

Data governance shouldn’t be seen as a project

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

Once buy-in has been achieved from stakeholders for the implementation to go ahead, there follows the greater challenge of winning over the hearts and minds of the wider business. But the need for a change in attitudes, behaviours and even culture can often be overlooked if an initiative’s success is measured by deliverables that can be ticked off on a checklist.

It will be difficult to implement a data governance framework without full commitment from everyone within a business, and future implementations will be even more difficult if the first attempt is perceived to be a failure.

The secret to ensuring an implementation is successfully embraced by the whole company lies in communicating the transition and timeframe from the current situation to one of data governance as a standard procedure.

Data governance isn’t about just ticking the boxes

In cases where the need to implement data governance comes from pressure to satisfy a regulator, it can often be tempting for an organisation to do as little as is needed to keep that regulator happy.

However, this approach can lead to more work for the company than if it had implemented a data governance framework in the first place.

Comprising a checklist showing only what needs to be accomplished and the consequences of not doing so. As a result, people will only do what they’re expected to do, going through the motions, seeing no benefit to their day-to-day work, and making it almost impossible to embed a data governance framework within a company.

It’s also worth considering how often regulators move the goalposts. If a data governance framework hasn’t been embedded within an organisation then, each time the regulations change and the checklist is updated accordingly, the organisation will need to return to square one, with a new set of boxes to tick.

It’s worth thinking from the outset about what’s needed to meet regulatory requirements as well as delivering benefits to the business. By adopting a principle of good data governance, an organisation should be able to comply with whatever is asked for by a regulator. Making the changes necessary for compliance should become a bi-product of an ongoing process without requiring the organisation to start again from scratch.

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

Rather than just a series of boxes to be ticked, it should be viewed as an ongoing process, requiring investment from the entire business. By taking this approach, and aligning the data governance framework with its wider strategic objectives, the business will soon enjoy benefits that far outweigh simply keeping the regulators satisfied.

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

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