Nowadays everyone agrees on the importance of the data governance. The understanding that it is critical to deliver trust, regulatory compliance and that it is a key element to deliver improved business has been well-accepted.
Successfully implementing data governance requires changes and investments in several domains:
People will need get trained and get support with their change. Don’t forget that certain co-workers will take up a new role (i.e. data steward), some people will need to share data ownership, etc. The necessary attention to change management is required.
Your business process will for sure benefit from optimizations but also require change. Important to realize in the data governance – process context is that you will become capable to tilt your organization from system or application silos to an approach where data is governed from a process point of view across your organizational landscape.
Also on a technology level you will need to optimize what you already have in place and most likely acquire data governance specific functionality that you currently lack. Think about a data governance capable business glossary, data catalog, etc.
Making it tangible
Understanding investments is one facet, getting value out of data governance is something else. How do you make all this tangible?
The most successful of our data governance clients focus on the next important areas:
Revenue Impact.Â
Focus on identifying and addressing new business opportunities through data analytics & data science use. The only hard requirement is obviously that your data governance foundations should be in place. You might have the fanciest and most powerful analytical tooling available but without data governance, it remains like finding the magnetic north point with a faulty compass. Calculating the return of this comes down to considering the cost of the data related efforts and the potential business outcome. This is an exercise that will require input from all the involved stakeholders – both business and it.Â
Proper Data Governance is primarily an enabler. The business user area is a great example to illustrate this. Allowing them to move from finding data to applying data, directly results in increased their productivity and value to the organization. They are enabled to focus their core business instead of wasting huge amounts of time before they can start. A recent IDC study calculates the productivity gains will have an average value of €1572 per impacted user per year.
Having better data quality, improved data controls, a connected data speech community, … will also generate operational benefits. No more waste of time due to ping-pong games caused by unclear roles and responsibilities, rework and churn due to dirty or incomplete data, …
Data governance is key for compliance and audit purposes. Having visibility on data lineage, ownership and track and trace of data consumption is elementary for GRC teams. Having a proper data governance platform facilitates this and allows your teams to act more quickly and efficient. Governed automation vs ad-hoc manual effort is what this is all about. In this area IDC projects, in the same study, that organization can realize a benefit of €1280 per impacted user per year.
Besides operational efficiency, the direct cost elements of the overall risk can be calculated quiet easily. Think about the GDPR legislation where penalties are set up to €10 million, or 2% of the worldwide annual revenue of the prior financial year, whichever is higher.
Calculating the indirect costs elements is a bit more complicated. Think about the same GDPR example. The penalty issued for an infringement is clearly specified but imagine that your organization is active in a market vertical where reputation and being a trustworthy party is extremely important. In that type of scenario, getting a GDPR penalty will also have a big impact on your revenue and generate substantial costs to brush up your reputation. Calculating these costs requires organizational and market vertical specific insight.
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