When I'm running training courses, one of the early topics we cover in the day is the various challenges of implementing data governance, but to be quite honest, the challenges start long before you even start designing and implementing your data governance framework.

It can be a real struggle to get your data governance initiative approved in the first place. So, I wanted to have a look at the reasons why this might be the case so that you can both plan for and mitigate them.

I think the challenges span four main themes:

·      data governance is rarely considered a top priority

·      it is hard to measure the value of data governance

·      it is hard to measure the success of your data governance initiative

·      your organisation may be successful in spite of its data

Let's have a little look at each of these in turn.

Data is not a top priority

This has been a common issue for many years, although the more recent focus on data and the drive for organisations to become “data-driven” has meant that this is getting slightly easier. But, be warned, it comes at a price as many senior executives hear about the “cool” data initiatives such as AI and Big Data Analytics and they want those without putting in place the data foundations (i.e. Data Governance) that enable such initiatives to be successful. 

 In order to overcome this, you need to sell Data Governance in terms of the outcomes it will deliver, and you need to tie those outcomes to the things that are a priority for your organisation (a good place to look for these is in your corporate strategy).

 It's hard to measure the value of data governance

The problem is a lot of the benefits which Data Governance will deliver can't be measured in advance. They are intangible.  You could say that you will protect the company from things like reputational damage or investigation and censure by regulators, but your stakeholders could respond with something like: “We've never had data governance before and have not faced those particular issues”.

However, I think it's fair to say that every organisation I have helped implement data governance has achieved significant cost savings.  Most organisations experience many inefficiencies as a result of data not being available or accurate.  Alex Leigh (a fellow consultant I often work with) always says that these inefficiencies cause a lot of organisations to be “data fix factories”. 

Reducing inefficiencies is just one cause of an increase in profits after implementing Data Governance.  Many of my clients report that they've been able to better identify new opportunities or provide better customer service because the quality of their data is better.

These are good examples of where data governance has helped find and resolve issues.  The trouble is that you don’t find and resolve them until you have put Data Governance in place. At the time you are asking for your business case to be signed off, it feels a bit like you're gazing into a crystal ball. You don't know what the issues are that you are going to solve.

My advice in these circumstances is to go on a hunt for your data quality horror stories. Try to get some examples of real things that have gone wrong in your organisation and cost money.  Without having some real concrete examples, you are building a business case based on an unquantifiable value that may be delivered at some point in the future!

It is hard to measure the success of your data governance initiative

This is very similar to the point above because if your potential future benefits are unknown it is hard to agree on indicators to measure the success of your initiative.  You will undoubtedly make cost savings and increase profits, but if you don’t know where these will be, you also don’t know what to monitor at the time you are writing the business case.

Using the data quality horror stories mentioned in the previous section will help you articulate where you will be looking to measure success. Another area to consider is new systems. If your organisation will be implementing or designing a new system, you will not have to spend a significant amount of effort and analysis of data (as was likely the case). Data will be well documented and its quality understood in advance of the project. So try to get evidence of how much effort this has taken on previous projects.

Sadly, there is no easy way to answer this is advance - you are in effect waiting for things to go wrong so that you can fix them.

Your organisation may be successful in spite of its data

Finally, an issue I've seen a number of times.  If your organisation is successful in spite of a lack of understanding and control of their data, it is hard for senior stakeholders to understand why they should invest in Data Governance, especially if there is no regulatory requirement for your industry to do so.

In this case, my advice is the same as point 2 – you need to find your data quality horror stories to provide evidence that poor data quality is having an impact on your organisation.

I don't want you to think that it's all doom and gloom. Creating a successful business case for data governance is possible, but I want you to go into it with your eyes open and aware of the challenges facing you. Having help from someone who has done it before, is a great way to make your business case more successful.

This article was originally published on www.nicolaaskham.com