Getting a data glossary in place can take a lot of hard work and effort, so it can be particularly frustrating if/when your business users don’t truly appreciate the value it brings and either don’t want to help you build it or don’t use it when it has been built.
Why are you creating a Data Glossary?
A big reason why such a scenario happens is because we often ignore why we are creating a Data Glossary in the first place. By this, I don’t mean you should have one because you are implementing Data Governance. I mean answering the question why your business users should want and use one?
This doesn’t mean rattling off a predefined list of benefits, but rather taking that deep breath, stepping back (figuratively speaking) and working out why exactly you’re building a data glossary in the first place and for who.
Why does your organisation need one?
I’m often asked how to engage business stakeholders (which you should be doing right from the start of your Data Governance initiative) with your data glossary. To do this you need to understand the value it would bring to them.
And this message needs to be tailored to each group of individuals you’re speaking to, as one reason why won’t work universally across different stakeholders. These messages need to be specific for your each of your groups of stakeholders, however, here’s a couple of benefits to give you some examples when seeking to communicate the value of your data glossary.
For instance, the faster development of reports is a common theme as a lot of time and effort often can be wasted creating reports without agreed definitions. This can result in ongoing disputes, wasteful meetings and, ultimately, poor decision-making with damaging consequences for an organisation.
Another potential benefit of a data glossary can be identified in the quicker implementation and deployment of new systems. Whether building a system from scratch or implementing a bought package, decisions need to be made as to the data which will reside in the system and this will result in lengthy debates on the exact definitions of certain terms like ‘customer’. Wouldn’t it be nice (and much quicker) if those debates happened just once and the agreed definitions logged in the data glossary to be referred to in the future instead of repeating this for each new system? And of course this approach inevitably results with different systems having slightly different definitions of the same thing! That is not going to help data integration and analysis…
A data glossary is invaluable for streamlining definitions across an organisation and ensuring a common understanding over data and how it can or should be utilised.
A data glossaries can act as a cornerstone of proper, consistent communication – the value of this speaks for itself.
Ah, you say, but we already have a business glossary but our business users are not engaged with it. How are we supposed to communicate value?
Simply put, don’t let the fact that you already have a data glossary stop you from taking the approach detailed above. You simply have to work out what value it will bring and communicate it. This would mean identifying what data challenges your business users are facing and to use these examples to demonstrate how a data glossary can solve those challenges.
When having conversations with your business stakeholders, it is common for them to get confused between a data glossary and a data dictionary. If that is a challenge you are facing this blog will help you explain with confidence. Read it here.
And you may want to share this video with the people you want to write definitions for your data glossary to make sure you get good quality useful definitions to put in your data glossary. Click here.
To read more about data, click here.