Data Governance maturity models can be a powerful tool for formulating improvement plans, communicating concepts and measuring progress, but they only work well when tailored to the specific context of the organisation.
I used to be convinced that Data Governance maturity models were highly overrated, with little or no added value. Nice pictures if you were lucky, standard terms that apply to most situations and a bit of extra fluff to sound clever.
A large part of my disapproval came from seeing multiple organisations struggling with Data Governance and seeing the (lack of) results achieved when using generic models, because little attention had been paid to organisation specifics including culture, actual data problems and the organisation’s goals and objectives. Any resulting output from the model was generally either irrelevant or too high-level to be useful. To make matters worse, because the output couldn’t be translated into a prioritized improvement roadmap, the end-result was usually a data governance effort which didn’t gain traction, got shelved, or was hugely inefficient.
I still have the same opinion of generic maturity models. However, if you take a generic maturity model and tailor it to a particular organisation, it is possible to identify specific improvement points within a short time frame. How do you do this? Tailoring the maturity model means focusing in on the organisation’s specific objectives, their actual data problems and the individual context within which the organisation operates. And adjusting the model accordingly.
Framing suggested improvements within an organisation-specific maturity model helps with focus, emphasising which particular data governance concepts need to be addressed and why this adds value. Tailoring the maturity model to the specific terms and language of the organisation helps with communication, highlighting where data governance fits into the overall picture. Prioritizing the improvements and translating them into a roadmap make the effort required even clearer, increasing enthusiasm levels as a result. And as this enthusiasm results in improved data governance, progression can be captured and shared by amending the maturity model graphic, generating yet more energy around the data governance programme.
Let’s make things more concrete.
Below is the generic Free Frogs Data Governance maturity model.
The various components of our overall view of Data Governance are visible in the model. However, we only use this generic version of the model in two specific situations.
(1) The generic model provides an initial framework for discussions
Sometimes when people are new to data governance, it can be difficult to grasp how wide its impact is on a broad range of business issues. By using the model as a guide, we can focus discussions on the different aspects of data governance, their implications and their importance within different business situations. It provides a useful framework for the conversation around data governance, ensuring all important angles are covered; and it provides a handy memory aid to refer to in follow-up discussions and reviews.
The model also helps highlight that while different organisations have different data problems and priorities, it is still important to approach the specific data-related challenges within the context of the organisation’s overall data governance. For example, it’s almost impossible to have a conversation about data quality without also discussing definitions, master data and business rules; and it’s not very future proof to talk about data quality without also looking at lineage and culture.
(2) The generic model provides an accelerant to the organisation-specific maturity model
The second situation in which we use the generic Free Frogs Data Governance maturity model is as a quick start to generate an organisation specific maturity model. Often, early on in conversations, it is already clear what pain is being experienced due to a lack of well-structured data governance. By placing these pain points within the context of the organisation’s particular goals, challenges and culture, we can focus in on the most relevant aspects of the generic maturity model. We then tailor these aspects to the organisation’s situation, adding in other organisation specific components and amending the language. This gives a more accurate picture of what needs to happen, than what is possible with a generic model. Additionally, an organisation specific model resonates more when we’re communicating.
After the model has been tailored to the organisation’s own situation, it can then be combined with the output of the data governance business case to quickly provide a concrete, prioritized, organisation-specific roadmap for the data governance effort.
The figure below shows one example of an organisation specific maturity model. In it, a subset of data governance subject areas with particular relevance to the organisation’s situation have been placed alongside other organisational factors to provide an organisation specific model.
It’s clear to see that a number of the subject areas are different to the generic maturity model. This tailoring helps the organisation focus on its particular data governance challenges. The model improves communication around data governance, highlighting which data governance aspects need focus if the overall added value of data in the organisation is to improve. When the underlying scoring level descriptions are shared, awareness of improvement steps needed becomes even clearer.
The tailored maturity model also gives an easy to understand overview of the original situation compared to the progression achieved in certain areas. Added to that, the underlying maturity model level descriptions and checklists provide concrete improvement points that the organisation can prioritize based on their unique situation of the organisation and translate into their data governance roadmap.
Conclusion: use a generic model only as an introduction; then switch to tailor-made to accelerate the data governance improvement efforts
Having compared the value of both maturity model uses outlined above I’m definitely a convert to the idea that a maturity model can add value, provided it is well thought out, and customized to the organisation’s situation. However, this has only served to further increase my perplexity for those in our subject area who try to apply standard data governance maturity models without thought to context, culture, and organisation specific challenges and goals. My advice: don’t do it!