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Leveraging Data Management Maturity Model to boost data management capabilities

As a business organization that wants to leverage data to drive insights & innovation, you must have realized that selecting the right maturity model is the most important factor in the data strategy. The Data Management Maturity Model (DMMM) helps enterprises to measure & improve their data management capabilities by providing guidelines for it.  Today’s enterprises can implement data management practices through this consistent, organization-wide framework. It helps in creating data that is accurate & accessible across the organization. DMMM is driven by strategies & policies that go with industry standards.

What are the challenges with existing data management models?   

Today, we have so many data management/governance maturity models to follow. Some of them are – DAMA-DMBOK2, CMMI CERT-RMM, IBM Data Governance Council Maturity Model, DCAM, Stanford Data Governance Maturity Model, and Gartner’s Enterprise Information Management maturity Model. However, the usage of these models is not full-proof.  

There are several challenges in the implementation of these models. One, you must be able to compare these models to find the optimum model for yourself, but, all of the above models are hardly comparable given the huge difference in their meta models. Two, if you want to assess your organizational data management maturity, you must first align/map the metamodel of the data management used in your company with the chosen model which is difficult. Three, Companies fail to reach one of the key goals of the maturity assessment – to benchmark maturity status of their organization against other similar companies in the industry.  

What does the DMMM have to offer?

  • It offers a practical, implementable, step-by-step approach to build, embed, and measure data management capabilities.  
  • It provides a standard method that every data officer can wield to track progress.  
  • It offers a consistent benchmark to put under comparison various data councils i.e. collection of data stakeholders.  
  • DMMM gives a granular list of artifacts which is helpful in demonstrating evidence & progress.  

It all started in August, 1986, when the Software Engineering Institute (SEITM) at Carnegie Mellon University started developing a maturity framework that would help enterprises in improving their software processes. The MITRE Corporation helped SEITM in its initiative.  

In the existing maturity models, DCAM V2 is very popular, while DAMA, CMMI custom maturity models are popular too. However, the success of any maturity models is dependent on how well they are implemented. 

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Reaching & maintaining maturity 

Different data governance activities such as data modelling, issue logging, and the documentation of the IT estate are continuously changing, so it becomes obvious that not all data management aspects of an enterprise will initially be mature. However, it is absolutely possible to enhance one’s maturity level by implementing the necessary changes. So, getting complacent after reaching a particular stage in the maturity model should not be your goal, because maturity is not a fixed state. Nevertheless, once considerable maturity is achieved, it is usually taken as ‘stable’, which means occasional manifestation of any issues are not responsible for the loss of maturity level. Changing data management tool is an example. In the process of changing data management tools, an organization may temporarily loose the compliance but that should not be considered as a degradation in the maturity level as long as it is an approved migration period.

There are so many data management & governance maturity models available, and each has its own approach. As an DataOps expert, ISmile Technologies help enterprises align their data strategy & choose the best maturity assessment tool. With deep expertise in this field, we don’t re-invent the wheel but provide the best solution to your data management issues by leveraging available solutions. We help businesses accelerate their journey to AI-powered automation & improve data quality to maximize their business potential. For more details, please get in touch with us.

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