We regularly post polls on LinkedIn on topics of data management and data lineage to collect insights on the experiences and thoughts of our colleagues. We would like to share these insights with you as well. A data management maturity model to assess maturity is the topic for today.

TODAY’S POLL:

These results are based on 2 LinkedIn polls:
View Poll 1
View Poll 2

RESULTS:

1. 47 % of respondents use DAMA-DMBOK2.

2. of respondents use DCAM® 2.2.

3. 5% of respondents use CMMI-CERR-RMM.

4. 5% of respondents use the IBM DG Council Maturity Model.

5. 9% of respondents use the Stanford DG Maturity Model.

6. 9% of respondents use the Gartner’s Ent. Inf. Man. Model.

7. 5% of respondents use their own self-developed/adjusted model.

8. 3% of respondents do not use any DM maturity model at all.

We interpret these results as the following:

  • DAMA-DMBOK2 remains the leading framework for assessing maturity. The model of data management maturity should be aligned with the data management model used in a company. If a company applies the DAMA-DMBOK2 model, it should also use the DAMA-DMBOK2 approach to assess maturity. Performing the mapping between two different models is often “mission impossible”.
  • DCAM® 2.2, The Data Management Capability Assessment Model, is the second leading framework to assess maturity. DCAM® 2.2 elaborates on a very detailed and practical description of the statuses of different capabilities.
    DCAM® 2.2 has been originally targeted the industry of financial institutions. It seems that DCAM® 2.2 has extended its focus and become more a generic framework.
  • Still, around 5% of respondents adjust existing models or develop their own. As I have mentioned above, a company should align the data management model with the maturity model. If a company has developed its model of data management, the maturity assessment model should match it.