When I attended Enterprise Data World (EDW) 2011 in Chicago, I was fortunate to sit in a session led by April Reeve describing how she used the DAMA Data Management Body of Knowledge (DMBOK) to develop a maturity assessment instrument that she deployed within a mortgage bank. Taking inspiration from this, I decided to undertake a couple of initiatives. One of these was to develop a comprehensive maturity assessment tool built around the DAMA DMBOK. (I will be writing about that in a future blog) The other was to document the experiences of other organizations in using it to drive their data management policy.
At EDW 2012 in Atlanta I presented 5 cases to a packed room- a pleasant surprise given the 7:30 am time slot! I had developed a good cross-section of studies- Statoil (oil and gas), State of Colorado (state government), Telus (telecommunications), National Bank of Abu Dhabi (banking) and Government of Canada (federal government). (to see the presentation, click here)
In every case, there was a unique business context, a unique way of applying the DAMA DMBOK, and a full range of results and lessons learned. This is the first in a series of blogs that will discuss how the DAMA DMBOK was used to improve data management in their organization.
In the case of Statoil, the leadership in the organization realized that data management activities were a strategically essential component of their exploration and development function (representing 15% of the cost) and that they were expending considerable sums of money having to “re-master” their archived data every year. They realized at that point that they needed to take a fresh look at how they were approaching data management, and recognized the potential of the DAMA DMBOK to provide a robust and objective framework to develop a comprehensive and unique insight to their complex data management picture. One aspect that appealed to them significantly was its plain language- thus easing the task of communicating with the business and their non-information management(IM) personnel.
Based on the DAMA DMBOK, Statoil established a completely new IM governance approach, an IM architecture, a mechanism for prioritizing IM functions. Finally, they were able to successfully implement Master Data Management(MDM) practices (no small feat itself)
More importantly- the successful improvements in their IM practices yielded key benefits for the business. They were able to visualize data volumes based on facts, not assumptions. This was important because they needed to focus on the areas experiencing exponential data growth (at the time in 2010 their volume had exceeded 1,250 terabytes). Their MDM strategies yielded demonstrable improvements in data quality. Finally they were able to objectively identify the functional areas of IM that required enterprise-wide improvements.
The primary lesson’s learned by Statoil included a stunning realization of just how many software applications they were employing (in excess of 3000). They realized that as an oil & gas company, they actually had a long history and depth of experience in certain areas of data management and were able to lever that expertise to the enterprise level. Their experience with MDM was more complicated than the usual case because the attributes were owned by so many different processes. Finally, and most significantly for us in the DM profession, they realized that the DAMA DMBOK provides a useful, objective and structured approach to enterprise information management.
If you would like more information about Statoil’s experience with the DAMA DMBOK, please feel free to contact me.