Member’s corner | Where are you on the data governance evolution scale?

This blog post was written by guest author Ronan Brennan, Chief Technology Officer, MoneyMate and is this week’s NICSA Member Feature.

Just about every asset management firm now claims to have a formal data governance process in place – in fact if firms aren’t saying this we should be worried indeed. So while all data quality management governance processes may be created as equals, they are very rarely at the same point of evolution – with the bottom of the evolution scale being a million miles from the top-end fully evolved processes.

DataGovernancePicIn the diagram on the right, you can see that processes in the early stages of evolution start as chaotic processes, with often low levels of standards and formal operating procedures, with very little sign of an obvious ‘master plan’  or strategy.

In order to move to the next stage on the evolution scale, you need to establish standards, you need formal operating procedures for data stewards such that a semblance of an operating data quality management process starts to take effect with a strategy and master plan identified and communicated to the applicable stakeholders.

The mid-point in the evolution scale is achieved when the process can be accurately described as defined – that is where you have identified key performance indicators that show the health of your process, where you have documented artefacts such as a data dictionary and rules dictionary, where you can show you have stewardship operating across the breadth of the data creation to data consumption processes, with applicable technology frameworks in place to support stewardship of the governance with key processes like root cause analysis being tracked and measured.

Very few firms have moved past the ‘defined’ stage in the evolution process. Getting to the next stage ‘Pro-active’ requires serious attention and investment and very often monumental cultural re-alignment. Pro-active governance is achieved when you can demonstrate a cast iron continuous improvement cycle, with error feedback loops constantly leading to process improvement – very much in the model of six sigma – in fact many firms who have attained this level, do so under the auspices of an investment in ISO9000 or Six Sigma. At this point of evolution, the firm is applying automation across the board to root out the manual human errors that plague many firms today. Key to the approach is a unified governance approach to how data is managed across all of the data silos in the firm.

Finally, you have reached the nirvana point of evolution when your data quality governance has become what many refer to as ‘Predictive’. At this point of evolution, not only is the process fully automated, it also has a fully demonstrable audit trail that fosters accountability and ownership. The top-down strategy is fully in tune with the bottom-up application of the strategy, with complete cultural alignment across the breadth of the firm, effectively with the people, the process and technology all working in harmony. At this point, your process feedback loops are fine tuning, rather than fixing.

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