6 thoughts on “What are your business drivers for data governance?

  1. I like the fact that, in discussing/introducing data governance, you make reference to laws and regulations because data governance is about compliance and mitigating risks. One story given about data governance is to thin of our water or electricity supply: Underlying all this is data quality as the main driver.

    I also like the fact that business drivers are framed in questions? That is how business intelligence/warehousing solutions are designed/delivered: what are your KPI? How quickly do you want must the info be made available, at what level of accuracy, to enable you make decisions? That sort of thing.

    You’ve also addressed one of my gripes with data governance – though I see that you seem to have fallen into the same trap. Simply stated without tools data governance policies and whatnot will be pieces of paper on walls. Here is the rub: for example, does MDM need data governance or does data governance need MDM? I agree it’s a chicken and egg scenario but understanding the relationship is important. Under point 2 you alluded to customer info potentially being stored across many systems/processes. Data governance needs to track that data. One solution to that is if all the master data were managed in a single repository – but not necessarily – a federated SOA can achieve that. So in this case data governance does not need MDM. Looked from the MDM’s point of view, MDM is about presenting a single version of the truth and in so doing improving the quality of data. Invariably MDM would need to cleanse the data and there will fallouts from this process. These fallouts would benefit from a data governance structures that has identified policies and accompanying data stewards that must help clean the data. Question is should we then list MDM as a driver of data governce? To me MDM is a just a tool data governance needs to achieve its goals as aptly phrased under point 2.

  2. I agree 100% that data governance without tools is largely useless. IN previous posts I have discussed, this – in particular, the importance of data quality tools to generate measurable issues.

    There is a massive difference between logging an issue as “Our medium business credit risk data is bad” and logging the “3% (16436records) of our credit risk records have do not have the required collateral data captured exposing us to losses of $23.5million”

    I was simply trying to draw the link between data governance (as a theoretical construct) and the practical application of applying these constructs to the management of master data an enterprise level.

    Most research shows a string link between successful MDM implementations and a focus (before, during and after implementation) on data governance and data quality.

    However,the principles of data management as formalised by data governance can be applied far more broadly than just to master data – e.g. Basel II requires that transactional data used for risk calculation is managed and measured. So I would suggest that while MDM is useful for Data Governance it is not essential

  3. I like your comments about starting small. Data Governance initiatives often seem quite intangible  to sponsors when first raised and a big project with grand plans and similarly sized budget requests may well have them running a mile. 

    Compliance reasons can be a hard sell for big projects – I’ve seen tendencies to follow the path of least resistance to hit these requirements rather than addressing the larger issues with work around data governance. In other areas our compliance drivers aren’t as compelling. For example, in Australia we’re yet to be hit with a SOX equivalent and privacy legislation has fewer impacts than elsewhere in the world. 

    I advocate getting those small, quantifiable wins in first, either through small budget tactical pieces of work or even via under the radar skunkworks, and then using these success stories to show value, probably either through cost reduction or cost avoidance in these first cases. From there  it’s easier to go to the sponsors or funding bodies and start to propose larger or more wide ranging initiatives, although I favour keeping these early proposals highly measurable in what they’ll deliver. That way you (and the sponsors) will know when you’ve been successful. This goes to the excellent point you make about communicating the wins.

  4. Pingback: Business driven data governance critical to manage cloud complexities - Kserokopiarki Kopiarki Wielofunkcyjne

  5. Pingback: Data quality will help insurance companies gear up for impending SAM regime - Kserokopiarki Kopiarki Wielofunkcyjne

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