The intersection between HR strategy and HR technology

Understanding HR Data Governance

Understanding HR Data Governance

Oct 4, 2010

We bought my wife a new bike this weekend.  She is not usually a bike rider, and the last time I took her out riding with me, she swore never to go riding with me ever again.  I suppose that one does not necessarily realize this if one does not have sufficient self awareness or awareness of the surroundings when in college, but it’s been about 15 years since my last bike ride with her.  This time around, rather than trying to take her out on (what I guess were) fairly advanced mountain biking trails, we decided that we would buy her a bike for cruising around town – a bike to have fun on, but certainly not to go fast on.  Today was my first bike ride with her, and we decided to head out to San Francisco’s new Chinatown over on Clement street to buy some dim sum.  We then proceeded to the Golden Gate Park where we sat by Stowe Lake eating. 

I know that we’re all sick of talking about Data Governance, but the reality is that most of us still have not implemented it.  In fact, I’m going to go as far as to suggest that most of us don’t really know what it is, even though we execute forms of data governance in our everyday lives.

Data Governance basically consists of three things:

  1. How we make decisions about data,
  2. How we define the data,
  3. How we execute processes that involve data.

To start, I really needed to make a decision about riding a bike around the town with my wife.  While I might enjoy the fast and aggressive weekend rides, spending time with my wife in a way that we both would enjoy was paramount.  The next step was to define the type of bike we’d get her – in this case, not a race worthy mountain or road bike, but a street type of a bike.  Finally, we needed to head out and ride at a pace and in a style that would keep her interested, in this case, food and the park.

The HR data governance structure begins with an organizational structure that allows us to make good decisions.  Usually this is a committee or set of groups that escalates what the needs are and how to deal with them. 

We then need to define the data.  Thinking that as we reach across multiple HR systems in a variety of global countries and regions, that we can easily define data might be naive.  Each system has their own definition and countries have widely varying approaches to data as well.  Without a common understanding, it’s next to impossible to have a resultant set of data outputs and outcomes that is reliable.

Lastly, we need to reformulate all of our data processes in a way that is consistent with our data definitions and maintains our quality standards.  Data governance and the definitional process is a predecessor to any HR process, but without HR process, the purpose of data governance (data quality and access controls) is a promise that cannot be kept.

At the end of the day, HR data is an enabler, and we have all experienced HR data that is so messy that it no longer enables anything.  Data Governance is the solution to this problem, but it comes with multiple components, each of which must be implemented for an overall governance program to have any use.

One comment

  1. Aditro is a partner to SuccessFactors in the Nordics and we very often notice that customers huge Strategic HCM projects is stopped because they’re lacking global masterdata. This data is often generated by local payrollengines and I agree with you, to fragmented and very different in quality. In SuccessFactors you could use “Employee Central” instead and we have named that kind of Data, “Human Capital Data” HCD. It will then function as a kind of overlay to traditional Masterdata/Headcount and contents BOTH personell info like adress, Visa etc AND data about competence/strategic skills etc.

    New but good thinking!!

    BR/Sture Ragnehag

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