Wednesday, May 12, 2010

Attributes of a Data Rock Star

Earlier this week, Jill Dyché (@JillDyche), successful author, blogger, BI, MDM and Data Governance consultant and all around information guru, created a flurry of creactivity (I just made that word up – it’s a combination of the words creative and activity), when she tweeted a simple response that suggested a couple of data rock star types, in response to an excellent on-line article Are You a Data Rock Star? by Elizabeth Glagowski.

Elizabeth’s article has some excellent descriptions and examples of the attributes of what makes a great data rock star and Jill’s vigorous (and often humorous) take on business and IT alignment always identifies the rock star behaviors of being able to communicate the linkage between a company's information and its business value.

The results of the flurried creactivity, was Jean-Michel Franco (@jmichel_franco) coming up with a name that was quickly adopted;The Rolling Forecasts”, and Jim Harris (@ocdqblog), in his latest Obsessive Compulsive Data Quality blog post, coined the brilliantly perfect and perfectly brilliant lyrics to the band’s first song: “You can’t always get the data you want”.

So what I decided to do here was attempt to compile all these rock start attributes and behaviors in a simple format, so that they can be easily re-used and referred to. I plan on adding these to our internal wiki and identifying them as behaviors of successful data stewards. I a) hope they get read and b) hope that they get people thinking, behaving, changing…

· Excellent communicator of business and IT concepts using common language

· Ability to link information to business value

· Effective at communicating concepts and new ideas at early stages in order to reduce change management efforts

· Has excellent self awareness and understands the link between trust and partnership

· Is able to express thoughts and opinions in various ways in order to be able to provide feedback when others may not be interested in hearing it

· And seeks out and is receptive to feedback and continuously provides the opportunity for others to provide it

· Actually listens to the feedback and changes behavior/process/approach for continuous improvement (don’t get me started on people who ask for feedback but couldn’t give a rat’s a**..)

· Understands the link between clarifying expectations and how that will lead to success

· Ability to know how to engage and enthuse others – must understand the body language, communication preferences, motivations and needs of others

· Must be able to spot opportunities and take advantage of them – and especially do it in a way that others are unaware of it

· Must be comfortable pushing the boundaries in order to change things and do so in a way that others are unaware the boundary is being pushed

· Must be comfortable exerting authority and using it appropriately – all the while smiling and engaging others

· Is able to identify key success measures from both business and IT perspective and communicate effectively – at the beginning to confirm what is expected and throughout to continue to re-iterate value

· Is well liked and respected – this will ensure access to resources, tools, other stakeholders, hidden information (you KNOW that happens), and will help pave the way through political and cultural roadblocks

· Be able to articulate solutions as practical and logical and tie them directly to group/organizational goals

What do you think?


  1. Hey Data Rock Star!

    I love the word "creactivity" (I must admit to being torn between this word and your other awesome word "communivate" - perhaps we could also "creactively communivate").

    Great job listing out the attributes of a data rock star. Just as Jill Dyché was quoted in Elizabeth Glagowski's article, "that we haven't invested in data like we should implies that we haven't invested in building the necessary skill sets." I don't disagree and often lament these skills are conspicuously missing from the job descriptions of many positions all across the organization that are essential for future success.

    As Elizabeth wrote, "not everyone needs to be a data rock star, a team that combines those who have specialized data skills with business-savvy data rock stars will make a winning combination."

    I think it's important to point out that many of the attributes of a data rock star have less to do with business or technical skills per se, and much more to do with effective interpersonal skills and the willingness to embrace communication and collaboration.

    Everyone is a rock star in their own way. And a rock band is way more powerful than any one of its members could ever be as a solo act.

    May "The Rolling Forecasts" and all rock stars, data or otherwise, forever rock on!

  2. YES YES YES!!

    As Jim points out, and I'll highlight AGAIN as this is SOOOOO critical: "much more to do with effective interpersonal skills and the willingness to embrace communication and collaboration." You get this right, and SO much more is right.


  3. Thank you Jim and Berry for the positive comments!
    I also love the statement: "effective interpersonal skills and the willingness to embrace communication and collaboration". It's risky right? To put yourself, your thoughts, your comments, your contributions out there because others may not agree with you? But what you are doing is being transparent, and inviting the trust of others, which can only lead to the best possible outcomes :)

  4. I have very little to add to such a great list of attributes. Good stuff, Jill!

  5. Another awesome post by an awesome data rock start. Now we need to get the band together again and start rocking at all occasions. Will you be the lead singer?

  6. Thanks for the supportive comments Phil, much appreciated!
    Nicole, you KNOW I am working on that right? :D

  7. I would also add...can explain the value of ad hoc visual analysis in the (3) contexts of data:

    1. The data you know - things like financial statements.
    2. The data you think you know - stuff you perceive but incorrectly interpret.
    3. The data you don't know you need to know - insight discovered through ad hoc visualization.