Deliberate data design and those pesky system constraints.

Is one of the success factors for good data governance due to the alignment of people and process before the technology? Don’t we have to get everyone pretty much on the same page on how we’re going to handle our data before we start talking about systems constraints? If we start to talk technology before the business get their ducks all in a row, won’t we go down the slippery slope of technology starting to drive the solutions vs. the all important business need? Won’t we all look silly if we aren’t even on the same page? 

I’m asking this because we’re at the point where we’ve got some high level processes drafted up, and we’re getting close to alignment. We’ve designed the processes based on the aligned business needs which is a guiding principle that I recommend be a driver for all data initiatives. And now that we’re getting close, but before we’ve got it nailed, the technology constraint talk is starting to creep in. Yikes! I’ve been there before. When you start to talk about ‘the system’ before the process is nailed it doesn’t go quite as planned. It didn’t work the first time and here we are again, only this time we have an opportunity to do things the right way. 

Of course once we get everyone on the same page we’ll have to figure out how we’ll implement the agreed upon process alignment taking into account our technology, resource and scheduling constraints. But isn’t that just um…normal common sense? And something we should do together? Once we’re all talking about the same thing? 

I would really like your thoughts. 

Thank you

2 thoughts on “Deliberate data design and those pesky system constraints.

  1. Nicole Carriere

    Not too sure how to answer this one. I totally feel the pain. Every time we ask the business to fit their processes into a given technology, I feel uncomfortable. I’m from a private sector background where when the business asked something, we had a ‘of course we can do it’ attitude. Knowing very well that it was a question of cost and resources but anything can be done.

    This ends up to be the famous question: is it the chicken or the egg first? The business and people or the technology first? And if we ask the business to follow the technology, will it still meet their requirements?

    So, my conclusion is going to be: if the business requirement fits the data management best pratices, go for it. Technology should be able to follow!


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