Top 3 Data Strategy Mistakes (and How To Avoid Them) – Part 5 of 5

In Part 4 of this series I explained that including details on “how” your Data Strategy will be achieved is critical to making it effective.  In this final post, I wrap-up the three most common mistakes and ask: what are the lessons we can take from them and how might you apply them to your Data Strategy, now?

Please read my Disclaimer by clicking here.

Bringing it all together

In summary, the Top 3 Data Strategy Mistakes (and How To Avoid Them) are:

Mistake #1: Unclear (or missing) Business Outcomes - Always start your Data Strategy with a clear articulation of what your Business is trying to achieve and map every recommendation to whatever those target outcomes are.

Mistake #2: Unbalanced or Biased Capability Mix - Make sure the broad range of potential Data capabilities are considered and recommendations are aligned to Business Outcomes with clear rationale explored and explained.

Mistake #3: Missing the "How" - The inclusion of practical steps to deliver the Strategy, including how it will be measured, is a critical component that moves your document from a glorified Vision statement to something that can be executed to deliver business value.

Applying these lessons to your Data Strategy now

  • Are you working on a Data Strategy now?  If so, is there anything in this series of posts that you could use to improve the one you’re working on?
  • Are you struggling to implement your Data initiative?  If so, have you considered looking back at your Data Strategy and considering whether you’ve made any of these mistakes?  Could the lessons here help you move to a more successful place?
  • For Data Professionals: have you seen a Data Strategy with any of these characteristics, or are there any other common mistakes that you’ve seen people make, that you think should have made the top list?


I hope you’ve found this series of posts on Data Strategies interesting and useful.  I’d love to hear any feedback that you have: is there anything you agree or disagree with?  Is there anything you’ve found particularly helpful or anything that could be clearer?

Comments

Post a Comment

Popular posts from this blog

Why does maintaining legacy technology cost so much?

Why does maintaining legacy technology cost so much? Let’s compare it to a building. Imagine you have an old converted barn, which has a thatched roof. In the past, thatching was one of the most advanced techniques for roofing, providing outstanding insulation and protection from the elements. Thatching was also a common skill, so maintaining a roof built using this technique was relatively cheap. Nowadays, a thatched roof is no longer cutting edge. More modern methods last longer with less need for maintenance. The skills needed to maintain a thatched roof are scarce, so expert craftsmen can charge more. Also, if you ever wanted to extend your house, to add more space or use it for other purposes, connecting it to modern roofing structures will be hard and expensive, and will make it even harder and more costly to maintain in the future. Unlike a thatched roof, your legacy technology doesn’t ‘look nice’, so other than the fact that it ‘still works’, the benefits of continuing to inves...
Read more

"The reluctant student" - Section 1 of 7: THE DATA LITERACY DRIVING SCHOOL (free excerpts)

Image
  This is the first part of the chapter titled “The Data Literacy Driving School”, from the book “ The Data Garden And Other Data Allegories ”. ______________________________ The reluctant student You look over at your driving instructor and sigh. Why do I have to do this again? you think. Taking data taxis had always been fine before. This seems like it’s going to be a lot of effort, and for what? Your company’s enrolled you on a mandatory data literacy driving course. For years, data employees have been paying to use other people’s data cars to get places, but after a series of wasted journeys and large-scale data car crashes, there has been a decision to educate everyone on how to drive. Someone realised that if people didn’t know how to drive a data car, they wouldn’t be able to effectively direct a data taxi driver to get the best out of their journey. At this point, you’re pretty sure you’re never going to need to use these new skills that you’re learning. Taxis have always ...
Read more

“Hope for the future" - Section 14 of 14: THE DATA ARCHITECTURE CONSTRUCTION PROJECT (free excerpts)

Image
This is the fourteenth part of the chapter titled “The Data Architecture Construction Project”, from the book “ The Data Garden And Other Data Allegories ”. ______________________________ Hope for the future After the meeting has finished, your Head Builder finds you back in the meeting room, leaning back in your chair and gazing out of one of the windows at the Data Insights Town skyline. The sun is setting behind one of the tall buildings in the distance and the sky is awash with hues of red, yellow and orange. His presence stirs you from your reverie and you look at him with a smile. “How do you think my first day went?” “Could’ve been worse,” comes the response, with a chuckle.  You laugh in return. “That sounded enthusiastic!” Your new deputy comes and sits next to you. He speaks slowly and with meaning. “I’ll be honest, Boss. Things haven’t been great around here for a long time. I think you can see that from what you’ve heard today. But you can also see how much everyone her...
Read more