This HBR article answers this question. It looks at the key ingredients most likely to lead to success in your data strategy. We like this article because the advice is transferable to the private and the public sector. Read the excerpt below or Hillary Mason’s full article here.
Excerpt: ...an excellent data strategy is specific in the short term and flexible in the long term. We know quite a lot about what the machine learning capabilities of tomorrow look like, but less about what the capabilities of next year will look like. We can only guess what will be possible in five years. Similarly, the business landscape is transforming, leading to new competition and new opportunities. Organizations that engage in five-year planning cycles will miss the opportunities that emerge in the meantime. An excellent strategy is one that is adaptable and considered to be a living document.
The best strategies are strong in directional conviction, but flexible in the details. You want to know where you want to end up, but not necessarily pre-define each step you need to take to get there.
Finally, an excellent data strategy takes into account one key insight: data science projects are not independent from one another. With each completed project, successful or not, you create a foundation to build later projects more easily and at lower cost.
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