Data is powering our economy. And businesses are using data to make better decisions, refine operations and create new revenue streams.
Or are they?
Companies are certainly amassing vast amounts of data every day. Plus, the number (and variety) of data professionals on their payrolls is growing each year. But, data technology isn’t for free — as skyrocketing revenues from the large tech companies can attest!
While many companies are investing fortunes into data, data professionals and data technology, Gartner and others are consistently reporting the devastating failure rates of data science projects.
Apparently, throwing money and talent at data — potentially a very valuable business asset — is not enough. The fatal 80% and upwards failure rate can eliminate even the smartest investments.
So, what is the problem?
Simply, a lack of data strategy.
WHAT IS A DATA STRATEGY?
Data strategy sounds like a boring corporate document. But in principle, it follows a very simple approach to maximising the benefits of data. We believe there are three parts to a data strategy:
1. What business problems do you want to solve?
2. What do you need to do that?
3. How are you going to get it done?
Sounds easy right?
Indeed, it is difficult to argue with such a generic problem solving approach. But connecting the dots across the data ecosystem holistically is challenging. Formulating the business case takes both data and investment prowess. And - undoubtedly - execution is harder than you might think.
For answers to these challenges, take a look at our paper Data Strategy - making data count
After all, as Yogi Berra so eloquently puts it:
“If you don’t know where you are going, you’ll end up some place else.”
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This article first appeared on LinkedIn https://www.linkedin.com/posts/chelsea-wilkinson-35527079_data-strategy-technology-activity-6899624677153538048-GJPc