If you were planning a road trip, surely your first step would be to look at a map and determine two things:
The same logic applies when it comes to making data-driven business decisions, yet many companies end up doing the equivalent of driving wherever the road takes them without planning their turns, their milestones or their necessities for the trip – they just cross their fingers and hope to end up somewhere good.
If your business is never going to create or touch any data, then you won’t need a data strategy (obviously). But if you plan on using data, producing data or otherwise keeping pace with technology, you need to have an analytics strategy and roadmap in place to store, protect and capitalise on the data you have access to. This is the case regardless of whether you’re B2B or B2C, or whether you’ve got 5 employees or 5,000.
There are a number of misconceptions around data strategies, one of which is that they’re only necessary for tech-heavy companies with huge, sensitive databases and high analytics budgets. In reality, it’s important for even small companies with few customers to ensure they’ve got their data storage, governance and analytics plan sorted - doing so early on will prevent a lot of headaches down the road.
Here are some examples of different use cases and areas of importance depending on company size and unique challenges:
As you can see, there are use cases highlighting the importance of a data strategy regardless of the size and nature of your organisation - creating one, and actually using it, is a key component to ongoing success in an increasingly data-driven world.
To succeed at analytics, it’s important to have defined both your organisation’s challenges and aspirations. You need to know where your business is going and what your data and analytics capability would need to look like if you get to that place. You need to define the key milestones and workstreams that need to be put in place in order to enable you to create value from your data.
If you don’t spend time up-front outlining these important things, you’ll end up facing a heap of challenges – such as the ones outlined below.
There are a number of problems that often present themselves in the absence of a data strategy. Do any of these sound familiar to your business?
A data strategy has three overarching sections that will enable analytics value capture and ensure ethical compliance:
If you’re keen to read more about Datamine’s take on the steps involved in each of the above areas, check out the Datamine Guide to Data Strategies. Matt Wilkins has outlined the different components of a data strategy (or analytics blueprint, as he calls it) designed to help businesses that are struggling to see value from their data. Got any other questions? Get in touch with our team.
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