does my organisation need a data strategy?

Does my organisation need a data strategy?



If you were planning a road trip, surely your first step would be to look at a roadmap and determine two things:

  1.  Where you want to go?
  2.  How you’re going to get there?

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, milestones, or necessities for the trip—they just cross their fingers and hope to end up somewhere good.

Virtually every business handles and generates some form of data.  And 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, have five employees or 5,000.



Data ScientistsEvery business interacts with data in some way

While it's true that data strategies are crucial for tech-heavy companies with huge, sensitive databases and high analytics budgets, it's important to note that even smaller companies with fewer customers need to have a solid plan in place for data storage, governance, and analytics.

Larger organisations typically have more complex data requirements and require more sophisticated data strategies to ensure that their data is well-organised and easily accessible.  However, regardless of the size of your business, having a well-crafted data strategy can help you extract valuable insights from the data so you can make informed decisions and stay ahead of the competition.

Here are some examples of different use cases and areas of importance depending on company size and unique challenges:

  • Small company: Julia, who owns a three-employee bakery, creates a data strategy and an analytics roadmap because she wants structure around using her data to decrease wastage and increase sales
  • Medium company: Chris, the head of IT at a 50-person insurance company, creates a proper data strategy to fix the disparate policies and existing documents around data governance and storage 
  • Large company: Jane, the CIO of a 500-employee travel company, and her team workshop a data strategy and analytics roadmap to help them streamline their information storage and plan for analytics optimisation


As you can see, many use cases highlight the importance of analytics project planning and strategy regardless of the size and nature of your organisation - creating a data strategy, and actually using it, is a key component to ongoing success in an increasingly data-driven world.


Teams - Datamine Purple-19 Setting your business up for successful analytics

You need to understand your problems well before you figure out where and how to apply analytics.  Once you know what areas you can use analytics in, look into how to capture that value. 


Solving problems requires change.  To achieve change, you need to get your people on board and processes sorted. This is particularly true for larger organisations.  The benefits and requirements of analytics touch every part of your business, so ensure your data strategy aligns across your teams rather than isolating it to your analytics department.


Identify the components necessary to implement the analytics plan.  Get an end-to-end view that covers every part of the process. What will your business need to adapt at each stage to realise the benefits of analytics?  While the technical side is important, your focus should be on your people and your business – that way, you can unlock the full potential of being a data-driven organisation.  


If you don't spend time upfront outlining your data analytics plan, you'll end up facing a heap of challenges, such as the ones outlined below.


Teams - Datamine Purple-16what happens when you don't have a data strategy?

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?

  • Difficulty accessing data and uncertainty about what data is available
  • Data quality issues and poorly understood data standards
  • Unclear responsibilities and disparate systems across teams
  • Increasing dissatisfaction with IT
  • Lack of understanding in the business around the importance of data
  • Inability to get analytics initiatives across the line and delivering value


Platformwhat are the components of a data strategy?

A data strategy has three overarching sections that will enable analytics value capture and ensure ethical compliance:

1.  Optimising the key workstreams to build analytics capability: this section involves filling and prioritising the pipeline of work, ensuring you have solid problem statements you can reference through every stage of the process.

2.  Creating technical environments that enable progress: there are three main ‘environments’ to create if you want to truly push the need – exploratory, prototyping and production.

3.  Solidifying legal and ethical guidelines: it’s important to outline the rules and principles around data ownership and usage before getting started with analytics.



Further reading


Got more questions?  Take a look at these blogs. 




Roadhow do I create a data strategy?

If you’re keen to read more about Datamine’s take on the steps involved in each of the above areas, check out the free Datamine Guide to Data Strategies below


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