A well-crafted data strategy helps you identify the people, processes, and technology you need to turn raw information into actionable business intelligence (BI). It encompasses the entire data management lifecycle (from collection and storage to visualisation and governance) to ensure consistency and accuracy across your organisation.
We’ve worked with companies at every stage of the data maturity curve, so we know how difficult developing a data strategy from scratch can be. That’s why we’ve created this 7-step guide to help you hit the ground running.
7 steps to developing a data strategy
1. Identify your key business challenges…
The purpose of developing a data strategy is to understand how you can use BI to solve problems, overcome challenges, and achieve your business objectives. Consider what you want to do with your data. Is your goal to:
- Make internal processes more efficient?
- Identify customer trends before your competitors?
- Capitalise on opportunities?
- Develop innovative new products?
By framing your objectives around the problems you want to solve, you can identify the data, tools, and skills you need to implement your strategy.
2. …and the data you need to solve them
Now you’ve defined your key business challenges, it’s time to think about the data you’ll need to overcome them.
Is it readily available? Can you extract the relevant insights from internal sources, or will you have to supplement your efforts with third-party data sets? A data discovery workshop will help you map out your data ecosystem and see what kind of insights you have at your disposal.
You must also consider how you store, organise, and manage your data. We recommend consolidating your business insights in a data warehouse or data lake. This makes it more accessible and avoids the problem of trying to move data between incompatible systems.
3. Decide how you’ll analyse and share your data
Like oil, data is of limited value in its raw state. When developing a data strategy, consider your analytical requirements. Do you have the internal expertise to draw strategic insights from the reams of structured and unstructured data you collect every day? More importantly, can you do it quickly and at scale?
Your answer to this question will tell you what you need in terms of in-house capabilities.
4. Evaluate your technological requirements
It takes the right combination of technology and knowledge to extract meaningful insights from unstructured data.
Evaluate your technology infrastructure. This will help you determine if you have the necessary hardware and software to collect, store, manage, and interpret your data or if you need to invest in additional solutions. For example, you might discover that your on-premises storage solution doesn’t have the capacity to grow alongside your business or that your current BI tool can’t process data at the scale you require.
5. Review your in-house capabilities
Next, you need to review your in-house capabilities. The biggest stumbling block for many businesses that want to do more with their data is that they simply don’t have the knowledge or skills to extract the insights they need.
You can overcome this skills gap in various ways:
- Train or upskill existing staff
- Hire data specialists
- Outsource to a third-party
6. Establish controls and policies
To make it as easy as possible for end-users to incorporate data analytics into their day-to-day work, you must pay close attention to governance.
This outlines the set of rules, policies, and controls that define and standardise data management across your business. Although it’s often closely associated with compliance, it has a far broader remit that encompasses:
- Quality
- Accuracy
- Transparency
- Security
- Privacy
- Accessibility
- Ownership
Ultimately, data governance is supposed to make it easier to use and enforce data standards. You can develop your policies in-house or, if you lack the necessary expertise, hire a data governance specialist.
7. Engage your end-users
Developing a data strategy is one thing. But unless the people responsible for deploying it buy into your vision, you won’t see the results you expect.
The easiest way to engage end-users with your strategy is to demonstrate the tangible benefits: how using data better will make their lives easier. For instance, greater visibility allows you to streamline your internal processes and reduce friction, provide more effective customer support, or improve collaboration between departments.
Solve your business challenges with data
Data has permeated every corner of the workplace. Businesses rely on data – and the insights they can extract from it – to optimise internal processes, create innovative new products and services, and capitalise on the latest customer trends.
A data strategy allows you to standardise data management across your business, so you can solve your biggest challenges and remain competitive.
