What’s the difference between a data-driven company and one that relies on intuition and assumptions to make decisions?
Research shows that data mature businesses are 58% more likely to beat their revenue goals. They’re also more agile and productive, which helps them achieve better results than their less data-minded competitors.
Successful organisations use data strategies to guide their efforts. In this article, we explain what they are and why they're important in the digital age – with a few data strategy examples to help you create one that works for you.
What is a data strategy?
Gartner defines a data strategy as:
“A highly dynamic process employed to support the acquisition, organization, analysis, and delivery of data in support of business objectives.”
This is a good starting point. But it doesn’t tell the whole story.
In our experience, a data strategy is more like a roadmap that guides your approach to data. It identifies the people, processes, and technology you must invest in to turn raw information into strategic insights that support your wider business goals.
Why are data strategies important?
Data doesn’t provide business value in its raw form. It’s the way you use your data that makes it a strategic asset.
An effective data strategy coordinates your efforts by creating a standardised approach to data management, analytics, sharing, and governance across your business. It creates consistency and gives every department access to high-level business intelligence (BI).
This empowers you to:
- Make more informed decisions
- Better understand your customers
- Optimise internal processes
- Overcome business challenges
- Spot emerging trends
- Capitalise on new opportunities
- Drive business-wide innovation
Data strategy examples
No two data strategies are alike. A fashion retailer will have significantly different data requirements to a B2B company that specialises in project management software, for example. This influences the type of insights you collect and how you use them.
That said, almost all data strategies follow the same basic structure. This breaks your strategy down into 4 key areas:
- Storage & data management
- Analytics
- Governance
- Alignment
1. Storage & data management
The way you collect, manage, and share business insights is the foundation of all good data strategies.
Most companies collect data from a wide range of sources. But rather than consolidate their business insights in a single location, they store it in a complex network of on-premises and cloud-based systems that often don’t play well together. This creates departmental silos, which makes it difficult to extract and share business insights – especially in the hybrid workplace.
Teams are more dispersed than ever. But everyone needs a fast and efficient way of accessing the data, no matter where they’re located. Data strategies tell employees where you store your data, along with clear instructions that explain how to securely access and move it between systems.
2. Analytics
Most businesses understand the value of data analytics, but few are equipped to capitalise on the opportunity.
An effective data strategy identifies the combination of data visualisation and analytics tools, infrastructure, and skills you need to analyse and interpret data effectively. These are tailored to your needs, so you only invest in solutions that support your wider business objectives.
Of course, a tool is only as useful as the person using it. Cutting-edge tools mean nothing if your team lacks the skills to analyse and interpret your findings. Data strategies highlight the strengths and weaknesses of your team. This tells you when to invest in additional training, hire new staff, or work with third-party experts.
3. Governance
Effective data governance is essential for every business.
Data breaches can have serious legal, financial, and reputational ramifications for your business. So, your data strategy should establish a clear set of rules, policies, processes, and controls to ensure your data is both secure and fully compliant with data privacy regulations, like GDPR.
Remember, data governance is a team effort that encompasses everyone from the C-suite to end-users. Your strategy should specify who’s responsible for each data set so that the right people have access to the right data. This is as much about creating a consistent, company-wide approach to data management as it is security and compliance. Done well, data governance makes it easier to collect, store, access, process, and share data.
Tip: Review your policies regularly
As your business grows, you’ll find that you need to update your permissions, processes, and controls. For example, moving from an on-premises storage solution to a cloud-based alternative may require additional layers of encryption beyond your basic server protection.
4. Alignment
The purpose of any data strategy is to help the business achieve specific organisational goals. And to do that, you must align it to your wider business strategy.
This requires you to think about what you want to do with your data. Do you want to use data visualisation to support enterprise decision-making? Or are you more interested in identifying market trends and opportunities?
As with any strategy, it’s important to set short and long-term data goals and map them to the company-wide objectives they support. An example of a short-term goal might be using automation tools to cut reporting times by 60% from days to hours and improve operational efficiency. While a long-term goal might be to move all your data onto the cloud within the next three years to make business intelligence more accessible.
This helps you understand how improvements to your data management processes support the business and demonstrate value to stakeholders.
Unlock your potential
Data has revolutionised the workplace. No matter what industry you work in, your ability to harness data and extract meaningful business insights is key to retaining your competitive edge. But not all data is valuable and collecting it for its own sake won’t guide your decisions.
A data strategy is a long-term project that coordinates your efforts. And, when correctly aligned to your business goals, it allows you to unlock the full potential of your data.
