What makes a good data strategy?

Steven Spielberg

Data has become one of the most valuable assets any business has — not just for digital giants like Google, Alibaba, or Facebook, but for small and midsize firms, too. Data allows companies to make better decisions, understand market trends and customers more accurately, deliver smarter products and services, improve their business operations, and generate new income streams. 

But what does this mean for those people charged with evaluating the return on investment of a data strategy and business use cases? How do you know what constitutes a valuable data strategy when you’re not a big data expert?

Why every company needs a data strategy

If every business is now a data business, it stands to reason that every business needs a data strategy. Whether you’re a small, family-run business or a large multinational, if you don’t have a data strategy, you risk missing out on the huge potential business value data offers.

The data strategy is an opportunity to set out how you want to use data, clarify your top data priorities, and make a plan for delivering your goals. It’s the surest way to drill down to your core business data needs and create an achievable plan for the future.

With technology advancing so fast these days, many businesses — especially at the smaller end of the scale — feel like they’re struggling to keep up. This may lead to inaction or a strong urge to ignore the big data revolution. Or it may cause the company to dive eagerly into new data opportunities without giving them proper consideration (resulting in a lot of data that isn’t very useful for the business). Neither is a great way to get the most out of data.

That, in a nutshell, is why every company needs a data strategy.

What should a data strategy cover?

Here is a quick summary of the key elements every data strategy should cover.

Start with your key strategic data use cases/data priorities

Essentially, this means working out why and how you want to use data. Note the word strategic, though, since this is a key part of working out how best to use data. Data use cases or data priorities must always be linked to your overarching business strategy — in other words, how will you use data to achieve the company’s key strategic objectives and solve its most pressing problems? A handy template for identifying data use cases is available at www.bernardmarr.com. (Editor’s note: This is from the author’s website.)

There are many ways companies can use data, but they broadly fall into the categories mentioned above. Most companies start by using data to improve decision-making, which may lead to data priorities such as:

  • Understanding and improving employee engagement;
  • Delivering a more personalised customer experience; and
  • Optimising prices.

Whatever use cases the business has identified, the role of the finance professional should be to evaluate the business impact and ROI of potential data projects in relation to the company’s strategic goals.

It’s also important that the data strategy focuses on an achievable number of use cases. When working with business leaders to develop their data strategy, it’s helpful to identify between one and five use cases — plus one or two quick wins (small data projects that can be implemented relatively quickly to demonstrate successes). Any more than that and the data strategy risks becoming cluttered and unrealistic.

Then set out the requirements and challenges for each use case

Having worked out how to use data, you’re then in a position to move onto the data strategy itself, and this should consider the requirements set out below. (A data strategy template that covers all these elements is available at www.bernardmarr.com.) You’ll note that the template identifies cross-cutting issues/challenges that are common to each use case; we do this because, even though each use case/data priority is different, they’ll probably share some of the same issues or challenges.

So, working through the template in order, the key elements of a good data strategy are:

  • Data requirements: What data does the business need, and how will it source that data?
  • Data governance: How will the business tackle issues around data quality, ethics, privacy, ownership, access, and security?
  • Technology: What software and hardware requirements are involved? This will span technology for collecting data, storing data, processing (analysing) data, and communicating insights from data. Does the organisation already have the technology in place to support the data strategy? If not, the business needs to identify what is needed in order to meet such requirements.
  • Skills and capacity: Lack of data knowledge and skills is a big issue for many companies, so how will your business close the data skills gap? This may include training staff, hiring new talent, partnering with external providers, and so on.
  • Implementation and change management: What challenges will need to be overcome in order to implement the data strategy successfully?

A good data strategy could cover all these elements and identify common themes and issues across your data priorities.

Key data strategy pitfalls to be aware of

When evaluating a data strategy, it helps to be aware of the most common mistakes companies make. These include:

  • Starting with an outdated business strategy: The data strategy must support a business strategy that’s up to date and relevant to today’s digital world.
  • Not linking data uses/priorities to strategic business goals and challenges: Too many companies develop their data strategy around use cases that are interesting or easy to implement, rather than use cases that get them to their goal.
  • Only considering internal, traditional data: Today, data comes in many forms and from many sources. A good data strategy should consider all avenues for accessing data, including options like photo data and video data, and external sources such as social media platforms and big data brokers.
  • Minimising or overlooking the ethical, privacy, and legal issues: Consumer trust is paramount, so it’s vital governance is given proper consideration.

A good data strategy is essential for today’s businesses. These tips will help you evaluate your data strategy with confidence and understand how to use data to best achieve the company’s strategic objectives.

Bernard Marr is a thought leader, speaker, author, and business, tech, and data adviser. The second edition of his book Data Strategy: How to Profit From a World of Big Data, Analytics and Artificial Intelligence was released in October. To comment on this article or to suggest an idea for another article, contact Chris Baysden, an FM magazine associate director, at [email protected].


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