6 Simple Steps for Creating a Robust Data Strategy

by   |   May 23, 2017 5:30 am   |   2 Comments

Bernard Marr

Bernard Marr

Whether you’re a Big Data giant like Facebook or Google, or a small, family-run business, all smartly-run businesses starts with strategy. And these days, every company, big or small, in any industry, needs to have a data strategy in place.

There are millions of ways data can help a business but, broadly speaking, they fall into two categories. The first category uses data to improve your existing business and helps you make better business decisions. The second uses data to transform your day-to-day business operations. However, you want to use data, you must always start with a data strategy. What data you gather and how you analyze it will depend entirely on what you’re looking to achieve, so the goal needs to be determined at the outset. Having a data strategy in place helps the whole process run more smoothly and prepares you and your people for the journey ahead.

Tips for Creating a Robust Data Strategy

Getting the key company players and decision makers involved early on helps you create a better strategy, and getting their buy-in at this crucial early stage means they’re more likely to put all that data to good use later.

Keep in mind that, like any business-improvement process, things may shift or evolve along the way. You may find that your data points to interesting new questions that you want to explore or leads to modifications to your existing data strategy. If that happens, simply revisit your data strategy, re-evaluating each of the points below in turn.

The Six Components of an Effective Data Strategy

A good Big Data strategy should answer the following key questions:

1) What do I need to know or what business problem do I need to solve?

Rather than starting with the data itself (i.e., what you already have, what you might be able to get access to or what you would love to have), it’s much better to start with company objectives. After all, why bother collecting data that won’t help you achieve your business goals?

Think about the strategic priorities you’ve laid out for the coming months or years. Define what it is you want to achieve and then think about the big, unanswered questions you need to answer to deliver that strategy. In short, work out what it is you need to achieve through Big Data. Are you looking to reach more customers, OR better understand your current ones, or determine where the best locations are to provide your service?

2) What data do I need to answer my questions?

In this age of Big Data it is even more important to think small. I recently worked with one of the world’s largest retailers and, after my session with the leadership group, their CEO went to the data team and told them to stop building the world’s biggest database and instead create the smallest database to help the company to answer their biggest and most important questions. This is a great way of looking at data.

Look at each question you’ve identified and then think about the ideal data you would want or need to answer that question. Once you have defined the ideal data, look inside the organization to see what data you already have. Then look outside and establish what data you could—and should—have access to.

3) How will I analyze that data?

Once you’re clear about your information needs and the data required, you need to define your analytics requirements (i.e., how will you turn that data into insights that help you answer your questions and achieve your business goals?).

Traditional data collection and analysis is one thing—like point-of-sale transactions, website clicks, etc.—but much of the promise of today’s data lies in unstructured data, like email conversations, social-media posts, video content, and so on. Combining this messy and complex data with other more traditional data, like transactions, is where a lot of the value is, but you must have a plan for the analysis.

4) How will I report and present insights?

Data is useless if the key insights from that data aren’t presented to the right people in the right way, to help with effective decision making. Making good use of data-visualization techniques and taking pains to highlight and display key information in a user-friendly way helps ensure that your data gets put to good use.

Keeping your target audience in mind is perhaps the most important thing to remember at this stage. So, in this step, you need to define how the insights will be communicated to the information consumer or decision maker. You need to think about which format is best and how to make the insights as visual as possible. You also need to consider whether interactivity is a requirement—e.g., do the key decision makers in your business need access to interactive self-service reports and dashboards?

5) What software and hardware do I need?

After defining what data is needed, how it will be turned into value and how it will be communicated to the end user, you need to define your software and hardware requirements. Is your current data-storage technology the right choice? Should it be supplemented with cloud solutions? What current analytic and reporting capabilities do you have and what do you need to get?

6) What’s the plan of action?

Having identified the various needs above, you’re now ready to define an action plan that turns your Big Data strategy into reality. Like any action plan, this should include key milestones, participants and responsibilities. After creating your Big Data strategy, one of your first steps is to make a robust business case for data to the people in your organization, effectively convincing them of the merits of using data. Importantly, you should also identify training and development needs within the company and identify where you might need external help.

Overall, these are some key steps towards a robust data strategy, something that is vital for every company and business unit that wants to thrive in the era of Big Data.


Bernard Marr is an internationally best-selling business author, keynote speaker and strategic advisor to companies and governments. He is one of the world’s most highly respected voices anywhere when it comes to data in business and has been recognized by LinkedIn as one of the world’s top 5 business influencers. In addition, he is a member of the Data Informed Board of AdvisersYou can join Bernard’s network simply by clicking here or follow him on Twitter @bernardmarr


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  1. Posted June 21, 2017 at 10:47 am | Permalink

    When I hear “data strategy” I do not think of business problems to solve. I think of how data can be used to multiply the effects of what the company is currently doing. This is why many data strategies fail because data is often used to solve a specific set of problems; problems that have been around since operational management hit the scene.

  2. Posted July 3, 2017 at 1:08 pm | Permalink

    @Chris Pehura,

    I don’t know Chris. I read Scott Berinato’s (Senior Editor at HBR) Good Charts, and he too said that before working at the data level, figure out what you are trying to solve or say — the big picture. So, I’m with Bernard.

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