Data Strategy | Why Do You Need a Data Strategy?

Many goals are set that require good data solutions and a well-functioning data culture. The best and most effective way to achieve these is to have a clear and solid data strategy.

Most organizations set one or more goals related to data and analytics. Sometimes goals are set where good data solutions become decisive for achievement, and sometimes the goals are specifically about creating value through data utilization. Perhaps the goals even contain a buzzword or two? (We’re just guessing).

Yet it is not always the case that a data strategy follows behind the data objectives. So how exactly did we plan to get there?

One shared data strategy or many random data strategies?

In most cases, the absence of an established data strategy does not mean that you lack a data strategy, but rather that you have many small data strategies scattered throughout the organization. Today, most teams have heard that data is “the new oil,” and that everything is about being “data-driven.” Without a clear path to the goal, different teams will try to find their own solution and pull in different directions.

The result is that data ends up in silos (the very silos we were supposed to break down), solutions have a short lifespan, we hire the wrong people because we cannot see what competence is actually needed, and we forget about data flows in technology development because the priority lies solely on production. The path to the goal keeps getting longer.

The data strategy connects goals and actions

A data strategy is important because it connects the organization’s objectives with the actions needed to achieve them. As the person responsible for data in the organization, it is your job to communicate what you need to achieve the organization’s data goals. Hard work is futile if everyone is pulling in different directions, and buzzwords leave a bad taste if we have not defined what they mean for our organization.

The data strategy defines the path from where you are today to where you want to be in the future. Establishing where you currently stand is the first step in any journey. The same goals have different implications for different organizations, simply because they have different people, cultures, technologies and budgets. Some organizations have highly competent data professionals but lack the right processes. Others have a great, modern architecture but low data maturity across the organization. This leads to different approaches, even when the goals are the same.

Reaching the goals requires clear strategic priorities

A data strategy is largely about setting priorities. Some organizations use the word “priority” loosely, about everything they think is important. But prioritizing is not about putting stickers on everything you want, and if you focus on everything you are really not focusing at all. Prioritizing means making strategic decisions about how to spend time and resources to reach our goals. It also involves making decisions about what you will not spend time on.

We are often reluctant to use negative words, and to say that we will not prioritize something, or that we cannot do something. We want to focus on the valuable things we will spend time on. Unfortunately, this tends to backfire. When old assumptions about priorities are not addressed, people will think (or at least hope) that they still apply. Making it completely clear what we will not spend time on is an excellent way to make it clear what we actually will spend time on, and it helps us avoid discussions and re-negotiations at a later point.

The data strategy is also a communication tool – and must be made known

Equally important as having a data strategy is the importance of clearly communicating it. The data strategy must be known by employees, including those who will not be involved in the implementation. This requires us to show ownership of it and talk about it, much more and to a wider audience than we might think is necessary.

The goal of the communication is not necessarily to convince or to gather support, but to avoid misunderstandings and the development of many small strategies. If you already have a data strategy, you should make sure it is strong and stands firm. An unsteady data strategy has the same consequences as the lack of a data strategy.

In summary: Your data strategy should give you the direction to reach your goals

Your data strategy should give you the direction to reach your goals. It should tell you how technologies, processes and people fit together in the big picture. Strategies are just as much about what we will not do as they are about what we will do, and the data strategy establishes what is important for the organization when it comes to data.

Read more about how Glitni can help you with your data strategy.

Want to talk to us about your data strategy or target vision? Get in touch with us, and we will be happy to tell you more about how we work with strategy and target vision at Glitni.