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What Is A Data Strategy?

A data strategy is a roadmap or a framework that defines how the data is collected, stored, utilized, managed, and shared in a company. Generally, a data strategy’s main purposes are:

• Explain how the company meets its goals by completing the desired data activities.  
• Describe what changes are necessary for the company to optimize the value of its data activities and outline plans for it. 
• Create a timeline for completing the planned activities, define milestones, and a strategy to move forward. 

How To Develop A Data Strategy in 7 Steps

To form a feasible data strategy, you need to follow 7 steps. Also, you’ll find instructions on how to do each step below.  

Step 1: Make a proposal and seek approval

The first and foremost stage in establishing a data strategy is to create a proposal for creating a data strategy and submit it for approval. Having your proposal approved by personnel at all levels is essential because you’ll need their participation for the strategy to be successful. 

To win approval from leadership, you’ll have to prove the strategy will do wonders for the business and how. It is vital that you include economic logic in your report. Also, illustrating how your rivals are utilizing data to better their business is a plus. You should also use compelling examples and data to support your claims. 

You’ll have to receive approval from leaders of departments, technology partners, and other employees who will utilize or contribute to managing data onboard as well. Remember that giving people a sense of ownership over the process will help improve your results significantly. 

Getting approval can be time-consuming to some extent. You may need to review and adjust your proposal several times to fix the possible flaws and make it more convincing. 

Step 2: Build a team to manage data and appoint data governance tasks

Once you’ve obtained adequate approval, you can jump to creating a data management team. The team should consist of senior managers and department heads from various parts and units, who are aware of the value of data and challenges relating to data.  

They also have a deep understanding of the company’s technological and organizational competence, as well as its opportunities and limitations. This team’s responsibility is allocating resources, implementing and upgrading policies, as well as handling data-related tasks and possible issues. 

When the team is fully formed, you’ll appoint data governance roles to the members. The crucial roles are mainly ensuring everything is standardized, deploying technologies, informing personnel about updates in policy, and more. Having these roles well assigned will boost the productivity of the team and create a deep sense of ownership among them. 

Step 3: Define the types of data you want to collect and their sources

What you need to do next is to identify the types of data you need and how to gather it. You’ll do this in accordance with your business goals. 

For example, if you’re a blogger and you want to optimize your posts to be in the topics your audience is fondest of, you’ll need to gather data of their interest and the types of posts they read. You can do this by observing which posts different groups of the audience click on or browsing your viewers’ social media profiles to see which pages they like, which community groups they’re in, and what topics they usually post about. 

Step 4: Identify objectives for data collecting and distributing

The keystone of an effective data strategy is having specific objectives. You ought to create both long-term and short-term objectives, as well as both overarching objectives and ones that apply to single tasks and departments. 

Specifically, describe how data can contribute to attaining goals of the business as a whole and how each department can benefit from it. That’s called long-term objectives of a data strategy. And for short-term objectives, define ones for establishing policies regarding the gathering, storage, usage, and sharing of data. 

Each department can set objectives for how they are going to utilize data as well. Thanks to this, they’ll be able to keep tabs on their progress and report to the data management team. This is with the aim of providing insights into how data is used across the company. 

Step 5: Develop a data strategy roadmap

When the objectives are already outlined, you’ll need to launch a plan for how to materialize them. This plan is called a data strategy roadmap. 

Your data strategy roadmap should consist of who owns the objective, what process and technology they will adopt, the expenses, the estimated time to fulfil and the expected results. During the process of the projects, you should regularly revise them to make evaluation to see if it’s working well. 

Step 6: Schedule for data storage and organization 

Data storage and organizing are chief components in a data strategy since they aid in defining how sharable and actionable your data is. 

Data storage is simple, whereas data organization might be distinct across companies. When developing plans for data storage, how much storage capacity should be considered. Besides, you should also consider how your storage method will affect data sharing and usage. How you organize data decides how accessible, understandable, and usable it is. Your storage approach impacts how easy it is for different parts of the company to share data. 

Step 7: Attain approval from the leadership and start adopting your data strategy

Once you have all your objectives mapped out, it’s time to submit in the form of a business plan to the company leadership for approval. 

To make sure you get approval, you should include the strategies you’ll employ to reach the company’s data goals in the business plan. Plus, there should be the resources you’ll need to carry out the strategy, as well as capital investments, new personnel, new processes, and new organizational frameworks. 

After earning the approval from the leadership, you can start the data strategy. As said before, you should revise the strategy frequently to make timely adjustments and improvements if needed.  Source: Data strategy by Synodus