Key Components of Data Strategy

For many years, Governments have viewed data as a byproduct of activity with little value. This sentiment, however, is changing rapidly. Today, organizations are trying to get every little advantage they can get over another to achieve their goals, and in doing so, have taken advantage of what data has to offer.

Government organizations have realized that data, a supposed “byproduct”, can be a valuable asset. Chief Data Officers (CDO), formal data management strategies, and using data driven decision making are now essential to how an organization can adapt quickly and become more agile.

To be effective, a data strategy must have a plan for governance, innovation, documentation of processes, storage, accessibility, and clearly defined goals. It must consider changing the underlying culture of the organization to appreciate, use, cultivate, and enhance the quality of the data to have the largest impact.

Government Program Managers and CDO’s developing a data strategy should consider these six major areas:

1. Align the Data Strategy Goals to the Organization’s Mission and Strategy – A data strategy must start with the mission of the organization and its strategic priorities. This allows a data strategy to build up the core foundation of an excellent data management program that can make a near-term impact to accelerate mission results.

2. Identify the Organization’s Data Strengths and Weaknesses – What unexpected strengths can accelerate data governance, data quality, or the use of data by leaders to drive decision-making? Does data quality or a lack of data standards across the organization hamper information sharing or accurate reporting?

3. Innovating with Data – How does your organization want to use data to work differently, to drive the organization to focus on the mission from the top of the organization down? How can data allow you to do the work in different ways? Are data visualizations common place and do they provide accurate information to senior executives or external organizations making inquiries? Do you incentivize your organization to innovate with data? These are all questions about what you want to do with the data, and this is a critical part of a data strategy.

4. Establishing the Governance Strategy – Managing how data sharing is occurring, having terminology standardization, and having data accuracy are key parts of data governance that help manage data consistently across an organization. Decisions about the managing, processing, and sharing of data should be made by the policies of data governance, and not a single individual. Who, how, and how often should agencies or programs meet to make decisions on data? The frequency of this type of discussion should happen often in the early stages of data program development and should also become a regular part of the organization. The Data Strategy informs an organization’s subsequent Data Management and Governance Plan.

5. Documentation of Processes and Standards – Proper documentation of data standards, data sharing policies, and processes like standard operating procedures (SOPs) also follow a strategy – focusing on the highest areas first. Documentation is important so that processes are understandable, provide consistent results, and repeatable. For example, it is important to have policies and a process for access to data, protection of data, and privacy considerations

6. Storage and Accessibility – Data does not need to be stored in one place. It does, however, need to be in a place where people can find it and access it easily. Accessible data is key for making sure that organizations in the future do not have issues finding it or are creating their own copies, further adding to duplication and data quality problems.

Data is a powerful asset that should not go unnoticed and unused. Developing and implementing a data strategy can transform data into an enterprise asset for any organization. By having a data strategy, organizations can coordinate efforts and prevent wasted resources. A data strategy does not need to be perfect, but it needs to be able to guide the organization’s solutions when needed, especially as organizations continue to evolve rapid in this changing word.

At Arc Aspicio, we use Design+Data to contribute to a program’s growth and evolution in data. We start by understanding an organization’s data strengths and weaknesses so that we can recommend goals and build a road map to a successful data strategy.