Blog Insights
Unifying Your Data Strategy
There is no “I” in data. No one team or person can handle all the data in a given organization, so how do you get everyone to pull together and gain alignment? Unifying your data strategy is not an easy task.
More and more, we’re seeing mission-driven organizations begin investing in a cohesive, centralized data strategy that can pull in what previously seemed like totally disparate parts of your organization to drive greater data transparency and impact. To get you started, here are the key tenants of a unified data strategy and where to focus your efforts as you envision a more data-informed yearly or quarterly plan ahead.
Define your data vision
Mission-driven organizations—nonprofits and government agencies like yours—are under ever-increasing pressure to demonstrate their impact.
When your organization understands where you are, then your organization can be prepared for the ever-changing future and be able to adapt and evolve creating lasting impact.
What’s in your data vision?
From membership to social to programs to surveys to fundraising to research, it may seem like every department in your organization is drowning in data. The systems and tools that both produce and use data just keep on multiplying. That’s why most mission-driven organizations can benefit from creating a unified data strategy that will keep you focused on your goals. A data vision helps:
- Define your organizational commitment to why data;
- Map your data goals to your strategic mission;
- Chart a course of actions for closing data gaps; and
- Set expectations across departments and teams.
Some common challenges your data strategy can help address include:
- The audiences and communities you serve
- The effectiveness of your programs’ efforts
- How your policies and ideas are consumed and adopted
- The needs of your donors and funders
Democratize data with governance
Data governance provides a framework to streamline and scale your data strategy. Successful data governance makes managing your data repeatable and can provide an organization with the support they need to grow sustainably. Once you’ve established the vision driving your data strategy, the governance framework will allow you to address the nuts and bolts of your data.
Key components of data governance
The people, processes, and technology are at the center of your entire data strategy. You need to put the right people in place to support, sponsor, steward, operationalize, and ultimately deliver a positive return on your data. You need to consider and implement the right technology or platforms that enable working with your data to achieve your goals. And you need to align your organization around policies and processes to make sure data is handled in a standardized—and even more importantly—ethical manner. The following are supporting concepts that allow for organizations to ensure they are building a strong governance framework.
Ownership: Having the right people at the table and in place to enact governance in an organization is critical. It’s often tempting to pin all of your “data” work on a centralized data team, but that is only sustainable for so long. That kind of team will have a large role to play in your data strategy, but identifying ownership and buy-in from other representatives throughout your organization is how you make it stick. These owners make sure to uphold the integrity of the data, that it continues to make sense from both a content and metadata perspective, and act as administrators for their relevant sources.
Accessibility: You want to deliver data and insights to the different people across your organization who can use it to make decisions – making the data accessible in the places and formats that fit their needs. A CEO who loves spreadsheets might not get the most out of a slick new dashboard and your program team probably doesn’t have the time to read a 30-page monthly report.
Security: This is where your IT team can really be a huge help. For some organizations, this means locking down permissions on who can edit different databases or data sources, while for others that deal with personally identifiable information (PII), there are more precautions to take.
Quality: “Garbage in, garbage out” has become a cliche for a reason. Establishing standard processes for how to input and handle data should be a high-priority outcome of any data governance framework. Work cross-functionally with the different people who will use data at your organization to ensure analysis is done properly, preventing any misuse or misrepresentation of the facts down the road.
Knowledge: Ensure you have the right skills and capabilities lined up to achieve the goals of your data strategy. If those skills or even the bandwidth to get things done are not available, it’s time to think about a hiring strategy or bringing on some outside help—or potentially both!
Drive data literacy
Defining your data vision and developing a strong framework for data governance are foundational elements of a data strategy, but increasing data literacy and maturity across your organization will make it stick. Building an organizational culture where many people can learn how to speak the language of your data and interpret it properly empowers everyone to use it to drive impact. Incorporating data literacy and advancing data maturity takes time, but you can start to think and talk about a unified data strategy now to help you and your fellow data advocates move the needle toward becoming a fully data-informed organization.
Remember to think of data as a team sport – people with different positions and skills have to work together toward a shared goal. Solidifying your data strategy is like coming in with a strong training plan. You’ll need to put in the hard work upfront, but the payoff, in the long run, is worth it.