If a social impact leader rolls out a major initiative without on-point, accurate information, that course of action may work out (intuition and experience do matter), but to some extent, the result is still based on guesswork, kind of like throwing a dart in a darkening room.

Reliable data provides the bedrock foundation on which to build a system of informed and effective decision-making. It offers a backdrop to understanding that didn’t exist half a century ago, in an era when most initiatives depended solely on prior experience, trial and error — and luck. It stands to reason that data can provide insights into creating solutions, and even develop a nuanced understanding of the problems.  

Given that, it’s worrisome how many social impact organizations and the people who run them aren’t currently engaged in data collection and analysis to understand and meet the complex, ever-changing challenges ahead. And sometimes when they do have the data, they don’t trust it. Part of the problem is that, for many leaders, data is both daunting and poorly communicated.

We understand the challenges faced by social sector organizations, which often have small staffs and tight budgets but ambitious goals. They may not have data scientists or even data analysts on board who can identify and access data and begin their research efforts. And even if they manage to gather significant data, many leaders don’t know how to incorporate it into their operation’s overtaxed workflow. They also may not know where to begin to ensure that they and their organizations are up to speed in gathering data that matters and interpreting it in ways that benefit their missions.

Yes, data can be daunting, but that doesn’t mean it can’t be used effectively by organizations if they are willing to break the process down into its component parts. As chief marketing officer at data.org, and in previous roles elsewhere, I’ve had to do just that.

The first step is for leaders to decide what data is most relevant for them by tying its collection closely to their missions so that when it’s harvested it provides touchstone metrics reflective of organizational success. This is particularly important for outlets that have limited resources. Data collection often produces a great deal of interesting but not actionable data. Collecting data aligned with organizational priorities requires discipline. The interesting can wait. The immediate focus needs to be on the actionable.

Next, the analyzed data needs to be communicated clearly, presented insight-first, with key findings directly related to the organization’s mission front and center. It can be tempting to dump reams of data into the discussion, replete with multicolor charts and graphs that are gorgeous and look impressive but get in the way of focusing what’s most important. If leaders and board members want to read beyond the topline findings, they’ll dive deeper on their own. If you don’t put your most important findings front and center, you run the risk that some leaders won’t see them and be moved by them.

Lastly, creating a culture of data-informed decisions requires focus on building organization-wide muscle around interpreting and acting on incoming data. While high-level data analysis can remain the purview of one or a few individuals, interpreting much of it needs to be a broader, more open process so that staff members who know the issues at the ground level can ponder it and respond, a process that has the added benefit of making data analysis something less mysterious and more a part of how an organization conducts its daily business effectively. That way, the institution can strengthen its ability to draw meaningful inferences from data and reduce spurious correlations. In so doing, social sector leaders can help ensure that their operations are making meaningful data-informed decisions, with buy-in from staff members.

When we emphasize the importance of having data-informed organizations, that doesn’t mean they’re not human-centered ones. At data.org we’re working alongside the community to build the field of data science for social impact, and to advocate for a reimagination of this work with a more interdisciplinary and inclusive approach. Rather than be daunted by data, social impact organizations have the opportunity to chart their course forward with the benefit of data as a compass, clearly communicated to drive mission-focused action.