Technology is making data more plentiful than ever and data can (should!) help make organizations and their work more efficient and powerful. That may be happening where you are but in many (if not most) cases, including mobilisation organizations, data can be paralyzing.
Recently, researchers from Idealware, a U.S. based nonprofit focused on technology analysis, worked with NTEN, the American nonprofit technology association, to survey nearly 400 nonprofit practitioners about how they manage and use data. Their efforts were also informed by six extended discussions with groups of nonprofit staff, consultants, foundation program officers and evaluation professionals.
The State of Nonprofit Data was released today. Reading it will help you will better understand what organizations are measuring and how data is affecting decision making. It’s especially timely for the Mobilisation Lab as we will soon be sharing data from metrics gathered by Greenpeace offices around the world.
The report raises big questions about why many (or most) organizations are making little use of data. We are especially interested in what the survey calls “outreach data,” metrics on web, email, and social media. The survey didn’t clearly ask about offline outreach, activist, campaign, and volunteer data.
What nonprofits are tracking (or not)
Not surprisingly, 99% of respondents reported tracking some amount of data. Almost all respondents track financial data and find it useful for making budget and program decisions.
Fewer organizations track outreach data and very few use this data (which includes marketing, communications, and fundraising information) to make budget or program decisions. The survey defines outreach data as:
- Number of people on your mailing list.
- Number of new donors in past year.
- Number of visitors to website.
- Number of comments on Facebook.
- Number of people who open emails.
When asked if these types of data were useful for budget or program decisions, just seven to 39% said yes. Probing for why this data isn’t used, focus group participants pointed out that this data is easy to track but hard to analyze. We tend to think that the structure of most organizations keeps this data from bubbling up to higher level decision makers.
It’s worth noting that these data points measure growth, not engagement depth. Growth of visitors, email subscribers, and donors can and should affect investment decisions but growth doesn’t necessarily tie to longer term program quality. When it comes to websites or donors it might be more informative to ask if organizations are tracking conversion rates. That may be less frequent but more likely to inform decision making.
Data does not inform decision making (much)
Do organizations in general have a plan for using data? Overall, does data inform decision making? Most respondents answered no to these questions.
Why do organizations struggle to use data effectively? First, many organizations report problems collecting data, including:
- Don’t know how to track certain data.
- Don’t have the technology to track it.
- Don’t have the time/money to track it.
Tracking data is the first step to using data but most also have difficulty working data into decision making. Organizations with larger budgets seem more comfortable using data. Perhaps this is because they are more likely to have skilled data-focused staff.
Data expertise is a commonly reported barrier to effective data analysis. Weak understanding of data – or putting responsibility for it in the hands of skilled but junior staff – will further prevent data from being used by decision makers. In focus groups, consultants and foundations reported that many organizations simply don’t have clearly defined goals which prevents them from knowing what to track.
Improving data use
The report identifies seven ways organizations may better use data, including:
- Start somewhere. Pick a metric – preferably tied to a programmatic goal – and work with it. Better to understand how to measure and use data effectively than get stuck trying to figure out what to do.
- Connect your goals to your mission and metrics. Don’t measure everything. Focus on metrics that clearly tie to your work. If it doesn’t connect, don’t measure it.
- Don’t start by obsessing about outcomes. It is natural to want to measure outcomes – the product of your work. But it isn’t always possible and it doesn’t always help you understand how you got to the outcome.
- Learn from others. Read the blogs, do some research, and give your staff time and resources to connect to others in the field. Ask peers what they are measuring and why.
- Change your culture to value data. Most organizations fail to move data into strategic decision making. Culture is one reason. Experts (rightly) want to rely on experience and training. The report points out that buy-in from the top down is critical. Our experience supports this.
- Train staff. Help staff be comfortable and familiar with data and they’ll be more likely to collect and use it.
- Make an investment. In organizations, investment means time, not necessarily money. Testing hypotheses takes time. Help make time for your staff.