Nonprofit Data Maturity Model — Stages 3 & 4

Social good organizations need data to report on outcomes, track client progress, secure funding and so much more—yet just 40% of nonprofit organizations say they use data to inform decision-making. Beyond that, nonprofits often struggle to figure out what to track, how to house their data efficiently and how to use it for more effective service delivery. Even though data is an enabler of high performance in our industry, not every organization has a data management strategy that lends itself to long-term success.

Why is measuring data maturity important?

Measuring data maturity is the first step in elevating your organization to one that is truly data-driven. After all, the first step to most things in life is simply getting our bearings and figuring out where we are and where we want to go. Only when that is determined can we navigate a larger plan of action.

No two organizations’ data-management processes look the same. Depending on your geographical service areas, your staff size, your budget, your service delivery (and so much more), the data you collect, manage, analyze, and store is going to vary greatly from others. That’s why it’s important to have a focused and specialized “data map” that details your journey to optimal data sophistication. To help organizations map their data journey, we created a set of standards and stages we call the Social Solutions Data Maturity Model. You may have read about this already in our first blog post, Nonprofit Data Maturity Model — Stages 1 & 2. If not, give it a read! The Maturity Model is intended to provide insight into where your organization can improve and show a clear path of how to grow and do more with your data.

Tools to help get you started

Our team at Social Solutions developed a Data Maturity Model Quiz to help you easily determine which stage your organization currently resides as well as a Mapping your Data Journey: The Social Solutions Maturity Model eBook that provides an in-depth look at each step of the data journey with helpful tips and best practices.

There are four stages of the Data Maturity Model:

1. Committed
2. Counting Outputs
3. Measuring Outcomes
4. Managing Outcomes

This post covers Stage 3 and Stage 4 of the Maturity Model. These blogs, along with the eBook and quiz, will help organizations determine where they are in their own data journey and help them understand what they can do to become more data-driven today.

Stage 3: Measuring Outcomes

“We’re seeing outputs at a high level and can even report improvements in how we deliver some of our services because of our ability to track key metrics. Pulling reports and discovering trends is a lot easier now that all of our data is organized and uniform. This is helping us communicate our value to our funders and has even helped boost internal morale because we can see the progress and impact we’ve made for the first time.”

In Stages 1 & 2, organizations are either having conversations about data strategies or are beginning to formalize their existing data-collection process. Stage 3 goes beyond laying the groundwork, and it’s where organizations start to form a systematic, organized, and possibly cloud-based process that is adopted throughout the organization. Data collection efforts are in good shape, and some benefits are beginning to take shape.

In this stage, you will be able to measure, track, and make short-term decisions based on what you see as well as report on trends and identify program outcomes. One of the biggest turning points organizations experience in Stage 3 is their ability to communicate their value to funders because reporting has now become more reliable and less resource-intensive.

However, there is still room for improvement in Stage 3. Since you’re just now seeing the trends of your outputs, you still can’t see an end-to-end view of your programs and service delivery. On top of that, issues may still exist due to data quality and data integrity, both of which are important for getting the most accurate data in real-time. Until an organization can close these gaps, long-term data-driven decision making is stunted. Without a truly sophisticated data system, organizations won’t have complete visibility into their data, which can limit their ability to manage outcomes and improve over the long term.

Stage 4: Managing Outcomes

“Our nonprofit has the tools in place to truly begin measuring outcomes rather than counting outputs, which tells us what’s working and what’s not. We can see the effect our work is having across all of our programs and across different time periods, in different regions, and even different demographics. The data is not only helping inform our service delivery but is guiding long-term decisions. We have confidence that the data we collect is informed and accurate—no more inharmonious gaps in reporting or metrics—which benefits our internal team and our partners. We get excited thinking about the future. While we know that there is a lot left to do, we feel empowered with our robust reporting structure.”

At this stage, your organization is using data optimally. You’ve mastered counting outputs and measuring outcomes, and it’s time to take the next step forward. Here, your leadership is using collected data to make informed, real-time decisions that benefit your programs and clients. Also, at this stage, your organization should be data agile and can easily use data, and your cloud-based software, to course-correct quickly.

Additionally, your organization has reached a level of high performance that allows you to continuously ensure that your organization is using your resources in the most optimal way to drive towards your desired outcomes. All of this is possible because of all the hard work you and your organization’s leadership committed to moving your data usage forward.

However, this stage has its own sets of pain points that need to be addressed. You are still likely to see data errors from time to time, even with your cloud-based software. It’s important to practice constant vigilance to avoid those mistakes and maintain data integrity. Along with that, it’s important to continuously make sure that your system has functionality in place that will help you continue to perform at a high level.

And lastly, remember, it’s not uncommon for you to still have inherited inefficiencies in place at your organization. But those inefficiencies can keep you from your goals and take resources away from areas where they are needed more. It’s wise to seek help from data professionals to overcome these hurdles so you can start reaping the benefits of robust data in your organization. Take our Data Maturity Model Quiz and download our Mapping your Data Journey: The Social Solutions Maturity Model eBook to get started on this exciting and rewarding data journey!