A Process for Making Data Understandable, Useful, and Actionable

By: Maria D. Guzmán-Rocha, YMCA of the USA


Ever wonder how to clearly connect the dots between the data we collect and the changes we make based on that data? As a result of stakeholder feedback, the YMCA of the USA (the national resource office for local YMCAs across the country) developed a set of resources that pull together best practices in implementation science, continuous improvement, and youth development research. These resources make up our evolving Making Meaning of Data (MMOD) process. The MMOD process ‘breaks down’ or ‘walks through’ systematically using data for continuous improvement. It is meant to make data understandable, useful, and actionable.

The process of making meaning of data provides us with an opportunity to examine data from our programs and explore what we can change to provide adults with resources and tools to support the development of the young people with which they work. Our goal in using data is to support continuous improvement in the services we offer and the ways we deliver them in our youth development programs and practices.

Below, we share some recommendations and lessons learned for those who maybe be interested in embarking on a journey of making meaning of your data.

When you collect data, you should expect to be able to use that data to develop a plan to improve your program. For every piece of data you have, your program team should be able to ask yourselves three key questions:

What? What does the data tell us?
So what? What did we learn and how can we use it for improvement?
Now what? How do we act on our data and what do we do next?

These three questions are the key to making meaning of data.

Before you can ask yourselves those questions about your data, however, it is important that your team is prepared to utilize the making meaning of data process. This includes learning what the making meaning of data process entails, preparing to make meaning of data, engaging the team in making meaning of data, and setting out to improve using an actionable plan based on what you have learned.

The MMOD process is continuous. It is a best practice that once your team goes through one cycle of the MMOD process, it engages in the cycle for every set of data that is available, preparing, engaging, and improving. Once the practice becomes routine, your team can make meaning of multiple sets of data at once, asking important questions that will allow you to see similarities and differences between them and prioritize areas of improvement based on these comparisons.

For example, in one national effort to change five adult practices that support youth character development, the MMOD process is being used to help local YMCA’s discuss data on everything from organizational capacity, to adult self-reflection on their SEL practices, to youth outcomes, and make meaning of it for what they do moving forward. For some YMCA’s, the data include youth outcomes but for most, they are primarily looking at how their adult practices impact the spaces where youth engage with adults and with each other. The goal is for them to set actionable improvement plans based on these data sets, engaging in the MMOD process as their data becomes available.

Below are three questions we have addressed frequently as we have tested and evolved our process with our stakeholders:

How long will this process take?

  • It might take more than one session to go through the MMOD process. You may need to meet for a longer period or include multiple meetings and planning sessions.
  • If your team is not ready to move on to the next step, it is okay to take a step back and check in on previous steps to see if they still make sense.
  • It may take some time for your team to get used to the MMOD process. Make sure you give yourselves enough time to integrate it into your practices, even if it means incorporating it in small, regular ways. Find a frequency and cycle that makes sense for your program and your team.

Does everyone in our team need to be involved from the start?

It is best practice that teams who make meaning of data have members who are comfortable using improvement cycles, are subject matter experts, know and can handle whatever change will be required to make based on the data, and can promote and participate in change at the organizational level. That means that teams should include program leaders, program managers, and organizational-level members. Ideally, key team members should be involved in the MMOD process from the beginning, although at times it may take a while to recognize who the important stakeholders are as the goals become clearer.

How much data do we need to review?

The amount and number of data sets you review is up to your team to decide, based on your discussions about your goals in implementing this process. Whether you decide to make meaning of one data set or three, the key is that you incorporate this practice into your continuous improvement cycles. You can begin with one data set and over the course of a few continuous improvement cycles, add more data sets.

Programs collect extensive data–administrative, performance, and outcome data–which provide insight into processes, strategies, and participant experiences. Data can tell us who attends our programs, what they are learning, and how they are changing. But alone, data are only numbers and words. For the numbers and words to support telling the story of our programs and improving them, we need to begin to understand what the data are telling us, what it means for us, and how to use data to help us determine what we should celebrate and where we can grow. Sometimes we jump too quickly to changes we want to make before we give data the time and attention it deserves. Slowing down to consider what we know, whether improvements are needed, and how improvements might be best informed by the data we have are important to consider first. It is especially important that the responsibility lies with a team and not with one individual. The more we can clarify, as a team, what we are trying to understand, the better off we will be in making our data understandable, usable, and actionable.

Our Making Meaning of Data process and resources are being developed in collaboration with various stakeholders, including some of our local YMCAs, other national youth-serving organizations, youth development researchers and practitioners, and several of our YMCA of the USA teams. We plan to share these resources more broadly in 2020 in hopes that other youth serving organizations can benefit from making their data understandable, useful, and actionable. Let me know if you are interested in learning more!


Contact Information:

Maria D. Guzmán-Rocha, Ph.D.
YMCA of the USA


Disclaimer: The Assessment Work Group is committed to enabling a rich dialogue on key issues in the field and seeking out diverse perspectives. The views and opinions expressed in this blog are those of the authors and do not necessarily reflect the official policy or position of the Assessment Work Group, CASEL or any of the organizations involved with the work group.

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One Comment

  1. The YMCA evaluation emphasizes processes more than outcomes. I would like more info on gathering data for the expectations they desire, like: physical health, mental health, optimism, fellowship, and other hoped-for results and with each of these parsed as they affect different age groups or cultural differences. In other words, a process may have been well planned and implemented, but did it impact member characteristics. I think this is a problem with school evaluations in measuring social, emotional outcomes also.

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