Using Data and Analytics to Ask the Right Questions, and Get the Answers: A Webinar with Year Up

What does it mean to be a data informed organization? Across the nonprofit sector there is a movement to use data to demonstrate success and communicate program outcomes to stakeholders. But to be data informed means going beyond storytelling, and using data to make important decisions about how to effectively run your organization.

In our recent webinar, “Year Up Levels Up Its Impact with Wave Analytics,” we took a deep dive into how Year Up uses Wave Analytics to give everyone in their organizations access to real-time data that provides insight into key aspects of their program.

Year Up is a national nonprofit organization working to close the “opportunity divide” — the divide between the 6 million young adults who are disconnected from employment and education due to systemic socio-economic inequities and the 12 million jobs that American employers are struggling to fill with quality talent. Since 2000, Year Up has served over 16,000 young adults through their year-long training and job placement program.

The webinar — led by Year Up staff, Daniel Freed, Director of Information Technology, and Zach Stor, Associate Director of Business Intelligence — featured a demo on how they use Wave Analytics to gain insight from their data. Throughout the webinar, they discussed the process of getting up-and-running with Wave Analytics and the questions they asked internally to make sure they were using their data to its fullest potential.

Wave Analytics is the Salesforce tool for organizational intelligence. It can pull data from multiple sources, including non-Salesforce databases or even spreadsheets, into easy-to-digest reports and dashboards.

Let’s take a look at our top takeaways from Year Up’s presentation and what questions you can ask to help your organization become more data-informed:

What data should we collect?

This is the foundational question for any organization that wants to use more data. Year Up created a set of metrics called RADIO, which stands for retention, admissions, development, internships, and outcomes. In each of those categories they figured out what was important to measure and which data points would support those measurements. From there, they were able to decide what data was important to collect and bring into Wave Analytics.

Is there organization wide agreement that the data is accurate?

As Year Up grew, so did the amount of data they were collecting and analyzing. Before implementing Wave Analytics, staff from around the country were using their own systems and spreadsheets to collect data. This created discrepancies and caused disagreements about the quality and usability of the data. By migrating to one system of record in Wave Analytics, Year Up was able to move past having discussions about data and start making decisions based on data.

Who on staff is best equipped to understand the data?

Year Up believes in the “democratization of data.” In their organization, the program staff know more about how to measure success than the technical staff. With that in mind they built reports and dashboards, as well as internal processes to bring program staff into the analysis process. Even for staff who aren’t the most tech or Salesforce-savvy, anyone has the ability to filter, sort and manipulate custom reports to explore the data and see if it matches what they are seeing in the field. This creates a culture of learning and exploration around the data and allows all staff to make data informed decisions no matter their role.

Now that we have the data, is there a better metric to understand what it is telling us?

One of Year Up’s goals is to make sure its participants go on to find high quality jobs. Originally, they measured this through looking at the average wage of program participants by site. If the average was over their benchmark of $16/hour, it indicated the site was doing well. However, through utilizing the data visualizations available through Wave Analytics, they were able to realize that using wage as a metric was actually more complex. They learned that some sites had a range of very high wage earners to very low wage earners, where as other sites had a more even distribution of mid-level wages. In this example, the sites had an average wage above $16/hour, but the outcomes for participants across the sites were quite different.

This insight enabled them to realize that a simple average wage is not the right metric to understand program success. The data guided them to a more nuanced view of wages that will lead to deeper understanding about their programs in the long-run. Using data is an iterative process and this is just one example of how metrics can evolve over time.

This case also illustrates what might be the most important question good data allows organizations to ask…

Why?

Through being able to visualize program data in real-time across all of their program sites Year Up was able to observe differences in wages. However, they didn’t jump to the conclusion that one site was performing much better than another. Rather, they started to ask, “why is this happening?” Is the economy in different locations driving wages? Is one program site implementing the program in a different way?

Being able to ask and then understand why outcomes are achieved is at the core of being a data informed organization.

We hope these questions will help you and your organization on the journey to use data more effectively. Learn more about how the Salesforce Nonprofit Success Pack and Wave Analytics can help through this comparison sheet.