According to a 2019 report from the U.S. Small Business Administration, almost all non-profit organizations in the United States have less than 500 employees. The median number of employees for non-profits is about 4. So naturally, employment of this kind tends to attract less coin-driven and mission-driven people, meaning staff members are often more willing to share duties if it helps the organization enact its vision.

Unfortunately, client bases for non-profits frequently exceed the number of available workers. Depending on their services, non-profits handle client numbers in the hundreds or even thousands yearly. That’s a lot for a small team to operate, and it’s easy to see how tracking data could get lost in the day-to-day shuffle, especially if data collection is decentralized or unstandardized. This is a problem if your organization is trying to coordinate care between staff members, furnish accurate reports for funders, and effectively track client progress.

Business concept. Analytics development

Client Data, Client Progress

There are numerous ways to measure a client’s progress. Many organizations have case management programs with unique benchmarks indicating how a client’s doing. For instance, an organization with a GED program may track how well students do on quarterly practice tests. There are other ways of tracking progress as well. For example, some organizations may use self-sufficiency inventories, regular employment performance reviews, or even simple attendance records. Keeping track of these data points over time is necessary to see how clients are taking to a particular program.

Of course, one way to track data is suitable old-fashioned paper files. But if you’re a skeleton crew, you’re likely already stretched for labor, and keeping good paper records is laborious and time-consuming. Without specialized clerks who can devote all of their labor time to keeping records shorn up, some data will inevitably fall through the cracks.

AI allows organizations to centralize all these processes and measure a client’s progress from when they enter a program to when they leave it. Different institutions can customize their intake forms to ensure that every client submits the necessary information to track progress and create reports to grant funders and donors.

What’s more, organizations can use similar customization features to create accessible and quantitatively reliable progress trackers. For example, a staff member need only enter client-submitted responses and data into the AI’s fields, and the program does the rest. This means that processes that used to take a whole team of highly-trained specialists can now be automated. Furthermore, a centralized data platform can pool all available data and sort it into HIPAA-compliant reports for funders with a push of a button. So again, what used to take weeks to create can now be produced almost instantly.

If you’re interested in learning more about how AI can benefit your organization, give C3S a call today.