Data Analytics to Advance HR Practices for the Social Sector

Data analytics has long been used by the private sector to provide a thorough examination of organizational performance in areas such as marketing, sales, and operations. However, the social sector has lagged behind in using data-driven approaches to support organizational goals, and this is also true when it comes to human resources. It is holding the sector back.

For more than a decade, First Book, a nonprofit social enterprise, has used data analytics to inform everything we do.  Research directs our work with educators and advances our mission: to further educational equity for children living in poverty.  Data analytics is also an integral tool for the administration of the organization.  Critical metrics inform the design of the organization and enable us to evaluate our performance. Over the years we have learned to collect key data as well as conduct deeper analyses in order to increase the overall impact of the organization as well as specific organizational functions, including HR. Here are two examples:

1)      Employee Retention. Instead of traditional retention rates, we examine employee turnover in a more significant way. At an initial glance, a retention rate of 82% over a five-year period may seem exemplary. However, we recognized that a better measurement of that data needed to take into account both employee tenure at the organization as well as their reasons for leaving. To do so, we created a scale that weighs several factors, such as long-tenured employees leaving for uncontrollable reasons versus short-tenured employees leaving for controllable reasons. For example, if a four-year employee resigns to go to Graduate school that is considered acceptable turnover, while an 8-month employee who resigns to take another job is considered early turnover. This process allows First Book to better understand the organization’s true and controllable retention rates, which rose to 90% over the same 5-year period when these additional factors were applied.

2)      Time to Fill Open Positions. Another important HR data point is the length of time it takes to fill open positions.  A quick analysis might assume that 45 days from posting to accepted offer is a bit too long.  But when a deeper analysis was done, we uncovered a strong core process with a few specific areas where improvements were needed.  Junior positions only require about 21 days to fill, which is slightly above average and represents the greater portion of the recruitment effort.  Senior positions where more thorough vetting is needed take longer (60 days), and IT positions, due to their nature and a competitive job market, take even longer (70 days).  This deeper analysis indicated that a few adjustments to First Book’s recruitment strategies were necessary, especially as it applied to the more challenging hiring categories. To address this, we altered the recruitment strategies specifically focused on the difficult hires: increasing our social media presence attracting more candidates, using more active candidate outreach approaches which put us in contact with passive job seekers, and streamlining the vetting process. These strategies have enabled us to successfully reduce the number of days to vet and fill senior positions from 60 to 40 days. These initial steps will be monitored for success and will continue to be tweaked as needed, through a data-informed process.

In both of these examples, we recognized that the topline summary was not an adequate gauge, and that by applying further data analysis, we were able to adjust our assumptions, underlying processes, and strategies to improve staffing outcomes.  In essence: additional examination and deeper analysis sometimes convey that what appears to be a problem isn’t, and what doesn’t seem to be, really is.

Now entering its 30th year, First Book’s commitment to being a data-driven nonprofit organization make this kind of analysis not only possible, but critical for the HR function. Importantly, this is exactly the type of approach needed throughout the social sector. With nonprofits addressing some of society’s biggest challenges, it’s important that the social sector integrate data-driven practices from the private sector to collect, examine and better understand organizational data related to hiring, training, retaining, and supporting employees. The ability of nonprofit organizations to meet their critical missions depends on it.

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