Here in North America Marketing, we have an entire team of analysts dedicated to enabling better decision making through data. Every day, Business Management Office (BMO) analysts – and I count myself as one – use SAP tools to make sense of our data: monitoring ongoing programs, evaluating Marketing effectiveness, and ultimately catching trends and insights that might otherwise have gone unnoticed.
Unfortunately, not every organization has the same analytical muscle behind it. Leaders and researchers in the nonprofit sector are surrounded by mountains of both quantitative and qualitative data, but often lack the manpower or the tools to really do anything with it. As a graduate student at Villanova University, I supported Dr. Lauren Miltenberger throughout the first two years of her research project studying the relationships between the nonprofit sector and our government as they “contract” to deliver many of the social services we’ve come to expect as a society. As with most professional relationships, some entities simply pair better than others and have higher levels of success. Lauren’s research seeks to profile this contract landscape, key into what factors cultivate the most efficient partnerships, and identify why some states do it better.
Although I graduated from VU more than a year ago, the nonprofit sector remains a strong interest of mine, and the DataGeek Challenge offered a great opportunity to harness my team’s analytical skillset and, hopefully, shed some new light on a real-life research question through the power of SAP Lumira. When I asked Lauren if she’d like to collaborate on this project, she was thrilled at the prospect and immediately shared her Excel file. The main question she wanted us to address is what factors might have led nine U.S. states to form co-sector task forces. After some data manipulation and standardization, we identified 20 measures that were vital to the research question, and got to work. Here are a few key highlights we identified using Lumira.
- CA, TX and NY may have some of the highest populations and total number of nonprofits, but they do not have very high nonprofit density (# of nonprofits per state citizen). In fact, less populous states such as IA and MT actually have a higher penetration of nonprofits.
- State & local contracting appears to be closely linked, while federal contracting primarily stands alone. An exception is states that have very low levels of federal contracting; in these cases, state contracting often spikes when compared to local contracting.
- While the 9 task force states do not have any standout distinguishing features, they have some general trends in common. 6 of the 9
states are based on the East coast, focused around the Mid-Atlantic region. Furthermore, they have an above-average number of NPs with State contracts, very close percentages of NPs with federal contracts, and relatively close “density” measures.
When I met with Lauren to walk through the results, she was incredibly impressed with the outcome. While she was already intimately familiar with the state profiles and general national trending, the visualizations brought the data to life for her in a new and unexpected way. We were able to identify some general clustering between the nine task force states which will provide a good baseline for further research, and she was surprised that we found as much correlation as we did. Despite this small victory, the full analysis revealed an overarching theme: when it comes to nonprofit contracting, states do not act in a highly predictable manner. Neither size, nor density, nor a history of contracting issues can predict how a state will stack up in certain measures. Sometimes states behave differently simply because of the human element. All it takes is one or two motivated individuals to dream up a new way of collaborating and to align the key contacts, and the rest, as they say, is history.
Project completed with the help of Sushmita Ghosh, Rita Kamau, Michael Laubach, and Marianne Moffett.
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