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Central administration at Rutgers University requested help from the Office for Research to develop a proof-of-concept tool to count collaborations between faculty, departments, schools and chancellor units across the university. This presentation will discuss how the Data, Analytics and Business Intelligence team focused on research administration and research output data to define a “collaboration,” structure available data, create interactive visualizations and allow end users to customize the level of detail displayed. This presentation will begin by discussing the importance of generating reliable collaboration data in a university setting including use cases for the data. It will then describe the dataset that was used for the proof-of-concept project and discuss why these sources were important. Finally, the presentation will discuss future development goals and collaborators for the collaboration project. 

Rutgers University is a R1 Research Institution with $929M in Sponsored Research funding in FY 2023 and $747M in Research Expenditures in 2022 as per the HERD survey. Since forming in 2019, the Data, Analytics and Business Intelligence team within the Office for Research has grown to three members, all with the mission of providing accurate and timely data about the Rutgers research enterprise for both internal leadership and decision makers across the university. The Office for Research leadership was receiving complaints from the field about sponsored research awards taking too long to be set up. The Data, Analytics and Business Intelligence team was tasked to find out: 1. Is this a common issue? 2. Is this a localized issue? 3. What’s causing this? Our team determined that by calculating the start and end of processes, and by categorizing responsible party within those processes, we can figure out what an average user might experience and then dig deeper into the outliers. We involved IT to extract the data from the award set up system into the data warehouse, and ultimately a Tableau data source. We also met with the business team to better understand the data in their system and define how their processes should be categorized, and if any of their processes might need to change to help generate important data. The final deliverable was a published Tableau Dashboard that leadership and the business unit could access that shows turnaround time trends broken down in various ways, with the option to drill down into outliers without leaving the dashboard. Since then, we’ve been able to replicate this method across other Office for Research business units including the teams managing IRB and IACUC protocols. Our presentation would include: 1. The problem that was presented to us 2. The process we followed 3. Samples of the dashboards we created 4. The outcome and lessons learned 5. Guiding questions on how other schools can use this method and replicate it across multiple systems within their Research Offices