Leveraging data to drive strategy for research leadership

In higher education today, research administration, research development, competitive intelligence, and research analytics serve their constituent leadership often within silos with ineffective decision support and without integrating on broader, contextual questions plaguing the leadership. The questions around new opportunities driven by leadership demands an integrated solution across the various actors described above in higher education. Most institutions capture sponsored research data which typically contains a breakdown of participants (investigators), their affiliation, effort allocation, funding allocations, sponsors, total cost, etc. The level and complexity of this raw data varies significantly among academic institutions and on the software they use. The availability of this data and its use in complex formats creates opportunities and challenges in driving strategic decision making for research leadership. This presentation highlights the integrated data used to drive strategic decision-making at two levels: the college/school level and the central/university level. Each institution either centrally or at departmental level through websites or other sources such as Elsevier Pure, Dimension, etc., curates local libraries and internal databases that further contain rich attributes such as areas of expertise, their rank, position title, time in organization, etc. that when combined with sponsored research databases produce new insights that help drive strategic decision making. We plan to showcase a few examples of joining and juxtaposing local databases with sponsor data that has helped departments and central organizations create actionable plans. Data is used to drive intervention decisions and support for i) Hiring and retention, ii) creating competitive teams iii) where to focus - which areas need support - allocation of resources, iv. alignment with university strategic documents and finally, v. hone in on the right questions to ask to organize data appropriately.