Program Analytics | HHMI

Program Analytics

I designed, developed, and implemented Program Analytics to longitudinally track and analyze the professional trajectories of all HHMI program participants and alumni.

“The easiest part of what I do is crunch and analyze numbers. The hardest part, and where I spend most of my time and energy, is ensuring that we have the appropriate infrastructure in place so that all of our processes and systems are sustainable. The general idea is really simple: If we have good data going in, we’ll have a great analysis coming out.”

Based on a federated model of governance, Program Analytics provides directors and senior leaders relevant data and actionable analyses. As part of this pioneering effort, I developed and implemented a metadata framework that bridges our science and program communities to Operations; developed and implemented a data ecosystem which aligns our governance, data collection and processing, our systems of record and underlying architecture. Currently, I am experimenting with natural language processing to empower users with their engagement of data analysis (e.g., ChatGPT in a secure and closed data environment).

Given the importance placed on governance, metadata, mapping structures and taxonomies, internal analysis is brought into conversation and benchmarked with national entities and efforts, such as: the National Science Foundation (NSF), Association of American Universities Data Exchange (AAUDE), Carnegie Classifications, Coalition for Next Generation Life Science (CNGLS), and the North American Industry Classification System (NAICS). This approach allow us to examine trends, situate our analyses within a broader context, and say relative to.

This information is utilized in the following areas: partnerships, research and program evaluation, strategic initiatives, development of evidence-based practices, and culture building.