Background

The National Science Foundation (NSF) is committed to promoting the progress of science, advancing national health, prosperity and welfare, and securing the national defense. It funds research projects across various scientific fields, provides grants to researchers and institutions, and aims to improve science education at all levels. With a budget of $9.6B, NSF receives approximately 46,500 grant proposals annually and funds about 12,900.

For the past two decades, NSF reviewers and panelists have relied on a legacy system for ad hoc proposal reviews and panel-based peer reviews. However, the legacy system’s aging technology hampered NSF’s ability to accommodate tailored evaluation needs for individual research programs, secure sensitive research information, and provide an intuitive user experience. This has resulted in numerous inefficiencies and user frustration.

GovReview Implementation at NSF

REI implemented our GovReview solution for NSF as their ‘Proposal Evaluation System (PES)’. GovReview is based on a modular architecture and provides for integration points from upstream and downstream systems, allowing NSF to “plug-and-play” the Panel Review process into their existing enterprise-wide Grants Management ecosystem. Using industry-standard development practices with Open API standards, GovReview enables other source NSF grants systems to provide configuration data for Programs, Solicitations, and Reviewers, thus reducing the need for duplicative data entry and supporting accurate and consistent data throughout the enterprise.

Today, GovReview is significantly enhanced from the original peer review solution that was piloted by NSF. We upgraded our solution to leverage the benefits of the Amazon Web Services (AWS) Cloud using cloud-native, scalable, and elastic design principles. This creates a modular architecture based on microservices and separated front-end components. Further, REI enhanced and simplified GovReview for use in NSF’s environments. REI trimmed down many features, from administrative components, that are handled instead in MyNSF, through messaging and web services, whose data is imported into GovReview. Also, REI trimmed down the microservices to reduce resource usage within AWS and reduce maintenance required for additional services. The remaining services are built to be cloud- native and deployed into the cloud.

Impact

GovReview replaced outdated technology in a key NSF application, offering a modern, easy-to-use, cloud-native tool for peer reviews. It integrated seamlessly into NSF’s existing grants ecosystem, improving data flow and reducing administrative workload. Since its go-live, GovReview has supported over 500 NSF panels and 3,000 panelists across ~120 programs. GovReview is designed to scale further, accommodating over 1,500 panels and more than 12,000 panelists annually.

The GovReview implementation at NSF has improved operational efficiency and enhanced the experience for both researchers and reviewers, leading to cost savings and faster scientific advancements.

Improved Efficiency of Panel Reviews:   

• NSF staff can use GovReview’s self-service features to set up opportunities, reviews, and panels according to their specific needs, without extensive technical support. NSF administrative staff handling proposal processing have seen a 25% decrease in workload associated with these tasks, allowing them to focus on other valued tasks.
• The new collaborative commenting and editing features boosted panel efficiency by 30%, allowing for real-time finalization of summaries during meetings and eliminating the need for lengthy offline back-and-forth edits.
• Dashboards and reporting tools effectively track the merit review process, helping NSF make data-driven decisions that significantly impact its mission.

Increased Quality of Panel Reviews:

• Tailored program-specific templates allow proposal reviewers to complete reviews based on solicitation-specific criteria, thus enhancing the quality of the review response. This includes a tailored panel summary template allowing individual programs to share meaningful and relevant information with the final approvers to support faster and better funding decisions.
• Shortening the review timeline led to a quicker turnaround for funding decisions, benefitting researchers by enhancing their ability to plan research timelines effectively.

Conclusion

The implementation of GovReview at the National Science Foundation marks a notable step forward in modernizing the peer review process for grant proposals. By replacing the legacy system with a cloud-native, scalable, and highly configurable solution, GovReview addresses long-standing challenges such as inefficiencies in manual processes, lack of system flexibility, and inadequate collaboration tools. GovReview has streamlined NSF’s panel review process, reduced administrative workloads, and improved the quality of evaluations. GovReview’s integration into NSF’s grants ecosystem has already demonstrated significant operational benefits, including a 25% reduction in administrative effort on proposal processing and a 30% boost in panel efficiency. Beyond immediate gains, the scalability and adaptability of GovReview positions NSF to better support its mission of advancing science and innovation.

Following successful implementations at NASA and NSF, GovReview’s modular, plug-and-play design is ready to enhance peer review processes for other agencies.

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