A new analysis published in Elsevier’s Funding Forward: Policy & Impact newsletter argues that government funders face a foundational challenge that underpins many of their most pressing priorities: the inability to effectively manage and integrate their own data.
Posted Monday on LinkedIn, Elsevier’s inaugural Funding Forward issue contends that while agencies often focus on aligning programs with societal goals, measuring impact and adopting artificial intelligence, these efforts are constrained by fragmented and underutilized data environments.
What Is the Core Challenge Identified?
According to Elsevier, many funding organizations have accumulated extensive datasets over decades — including grant records, publications, patents and policy documents — but lack the infrastructure to integrate and analyze them cohesively.
This fragmentation limits their ability to establish clear links between funding decisions and real-world outcomes. A cited study found that 65 percent of funding professionals said their systems do not track whether researchers use multiple grants to pursue similar objectives, highlighting gaps in portfolio visibility.
How Does This Affect Decision-Making and Impact?
The report identifies data fragmentation as a bottleneck that affects multiple aspects of the funding lifecycle.
Without integrated systems, agencies face challenges in demonstrating the public value of investments, making evidence-based policy decisions, and identifying missed or duplicative funding opportunities. The lack of accessible data can also increase administrative burden, as agencies may request information that already exists within their systems from researchers.
In addition, the report notes that inconsistent or siloed data environments can hinder the adoption of AI tools, which rely on structured and high-quality datasets to generate reliable insights.
What Limits Centralized Grant Management Systems?
While some agencies have adopted centralized, cloud-based grant management systems, Elsevier notes that these platforms often fall short in supporting comprehensive impact analysis.
The report points out that many systems focus on operational functions such as proposal submission and grant management, but provide limited capability to connect funding inputs with downstream outcomes such as publications, patents or policy influence.
What Barriers Are Slowing Progress?
The analysis highlights several obstacles to modernizing data infrastructure, including concerns around data security and privacy, high implementation costs and limited technical expertise.
It also points to organizational challenges, such as resistance to shifting away from manual processes and the complexity of integrating philanthropic goals with enterprise technology systems.
What Approach Does the Report Recommend?
Rather than relying solely on centralized platforms, Elsevier suggests a combination of strategies, including adopting data standards such as the Findable, Accessible, Interoperable and Reusable Data Principles and leveraging third-party capabilities, such as its InsightGraph integrated knowledge graph technology, to integrate and contextualize disparate datasets.
The report emphasizes that building a unified data foundation is critical to enabling advanced analytics, improving transparency and supporting more effective decision-making.
