What's Wrong With Site Benchmarking? A Site-Centered Perspective On Its Alignment, Transparency, And Use

By The League Benchmarking Working Group

Clinical trial stakeholders consistently express a need for better benchmarking of site performance. Sites, sponsors, and CROs all rely on metrics to evaluate performance, inform decisions, and guide operations. However, few agree on how metrics are defined and contextualized at different organizations. Furthermore, there is no standard for how and why metrics are used to compare organizations or to create industry benchmarks. And yet, these organizational metrics drive industry benchmarking at an aggregate level. Therefore, site benchmarking efforts remain fragmented, inconsistent, and difficult to operationalize and interpret.

This creates a central paradox: Benchmarking is widely used and highly valued, yet trust in benchmarking is limited. Stakeholders recognize the importance of metrics but they aren’t confident in whether those metrics are defined, contextualized, and applied in ways that support fair and meaningful comparison. This tension between reliance on metrics and limited confidence in their validity is central to the benchmarking paradox.

Why Site Benchmarking Matters: Use Cases And Value

Benchmarking has become essential to how sites operate and engage with sponsors and CROs. Site operational and performance metrics serve multiple distinct purposes, which are often not explicitly defined and are frequently conflated.

At its core, benchmarking supports three primary uses that each have different goals and audiences:

• Internal awareness and improvement
• External advocacy
• External evaluation and industry benchmarks

Internal Awareness & Improvement

Internally, benchmarking is critical for awareness of operational performance. Sites use metrics benchmarked over time and across the organization to evaluate workflows, identify bottlenecks, allocate staff, and improve performance. Many organizations track start-up timelines or enrollment performance through internally developed dashboards or spreadsheets, often combining data from multiple systems to oversee operations.

Benchmarking also plays a central role in financial sustainability. Sites use metrics to understand study-level profitability, support budgeting decisions, and justify resource needs. In some cases, organizations have built integrated views that combine CTMS and financial data to assess enrollment performance against fully allocated costs, enabling more informed decision-making.

External Advocacy

Externally, site metrics can be used to communicate capabilities and performance to sponsors and CROs at timepoints throughout the study. They can help demonstrate capabilities during site selection, justify timelines or budgets during start-up, and support resource requests during study conduct. In this context, metrics are both descriptive and strategic, providing transparency and support for sponsor/CRO decision-making and serving as both a signal of performance and a lever in negotiations.

Benchmarking also builds trust. Over time, consistent use of metrics can establish patterns, build credibility, and strengthen collaboration between sites and sponsors. In practice, sites with established relationships often find it easier to contextualize their data and leverage historical performance.

Finally, some sites use their metrics to recruit and retain investigators, site staff, and even participants. Metrics about study volume, years of experience, and access to new or lifesaving therapies build trust with potential employees and participants.

External Evaluation And Industry Benchmarks

In addition to their own internal benchmarking efforts, sites are also evaluated using externally generated data and industry benchmarks. These may include aggregated data sets, third-party benchmarking tools, or sponsor-developed data sets and performance models. At the industry level, site benchmarking is often seen as a mechanism to establish standards, make informed decisions, and improve overall trial execution. However, the level of detail in these data sets varies widely, and they often lack site-level verification, context, or transparency. While benchmarking is often positioned as an industrywide tool, sites frequently experience benchmarking as something done to them, rather than with them.

One Approach Doesn’t Meet All Needs

These three benchmarking uses are frequently treated as interchangeable, but they are not. A metric that is useful for internal process improvement may not be appropriate for external comparison. Similarly, high-level public benchmarks may support broad communication but lack the specificity needed for operational decision-making. Effective metrics must be tailored for the audience and purpose so that they are not misapplied or misinterpreted.

Core Realities And Challenges Of Site Benchmarking

There are common issues that make measuring and benchmarking challenging across the industry that generally fall into the following categories:

Lack Of Standardization

Although many organizations track similar types of metrics around start-up, enrollment, quality, financial performance, and resource utilization, there is little consistency in how those metrics are defined, calculated, or visualized. Start and end points for timelines may differ, units of measurement may vary (e.g., calendar vs. business days), and methodologies are often organization-specific. Even seemingly simple metrics, such as study start-up time, can be calculated in fundamentally different ways (e.g., Invite to SIV at the sponsor vs. Protocol receipt to IP receipt at the site). This leads to a situation where stakeholders are effectively speaking different languages, making meaningful comparisons difficult. Often these fundamental misunderstandings may not be surfaced without discussion and open communication between sites and sponsors/CROs.

Lack Of Context

Site performance metrics may depend on contextual factors such as therapeutic area, study complexity, patient population, infrastructure, and staffing. However, metrics are often presented without this context, particularly in industry databases. High-level figures may appear comparable but lack the detail needed to interpret what they actually represent. As discussed in the working group, a metric such as total number of studies or average start-up time provides limited insight without understanding the underlying context and conditions.

Aligning To The Audience And The Goal

Metrics are not always fit for purpose. Data collected for one use case is frequently applied to another without appropriate adjustment. One example is scraping cancer center statistics from clinicaltrials.gov for site identification, when those statistics do not differentiate between self-reported IITs and sponsored trials. Public or externally reported benchmarks may be useful for high-level communication but are often too broad to inform operational decisions. Similarly, internal metrics may be shared externally without sufficient framing, increasing the risk of misinterpretation. For example, start-up time for an organization may be in an internal database without the context of which department or study phase resulted in that start-up time.

Data Fragmentation

Within all organizations, relevant data is often spread across CTMS platforms, financial systems, regulatory tools, and manual trackers. Integration is limited, and many processes remain manual. Important external data, such as detailed quality metrics or EDC-related performance indicators from sponsor/CRO systems, may not be accessible to sites at all. Recently, sponsors and CROs have been causing further fragmentation by imposing onerous confidentiality restrictions that limit the data sites can use for external reporting. This means that significant time and effort are needed to establish and maintain metrics, often resulting in incomplete and difficult-to-maintain benchmarking efforts.

Transparency And Trust

First, organizations are often afraid of losing a competitive advantage by sharing their own metrics too broadly, leading to a lack of transparency.

Sites often have limited visibility into how their data is used once shared with sponsors and CROs in feasibility questionnaires or at site qualification visits. It is rare for sponsors and CROs to share their own internal metrics about site performance with sites. Often this data lacks the context needed to really understand it and to make it useful to compare across sites.

One group member shared that a sponsor CTMS captured a site start-up time at 452 days. A different site on the same study reported a start time of 91 days. The study team using this internal data for site selection naturally wanted to omit the first site and include the second site. However, the decision to do so would have ignored context. The sponsor selected and invited the first site in the first wave of study start-up. Unfortunately, the sponsor had to dramatically change the protocol shortly after the invitation, causing a pause in start-up. The sponsor invited the second site after the protocol revisions were completed. The start-up time metric did not correctly capture the pause, and so the sponsor unfairly judged the first site by using an incorrect metric. The sponsor did not ask the site to provide context, since these internal metrics were accepted as accurate and useful. Without visibility or the opportunity to provide context, sites may be evaluated using metrics that do not accurately reflect their performance.

Sites also have little insight or visibility into how third-party industry data sets and benchmarks are developed, the data and metrics they contain, or how they are evaluated by sponsors and CROs. Despite this lack of visibility, the stakes these data points play in sponsor/CRO decision-making is high. These benchmarks can directly influence decisions about site selection and trial decisions that have direct impacts on the trial success or timelines. From a site perspective, this overall lack of transparency creates a significant imbalance. Sites are evaluated against data and benchmarks they cannot fully see, influence, validate, or improve upon when necessary. This dynamic can lead to misalignment between how sites understand their own performance and how that performance is interpreted externally.

Principles For Alignment On Benchmarking

Addressing these challenges requires a shift in how benchmarking is approached across the clinical trial ecosystem.

Benchmarking should first and foremost be understood as a tool for continuous learning and improvement, not judgment. Exploring the details behind both high and low performance can surface insights that enable better decisions, more effective operations, and stronger collaboration, driving our whole industry forward.

Several principles are critical to achieving a more aligned approach to benchmarking:

• Purpose must come before measurement. Organizations should clearly define the use case for a metric before measuring it, including the audience, the decision being supported, the level of detail required, and whether the metric will be benchmarked.
• Context must accompany comparison. Metrics should be interpreted within the operational environment in which they were generated, including site characteristics, study design, and resource constraints. All stakeholders must communicate how they are defining each metric, the context for the metric, and the scope of the data set used to generate the metric.
• Definitions must be aligned. Consistency in how metrics are defined and calculated is essential for any meaningful comparison.
• Transparency must be prioritized. Stakeholders should have clarity into how metrics are constructed, how they are used, and what decisions they inform.
• Trust must be established. Effective benchmarking depends on shared understanding, appropriate data use, and ongoing collaboration between sites, sponsors, and CROs.
• Variability should be recognized as inherent. Differences across sites and studies are expected and should be incorporated into interpretation, rather than treated as noise to be eliminated.

Looking Ahead: A Call For Shared Accountability

Benchmarking will continue to play a central role in decision-making in clinical trial operations. However, its effectiveness depends on how thoughtfully that data is defined, contextualized, communicated, and applied.

For sites, continued investment in the collection, management, and monitoring of well-defined internal metrics will be essential to understanding their own performance and support operational improvement, financial sustainability, and informed engagement with sponsors and CROs. For these metrics to translate to industry benchmarks, the metrics must be aligned more globally.

For sponsors and CROs, there is a need to evaluate how benchmarking data is sourced, interpreted, and applied. Greater transparency into benchmarking methodologies, along with intentional collaboration with sites, can improve the accuracy, credibility, and usefulness of performance metrics.

Moving forward, benchmarking must evolve from a unidirectional evaluation tool to a shared framework grounded in context, transparency, and mutual understanding. Only then can it fully support better decisions, stronger relationships, and improved outcomes across the clinical trial ecosystem.

About The Experts:

The League is a thought leadership community convened by Florence Healthcare. The following League members contributed to this article:

Andrea Bastek, Ph.D.
VP Market Strategy
Florence Healthcare

Trevor J. Cole, BS, MBA-HCM, CCRC, PMP, RN
Program Director, Clinical Solutions and Partnering
WCG Clinical

Jana N. Dock, CPA
Director – Business Operations
Mercy Research

Amber Hood, DFS, MS, CPIA, CIP
Director, Regulatory Compliance and Research Facilities
Oklahoma State University Center for Health Sciences

Janet Matthews, MSN, RN
Senior Director of Research Program Development
Drexel University College of Medicine

Matthew Miller
Director, Research Business Operations
Banner Health

Megan Solomon, LPN
Lead Coordinator, Regulatory & Compliance
Northwest Georgia Oncology, a Service of Wellstar Cobb Hospital