Clinical research organizations are using more technology than ever. According to a Society for Clinical Research Sites (SCRS) poll, many sites are using 20+ systems on a daily basis. CTMS platforms, EDC systems, eRegulatory tools, shared drives, spreadsheets, and communication platforms all play important roles. Yet even with this extensive technology stack, many research organizations still rely heavily on manual processes to keep studies moving.
The problem is not necessarily a lack of technology. It is a lack of orchestration.
When systems, data, and teams are not connected, the organization itself becomes a challenge. Staff fill the gaps with disconnected spreadsheets, emails, manual data entry, and countless handoffs. That approach may work for a small number of studies, but as organizations grow, so does the operational risk.
Having Technology Is Not the Same as Having an Operating Model
A collection of individual tools does not automatically create a connected research operation.
Consider a typical workflow. Study information may live in a CTMS, regulatory documents in SharePoint or a shared drive, enrollment data in spreadsheets, study data in a sponsor EDC, and day-to-day communication in email. Each system may work as intended, but moving information between them often depends on people and manual processes.
This creates additional work and introduces opportunities for delays, duplicate data entry, inconsistent information, and missed tasks.
A modern operating model should do more than store information. It should connect the people, processes, and technology responsible for moving a study forward.
The Coordinator Experience Matters
For research coordinators and site staff, fragmented technology is more than an inconvenience. It can cause wasted time and effort, leading to study delays.
When users have to move between multiple applications, remember where information is stored, and manually transfer data, administrative burden increases. Every additional handoff yields an opportunity for something to be overlooked or entered incorrectly.
Capacity is not constrained by clinical complexity – it is constrained by how much manual work the operating system includes.
Compliance Should Be Built into the Workflow
Regulatory compliance is another area where organizations can become dependent on manual coordination.
When documentation, study activities, and data are managed across disconnected systems, maintaining consistency and audit readiness often requires additional oversight. Teams may need to verify that information matches across systems, confirm required activities have been completed, and track documentation manually.
Connected workflows can reduce this burden by embedding standardized processes, permissions, audit trails, and required steps directly into the way work gets done.
Compliance becomes part of the workflow rather than another layer of work added on top of it.
Reporting Shouldn't Require a Reconstruction Project
Leadership needs visibility into study performance, enrollment, timelines, financials, and operational metrics. Unfortunately, when information is scattered across multiple systems, producing a reliable report can become a manual exercise.
Teams may export data, combine spreadsheets, reconcile discrepancies, and validate information before leadership ever sees it. This creates two problems: reporting consumes valuable staff time, and the information may already be outdated by the time it reaches decision makers.
A connected operating model provides a more consistent source of information and enables teams to access current data without repeatedly reconstructing the story from multiple systems.
Growth Exposes the Gaps
Fragmented processes often become most visible when an organization starts to scale.
Adding more studies, sites, or staff increases the number of handoffs and data points that need to be managed. Processes that once depended on a few experienced employees become increasingly difficult to maintain consistently across a larger organization.
This is where workarounds become an even bigger risk.
An operating model that depends on institutional knowledge and manual coordination may struggle to deliver the same level of visibility and consistency as the organization grows.
What a Modern Research Operating Model Looks Like
A modern clinical research operating model should make the organization easier to manage, not more complicated. It should provide:
- Connected workflows that move information naturally between teams and functions.
- Centralized data that gives everyone access to a consistent source of truth.
- Automation that reduces repetitive administrative work.
- Standardized processes that improve consistency and support compliance.
- Real-time visibility into study, operational, and financial performance.
- Actionable analytics that help leadership identify trends and make better decisions.
- Scalability that allows organizations to grow without multiplying manual processes.
Most importantly, the technology should fit the way research teams actually work.
A Unified Approach with RealTime SOMS
This is the philosophy behind RealTime’s Site Operations Management System (SOMS). Rather than treating clinical research functions as isolated processes, SOMS connects the critical components of site operations within a unified platform.
For example, Cedar Health Research unified its operations with SOMS, creating a centralized environment for managing studies, streamlining workflows, and improving operational visibility. With essential tools and information accessible through one integrated platform, their team is better equipped to manage day-to-day operations and support continued growth.
“I know we hear a lot about technology fatigue, so being able to really leverage one platform for all things from eSource to CTMS is huge,” said MJ Hamersma, Vice President of Operations at Cedar Health Research.
With RealTime SOMS, CTMS, eReg/eISF, eSource, participant engagement, business intelligence, and other capabilities work together to create continuity across the research lifecycle. Instead of requiring teams to manually connect information between separate systems, SOMS provides a centralized environment where data and workflows automatically move with the study.
For research coordinators, that means less time switching between applications and more time focused on patients and study execution. For leadership, it means greater visibility into real-time operational and financial performance. For organizations, it creates a foundation for standardized processes, stronger compliance, better resource utilization, and scalable growth.
The Future of Clinical Research Is Connected
Clinical research will continue to become more complex. Study volumes will grow. Protocols will evolve. Sponsor expectations will increase. Organizations will continue adding specialized technologies to address emerging needs.
For research organizations looking to scale, the question is no longer: “Do we have the right technology?”
It has become: “Do our systems work together well enough to support the way we operate?”
That distinction can make the difference between an organization that is constantly managing workarounds and one that is built to operate, adapt, and grow with confidence.
Request a demo to see the market-leading SOMS orchestration system in action today.
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