Not Just Trials and Numbers: How SSM Enriches Implementation Science

Understanding Where Soft Systems Methodology Fits in the Implementation Science Landscape

Implementation science is a rapidly growing field that seeks to bridge the "know-do gap"—the space between what research shows is effective and what gets implemented in real-world health and social systems. It's distinct from traditional research in several crucial ways:

1. Focus on Uptake and Integration, Not Just Efficacy
   While traditional clinical research asks, "Does this intervention work under ideal conditions?" implementation science focuses on, "How can we ensure this intervention works in practice—and is sustained?"

2. Emphasis on Context and Barriers
   Traditional studies often try to control for contextual variables. Implementation science, by contrast, dives deep into the environment, uncovering how settings, culture, resources, and systems influence uptake.

3. Stakeholder Engagement
   Rather than viewing participants merely as subjects, implementation science involves patients, practitioners, and policymakers as co-creators and evaluators of the research process.

4. Use of Diverse, Mixed Methods
   Implementation studies often combine interviews, focus groups, quantitative analyses, and real-world observations to paint a holistic picture of what works, for whom, and why.

5. Focus on Implementation Strategies and Outcomes
   Instead of only measuring clinical results, implementation science looks at adoption, fidelity, acceptability, and sustainability.

6. Iterative and Adaptive
   Implementation science welcomes course correction. Studies are often cyclical, with built-in reflection and adjustment points.

Classification of Research Methods in Implementation Science

One of the defining features of implementation science is that it's not tied to a single methodology. Instead, it draws on a diverse toolkit from multiple disciplines:

• Qualitative research (interviews, focus groups, ethnography)

• Quantitative research (e.g., RCTs, surveys)

• Mixed methods

• Economic evaluation

• Social marketing

• Stakeholder and policy analysis

• Systems analysis and improvement science

• Operations research

• Process mapping

Each method is selected based on its contribution to answering the central question of implementation science: How can we improve the adoption, adaptation, and sustainability of evidence-based practices in real-world systems?

Where Does Soft Systems Methodology (SSM) Fit In?

Soft Systems Methodology (SSM) is a qualitative, systems thinking approach developed to tackle complex, "messy" problems—those that don't have a clear definition, let alone a straightforward solution. SSM emphasizes:

• Understanding different stakeholder perspectives

• Mapping purposeful activity systems

• Facilitating learning and systemic change

While SSM may not be listed explicitly in many standard implementation science frameworks, its values align closely with the spirit and aims of the field. Specifically, SSM is useful when:

• Addressing organizational or inter-organizational change

• Exploring complex systems where multiple actors and goals intersect

• Designing participatory processes for co-implementation

• Surfacing and managing implementation barriers in a structured way

Thus, SSM is absolutely compatible with implementation science—especially when used to support systems analysis, stakeholder engagement, and organizational learning.

Conclusion

Soft Systems Methodology is not automatically classified as implementation science, but it clearly belongs within its orbit when applied to improving the adoption and effectiveness of evidence-based practices. In fact, its participatory, systems-based lens makes it especially valuable for tackling the organizational and systemic challenges that often hinder implementation.

Ultimately, implementation science is defined by its purpose—not its methods. Whether using RCTs or rich, qualitative mapping like SSM, what matters is whether the research helps us better understand and support change in complex, real-world systems. When SSM is used in this way, it is not only compatible with implementation science—it's an essential tool in the box.

About the Editor

Paul Nunesdea is the English pen name of Paulo Nunes de Abreu, an IAF Certified™ Facilitator, Master of Ceremonies, author, and publisher of the Architecting Collaboration book series. He designs and facilitates high-impact events for corporations, public institutions, and civic organisations across Europe and beyond.

As the curator of Architecting Collaboration, Paul writes about the intersection of collaboration, facilitation, and digital transformation, drawing from decades of practical experience and system thinking. He is also the founder of col.lab | collaboration laboratory, which serves as a hub for innovation in meeting design and participatory processes, including its spin-off, Debate Exímio Lda.

In the health data space, Paul leads the Health Data Forum, a UK-registered charity advancing ethical AI adoption and digital health transformation. He spearheads the Data First, AI Later movement and manages a curated network of independent consultants specializing in health data governance and AI strategy.