An Article written by Remilekun Olaniyan, 2026 EPLF Cohort Fellow
In today’s complex political environment, many of the challenges confronting governments and political systems are treated as isolated problems rather than as consequences of decisions, policies, and institutional choices made over time. Political actors often respond to visible symptoms with immediate interventions without first examining the deeper causes that produced those outcomes.
The Retroactive Propagation Model (RPM) offers a structured approach to understanding this relationship between political decisions and their consequences. Rather than focusing solely on what should happen next, the model begins by looking backward to understand how a political or governance problem developed, before projecting how different decisions may shape future outcomes.
The Four Core Pillars of RPM
1. Backward Diagnosis
The model traces a political or governance challenge backward through its contributing factors, decisions, policies, and institutional conditions to identify the underlying causes rather than simply addressing the visible symptoms.
2. Forward Propagation
Once the underlying causes have been established, RPM projects possible interventions forward across different time horizons, examining how present decisions could influence future political, economic, and social outcomes.
3. Dynamic Segmentation
This stage connects identified root causes with potential policy responses while accounting for real world constraints such as available resources, institutional capacity, legal frameworks, political realities, and implementation limitations.
4. Deduction Report
The final stage synthesizes the findings into a structured decision making framework, presenting the relationships between causes, interventions, constraints, and possible consequences to support more informed political and governance decisions.
Why RPM Matters in Politics and Governance
In public policy and governance, RPM can provide a framework for examining how political decisions translate into long term outcomes. For example, political analysts and civic leaders could use the model to examine policy proposals, campaign manifestos, institutional reforms, or development plans by tracing their underlying assumptions and considering how they may unfold within the realities of a particular political and economic environment.
The model can also encourage a deeper examination of political outcomes. Rather than asking only “What went wrong?”, decision makers can ask: What decisions and conditions led us here, what alternatives existed, and what consequences could follow from the choices we make now?
This approach is particularly relevant in an environment where political decisions rarely produce isolated effects. A decision relating to public spending, taxation, education, security, energy, or institutional reform can create consequences that extend across multiple sectors and may only become visible years later.
RPM therefore seeks to create a bridge between historical diagnosis and future decision making. By connecting past causes with present choices and potential future consequences, it offers a framework through which political leaders, policy analysts, researchers, and civic actors can examine complex problems more systematically.
At its core, the model is built around a simple principle:
To understand where politics is going, we must first understand how it got here.
