Systems Informed Foresight® (SIF®) is a methodology developed by RIAHSAH Co. to help organisations understand and act within complex systems.
SIF® integrates systems thinking and strategic foresight to help actors examine the systems they operate within. It supports in identifying leverage points for change, and designing responses that remain adaptable as conditions evolve across markets, institutions, and social systems.
We apply SIF® across market systems, value chains, policy environments, and social programmes to generate system-level insight that informs adaptive decision-making.
SIF® operates through a continuous learning cycle that connects system understanding, action, and learning.
The methodology is structured around three interconnected phases:
Awareness
Understanding how the problem or opportunity is situated within the wider system; examining actors, relationships, incentives, narratives, and structural dynamics.
Application
Translating system insight into action through interventions, research, experimentation, or coordinated initiatives.
Adaptation
Learning from how the system responds and adjusting approaches as conditions evolve.
Together these phases form an iterative cycle that links system analysis, decision-making, and learning over time.
Complex environments rarely behave in linear ways. Outcomes emerge from the interaction of multiple actors, incentives, institutions, and structural forces.
Traditional planning approaches often assume that implementing the right activities will produce the desired outcomes. In complex systems, this assumption rarely holds.
SIF® provides a structured way to:
understand how systems function
examine how actors and incentives interact
identify leverage points within the system
explore how systems may evolve in the future
design actions that can adapt as conditions change
SIF® combines system analysis with foresight to generate insights that support more informed decisions across both market and social systems.
During the Awareness phase, SIF® examines how systems operate across several dimensions:
Domains
Systems often intersect with multiple domains such as markets, governance, finance, technology, or public policy.
Scales
System dynamics occur across different levels, from local actors and organisations to regional, national, and global systems.
Contexts
Political, cultural, economic, and ecological conditions shape how systems behave in different environments.
Time horizons
Some system dynamics emerge quickly, while others unfold over years or decades.
Examining these dimensions helps reveal how challenges are embedded within nested systems where developments at one level influence dynamics at another.
The methodological logic of SIF® remains consistent across different systems. At RIAHSAH, we apply the approach across several domains.
Market Systems
Understanding how firms, regulators, infrastructure, and financial actors interact within industry systems.
Value Chains
Examining how value flows through production, logistics, and distribution networks.
Industry Ecosystems
Analysing how industries evolve through interactions among firms, institutions, technology, and policy.
Policy Environments
Exploring how governance structures and regulatory dynamics influence system outcomes.
Social Programmes
Supporting programme design and coordination across public institutions, civil society organisations, and communities.
Innovation Ecosystems
Understanding how entrepreneurs, research institutions, investors, and policy environments interact to enable innovation.
Across these domains, SIF® supports research, facilitation, strategy processes, and system-level learning.
At RIAHSAH, Systems Informed Foresight® is applied across research, strategy development, model design, facilitation, and system-level learning engagements.
Examples of how the SIF® approach is applied in practice:
Youth@Work Systems Learning Initiative
Through Youth@Work, RIAHSAH applies SIF® to map youth employment systems, covering labour markets, education pathways, policies, and community actors to uncover barriers and pinpoint opportunities for interventions that strengthen pathways into work.
Systems Skills Labs and Scenario Learning
Through the Dariro Scenario Skills Labs, SIF® convened civic actors to explore the future of human rights defence, feminist organising, and youth climate leadership in Southern Africa, examining emerging signals, developing scenarios, and identifying pathways for collective action.
Market and Industry System Analysis
In market and industry contexts, SIF® supports research and intelligence work for RIAHSAH’s clients, examining how industry systems, value chains, and regulatory environments interact to identify structural shifts, emerging risk signals, and opportunities for innovation across market ecosystems.
Policy and Institutional Systems
RIAHSAH applies SIF® in commissioned projects to analyse how policy and institutional relationships shape system outcomes, mapping governance dynamics and coordination gaps to guide action across public institutions, civil society, and other stakeholders.
Across these contexts, SIF® helps translate system understanding into structured insight that informs decision-making, collaboration, and adaptive action.
Systems change rarely occurs through the actions of a single actor.
Markets, programmes, and policy environments are shaped by networks of relationships connecting organisations, institutions, communities, and knowledge actors. These relational ecosystems influence how information flows, how decisions are coordinated, and how systems respond to emerging pressures.
Within SIF®, attention is given not only to analysing systems but also to strengthening the relational environments in which actors interact.
Healthy relational ecosystems help actors:
share knowledge across silos
coordinate responses to shared challenges
develop new collaborations
respond more effectively to change
Strengthening these relational dynamics helps translate system insight into coordinated action across the system.
Interested in applying SIF® in your organisation or sector?