# Systems Analysis > *“When one tugs at a single thing in nature, they find it attached to the rest of the world”* — **John Muir** Systemic investing embraces the complex and interconnected nature of the big societal challenges of our time. This not only requires investors to adopt a systems orientation, but also analytical approaches attuned to working with systems and complexity. And it is through the process of systems analysis that investors dive deep into the systems they seek to transform with the goal of building the strategic intelligence that later informs their capital allocation decisions. Systems analysis therefore plays a foundational role in the systemic investment process and has two overarching aims: {% stepper %} {% step %} ### Gaining a deep and holistic understanding of the system In order to make capital allocation decisions that hold the potential to contribute to genuine system transformation as opposed to mere optimization (or even inadvertently creating negative side-effects), you will need to acquire a deep understanding of the system. This includes inquiring about the dynamics that drive the system and its leverage points, places where an intervention may lead to outsized impact. {% endstep %} {% step %} ### Creating momentum through collaborative and participatory modes of working Systems analysis should always be done as a co-creative process with other stakeholders in the ecosystem, which serves the vital function of creating and strengthening alignment with those stakeholders. It also continues and amplifies the process of building and growing a change coalition, in part by creating outputs—maps, diagrams, etc.—that serve as anchors to facilitate conversations. {% endstep %} {% endstepper %} There are **three parts** to the systems analysis stage of the systemic investing process: * **Research**, to collect various kinds of data through, for instance, literature review and stakeholder dialogues; * **Systems mapping,** as a way of organizing and making sense of research outputs; and * **Identification of leverage points,** which build the foundation for moving into the design phase of the systemic investing process. While there is a sequential logic to these three steps, iteration is—again—a key feature of system analysis. You need to be prepared to go back and forth between these stages, revisiting research outputs, refining and expanding your system maps, and drilling deep into the root causes that present the points of highest potential leverage for driving change. But before jumping into the details of the process itself, it’s worth pointing out a few factors that will shape how this stage of the work may play out. Systems analysis is resource intensive and has no real parallel in conventional investment practice, not even in impact investing. Through our work, we have come to identify a set of key factors that will influence the quality of your systems analysis: * **Clear system boundaries and transformative intent:** The boundaries of your system/challenge constellation and the scope of your transformational intent are the main guardrails for the systems analysis process, and even these can be in flux and might need revisiting as the analysis proceeds and you learn more about the context of your work. See previous chapters for more detail about [system boundaries](/systemic-investing-practice-guide/part-1-program-design-and-development/systems-orientation/system-boundaries.md) and [transformational intent](/systemic-investing-practice-guide/part-1-program-design-and-development/systems-orientation/transformational-intent-setting.md). * **Familiarity with and access into the system:** Systems analysis requires both depth and breadth. Personal experience and domain expertise will ease the process, but more important is having access to stakeholders in the system. Strategic partnerships as part of an overarching change coalition are therefore critical. Also, bear in mind that different stakeholders see the same system in different ways, so at the minimum you will need a diversity of perspectives represented in the process (or, ideally, work with multiple maps that represent different viewpoints). * **Mapping expertise:** While mapping is not rocket science, having some experience nevertheless helps in both designing and working through the process. It might be worth partnering with organizations specialized in systems analytics for this part of the systemic investing journey. * **Pre-existing analyses:** If and where you can, consider building on existing work. While every system is unique, many underlying dynamics (especially in thematically related systems) are shared across systems, and chances are someone has already done some of the research work in your specific context or a related one. So it’s always worth checking out existing system analyses. That said, the *output* of systems analysis is only half the reason to do it; the other is the opportunity to engage stakeholders in the process to generate a sense of co-ownership and secure buy-in. So you will always have to do some of this work yourself. And of course there are also other factors relating to operational realities (like budget and time restrictions) that shape the design of this phase. It’s worth noting, however, that advances in artificial intelligence hold significant potential to speed up parts of the process. The intersection of AI and systems mapping presents an exciting space to watch over the coming months and years. #### Research How to get started on gathering data? Which frameworks can help to unearth relevant insights? How to work with stakeholders in the system? And how to manage information throughout the process? [Research](/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis/research.md) #### Mapping the system How to make sense of the gathered data? In what ways can system mapping be useful to the systems analysis process? And how to tailor the mapping process to the context of systemic investing? [Systems Mapping](/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis/systems-mapping.md) #### Identifying leverage points How to identify places in complex systems where a small shift creates ripple effects throughout the entire system? [Leverage Point Identification](/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis/leverage-point-identification.md) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://transcap-initiative.gitbook.io/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.