> For the complete documentation index, see [llms.txt](https://transcap-initiative.gitbook.io/systemic-investing-practice-guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://transcap-initiative.gitbook.io/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis/research.md). # Research ## Essence As in any process of inquiry, research stands at the outset of systems analysis and serves to generate raw data points. In the context of systemic investing, research is about harvesting a wide collection of information to gain a high-level and holistic view of the system of interest. > It should enable you to grasp the most important dynamics and identify the main stakeholders and actor groups that shape the system’s behavior. This means that you will need to start out broad and iteratively increase the level of depth and detail over time. Also, the work of systemic investing is fundamentally about solving complex societal problems. This means that the process of data gathering should be grounded on a plurality of perspectives and follow a participatory approach to ensure that different voices and viewpoints are represented in the analysis. ## Guidance ### 1. The Basics {% stepper %} {% step %} Scan the relevant **literature,** both published and peer-reviewed scientific literature as well as a variety of grey literature which may include everything from white papers and reports to keynotes and podcasts. Increasingly, AI tools like ChatGPT or Google’s Gemini Deep Research will help you identify and summarize relevant sources. {% endstep %} {% step %} Deepen your insights—and corroborate those found from your literature review—through **interviews** with system stakeholders. Curate a diverse group of interviewees, including both subject matter experts from domains that are relevant to the system as well as stakeholders who both shape the system and are impacted by its dynamics. Interviews also serve a secondary purpose: to build trustful relationships with people you may want to attract into your system transformation and investment coalition. {% endstep %} {% step %} Consider running **multi-stakeholder workshops** to generate novel and context-specific data and insights that require tapping the collective intelligence of a group, and to validate what your other research activities have surfaced. {% endstep %} {% endstepper %} When interviewing stakeholders with the intention to unearth information about the dynamics shaping a specific system, focus on identifying **enablers and blockers of system transformation**. This is best done by using [semi-structured interviews](https://en.wikipedia.org/wiki/Semi-structured_interview) with open-ended questions. For example, in our [prototype](https://transformation.capital/places/systemic-investing-meets-regenerative-agriculture) on regenerative agriculture in the American Midwest, we sought to identify the factors that both support and hinder the adoption of conservation agriculture practices. We used open-ended questions (e.g., “What enabling factors support farmers to adopt conservation practices?”) and also tested specific hypotheses about drivers of system behavior (e.g., “Do you believe policy, financial or market incentives would scale adoption of conservation practices?”). You can find a sample questionnaire that can be easily adapted to your specific system/challenge constellation in this [Miro](https://miro.com/app/board/uXjVIeqhgzM=/?share_link_id=758665765448) board. ### 2. Analytical Frameworks As part of your research, you should consider using a range of different frameworks to shape the kind of questions you’re exploring and making sense of the answers you will get. The more angles of inquiry you use, the richer the data you’ll collect. What follows is a list of frameworks from disciplines of systems thinking and systems innovation. Each has been designed with a different purpose, and as such will give you different lenses through which to study the system/challenge constellation you’re addressing. * [**Multi-Level Perspective**](https://www.cambridge.org/engage/coe/article-details/674dc3ed7be152b1d0aef5d8)**:** to understand how systemic change unfolds across different levels of society (niches, regimes, and landscapes) * [**Iceberg Model**](https://www.thinknpc.org/resource-hub/systems-practice-toolkit/the-iceberg-model/)**:** to distinguish between visible events, underlying patterns, systemic structures, and mental models, enabling you to differentiate between symptoms and root causes * [**Donella Meadows’ “Places to Intervene” Framework**](https://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/)**:** to differentiate different categories of drivers of a system’s behavior * [**Three Horizons**](https://www.h3uni.org/tutorial/three-horizons/)**:** to understand trends in a system as a function of time, that is, as short-term incremental improvements over the status quo (Horizon 1), emerging innovations (Horizon 2), and the desirable future state (Horizon 3) * [**Horizon Scanning**](https://www.futuresplatform.com/blog/horizon-scanning-and-vigilance)**:** to identify emerging trends, weak signals, and potential disruptions that could shape future systemic transitions, and to anticipate risks and opportunities before they become mainstream ### 3. Information Management Where to put all the information you gather during the research phase? The answer depends as much on best practice as it does on personal preference. Some people like working with lists and spreadsheets, others use online documents and presentations, still others prefer working in online whiteboards such as [Miro](https://miro.com/) or [Mural](https://www.mural.co/). At the TCI, we work extensively with online whiteboards for collective sensemaking and analysis of research data. The reason we like online whiteboards is that they offer a lot of creative freedom for how to record and make sense of information. You can add sticky notes, draw arrows and lines between them, and arrange them in a logical way. You can also upload files or paste screenshots from reports. Most importantly, you can invite others in your coalition to add or browse the content, and use the whiteboard for co-creative workshops. Below is an example of what a research and sensemaking canvas could look like, taken from the online whiteboard we use in our prototype on [Swiss food system transformation](https://transformation.capital/places/systemic-investing-in-swiss-food-system).

Excerpt from knowledge repository and sensemaking canvas on our Swiss food system prototype

## Example The work of [Regen Melbourne](https://www.regen.melbourne/) provides a great example for systemically-minded and participatory research designs. In one of their foundational pieces of work, they embarked on a 9-month community research process featuring workshops, interviews, and roundtable discussions to produce a [Melbourne Doughnut](https://doughnut.regen.melbourne/) based on the [Doughnut Economics](https://doughnuteconomics.org/about-doughnut-economics) framework. Their approach and methodology is detailed in the report “Towards a Regenerative Melbourne”.

Regen Melbourne’s participatory research design (from “Towards a Regenerative Melbourne”, 2021)

In terms of the specific use of different analytical frameworks, below is an example of how we made use of Three Horizons to understand the innovation landscape in the Swiss mobility system (as part of the research we conducted in the context of our [Net-Zero Mobility Switzerland](https://transformation.capital/places/systemic-investing-in-swiss-mobility) prototype). You can find the original version of this on this online [whiteboard](https://miro.com/app/board/uXjVIeqhgzM=/?share_link_id=929304384247).
And here is an example of how we used the Horizon Scanning framework to generate insights for the same project (the original version can be found [here](https://miro.com/app/board/uXjVIeqhgzM=/?share_link_id=929304384247)).
## Tips * Systems research is a bottomless pit—don’t fall victim to analysis paralysis. Also, be aware that systems constantly change, and what you might discover in your research today might be outdated tomorrow. So don’t dwell in research mode for too long; better to think of research as a journey rather than a destination, something you build into your long-term investment implementation strategy and revisit on an iterative basis rather than treating as a one-off activity. * A complex system is, by definition, characterized by uncertainty. There’s only so much you can actually *know* about it. So take all your research results with a grain of salt. * AI tools like ChatGPT or Gemini Deep Research are great for brainstorming and ideation, while interviews and workshops are great for validation and sensemaking. * Don’t underestimate the power of collective human intelligence. The most surprising and insightful moments often happen through dialogue and co-creation. ## Further Reading * **For an overview of participatory research approaches** and guidance on specific methods, refer to the [Handbook of Participatory Research and Inquiry](https://www.participatorymethods.org/handbook-of-participatory-research-and-inquiry/) (DATE) * **For a deep dive into the world of mixed method research**, refer to “[Innovation in Mixed Methods Research](https://uk.sagepub.com/sites/default/files/upm-assets/114915_book_item_114915.pdf)” by Cheryl N. Poth (2018) * **To gain an impression of the practical challenges** related to this type of research, check out our [blog post](https://transformation.capital/places/unlocking-system-access-and-the-need-for-collaboration-in-systemic-investing-2) on lessons learned around the issues of partner selection, research design and data capture from our Net-Zero Mobility Prototype in Switzerland * **For a comprehensive roundup of insights and tools around participatory methods**, check out the webpage of the [Nesta Centre for Collective Intelligence Design](https://www.nesta.org.uk/project/centre-collective-intelligence-design/) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://transcap-initiative.gitbook.io/systemic-investing-practice-guide/part-1-program-design-and-development/systems-analysis/research.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.