Researching Systems: Synthesizing Research
This article highlights lessons learned from the 2024 workshop with Tara Campbell, a Systemic Designer.
Table of Contents
Inductive Synthesis
Inductive synthesis follows a process articulated by John Koko, a design researcher. This process involves four key steps:
Externalizing your data – You will likely gather a large volume of information, which is too overwhelming to process mentally. It is essential to externalize this data by writing it down—either on paper, sticky notes, an online whiteboard (like Miro or MURAL), or a Google Document. The goal is to put everything in one place where you can visually assess and interact with it.
For example, if you have taken notes from different secondary sources or conducted several interviews, you can lay out all your notes and findings, possibly organizing them by source.Filtering and pruning – Once your data is externalized, it’s important to determine what is most relevant to your research. This step involves critically analyzing the information and filtering out data that is less significant to your understanding of the systemic challenge.
Identifying relationships and patterns – As you review your refined data, you will begin to see relationships between different pieces of information. Similar data points can be grouped together, and connections between them can be visualized. This may involve moving related pieces closer together or drawing lines between them to illustrate connections.
Theming and insight generation – Once you have grouped and connected related information, you can begin identifying emerging themes and insights. These themes can be labeled to reflect the patterns in the data, helping to create meaning from the organization process.
This is a high-level overview of inductive synthesis, and now I’d like to discuss deductive methods.
Deductive Synthesis
Deductive synthesis begins with an existing framework or set of categories, and data is organized within that structure. There are many frameworks available for structuring data. Here are a few I frequently use when analyzing systemic challenges:
Causal Layered Analysis (CLA) – This approach examines surface-level problems and events and then delves deeper into their systemic causes, underlying worldviews, and foundational myths or metaphors. It is similar to the iceberg model, which identifies visible issues at the surface while exploring the hidden forces beneath them.
Historical Scan – This approach involves organizing data chronologically to understand the factors that have contributed to a current issue. It helps contextualize systemic challenges by mapping past causes and previous solution attempts.
Three Horizons Framework – This framework views systems as evolving through three stages:
The first horizon represents the dominant system that may no longer be effective.
The third horizon represents the future system we want to move towards.
The second horizon represents the transition phase between the two.
Each of these frameworks serves as a tool for structuring and making sense of data. There are many other frameworks available, and I encourage you to explore them based on your research needs.
Additional Resources
If you're interested in learning more about systemic research methods, I recommend the book Design Journeys Through Complex Systems. It provides an in-depth look at various tools and frameworks for analyzing complex challenges. Additionally, The Student Guide to Mapping a System offers extensive resources on research methodologies, particularly expert interviews.
Key Research Tips
Here are a few final tips for conducting research and synthesis effectively:
Integrate primary and secondary research – Your findings will be much stronger if they combine insights from both desk research and first-person perspectives. However, you don’t necessarily need to conduct interviews yourself; you can use first-person perspectives found in news articles, academic studies, or other media.
Cite all secondary research – Any source you use, whether academic, media-based, or online content (e.g., YouTube videos, websites), should be cited. Choose a citation style and be consistent with it. Also, use in-text citations, not just a bibliography, to directly attribute information to sources.
Keep a research journal – Maintaining a research journal helps you track sources, quotes, and reflections. If working in a team, consider using an online tool like Google Docs or Miro for collaboration. It’s okay if your journal is messy—the process of research and synthesis is inherently iterative.
Embrace iteration – Don’t be afraid to create incomplete or imperfect maps. Mapping is a tool for externalizing your assumptions, which can then be validated and refined with feedback from teammates, advisors, or experts.
Maintain awareness of interrelationships, perspectives, and boundaries – When researching a system, consider the various relationships within it, the diversity of perspectives involved, and the boundaries of your research. These three elements are essential to a strong systemic analysis.
Q&A Session
Question 1: When selecting relevant information during synthesis, how do you check for biases in the filtering process?
That’s a great question. The first step is to acknowledge your own biases and positionality within the system. Often, researchers are stakeholders in the issues they study. A useful exercise is to map your own position within the system and consider the privileges or assumptions you bring.
Additionally, using frameworks like STEEPV (which categorizes sources by Social, Technological, Economic, Environmental, Political, and Values-based dimensions) can help ensure diversity in your sources. If you notice your sources are concentrated in one area (e.g., only academic research), consider seeking alternative perspectives.
Follow-up Question: Would it be useful to include yourself in the stakeholder map to reflect positionality?
Yes, absolutely! Many researchers include their perspective in the introduction of their research paper, discussing why they are interested in the topic and the context they bring. Every map is inherently biased, so acknowledging your perspective upfront is a valuable practice.
Question 2: Do we need ethical clearance for primary research, particularly interviews?
It depends on your academic institution. Generally, if you are conducting research affiliated with a university, ethical approval is required for interviews that involve vulnerable populations. However, expert interviews (e.g., speaking with professionals in the field) typically do not require ethical clearance. If in doubt, check with your institution's research ethics office.
Question 3: If we want to expand our project beyond Map the System, are there any intellectual property rights we should be aware of?
Yes, you retain the right to continue your research. If your submission is published on Map the System’s website, any further work should be expanded or built upon rather than directly replicated.
