Step 2: System Mapping

Where This Fits

This is the second step of the SiD five-step method (Goals and Indicators, System Mapping, System Understanding, Solutioning and Roadmapping, Evaluate and Iterate). In Step 1 you set your destination. Now you need to see the terrain. System mapping is how you build that picture.

What System Mapping Does

In this step, we analyze the system by charting its objects, constructing the network of relationships between them, and establishing what the system looks like in space, how it behaves in time, and what it affects. From these maps, we can derive insight into possible improved states and solutions.

System mapping is one of the fundamental tools of SiD. It serves three purposes at once: understanding systems, working to improve them, and communicating them to others.

Why Maps?

Mapping has been with us as long as human history. A map is a graphical representation of information. The first world maps changed the course of civilization. System maps do the same thing, except they map more than geography. They map relations in time, movement, and the flow of resources.

When properly executed, a good system map hands you solutions on a plate, simply through the insight it provides. Just as being lost in a city becomes immediately solvable when you pull out a city map, system maps reveal pathways that were invisible before. The same map may suggest different routes depending on different destinations.

People handle large amounts of data better visually than in text. In visual formats, more correlations and insights emerge, and a clearer oversight of complex issues becomes possible. When done right, system maps reveal both root causes and solution pathways. They function as strategic strongholds for years, create unified understanding across teams, enable stakeholder participation, and become powerful planning tools.

System mapping is therefore a worthwhile investment, both as a learning experience for the team and as a strategic asset for the organization.

What Is a System Map?

A system map organizes data from the real world in a way that reveals underlying order or pattern, to determine the nature or behavior of a system. Maps are usually visual, but can also be lists or spreadsheets. System maps rarely come alone. To map a system, you need multiple perspectives and scales, which means making sets of interrelated maps.

Maps exist in three dimensions:

• Space (geographical, physical layout)
• Time (historical trends, cycles, projections)
• Context (relationships, flows, causes and effects)

Examples: A geographical map of a neighborhood's available energy sources is a space-based system map. A graph of the times you enter and leave your house is a time-based map. A flowchart of an organization's legal structure, the causal relationships between a tax policy and a senior citizen's income, or the evolutionary family tree of a badger: all context maps.

A typical SiD system map shows multiple relevant parameters at once. When mapping energy and material flows in relation to economic gains, you represent the information so that new insights emerge, both from the resulting map and from the mapping process itself.

What Makes a Good System Map?

A good system map:

• Reveals important connections or disconnections
• Is readable (not so complex it becomes impenetrable)
• Does not oversimplify reality to the point of being misleading
• Can be easily augmented and adjusted
• Is visually clear and appealing
• Is part of a larger organizing system where multiple maps form a complete overview together

Start with a Sketch

System mapping begins on paper. In the first iterations, work at sketch level to figure out what you are dealing with. In later iterations, find the form and layout that works best. Often, the sketches themselves provide all the insight you need. In some cases, they can be elaborated and redesigned in several steps, with new research in between. In some cases, you advance to computer models or polished illustrations.

Computer visualizations allow dynamic system maps and maps based on large data sets. You can embed the time dimension in space or context maps and watch patterns emerge. The Gapminder project (www.gapminder.org) is an excellent example of dynamically mapping global statistical data across time, space, and context.

For large projects or organizations, specialist tools for big-data analysis or agent-based modeling can be powerful, but they require technical expertise beyond the scope of this guide.

Managing Complexity

The purpose of mapping is never completeness. Complex systems have too many components to map exhaustively. The purpose is to reach an understanding of the system, taking into account as many aspects as possible without being overwhelmed.

We manage complexity by simplifying maps at higher levels of abstraction, making them rougher and less detailed. But here is the critical point: do not simplify by restricting the categories you map. Do not map only energy flows or only economic relations. Make sure you cover all dimensions, scales, and aspects (as covered in the ELSI-8 framework: Energy, Land use, Materials, Ecosystems, Species, Culture, Economy, Health and Happiness).

This is not for the sake of completeness. It is for the sake of range and depth. If you miss important aspects, the solutions you develop later will not create the sustainable state you had in mind.

Limit resolution and depth, not scope.

How to Make a System Map

Getting Started

Mapping usually begins with a diverse team, large sheets of paper, a healthy dose of energy, and plenty of time to explore different approaches. After the initial session, maps may be refined with software, new data researched, graphic layout polished, or mathematical models built to simulate the system.

When facing a new, unmapped system:

1. Decide what maps to make
2. Map the objects in the system
3. Map the relations between those objects
4. Look at (and perhaps map) the behavior of the system itself

Understanding may arise simply from mapping the objects and the network. Remember: the process of mapping itself is often what brings insight. Some system maps are illegible to anyone who did not make them, but for those who did, they were the key that unlocked a particular aspect of the system and led to a solution.

Step 1: Determine Subject and Goal

What is the objective of the mapping? Are you making maps to figure out a strategy for improving the system, to find a specific relationship, or to create general awareness? What will you be mapping: a neighborhood, a person, an organization, the influence of a policy decision?

Step 2: Determine What Maps to Make

You will likely make at least three maps, probably more. For them to relate to one another, you need a framework so they speak the same language.

One of the best ways to start is with a map of maps. You need to map in at least three dimensions (space, time, context) and at three scales (small, medium, large). Make a quick grid with two vertical and two horizontal lines, creating nine areas. Fill in each area with the subject and map type you think you can create for your challenge.

Space Maps. We are all familiar with city maps and floor plans. But space can be mapped in many ways. It does not have to be geographical or uniform. Make sure to list maps at different scales: surroundings, city, region, country.

Time Maps. We know these as graphs and timelines. Typical scales include daily, weekly, monthly, yearly, decade, and century. We usually do not map beyond 50 years into the past and future (we are a shortsighted species), but if you do, the results are often fascinating.

Context Maps. These can be the most confusing map type and simultaneously the most powerful. Context maps have no fixed meaning for their axes, so they can show relationships that space and time maps cannot. Simple examples: a shopping list, a budget spreadsheet. More advanced examples: causal loop maps, connectivity diagrams, material and energy flow diagrams. Different scales can represent different levels of connectivity, for example, the chain of connected stakeholders in a supply chain.

For content, use ELSI-8 as a starting point. Fill the categories with areas of interest, gather data, map them individually, and expand from there. ELSI-8 serves as an index to determine what data to map and to ensure a broad spectrum of analysis.

Then consider:

• What type of maps will you use for each dimension? (Causal loop diagrams for context? Agent-relation maps?)
• How many scale steps? (For the time dimension: a 50-year span, or a single day?)
• What subjects or data go on which map? (A basic set of ELSI indicators, an extended set, or a different set of relationships?)
• In what way will you make the maps? (Workshop format, or individual experts creating separate maps and then combining them?)

Step 3: Sketch the Maps and Collect Data

With your map of maps in hand, start sketching. In the first iteration, just see if you can sketch what you want a map to look like. This informs you of what data you need and what insights you expect. Do not dive too deeply into one map. Sketch them all roughly first and work on all areas evenly. You will make more coherent and communicative maps this way.

If certain map types do not work, that is fine. Adjust the framework and repeat until you have maps that serve the goals you set.

Data collection can be time-consuming. To narrow the effort, make sketch maps first, document data needs along the way, and then focus data research on the areas of interest.

Step 4: Select and Refine

After making a range of sketches, select the most interesting ones. See if you can merge maps on the same dimension (for example, combining geographical maps of different subjects or putting information on a single timeline). Research missing information. Redraw.

When you are happy with the framework, map types, and data, finalize all maps. Have a subject-matter expert add details and a designer polish the representation. Involve stakeholders for final evaluation and additional insights.

What Next?

The maps should be revealing opportunities and patterns. If they are not, re-iterate the process and consider setting new goals.

Once you have mapped the current state, you will map the desired state later in the solution cycle. Using the same framework, map the system as you would like it to be: resilient, harmonious, and autonomous (RAH) to the degrees necessary. Use these future projections as discussion points or as tools for finding pathways to improved performance.

Takeaway: System mapping translates complexity into shared visual understanding. Start with context maps, add detail through network and process maps, and project future states using RAH indicators. This unit continues in "Step 2: System Mapping (Part 2)" with standard map types and practical mapping techniques.