Assumption mapping: Systematically minimize risks

• An assumption map visualizes assumptions using the axes “importance” and “existing evidence”
• The goal is to prioritize and validate risky assumptions through targeted experiments
• A culture of experimentation promotes rapid prototyping, hypothesis testing, and continuous learning (e.g. design thinking, lean startup)
• Assumption mapping helps to identify uncertainties, minimizes risks, and supports informed decision-making
• Promotes collaboration, clear data collection, and prioritization through workshops with interdisciplinary teams

Assumption mapping systematically identifies, categorizes, and prioritizes unsecured assumptions. This method allows you to filter out the riskiest assumptions for immediate testing and validation.

An assumption map visually categorizes assumptions on two axes: "Importance" and "Existing evidence." The "Importance" axis shows how central an assumption is to a project’s success, while the "Existing evidence" axis indicates the level of existing research or data for that hypothesis.

Instead of relying solely on long-term planning cycles, successful companies foster a culture of experimentation, enabling rapid decisions based on well-founded hypotheses. They embrace curiosity and openness, actively seeking new ideas and perspectives.

Through experimentation, they challenge assumptions, test hypotheses, and embrace learning from mistakes. This allows flexibility and quick adaptation to change without losing sight of strategic goals. Rather than pursuing a perfect solution for months, they rely on quick prototypes that are continuously tested and refined.

One example of this approach is design thinking, which promotes understanding problems from the customer's perspective and creating solutions that truly meet their needs. Prototypes are developed, tested, and refined in iterative cycles, with continuous user feedback ensuring solutions are practical and relevant.

Uncertain assumptions are based on speculative or incomplete information, presumptions, or unproven statements. When companies make decisions based on such assumptions, costly errors can quickly arise.

For instance, imagine assuming that a new product feature will excite users, prompting immediate development. If the feature fails to engage users after launch, resources and time are wasted. Assumption mapping helps to reveal these uncertainties early, allowing targeted assumption testing to avoid costly mistakes and resource misdirection.

If a service or business idea is founded on uncertain assumptions, unexpected and undesirable outcomes often follow.

Conversely, a safe assumption is based on solid data, knowledge, or widely accepted principles. Such assumptions carry a low risk of being proven wrong. Quantitative (measurable) data and observational data best support these assumptions.

Minimize risks – and make informed decisions

Especially in dynamic fields like service design, identifying and mitigating risks early is essential. Journey maps often reveal knowledge gaps, which can be systematically addressed. This is where assumption mapping proves invaluable. Known in product design, this method structures uncertain assumptions to reduce uncertainties and enable informed decision-making.

This visual mapping technique helps to quickly identify unsafe assumptions, particularly those that are important yet lack strong supporting evidence. These high-uncertainty assumptions require immediate testing. By conducting targeted experiments, you can validate these assumptions, reduce risks, and clarify uncertain factors.

Assumption maps are usually created during a moderated workshop, where assumptions are visually displayed and prioritized. This approach highlights the assumptions that need prompt investigation to reduce uncertainties and reveal potential project risks early on.

Assumption mapping provides a structured approach to identifying and minimizing strategic uncertainties, adding clarity and efficiency to your decision-making which helps you avoid costly mistakes

• Risk reduction: Systematically collecting and categorizing assumptions allows early risk identification and mitigation.
• Collaboration enhancement: Engaging relevant stakeholders builds a shared understanding of upcoming challenges.
• Efficient data collection: Drawing on various departments’ expertise leads to precise assumption and hypothesis formulation.
• Clarity and prioritization: Joint assessments clearly prioritize essential assumptions for focused further development.

Priming your team to be thinking about the same important questions in the same words will lead to better collaboration and more insights in a shorter amount of time. Also, it's a good way to increase comfort with admitting ignorance.

Erika Hall, Founder of Mule Design and Author of “Just enough Research”

For a successful assumption mapping workshop, gather participants from various departments. An ideal team includes product managers, marketing experts, UX designers, and executives. This interdisciplinary collaboration helps the workshop reach its full potential.

Ideally, invite 4 to 6 participants (excluding the moderator). If user research exists, bring the findings along. The workshop output will be a comprehensive assumption map.

The objectives should be clearly communicated to the participants in advance. Possible goals could be:

• Project kick-off: All team members are aligned on a data-driven strategy to implement the project efficiently.
• Assumption collection: Ideas and hypotheses are developed, discussed and prioritized.
• Knowledge and vision sharing: Team members’ perspectives are aligned to find a common direction.
• Generating research objectives: Goals are derived from collective knowledge, not hierarchical decisions.
• Business model canvas: Input is collected to fill in the canvas with verified data.

How does an assumption mapping workshop work?

A structured approach maximizes the impact of your assumption mapping workshop. This process systematically identifies and validates assumptions, from preparation to prioritization along the categories "Desirable," "Expandable," and "Feasible."

Two time management tips:

1. If possible, plan a break every 1.5 hours to maintain concentration.
2. Depending on the size of the group, you can skip the individual brainstorming process and jump straight into the group discussion.

Deep dive: Detailed analysis of assumptions and hypotheses

Focus particularly on "Desirable" post-its from step 3, as they pose the most significant risks. Break down solutions into specific assumptions and represent them visually in a tree diagram.

The main assumption is at the top, followed by detailed sub-assumptions. Clear assumptions enable specific hypotheses, each tested individually. Use a separate solution tree for each new function or feature.

The follow-up

• Formulate hypotheses for the uncertain assumptions.
• Plan experiments to validate these hypotheses.
• New assumptions arising from experiments should be placed on the assumption map.
• Tip: Keep a change log to inform stakeholders regularly.
• Add ongoing assumptions to a Kanban board to facilitate continuous testing.

Assign someone to oversee the assumption mapping process, ideally the journey mapping manager, to regularly integrate new findings every 3 to 5 months. This ongoing assessment keeps stakeholders informed and encourages continuous journey optimization. New assumptions and validated hypotheses should be shared to discuss progress and insights.

Curious? Copy our Miro template to create your own assumption mapping workshop.

To the Miro template