When software assumptions become strengths
Assumptions are the invisible friction in software development: When left undetected, they can bring projects to a complete halt. This article reveals why 80% of failed projects stem from incorrect hypotheses, and how structured assumption management helps you minimize risks while driving innovation. Discover how industry leaders use documented assumption logs and lean validation to transform hypothetical pitfalls into strategic advantages. Learn why even seemingly harmless assumptions about user names have caused entire systems to collapse and how you can make your teams resilient.
#Project Management#Software DevelopmentThe Invisible Threat
Assumptions are the invisible code in every software development project: Often implicit, rarely questioned, but always decisive for success or failure. This section reveals why even experienced teams fall into the "assumption trap."
Imagine this scenario: An experienced development team spends months working on an international e-commerce platform. Everything runs perfectly until go-live. Then comes the harsh reality: The system crashes as soon as customers with Chinese or Arabic names try to register. The reason? A simple assumption: "All usernames can be ASCII-encoded." This single false belief costs the company both revenue and reputation. [4]
- The Assumption Paradox: The more experienced the team, the greater the risk
It sounds absurd, but it's true. The best development teams are the ones that most often fall into the assumption trap. While beginners question every step, professionals rely on their experience. This routine becomes a weakness.
- The figures speak for themselves
The Carnegie Mellon Software Engineering Institute analyzed over 2,500 software projects. The result is sobering: Forty-three percent of all critical software errors are caused by undocumented assumptions. Even more alarming, teams with more than five years of joint project experience make 60 percent more implicit assumptions than newly formed groups. [1]
- Why experience becomes a trap
Experienced teams develop mental shortcuts. They deliberately skip discussions about "obvious" aspects. For example, a senior developer may no longer explain why he makes certain design decisions. A project manager does not document assumptions about the infrastructure. This efficiency becomes problematic when the framework conditions change. [3][11]
- The complexity dilemma
The more demanding a project becomes, the more assumptions teams make. For a simple CRUD system, there may be 20 critical assumptions. For an enterprise solution with a microservices architecture, there may be over 200. Each one carries potential risk. [3]
- The hidden vicious circle
The insidious thing about assumptions is that they reinforce themselves. For example, a team might make a wrong assumption about the user interface. All subsequent design decisions are based on this initial assumption. With each iteration, it becomes more difficult to correct the original assumption. Ultimately, fixing the mistake costs many times more than the original implementation.
Relevant research and studies
- Software Engineering Institute
The Carnegie Mellon SEI conducts research for public authorities and industry. This dual role provides access to real project data and makes the research relevant to practice. The SEI identified assumptions as a major cause of project failures and showed that undocumented assumptions lead to significant cost increases.
- IEEE Computer Society
The IEEE Computer Society is the world's largest organization for computer professionals and the leading authority on software engineering. Their research shows that 60-70% of all software projects are affected by inaccurate or incorrect assumptions. Assumptions about user behavior, performance and integration are particularly critical.
- Standish Group Chaos Report
The Standish Group's Chaos Report is an influential long-term study in IT project management. Since 1994, the study has analyzed the success rates of software projects every two years. It has repeatedly documented that incorrect assumptions are among the top 5 reasons for project failures.
Psychological aspects
- Confirmation Bias
Development teams tend to favor information that confirms their existing assumptions.
- Anchoring Effect
Early assumptions in the project are often used as an "anchor" for all further decisions, even if they turn out to be wrong.
- Dunning-Kruger effect
Less experienced team members overestimate their ability to make correct assumptions.
The solution is not to make fewer assumptions. That is impossible. Instead, teams must learn to consciously make their assumptions and systematically validate them. This is the only way to turn experience from a risk factor back into an advantage.
The taxonomy of assumptions: Ten critical categories and their pitfalls
Not all assumptions are equally dangerous. While some assumptions remain harmless planning aids, others can cause entire projects to collapse. The systematic categorization of assumptions helps teams to identify their most critical weak points and address them in a targeted manner.
- 1. Technical assumptions: When compatibility becomes an illusion
The danger: Teams assume that different systems, APIs or technologies will work together without any problems, without testing this in advance. [8][15]
Why it happens: Developers rely on documentation and theoretical compatibility promises without creating proof-of-concepts. The assumption that "API is API" underestimates the complexity of real system integration.- 2. Operational assumptions: The infrastructure lie
The danger: Teams assume stable operating conditions without considering the real environments. [5][7]
Why it happens: Development teams usually work in privileged environments with perfect infrastructure and mistakenly transfer these conditions to all users.- 3. Data assumptions: When small numbers cause big problems
The danger: Incorrect assumptions about data volume, format or quality lead to system failures. [1][4]
Why it happens: Data volumes grow exponentially, but assumptions remain linear. Teams systematically underestimate how usage behavior changes over time.- 4. Process assumptions: The fallacy of plannable people
The danger: Teams assume that human processes are predictable and controllable. [10][13]
Why it happens: Software development is predictable, people are not. Teams confuse technical processes with social dynamics.- 5. Environmental assumptions: When the market doesn't play ball
The danger: External factors are assumed to be constant, even though they are constantly changing. [5][11]
Why it happens: Teams focus on technical development and forget that the environment changes faster than software is developed.- 6. Resource assumptions: The expert problem
The danger: Critical human resources are assumed to be available without developing backup plans. [7]
Why it happens: Knowledge carriers are underestimated, knowledge documentation is neglected. Teams treat people like interchangeable resources.- 7. Legacy traps: The Time Travel Illusion
The danger: Assumptions about outdated systems are based on information that is long out of date. [3]
Why it happens: Legacy systems change through patches, workarounds and environment changes without being documented. Teams work with outdated assumptions.- 8. Cultural assumptions: False generalization
The danger: Design and functional decisions are based on developers' cultural assumptions. [4][8]
Why it happens: Developers unconsciously project their own cultural norms onto all users.- 9. Temporal assumptions: The planning illusion
The danger: Time estimates are based on ideal cases without taking interruptions into account. [7][9]
Why it happens: People estimate pure working time, but forget about coordination, interruptions and unforeseen problems.- 10. Complexity traps: The modularity myth
The danger: Systems are assumed to be less complex than they actually are. [1][3]
Why it happens: Mature systems develop hidden dependencies that don't show up in documentation. Teams systematically underestimate the networking of their components.
From recognition to action
Categorizing assumptions is only the first step. Systematic validation is crucial: technical assumptions through prototypes, operational assumptions through stress tests, cultural assumptions through user research. Teams that consciously categorize and question their assumptions in a targeted manner transform potentially hidden risks into manageable challenges.
The Assumption Log: From Hidden Problems to Controllable Factors
An assumption protocol transforms a central weakness in software development into a strategic advantage. Instead of allowing assumptions to remain hidden, it makes them visible, measurable and controllable. But how does this tool work in practice?
Structure of professional assumption documentation
An effective assumption log follows a clear structure. These eight core areas form the backbone of systematic assumption management:
- Unique ID
Each acceptance receives a reference number for seamless tracking. "ASM-2025-001" is more precise than "the database thing". This system enables traceable discussions and prevents assumptions from disappearing in email chains.
- Category
Technical, operational, legal or resource assumptions require different validation strategies. A cloud compliance expert can check legal assumptions, whereas a DevOps engineer can check technical assumptions.
- Precise description
"The system is stable" is useless. "The API processes a maximum of 1,000 requests per second without any loss of performance" is validatable. Concrete formulations enable real verification.
- Impact analysis
What happens if this assumption is wrong? IF-THEN statements make risks tangible: "IF the General Data Protection Regulation is interpreted differently in region X, THEN the launch will be delayed by 6 months".
- Validation date
By when must there be clarity? Fixed deadlines force a review and prevent the postponement of critical decisions.
- Current status
Open, under review, confirmed, refuted or obsolete. Clear status information shows at a glance where action is required.
- Person responsible
Every acceptance needs a responsible person. Clear responsibilities prevent important validations from disappearing into team irresponsibility.
- Concrete measures
What is being done to check acceptance? "Proof of concept by Friday" is a plan. "Think about it again" is not one.
Prioritization Matrix: Math versus gut feeling.
Not all assumptions are equally critical. The risk formula probability × impact brings objectivity to the assessment. Both factors are rated on a scale of 1 to 10:
- Probability scale
- 1-2: Very unlikely (less than 20% chance)
- 3-4: Unlikely (20-40% chance)
- 5-6: Possible (40-60% chance)
- 7-8: Probable (60-80% chance)
- 9-10: Very likely (over 80% chance)
- Impact rating
- 1-2: Minimal impact (small delays)
- 3-4: Low impact (budget overrun of less than 10%)
- 5-6: Medium impact (delays of several weeks)
- 7-8: High impact (project rescheduling required)
- 9-10: Critical impact (project at risk)
Example from practice: Assumption "Cloud provider complies with GDPR requirements in all EU countries" receives probability 6 (quite possible that there are differences in interpretation) and impact 9 (legal problems jeopardize the entire project). Risk score: 54. This assumption immediately belongs on the top priority list.
Life Cycle: From birth to death.
Assumptions go through a structured life cycle:
- Phase 1: Identification (project start)
Teams systematically collect all assumptions. Brainstorming sessions uncover hidden assumptions. Questioning techniques such as "What would have to be right for our plan to work?" promote awareness.
- Phase 2: Documentation (planning phase)
All assumptions end up structured in the protocol. Completeness is more important than perfection. Better 50 documented assumptions than 10 perfectly formulated ones.
- Phase 3: Prioritization (before implementation)
The risk matrix determines the sequence. High-impact assumptions are validated first, even if they are more difficult to test.
- Phase 4: Validation (development phase)
Concrete tests, experiments or research clarify the facts. Proof-of-concepts are often more meaningful than theoretical analyses.
- Phase 5: Monitoring (operational phase)
Confirmed assumptions may change. Regular reviews check whether the fundamentals are still correct.
- Phase 6: Post-mortem (end of project)
Which assumptions turned out to be wrong? What should have been validated earlier? Learning for future projects closes the circle.
Fictitious Example: Cloud Migration and Compliance Pitfalls
Project context: A German fintech migrates its core banking systems to the AWS cloud in order to open up international markets.
Critical assumption: "AWS services fulfill banking compliance requirements identically in all target countries (Germany, France, Poland)."
- Assumption log entry
- ID: ASM-2025-007
- Category: Legal/Compliance
- Description: AWS cloud services (EC2, RDS, S3) fulfill banking compliance for DE, FR, PL without additional measures
- Impact: IF there are compliance differences, THEN the launch will be delayed by 3-6 months due to additional certifications
- Validation date: 15.03.2025
- Status: Under review
- Person responsible: Dr. Sarah Müller (Compliance Officer)
- Measures: Legal advice in all three countries, check AWS compliance documentation
Validation result: The audit reveals that Poland has a more restrictive interpretation of data localization for bank data. Additional measures (local encryption, national backup locations) are required. Early detection prevents expensive rework after launch.
From Theory to Transformation
The assumption log is more than just a documentation tool. It changes the culture of questioning in development teams. Instead of hiding assumptions, it makes them a topic of conversation. Instead of ignoring risks, it turns them into manageable tasks.
Teams that systematically use assumption logs report fewer surprises, clearer decisions and more robust systems. The tool takes time to implement, but saves weeks in troubleshooting.
The question is not whether your team has assumptions. The question is: Will you master them before they master you?
Do you want to make the assumptions in your project manageable? We can support you!
Sprechen Sie uns gerne an.Implementation in a Team: How to Make Assumption Management Routine
The best theory is useless if it isn't implemented in everyday team life. Assumption management does not fail because of the complexity of the methods, but because of the implementation in the team. There are three factors that determine success or failure: functioning team dynamics, clear roles, and comprehensible visualization.
Team dynamics: the Monday effect
It's clear that after the initial enthusiasm, assumption management becomes a major issue in projects, bogged down by stress. Excel lists remain unupdated, important assumptions are clarified in hallway conversations, and after three weeks everything is back to normal.
- The 30-minute revolution
Successful teams make assumption reviews a fixed Monday appointment. This is not an additional burden; it is a replacement for unstructured status meetings. The agenda is clear:
- Status check
First 15 min: "What assumptions have we clarified since last week?" Each participant reports briefly on validated or refuted assumptions. No discussions, just facts. This discipline creates progress and momentum.
- New findings
Next 10 minutes: "What new assumptions have emerged?" Teams discover new assumptions every day, often unconsciously. The structured collection prevents critical points from being overlooked.
- Escalation
Last 5 minutes: "What needs immediate attention?" Some assumptions require external expertise or management decisions. Early escalation prevents blockages.
- Change of perspective
Every team needs an official skeptic. Not the eternal grumbler, but a constructive questioner. This role rotates between the team members every three months and brings fresh perspectives.
Practical implementation: The current "Devil's Advocate" asks uncomfortable questions in every review. "What if our main assumption is completely wrong?" or "How would a competitor attack our system?" This method uncovers blind spots before they become problems.
- Creating psychological security
Admitting assumptions requires courage. Teams must learn that documented uncertainty is more professional than hidden assumptions. Managers set the tone by talking openly about their assumptions themselves.
A successful team leader may start a meeting with: "My assumption for this week was wrong. I thought the API integration would take two days, but we need a whole week. What can we learn from this?" This openness normalizes the topic and encourages others to be transparent.
Clarifying roles: Who does what?
Confusion over responsibilities is the most common reason for failed assumption management initiatives. If everyone is responsible, no one is responsible.
- Product owner is the Assumption Guardian.
The main responsibility lies with the product owner, not the project manager. There are strategic reasons for this decision:
- Technical proximity: Product owners understand the business logic behind technical decisions. They can assess which assumptions are critical for product success and which are negligible.
- Stakeholder access: Many assumptions can only be validated by external sources. Product owners have direct contact with customers, specialist departments and decision-makers. These connections are essential for effective validation.
- Long-term focus: Project managers think in terms of sprints and deadlines. Product owners keep an eye on the product vision and can evaluate assumptions beyond the current release cycle.
- Project managers are process supporters.
Project managers provide operational support without assuming responsibility. Their tasks include:
- Tool integration: ensuring assumptions logs are correctly configured in Jira, Asana or other systems.
- Deadline monitoring: Reminders before validation deadlines and escalation in case of delays.
- Process compliance: Checking that new assumptions are documented and categorized.
- Developers are assumption detectives.
Developers identify technical assumptions during implementation. They are closer to the code than product owners and discover hidden assumptions about APIs, performance or compatibility.
Practical example: A developer realizes that the selected JSON parser fails with files over 10 MB. This finding is immediately documented as a new assumption: "Input data never exceeds 10 MB." The product owner decides on the priority of validation.
- Departments are the validation partners
Domain experts from the specialist departments validate business assumptions. A compliance officer checks legal assumptions, a UX designer questions user behavior assumptions.
The clear allocation of roles prevents conflicts of responsibility and ensures efficient validation by the most competent persons in each case.
Visualization makes complexity manageable
Lists of 50 assumptions overwhelm every stakeholder. Successful teams translate their assumption protocols into visual language that even non-technical people understand.
- Risk heat maps: Here's the overview.
Two-dimensional representation makes risks immediately comprehensible. The X-axis shows the potential impact (1-10), the Y-axis the probability of occurrence (1-10). Each assumption appears as a color-coded point:
- 🟢 Green (scores 1-30): Low risk, routine monitoring
- 🟡 Yellow (scores 31-70): Medium risks, regular validation required
- 🔴 Red (Scores 71-100): High risks, immediate attention required
- Status dashboards for everyday project work
Development teams need operational overviews. A simple dashboard shows the most important key figures:
A simple table as a dashboard with the most important key figures- Management communication requires executive summaries
Managers need summaries, not details. A concise report focuses on three key statements:
- Current status: "We manage 49 project assumptions. 4 are in the critical risk area."
- Trend development: "In the last two weeks, 6 assumptions have been refuted and 11 confirmed. The risk distribution is improving."
- Need for action: "3 assumptions require management decisions by the end of the week."
- Use these interactive tools in team workshops
Digital whiteboards such as Miro or Figma are ideal for assumption mapping sessions. Teams visualize dependencies between assumptions and identify clusters with high risk potential.
Workshop format: Each assumption is presented as a post-it. Teams group related assumptions and draw in dependencies. This visual work often reveals connections that remain invisible in list form.
From introduction to established practice
Acceptance management only works if it fits seamlessly into established working practices. Separate tools and additional meetings fail due to the reality of overloaded teams.
Our recommended intermediate steps:
- Agile integration
- Tool integration
- Performance measurement
- Continuous improvement
Integrate this into your existing processes. We will help you become an assumption-aware organization.
Sprechen Sie uns gerne an.Further information
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- References
- Lewis, G.A. (2004). Assumptions Management in Software Development. Carnegie Mellon University. CMU/SEI-2004-TN-021
https://insights.sei.cmu.edu/documents/2049/2004_004_001_14327.pdf - Minepla (2023). The curse of software development; "Assumptions".
https://www.minepla.net/2023/01/the-curse-of-software-development-assumptions/ - Programmer's Paradox (2025). Assumptions.
http://theprogrammersparadox.blogspot.com/2025/07/assumptions.html - Kalzumeus (2010). Falsehoods Programmers Believe About Names.
https://www.kalzumeus.com/2010/06/17/falsehoods-programmers-believe-about-names/ - BrightWork (2025). How to Manage Project Assumptions - Best Practices.
https://www.brightwork.com/blog/do-you-practice-assumption-management-with-your-projects - Project Management Knowledge (2017). Assumptions Log.
https://project-management-knowledge.com/definitions/a/assumptions-log/ - Deeprojectmanager (2023). The Role of Assumption Log in Project Management.
https://deeprojectmanager.com/assumption-log-in-project-management/ - QAT (2025). Writing Assumptions and Constraints in SRS: Best Practices.
https://qat.com/writing-assumptions-constraints-srs/ - MyPMP (2023). Assumption Log.
https://pmp-tools.com/2023/02/assumption-log-4.html - Rocketlane (2023). Your ultimate guide to project assumptions.
https://www.rocketlane.com/blogs/project-assumptions - The Lean Apps (2021). Assumptions kill products and burn your money.
https://www.theleanapps.com/assumptions-kill-products-and-burn-your-money/ - Strategyzer (2017). How To Test Your Idea: Start With The Most Critical Hypotheses.
https://www.strategyzer.com/library/how-to-test-your-idea-start-with-the-most-critical-hypotheses - UserTesting (2015). How to Implement the Lean Startup Method at Large Organizations.
https://www.usertesting.com/blog/how-to-implement-the-lean-startup-at-large-organizations
- Lewis, G.A. (2004). Assumptions Management in Software Development. Carnegie Mellon University. CMU/SEI-2004-TN-021
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