Quick Reference
Category | Law | Summary |
---|---|---|
Complexity, Context & Agile Foundations |
Adapted Stacey Matrix | Helps determine when Agile is appropriate based on problem complexity. |
Cynefin Framework | Provides dynamic sensemaking domains for decision-making under uncertainty. | |
Denning's Agile Laws | Frames Agile as a response to complex, adaptive challenges. | |
Occam's Razor | Encourages simplicity in system design and decision-making. | |
Agile Decision Heuristics & Mental Models |
Hick's Law | The more choices, the longer the decision time; design for simplicity. |
Simon's Satisficing Principle | People choose 'good enough' options in uncertain conditions. | |
Goodhart's Law | When a measure becomes a target, it ceases to be a good measure. | |
Sayre's Law | Conflicts in low-stakes environments are often the most intense. | |
Dude's Law | Value = Why ÷ How; prioritize purpose over process. | |
Learning & Adaptation Models |
Shu-Ha-Ri | Describes how people master practices through stages of learning. |
Double-Loop Learning | Challenges assumptions to support deeper reflection and lasting change. | |
Chesterton's Fence | Understand the purpose of a system before changing it. | |
OODA Loop | Adaptive decision cycle that enables teams to sense, reframe, decide, and act in uncertainty. | |
Boyd's Law of Iteration | Fast, repeated cycles enable learning and adaptability. | |
Lehman's Laws of Software Evolution | Software evolves continuously; change is inevitable. | |
Wirth's Law | Unchecked software grows bloated; reminds us to improve continuously. | |
Product Thinking & Customer Behavior |
Jobs-To-Be-Done Framework | Build what people truly need by understanding the job they're hiring your product to do. |
Law of 3 | People can remember only a few items at once; simplify communication. | |
Golden Circle | Inspires purpose-driven product thinking through why, how, and what. | |
Kano Model | Not all features create the same value; focus on delighters. | |
Pareto Principle (80/20 Rule) | Most results come from a small set of causes. | |
Fitts' Law | Time to target is a function of distance and size; important for UX. | |
Zeigarnik Effect | Unfinished tasks are remembered more; supports engagement strategies. | |
Law of Triviality (Bike Shed) | Teams focus on minor issues to avoid big decisions. | |
Lindy Effect | Long-lasting practices tend to endure longer. | |
Miller's Law | People can hold about 7±2 items in working memory. | |
Shalloway's Law of Requirements | If it can be misunderstood, it will be. | |
Krug's First Law of Usability | Don't make users think; simplicity rules. | |
Van Rest's Law | Simpler visuals are easier to remember and act on. | |
Agile Complexity & Uncertainty |
Ziv's Law | Requirements are never fully known until implementation begins. |
Gall's Law | Complex systems evolve best from simple ones; justifies MVPs. | |
1 in 60 Rule | Small early misalignments can cause major downstream drift. | |
Murphy's Law | What can go wrong, will go wrong. | |
Humphrey's Law | People behave differently when observed. | |
Weinberg's Law | Fixing a problem may introduce new ones. | |
Continuous Improvement |
Deming Wheel (PDCA) | Grounds improvement in an inspect-and-adapt loop. |
Shingo Model | Aligns principles, behavior, and systems to sustain cultural improvement. | |
Lean Thinking | Maximizes value and flow by eliminating waste and promoting learning. | |
Kaizen | Make small, continuous changes driven by the team. | |
Toyota Kata | Practice improvement routines to build a culture of learning. | |
Gemba Principle | Go to the source to see the real work and surface true problems. | |
DMAIC | Apply structured steps to define, measure, analyze, improve, and control processes. | |
Iterative Delivery & Flow |
Little's Law | Connects throughput, WIP, and cycle time; enables system design. |
Boehm's Curve | The cost of change increases the later it's made. | |
Kingman's Formula | Variability in demand or process increases wait times. | |
Ninety-Ninety Rule | The last 10% of work takes 90% of the effort. | |
Cognitive Biases & Decision-Making Pitfalls |
Bias Blind Spot | We see others' biases but not our own. |
Ladder of Inference | We act on assumptions and beliefs built from filtered observations. | |
Dunning-Kruger Effect | Inexperienced people often overestimate their ability. | |
Status Quo Bias | People prefer familiar patterns even when flawed. | |
Sunk Cost Fallacy | People continue bad plans due to past investment. | |
Dead Horse Theory | Satirizes stubborn adherence to failed practices. | |
Einstellung Effect | Past success can blind us to better solutions. | |
Law of the Instrument (Hammer) | Over-reliance on familiar tools. | |
Streetlight Effect | People search where it's easy, not where the answer is. | |
Hanlon's Razor | Never attribute to malice what can be explained by ignorance. | |
Icebergs of Ignorance | Important information is often trapped at lower levels. | |
Productivity & Estimation |
Parkinson's Law | Work expands to fill the time available. |
Hofstadter's Law | Everything takes longer than you think. | |
Triple Constraints | Only two of scope, time, and cost can be fixed, Agile favors fixed time and cost, letting scope flex. | |
Scotty Principle | Underpromise and overdeliver to appear heroic. | |
Systems Thinking & Organizational Complexity |
Theory of Constraints | Focus improvement on the system's constraint. |
Deming's System of Profound Knowledge | Understand systems, variation, learning, and psychology to lead effective change. | |
Deming's 14 Points for Management | Guides systemic improvement through leadership and quality focus. | |
Deming's 94/6 Principle | Most problems stem from the system, not the people. | |
Deming's 7 Deadly Diseases | Identifies management habits that hinder long-term performance. | |
Amdahl's Law | Optimizing a part doesn't always improve the whole. | |
Ashby's Law of Requisite Variety | To control complexity, you must match it. | |
Requisite Organization | Aligns role structure and decision authority with the complexity of work using time-span-based strata. | |
Second-Order Cybernetics | Observers are part of the system they seek to understand or change. | |
Wegner's Lemma | Interactive systems can't be fully specified. | |
Langdon's Lemma | Local optimization may harm global performance. | |
Kranzberg's First Law | Technology is never neutral; context matters. | |
Martec's Law | Technology changes faster than organizations adapt. | |
Shirky Principle | Systems preserve the problems they were designed to solve. | |
Prescott's Pickle Principle | Systems preserve dysfunction as well as value. | |
Organizational Change & Transformation Models |
Kotter's 8 Steps for Leading Change | Drives change through urgency, coalition, and vision. |
Kotter's XLR8 Framework | Accelerate strategic change without slowing down delivery. | |
ADKAR | Maps change into five actionable building blocks: Awareness to Reinforcement. | |
Roger's Diffusion of Innovations | Describes how innovations spread among users. | |
Change Handbook | Offers dozens of models and approaches for leading change. | |
Lewin's 3 Stage Theory of Change | Classic unfreeze-change-refreeze pattern. | |
Satir Change Model | Adds performance dynamics to team-level transitions. | |
Bridges' Transition Model | Emphasizes internal psychological transitions. | |
Kübler-Ross Change Curve | Charts emotional reactions during disruption. | |
Collaboration & Team Dynamics |
Prime Directive | Promotes safety and trust during team Retrospectives. |
Tuckman's Ladder | Teams evolve from forming to performing. | |
Five Dysfunctions of a Team | Highlights core breakdowns in team trust, conflict, and accountability. | |
Flexible Framework for Retrospectives | Outlines five elements for effective, adaptable Retrospectives. | |
2 Pizza Team Rule | Teams should be small enough to be fed with two pizzas. | |
Johari Window | Team awareness expands through feedback and disclosure. | |
Hackman's Law | Great team conditions matter more than individual talent. | |
Prisoner's Dilemma | People hesitate to collaborate when trust is low. | |
Pygmalion Effect | People rise to the level of expectations. | |
Maslow's Hierarchy of Needs | Shows how unmet needs block team growth and collaboration. | |
Agile Mindset Model | Defines agility through reflection, openness, and outcome focus. | |
Ringelmann Effect | People put in less effort in larger groups. | |
Dunbar's Number | There's a cognitive limit to stable relationships. | |
Brooks' Law | Adding people to a late project makes it later. | |
Communication Principles |
Grice's Maxims of Communication | Cooperative conversation follows clarity, relevance, and honesty. |
Law of Communication | Communication clarity degrades as messages pass through more intermediaries. | |
Postel's Law | Be conservative in what you send, liberal in what you accept. | |
Conway's Law | Teams design systems that mirror their communication structure. | |
Larman's Laws | Organizational behavior resists change in predictable ways. | |
Brandolini's Law | It takes more effort to refute misinformation than to create it. | |
Organizational Constraints & Bureaucracy |
Peter Principle | People rise to their level of incompetence in hierarchies. |
Putt's Law | Incompetent managers rise while competent people do the work. | |
Pournelle's Iron Law of Bureaucracy | Bureaucracies prioritize their survival over their mission. | |
Gresham's Law | Bad practices drive out good ones. | |
Moore's Law of Hiring | As you grow, average talent often declines. | |
Jevons Paradox | Increasing efficiency can increase total consumption. | |
Network Dynamics & Scaling |
Sarnoff's Law | Value grows linearly with audience size. |
Metcalfe's Law | Network value increases with the square of participants. | |
Reed's Law | Value grows exponentially with group formation. | |
Kurzweil's Law of Accelerating Returns | Technology change accelerates; past pace ≠ future pace. | |
Innovation & Knowledge Sharing |
Sturgeon's Law | Most output is low quality; encourages discernment and review. |
Linus's Law | With enough eyes, all bugs are shallow. | |
Clarke's Three Laws | Sufficiently advanced tech appears magical; embrace emergence. |