Principles Library

Entrowise's Principles Library contains 30 fundamental delivery principles organized by domain. Each principle captures a truth about how healthy delivery systems behave—and what goes wrong when it is violated. These principles form the backbone of the PPA Method.

Browse by category or search for specific principles. Each principle page includes the principle intent, early warning signs of violation, systemic consequences, coaching questions, and recommended practices.

Lean Principles

• Optimize the Whole — Optimize the end-to-end value delivery system rather than individual teams or components. System performance is determined by flow across the whole, not by local efficiency.
• Build Quality In — Treat quality as a built-in system property rather than an inspection step at the end. Preventing defects at the source is always faster and cheaper than detecting and fixing them later.
• Eliminate Waste — Continuously identify and remove activities that consume resources without adding customer value. Waste slows delivery, obscures real problems, and diverts energy from what matters.
• Deliver Value Fast (Reduce Lead Time) — Reduce the time between recognizing a need and delivering value to the customer. Fast delivery enables faster learning, earlier feedback, and greater responsiveness to change.
• Defer Commitment (Last Responsible Moment) — Delay irreversible decisions until the last responsible moment—when the most information is available and the cost of change is still acceptable.
• Continuous Improvement (Kaizen) — Build a culture of ongoing, incremental improvement where everyone contributes to making the system better. Improvement should be habitual, not episodic.
• Respect People — Design systems that respect the expertise, judgment, and dignity of the people who do the work. People are not resources—they are the intelligence of the system.

Agile Principles

• Embrace Change — Adapt plans and priorities based on learning and emerging realities. In complex systems, change is evidence of learning—not a failure of planning.
• Empowered, Cross-Functional Teams — Design teams with the skills, authority, and context required to deliver end-to-end value. Empowered, cross-functional teams reduce dependencies, speed decisions, and improve ownership.
• Frequent Feedback Loops — Create frequent, meaningful feedback loops that inform decisions and guide adaptation. Feedback is how learning enters the system and influences behavior.
• Incremental Delivery — Deliver value in small, meaningful increments to reduce uncertainty and enable learning. Incremental delivery exists to discover the right solution when outcomes cannot be known upfront.
• Transparency — Make work, risks, progress, and outcomes visible so decisions are grounded in shared reality. Transparency enables informed action; without it, decisions are based on assumptions and perception.
• Value Is Contextual and Time-Dependent — Recognize that value is not fixed. It evolves based on timing, context, and changing conditions. Decisions about what is valuable must be continuously revisited.

System Integrity

• Accountability Must Match Control — People and teams can only be accountable for outcomes they have the authority, capability, and resources to influence. Accountability without control breeds frustration and learned helplessness.
• Alignment over Compliance — Sustainable delivery improvement comes from shared understanding and genuine commitment—not from enforced process adherence. When people understand why, they adapt intelligently.
• Constraints Create Focus — Constraints are not just limitations—they are design forces that create boundaries, focus energy, and guide decisions. Effective leaders work with constraints, not around them.
• Learning Before Scaling — Validate that a practice, solution, or system works at small scale before expanding it. Scaling unvalidated approaches amplifies both costs and failure modes.
• Every Hand-Off Has a Cost — Every time work moves between people, teams, or systems, information is lost, delay accumulates, and accountability becomes diffuse. Design flows that minimize unnecessary hand-offs.
• More Choices Make Decision-Making Harder — Expanding options increases cognitive load and often leads to worse decisions, analysis paralysis, and delayed action. Clarity and constraints often serve better than freedom and abundance.
• New Solutions Create New System Constraints — Every solution introduces new dependencies, trade-offs, and constraints. Leaders must anticipate second-order effects—what new problems will this solution create?
• Understand the Original Intent Before Removing or Replacing Existing Capabilities — Before removing or replacing an existing process, rule, or system, first understand why it was introduced. Removing constraints without understanding their purpose often reintroduces the original problem.
• Vague Guidance Creates False Alignment — Ambiguous goals, principles, or strategies create the illusion of agreement while allowing divergent interpretations. False alignment is more dangerous than open disagreement.

Scrum Principles

• Empiricism — Base decisions on observation, experimentation, and evidence rather than assumptions, predictions, or plans. In complex environments, what is true must be discovered, not assumed.
• Timeboxed Learning Cycles — Use fixed-length cycles to create predictable cadences for planning, execution, inspection, and adaptation. Timeboxes create urgency, limit scope creep, and force regular reflection.
• Commitment to Outcome Intent — Commit to the intent and outcome of a goal—not to a fixed scope of deliverables. Rigid scope commitments in complex work prevent the adaptation needed to actually achieve the goal.

AI & Automation Principles

• Human Accountability Cannot Be Delegated — Humans retain accountability for decisions and outcomes even when AI systems perform the work. Delegation of tasks does not transfer responsibility for results.
• Decision Authority Must Be Explicit — In systems where AI and humans collaborate, it must be unambiguous who—or what—has authority to make each category of decision. Unclear authority leads to gaps, conflicts, and unintended outcomes.
• Observability Before Autonomy — Before granting AI systems autonomous action, ensure humans can observe what the system is doing, why, and what outcomes it is producing. You cannot govern what you cannot see.
• Feedback Loops Must Include AI Behavior — Feedback and review mechanisms must explicitly include evaluation of AI agent behavior—not just human team behavior. AI systems can drift, degrade, or amplify errors silently.

Flow & Kanban Principles

• Visualize Work — Make work, workflow, and bottlenecks visible to the entire team and system. Visibility is a prerequisite for understanding, managing, and improving flow.
• Limit Work in Progress (WIP) — Actively constrain the number of items in progress at any stage. WIP limits expose bottlenecks, reduce multitasking, and improve flow and quality.
• Manage Flow — Focus management attention on the smooth, predictable movement of work through the system rather than on keeping people busy. Flow management prioritizes outcomes over activity.
• Make Policies Explicit — Surface and document the rules that govern how work is selected, prioritized, and handled. Explicit policies enable consistent decisions and make system behavior understandable.
• Small Batches — Process work in the smallest viable increments to reduce risk, improve flow, and accelerate feedback. Large batches hide problems, create queues, and delay learning.

Learn how principles are applied in the PPA Method | Use the AI agent to identify violated principles in your situation