Probabilistic Delivery

Your team hits 95% of sprint commitments. Velocity is "stable." Retrospectives generate thoughtful action items.

So why did your project miss its deadline by four months?

After 18 months analyzing 112,000 Flow Items across 47 enterprise projects, I discovered the uncomfortable truth: Most organizations are practicing Agile Theatre—following rituals without measuring whether they actually improve delivery predictability.

The pattern is consistent:

• Story points inflate 43% within six months (same complexity, different calibration)
• 67% of "velocity improvements" come from measurement drift, not real throughput gains
• Projects burn £2.3M in average cost overruns while reporting "Green" status

This isn't a failure of Agile. It's a failure of measurement.

What This Book Provides

Probabilistic Delivery replaces subjective estimation with actuarial-grade forecasting—the same statistical rigor insurance companies use to price risk.

You'll learn:

Foundation: Measurement That Doesn't Lie

• The Unit of Work: Why Flow Items (90-120 minute tasks) eliminate the "Rubber Ruler" problem of story points
• The Binary Gate Protocol: Four non-negotiable criteria that define "Done" and prevent rework cycles
• NET (Net Effective Throughput): How to quantify your Defect Tax as a percentage of capacity (most teams discover 18-22% of their workforce is fixing yesterday's mistakes)

Discovery: Finding the Hidden Work

• The Pulse: Weekly throughput measurement that detects degrading velocity 8-12 weeks before traditional governance notices
• The Iceberg Theorem: Why teams systematically underestimate by 40-70%—and the 1.4x multiplier that corrects for it
• Reference Class Forecasting: Using your organization's historical variance (σ) instead of hoping "this time will be different"

Forecasting: Monte Carlo, Not Guesswork

• Inside the Black Box: The Monte Carlo algorithm that converts variance data into P50/P85/P95 probability distributions
• The Menu of Options: How to present three delivery dates (Median, Professional Standard, Insurance Grade) instead of one "best guess"
• The Risk Horizon: Real-time dashboard showing confidence levels, not sprint burn-downs

Governance: Fiduciary Leadership

• Traffic Light Protocol: Green (≥85% confidence), Amber (70-84%), Red (<70%)—with mandatory escalation triggers
• Real-Time Pivoting: The three levers (Scope, Sequencing, Acceptance) and when to pull each
• Structurally Bankrupt Test: How to calculate Expected Loss and know when to terminate a project before it destroys more capital

Who This Book Is For

You Should Read This If You Are:

A CTO, VP Engineering, or Engineering Director who:

• Gets asked "When will this be done?" and can't give a statistically defensible answer
• Sees teams reporting "stable velocity" while projects slip months behind schedule
• Needs to justify £2-5M capital allocations to a CFO or Board with probability distributions, not hope

A CFO, CEO, or Board Member who:

• Funds technology projects but receives status reports that feel more like performance art than risk analysis
• Wants the same actuarial rigor applied to software delivery that you demand from finance and operations
• Needs to know at Week 8 (not Month 11) whether a project is viable

A Senior PM, Delivery Lead, or Tech Lead who:

• Spends hours in planning poker debates that have no correlation with actual delivery speed
• Knows something is wrong with your measurement system but can't articulate what
• Wants to transition from "facilitating ceremonies" to "governing risk with data"

An Agile Coach or Scrum Master who:

• Recognizes that perfect stand-ups don't prevent project failure
• Wants tools that detect structural problems (technical debt, scope creep, throughput collapse) before they become crises
• Is ready to evolve from process compliance to statistical governance

You Can Skip This Book If:

❌ Your projects consistently deliver within ±2 weeks of initial forecasts (you're already doing actuarial delivery, whether you call it that or not)
❌ You believe story points are scientifically rigorous measurement units
❌ You think "working harder" is a valid response to falling behind schedule

What Makes This Different

1. Empirical Rigor, Not Consultant Frameworks

This isn't another Agile methodology. It's a measurement layer grounded in:

• 112,000 Flow Items from 47 real projects (2020-2026)
• Paired t-test validation (p < 0.001, Cohen's d = 2.9)
• 47-project breakdown showing 51.5% reduction in delivery variance

Every claim is backed by data. Every protocol is tested in production. Every formula is reproducible.

2. Multi-Audience Design

Most technical books speak to developers. Most business books ignore implementation.

This book provides:

• For Boards: Fiduciary governance protocols and risk-adjusted NPV calculations
• For C-Suite: Traffic Light dashboards and escalation triggers
• For PMs/Tech Leads: Binary Gate specifications and decomposition checklists
• For Developers: Why the system measures you incorrectly—and how to fix it

3. Complete Implementation Roadmap

You get:

• 90-day implementation plan (Days 1-30: Foundation, 31-60: Forecasting, 61-90: Governance)
• Binary Gate automation guide (CI/CD integration for tamper-proof quality)
• Monte Carlo simulation code (Python/JavaScript—reproducible with seed=42)
• Anti-Pattern Field Guide (10 common resistance patterns + actuarial rebuttals)
• Risk Horizon Dashboard spec (build your own or use the author's open-source version)

This isn't philosophy. It's an engineering manual for delivery governance.