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Stage Gates and Stopping Rules by the Numbers

Expected value, the value of information, real options, sunk costs and kill criteria, worked through one new-product programme from first gate to pivot

Avoid committing too early and continuing too long: decision trees at each gate, the value of tests and of waiting, sunk costs, escalation, kill criteria and a pivot.

10 chapters · About 112 minutes · Free to read · Intermediate project and product investment decision practice

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KEVOS® LibraryPROJECTSG1G2G3G4GOStage Gates andStopping Rulesby the NumbersKEVOS® ORIGINAL BOOK10 CHAPTERS

About this book

Development projects fail in two opposite ways. Some commit too early: tooling is ordered, launch dates are announced and suppliers are booked before the business knows whether the product works or whether anyone will buy it, so that stopping later costs far more than it needed to. Others continue too long: each review finds a reason to spend a little more, money already spent becomes the argument for spending the rest, and a project that should have been stopped or changed runs on to launch. Both failures come from the same place. Commitments get out of step with what is actually known.

This book treats that problem with numbers. It starts with premature commitment and the difference between spending money and committing it, then builds a decision tree for a staged programme and puts a dollar value on the right to stop at a gate. It goes on to the value of information, perfect and sample, which says how much a test or a trial is worth before it is run, and to waiting as a simple real option. The second half turns to the forces that keep projects going: escalation of commitment, the sunk cost effect, and the stopping rules and kill criteria that work only if they are written before the evidence arrives. It ends with a choice between continuing, pivoting and stopping in favour of a competing investment, and with a review that judges the decisions separately from how they turned out. Each chapter carries one running case, includes a plausible error and how it was found, and ends with an exercise and its worked answer.

It is for owners, general and engineering managers, product and project managers and finance staff in small and medium Australian businesses. It assumes spreadsheet arithmetic and simple probability: expected values, conditional probabilities and Bayes’ rule are explained where they are first used. Stage gates that make real decisions describes how a gate process is set up and run; this book does the arithmetic that tells a gate what to decide.

The running case

Every chapter follows one fictional programme. This is an illustration. Corella Plains Implements is a family-owned maker of trailed boomsprays and chaser bins in the Wimmera region of western Victoria, with about 70 staff. In February 2025 it starts developing the SB36, a 36 m trailed boomspray with cameras that detect weeds in fallow paddocks and spray only the weeds, rather than the whole paddock. The programme runs through five stages separated by gates: scoping (A$40,000), concept and a bench detection trial (A$180,000), development of two prototype booms (A$560,000), a summer field-validation season on growers’ farms (A$320,000) and a launch costing A$1.8 million, all excluding GST. The development stages total A$1.1 million and the whole programme to launch A$2.9 million.

The programme meets most of the problems the book describes. A tooling order is placed too early. The development stage runs over through a series of small top-ups. The field season returns a weak result, and at the launch gate the team must choose between launching anyway, waiting a season, pivoting to a cheaper retrofit kit for growers’ existing booms, or stopping, while a robotic welding cell for the chaser-bin line competes for the same capital.

The business, its people, its products, its records and every number in the case are invented. None describes KEVOS® work, a real business or a real product.

How to use the book

Read Chapters 1 and 2 first: the distinction between spending and committing, and the decision tree built at the development gate, are used in every later chapter. Chapters 3 to 5 value flexibility (the right to stop, information and waiting) and are best read in order. Chapters 6 to 8 deal with the behaviour that keeps projects going and the rules that counter it, and Chapters 9 and 10 cover the launch-gate decision and the review that follows. Every calculation in the book was checked by running it, and the figures are rounded only for display.

The book is one of a series of Library books on delivering projects, written to be read together. Reference Class Forecasting by the Numbers supplies the outside-view estimates of cost and time that the trees in this book need as inputs. Front-End Planning by the Numbers covers the work done before the first gate that decides what the options are. Demand and Benefit Forecasts by the Numbers deals with the market estimates behind the payoffs at each branch, and Prototypes and Simulation by the Numbers with designing the tests whose value this book calculates.

Source limits and professional responsibility

The methods are established and the sources are listed with what each was used for. Where the book quotes published research findings, they are attributed and describe the studies that produced them, mostly laboratory experiments and studies of larger organisations; how far they apply to a small business is discussed where they are used. The case’s probabilities, payoffs and costs are teaching values, not market data, and a real appraisal needs its own estimates, checked by the people who will be accountable for them. The figures are before tax and ignore any R&D tax offset; accounting and tax treatment needs advice from the business’s accountant. This book is general information about project and investment decisions. It is not financial, accounting, tax or investment advice.

Who this book is for

Owners, general and engineering managers, product and project managers, and finance staff in small and medium Australian businesses who approve, fund, review or stop development projects in stages.

What you will learn

  • Recognise premature commitment, and keep commitments in step with what is known by separating spending from committing at each gate.
  • Build and roll back a decision tree for a staged programme, and put a dollar value on the right to stop.
  • Calculate the expected value of perfect and of sample information, and decide whether a test or a trial is worth its cost.
  • Value waiting as a simple real option, and tell when waiting, testing or proceeding is the better way to learn.
  • Exclude sunk costs, spot the pattern of escalation, and write stopping rules and kill criteria before the evidence arrives.
  • Compare continuing, pivoting and stopping against a competing use of the same capital, and review decisions separately from their outcomes.

Inside this book

Chapters

  1. 01Committing before you know: spending, committing and the gate planSpent versus committed, a maker's record of 4 failed products in 8, the SB36 gate plan to A$2.9m, and a A$600k tooling order placed ten days after Gate 3.
  2. 02Expected value and the decision tree at the development gateThree market states, Bayes' rule for a field signal and a rolled-back tree that values Gate 3 at A$323.1k, against a single-scenario paper that said stop at −A$868.2k.
  3. 03What the right to stop is worthStaged against all-in approval of the SB36: A$323.1k against −A$81.5k, a right to stop worth A$404.6k, the risk profile of each, and gates that never said no.
  4. 04Paying for information: perfect, sample and uselessEVPI of A$471.5k for the SB36 market, EVSI of three market tests (A$0k, A$149.5k, A$304.4k), and a A$140k third prototype that could not change any decision.
  5. 05Waiting, testing or proceeding: simple real optionsWaiting a year at Gate 3 to watch a competitor: A$214.8k against A$323.1k for staging now, a close call that turns on lost High-market sales, and a naive wait of A$643.9k.
  6. 06Escalation in small stepsSB36's development stage grows from A$560k to A$705k through three top-ups under A$75k; the forward test each time, the missed re-gate at 115% and the rule that fixed it.
  7. 07Stopping rules and kill criteria written before the evidenceA break-even P(High) of 0.0980 becomes field and dealer-deposit criteria signed at Gate 4; the field season returns 89% detection and 6 deposits, and a draft paper tries to move the goalposts.
  8. 08Sunk costs at the launch gateSB36 has spent A$1,245k by Gate 5. A note that set stopping's sunk loss against launching's forward value made launch look A$983.8k better; on one basis, stopping beats launching by A$351.2k.
  9. 09Pivot, stop or switch to the competing investmentFive Gate 5 options under a A$1.8m capital limit: full launch A$116.8k, waiting a season A$650.2k, and a pivot to the retrofit kit with the welding cell funded now, A$893.7k.
  10. 10Reviewing the decisions, not the outcomesSB36's October 2026 review: the gate log, regret of A$392.3k against A$1,131.4k, spend stopped at 42.9% of plan, and a Brier score of 0.3534 that exposes overconfident schedules.

Apply This in Practice

Use these KEVOS® tools to try the method from this reading with your own numbers.

References and source notes

The manuscript and worked examples are original KEVOS® writing. References inform particular concepts; their authors do not endorse this book. Web references were consulted on 28 October 2026.

  • Bent Flyvbjerg and Dan Gardner. How Big Things Get Done (2023). Supplied source, © Connaught Street Inc. and Bent Flyvbjerg, in copyright. Used as a subject map only, for the theme of committing too early and continuing too long. No passages, chapter structure, stories, figures or heuristics are reproduced.
  • Barry M. Staw, Organizational Behavior and Human Performance 16, 27–44. Knee-deep in the big muddy: a study of escalating commitment to a chosen course of action (1976). The experiment that introduced escalation of commitment: people committed the most further resources to a failing course of action when they were personally responsible for choosing it. Used in Chapter 6, with the published study design quoted as given in the paper's abstract.
  • Barry M. Staw, Academy of Management Review 6(4), 577–587. The escalation of commitment to a course of action (1981). Background for Chapter 6 on why losses can prompt further investment in the same direction, and on self-justification as a cause.
  • Hal R. Arkes and Catherine Blumer, Organizational Behavior and Human Decision Processes 35, 124–140. The psychology of sunk cost (1985). Source for the sunk cost effect, the tendency to continue an endeavour once money, effort or time has been invested, including its field study of theatre season-ticket buyers. Used in Chapter 8; its findings are described, not its figures.
  • Chip Heath, Organizational Behavior and Human Decision Processes 62(1), 38–54. Escalation and de-escalation of commitment in response to sunk costs: the role of budgeting in mental accounting (1995). Source for the finding that people who set and track a budget for an endeavour tend to stop when it is exceeded, and that escalation is more likely when no budget is set or spending is hard to track. Used for the stage budget caps in Chapters 6 and 7.
  • Stefan Roth, Thomas Robbert and Lennart Straus, Business Research 8(1), 99–138. On the sunk-cost effect in economic decision-making: a meta-analytic review (2015). Meta-analysis of 98 effect sizes, cited in Chapter 8 for the finding that the sunk-cost effect is real but varies with the kind of decision, and for its distinction between decisions to use what was bought and decisions to keep investing.
  • Robert G. Cooper, Business Horizons 33(3), 44–54. Stage-gate systems: a new tool for managing new products (1990). Origin of the stage-and-gate model for new product development, in which work proceeds in stages separated by go or kill decisions. The case's five stages follow the general idea; their names, budgets and criteria are the book's own.
  • Robert G. Cooper, Basic Books. Winning at New Products: Creating Value Through Innovation (2017 (fifth edition)). Background on gate criteria, gatekeepers and the use of gates as investment decisions, used in Chapters 1, 3 and 7.
  • Ronald A. Howard, IEEE Transactions on Systems Science and Cybernetics 2(1), 22–26. Information value theory (1966). Origin of valuing information by its effect on a decision, the basis of the expected value of perfect and sample information in Chapter 4.
  • Howard Raiffa and Robert Schlaifer, Division of Research, Harvard Business School. Applied Statistical Decision Theory (1961). Standard source for the expected value of sample information and preposterior analysis: valuing a test before its result is known. Used in Chapter 4.
  • Ronald A. Howard, Management Science 34(6), 679–695. Decision analysis: practice and promise (1988). Background on decision analysis as a professional practice: framing alternatives, assigning probabilities and values, and rolling back a decision tree. Used in Chapters 2 and 10.
  • Avinash K. Dixit and Robert S. Pindyck, Princeton University Press. Investment under Uncertainty (1994). The standard text on investment as the exercise of an option when spending is irreversible, the future uncertain and timing flexible. Chapter 5 uses only its simple discrete-time ideas; no formulas beyond a one-period example are used.
  • Robert McDonald and Daniel Siegel, Quarterly Journal of Economics 101(4), 707–727. The value of waiting to invest (1986). Source for the result, quoted in Chapter 5, that the rule 'invest when benefits exceed costs' ignores the value of waiting, and that under plausible conditions the best policy can be to wait until benefits are about twice the cost. The URL is the earlier NBER working paper version.
  • Infrastructure Australia. Assessment Framework: Guide to risk and uncertainty analysis (July 2021). Australian government guidance that includes real options analysis and a worked decision tree. Named in Chapter 5 as an example of the method in public appraisal; its examples are not reproduced.
  • Australian Accounting Standards Board. AASB 138 Intangible Assets (as amended). Named by number and scope in Chapter 8 as the accounting standard that separates research and development phases and sets when development costs may be recognised as an asset. The case's accounting treatment is illustrative; the book gives no accounting advice.
  • Australian Taxation Office, with the Department of Industry, Science and Resources. Research and development tax incentive (current online guidance). Named only to make clear that the case's figures are before tax and ignore any R&D tax offset, which a real appraisal would include with professional advice.
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