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Product Development and Launch
From customer insight and ideas to prototypes, experiments, R&D governance and a process ready for production.
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Chapters
- 01Finding and testing a business idea: spotting gaps, networking, A/B tests, minimum viable products and the Lean CanvasWhere strong business ideas come from and how to test them cheaply: gaps between expectation and offer, asset-light models, networking, A/B testing, minimum viable products and the Lean Canvas.
- 02What makes a useful product worth building?A practical way to judge whether a product solves enough of a real problem to justify the time, money and risk of building it.
- 03The empathy map: seeing your customer from the insideAn empathy map captures what a customer says, thinks, does and feels. How to build one from real evidence, how sales and product teams use it, and the mistakes that turn it into guesswork.
- 04User experience for products, services and processes: seamless, easy and repeatableUser experience beyond software: removing unneeded features, designing from research not opinion, in-store, phone and online journeys, trials, and making business-to-business ordering easy.
- 05Designing quality in: turning the voice of the customer into critical-to-quality requirementsCustomers say quiet, easy and reliable; factories need numbers and tolerances. How to translate needs into measurable requirements, link them to design and process drivers, and verify them.
- 06Owning a place in the customer's mindWhy products that customers choose out of habit and trust can earn for decades without changing, and what product designers can learn from that kind of durability.
- 07Product innovation for small businesses: customer-centred ideas, focus, disruption and a practical frameworkHow small businesses can innovate: start from customers' future needs, learn from technology shifts, focus narrowly, borrow ideas from other industries and use a five-step framework.
- 08Choosing and governing R&D projects: buying information, weighing odds and judging decisions fairlyR&D spending buys answers to uncertain questions. How to frame projects, weigh value against probability and cost, stage spending, keep the portfolio balanced and judge decisions fairly.
- 09Notes on prototyping earlyWhy rough prototypes are often more useful than polished ones, how to decide what each prototype should learn, and how to keep early tests cheap, quick and honest.
- 10Experiment before you standardise: using designed experiments to find robust process settingsWhy changing one setting at a time misses interactions, and how a simple designed experiment finds process settings that hold up before you lock them into standard work.
- 11From approved design to first production: tooling, off-tool samples, corrections and launch readinessThe riskiest months of a new product sit between design approval and first stock. How to plan tooling quotes, off-tool sample loops, gates and production release so launch dates hold.
- 12Proving a process is ready for production: measurement, stability, capability and PPAP-style evidenceWhy good samples do not prove a process is ready to scale, and how measurement checks, control charts, capability indices and a traceable evidence chain show it can repeat.
These topic-based reading collections are organised alphabetically; chapters may be read in any order.
Apply This in Practice
Use these KEVOS® tools to try the method from this reading with your own numbers.
Explained in this book
Capability Confidence Check (Cp, Cpk and Their Lower Confidence Bounds, Sample Size)
Tests whether a capability study proves the required Cpk at a confidence level, the evidence this chapter says good samples alone do not give.
Applies this method
Process Capability Check (σ from R̄, Cp, Cpk, Rejects, Limits)
Calculates capability indices and expected rejects, part of the evidence this chapter asks for before scaling.
Related Tools and Examples
Useful alongside
Normal Tolerance Interval Check (Coverage, Confidence, Tolerance Factor, Against Specification)
Turns a capability sample’s mean and standard deviation into limits that contain a stated share of parts with confidence, alongside this chapter’s Cpk.
Useful alongside
One-Way ANOVA Check (Group Means, F Test, Machines, Suppliers or Settings)
Tests whether results at different settings in this chapter’s kind of trial differ by more than the scatter between repeat runs.
Related to Experiment before you standardise: using designed experiments to find robust process settings