Design thinking, blue ocean and technology

Human-centred design thinking

Design thinking investigates a human problem before committing to a solution. Observation, conversations and practical experiments help a team question its initial assumptions. It is useful when the problem itself is uncertain: improving the wrong feature more efficiently will not solve an unmet need.

IDEO describes three considerations that must work together. A popular idea is insufficient if it cannot be delivered; technical sophistication is insufficient if nobody needs it.

Desirability

Identify the outcome people want, including practical difficulties, emotions and accessibility needs. Look beyond what customers say they would buy.

Feasibility

Establish whether the technology, people, partners and operating processes can deliver the outcome reliably.

Viability

Explain how the organisation will fund delivery and sustain the offer through revenue, savings or another appropriate funding model.

Concept sources: IDEO — Design Thinking — Concept reference; cards prepared for these notes.

Include people with different experiences in research and development. Averages can conceal a problem faced by an important customer group. Co-creation means involving users in shaping possible solutions, rather than merely asking them to approve a finished design.

Divergence, convergence and iterative testing

The Design Council's Double Diamond distinguishes exploring possibilities from narrowing choices. Its four recognised stages describe the work, rather than an irreversible sequence.

Concept sources: Design Council — Framework for Innovation — Concept reference; table prepared for these notes. The framework is available under CC BY 4.0.

Divergence expands the range of explanations or options. Convergence uses evidence and criteria to select a direction. Testing may reveal that the original problem definition was wrong, so returning to an earlier stage is productive rather than a failure to follow the process.

Liedtka's design-thinking work also uses four questions: What is? examines present experience; What if? generates possibilities; What wows? examines the appeal and assumptions of promising concepts; What works? tests and improves them with stakeholders. These questions provide another way to organise learning, not a competing rule that every project must follow identically.

Concept sources: UVA Darden — How to Use Collaborative Creativity to Solve Problems and Innovate — Concept reference for the four questions.

IDEO and Riverdale's educator toolkit uses five phase names: Discovery, Interpretation, Ideation, Experimentation and Evolution. Recognise this vocabulary alongside the other formulations; the shared purpose is learning about a problem and improving a tested solution.

Concept sources: IDEO and Riverdale — Design Thinking for Educators — Reference to the toolkit's phase names.

A prototype makes an assumption testable. It can be a paper screen, a role-played service or a simple physical model. A 3D-printed shape may test handling, while leaving durability and manufacturing cost untested. Decide what an experiment can demonstrate before interpreting the result. Friendly feedback alone does not establish repeat demand, willingness to pay or commercial viability.

Concept sources: IDEO — The Design Thinking Process — Concept reference for iteration and making ideas tangible.

Blue ocean strategy and value innovation

Chan Kim and Renée Mauborgne's blue ocean approach seeks new demand by changing the basis on which buyers receive value. A red ocean describes competition within established market boundaries; a blue ocean concerns creating market space through a different offer. The labels describe strategic conditions, not permanent categories of organisations.

Value innovation seeks differentiation and lower cost together. This requires choosing which activities or features to remove or reduce, while improving or creating benefits that matter. Adding every possible feature usually increases cost and complexity. A technological invention is not automatically value innovation: buyer utility, price and the organisation's cost structure must support each other.

Concept sources: Kim and Mauborgne — Value Innovation — Concept reference.

An apparently unique offer still needs evidence. Customers may prefer existing alternatives, imitation may follow, and delivery constraints may defeat the economics. Treat the proposed market opportunity as a hypothesis to test.

Strategy canvas and the value curve

A strategy canvas compares the factors on which an industry competes and the level of each offered by competing alternatives. Connecting an offer's factor ratings produces its value curve, or strategic profile. An as-is comparison reveals where firms look similar; a proposed curve shows how an alternative would differ.

Choose factors from buyer research, define rating scales consistently and distinguish evidence from estimates. High ratings on everything do not demonstrate a strategy. A price factor also needs careful interpretation: a high price is not automatically greater customer value.

Concept sources: Kim and Mauborgne — Strategy Canvas — Concept reference; application table prepared for these notes.

This comparison should lead to choices. If the proposed offer requires high spending on every factor, revisit what can be simplified. If the proposed curve resembles existing offers, explain why customers would switch instead of assuming a different brand name creates differentiation.

Buyer utility across the whole experience

The buyer utility map broadens attention beyond the moment of use. It combines stages in a buyer's experience with ways an offer could improve that experience. Its purpose is to expose obstacles that current customers tolerate and noncustomers avoid.

Experience stages

Purchase, delivery, use, supplements, maintenance and disposal. Supplements are additional items or services needed alongside the main offer.

Utility levers

Customer productivity, simplicity, convenience, risk reduction, fun and image, and environmental friendliness.

Application

Select a specific obstacle, establish who experiences it, and test whether removing it changes willingness to use or buy the offer.

Concept sources: Kim and Mauborgne — How to Turn Your Customers' Pain Points into Opportunities — Concept reference; cards prepared for these notes.

One improvement may affect several stages, but this does not justify counting the same benefit repeatedly. Reduced effort and reduced risk should be supported by different evidence where they are presented as separate benefits.

Four actions and the ERRC grid

Kim and Mauborgne's Four Actions Framework challenges the existing industry offer. The Eliminate–Reduce–Raise–Create (ERRC) grid records the resulting choices. The first two actions can release resources; the other two direct resources towards a more useful offer. The result should describe concrete decisions rather than aspirations such as “be better”.

Concept sources: Kim and Mauborgne — Four Actions Framework and ERRC Grid — Concept references; table prepared for these notes.

The table is a set of proposals, not proof of a successful strategy. Removing a feature may damage trust or exclude a customer group. Calculate its full consequences, including any new support burden created elsewhere.

Commercial sequence: utility, price, cost and adoption

The blue ocean commercial sequence tests whether an attractive idea can become a viable offer. Each stage can send the team back to redesign its proposal.

Concept sources: Kim and Mauborgne — Sequence of Creating a Blue Ocean — Concept reference; diagram prepared for these notes.

Utility concerns the practical improvement buyers receive. Price must work for the intended market rather than merely recover a chosen cost base. Target cost starts with that price and the required margin. Adoption concerns obstacles for employees, partners and customers, including incentives, trust, training and transition effort.

Information technology, experimentation and niche demand

Digital tools can reduce the cost of collecting feedback, distributing offers and coordinating delivery. Their strategic purpose should be explicit: better insight, easier access, more reliable execution or a new revenue model. Installing software without changing a customer outcome or an operating constraint is not evidence of innovation.

An online experiment can compare two clearly described offers using the same outcome measure. Record who saw each version and watch for differences in customer mix or timing. A landing page can test interest, but clicks are weaker evidence than completed purchases and repeat use. Describe trials honestly; do not imply that an unavailable product is ready for delivery.

Machine learning may identify patterns in enquiries, transactions or product usage, but patterns need interpretation. Test accuracy, privacy, security and harmful bias throughout development and operation. Human oversight should fit the consequences of a wrong result.

Concept sources: NIST — AI Risk Management Framework FAQs — Concept reference for AI risk evaluation.

The long tail describes the combined importance of many low-volume niche offers. Research by Brynjolfsson, Hu and Simester links lower online search costs with greater demand for niche products. This is a possible market effect, not a promise that every niche will be profitable. Low sales volumes can still make acquisition, fulfilment and support expensive.

Concept sources: Brynjolfsson, Hu and Simester — Goodbye Pareto Principle, Hello Long Tail — Reference to the authors' research abstract.

Standards, compatibility and network effects

A standard specifies agreed requirements or interfaces. Some are developed through formal standard-setting processes; others become de facto standards through widespread market adoption. Compatibility helps products, services and participants work together. Standards can reduce uncertainty and facilitate innovation, while compliance costs or restrictive specifications can also limit it.

Network effects occur when an offer's value depends partly on other participation. Direct effects involve other users; indirect effects involve complementary participants or products. These effects are different from economies of scale, which concern falling average production costs.

Concept sources: ISO — Standards and Innovation: What Does the Research Say? — Concept reference for compatibility, network effects and innovation trade-offs.

Shapiro and Varian's analysis of standards competition explains why technical quality alone may not determine adoption. Existing users, complementary products, alliances, early market presence and expectations about future support can influence the outcome. A firm must balance attracting other participants against retaining a commercially useful position.

Concept sources: Shapiro and Varian — The Art of Standards Wars — Reference to the authors' published abstract.

An open standard does not automatically mean that every implementation is free of licensing conditions or patent issues. Check the relevant policy: W3C, for example, has a specific royalty-free patent policy for its Recommendations. Its arrangements should not be assumed to apply to every standards body or every technology.

Concept sources: W3C — Patent Policy — Official reference for W3C's policy and scope.

Sources and further reading

• IDEO — Design Thinking and The Design Thinking Process.
• Design Council — Framework for Innovation.
• UVA Darden — How to Use Collaborative Creativity to Solve Problems and Innovate.
• IDEO and Riverdale — Design Thinking for Educators.
• Kim and Mauborgne — Value Innovation and Strategy Canvas.
• Kim and Mauborgne — How to Turn Your Customers' Pain Points into Opportunities.
• Kim and Mauborgne — Four Actions Framework, ERRC Grid and Sequence of Creating a Blue Ocean.
• NIST — AI Risk Management Framework FAQs.
• Brynjolfsson, Hu and Simester — Goodbye Pareto Principle, Hello Long Tail.
• ISO — Standards and Innovation: What Does the Research Say?.
• Shapiro and Varian — The Art of Standards Wars.
• W3C — Patent Policy.