RID Innovation Wheel Framework

• RID Innovation Wheel is a systemic, proof-driven framework that rigorously separates problem setting from problem solving to create market-ready innovations.
• The framework structures innovation in two macro-stages and mandates three proofs—value, concept, and innovation—for evidence-backed progress.
• Empirical applications demonstrate that meticulous need definition and proof-based gating significantly enhance concept viability and strategic alignment.

The RID Innovation Wheel is a systemic, proof-driven framework for engineering radical innovation within company ecosystems, structured to rigorously separate and iterate between the phases of problem setting (clarifying "where" and "what" to innovate) and problem solving ("how" innovation should be instantiated). Developed by Yannou et al. as Radical Innovation Design® (RID), this methodology is designed to transform unpredictable creativity into a value-focused investigation that delivers measurably feasible and strategically aligned innovation outcomes (Yannou, 2013).

1. Structural Overview of the RID Innovation Wheel

The RID Innovation Wheel structures innovation as a closed, iterative progression through two macro-stages—Problem Setting and Problem Solving—that begin with an initial idea and end in a comprehensive Feasibility & Innovation Dossier. Unlike ad hoc brainstorming methods, the RID Wheel emphasizes the systematic alternation of value exploration (maximizing potential opportunities) and value exploitation (engineering workable solutions with business viability).

Conceptually, the wheel is depicted as follows:

Problem Setting	Problem Solving	Final Output
Initial Idea → Ideal Need → Perimeter of Ambition	Briefs → Innovation Leads → Concepts (organized creativity)	Feasibility & Innovation Dossier

Core to this process is continual reinforcement of three categories of proof at all stages:

• Proof of Value: Demonstrated potential for market/user willingness to pay for the innovation's differentiation.
• Proof of Concept: Evidence that the innovation can be technically realized under real usage.
• Proof of Innovation: Support for the novelty being protectable (e.g., IP), communicable, and capturable.

The end product is always a structured dossier of feasible, market-targeted concepts, not a mere collection of unfiltered ideas.

2. Phases and Mechanics of the Innovation Wheel

Each macro-stage is subdivided into detailed steps, each with explicit activities, inputs, and outputs:

A. Problem Setting

• (1) Initial Idea: Defined by any prompt; captured as an "Initial Statement."
• (2) Ideal Need Definition: Uses usage scenario exploration (e.g., customer interviews, usage diaries) to build an abstract, constraint-free need ("what people would love if anything were possible").
• (3) Perimeter of Ambition: Refines the Ideal Need through business and technical filters into a credibly addressable set of opportunities. Tools such as value-chain maps and stakeholder matrices are applied.
• (4) Scenarios of Value Creation: Develops several specific, quantified value proposition briefs for each high-priority context.

B. Problem Solving

• (5) Innovation Analysis & Leads: Dissects scenarios into Value Drivers and derives Innovation Leads via structured analysis (such as TRIZ, technology scouting).
• (6) Organized Creativity Workshops: Multi-disciplinary workshop sessions produce a Book of Knowledge containing sketches, boundary diagrams, and rationale.
• (7) Concept Synthesis: Concepts are synthesized from promising knowledge fragments, prototyped in low-fidelity forms.
• (8) A Priori Proofs & Concept Choice: Concepts are scored via weighted multi-criteria (proofs of value, concept, innovation), employing tools like Usage Coverage Simulation and patent novelty reviews.
• (9) Detailed Prototype(s): Prototyping and targeted usage validation.
• (10) Feasibility & Innovation Dossier: Comprehensive packaging, including business models, IP strategy, and technical specs for organizational hand-off.

3. Theoretical Underpinnings

The methodology is grounded in established theories and empirical research traditions:

• Problem Setting vs Problem Solving (Simon): The Wheel’s explicit division mirrors Simon’s dichotomy.
• Issue-Based Design/CK Theory: Prioritization of exploratory question spaces over premature ideation, facilitating broader value mapping.
• Intermediary Design Objects: Recognition that storyboards, sketches, and prototypes themselves drive knowledge creation and solution space expansion.
• Blue Ocean Strategy: Early-stage efforts seek uncontested value perimeters, minimizing direct competition.
• Usage Coverage Models: Formalization of anticipated user scenarios for quantitative assessment of how well future concepts cover these contexts.
• Proof-Centric Progression: Stage gates require documented evidence for all three proofs, reducing bias and unwarranted optimism.
• Action-Research Approach: RID tools were field-tested and iterated in collaboration with industrial partners, optimizing for company-perceived value.

4. Quantitative Metrics and Computational Tools

Although the emphasis is on structured process, several quantitative indicators formalize assessment and comparison:

Usage Coverage Indicator (UCI)

Measures the fraction of critical usage scenarios in which a concept meets the minimum required performance:

$$\mathrm{UCI}(p) = \frac{1}{n} \sum_{j=1}^n \mathbf{1}\bigl(f(p,u_j)\ge q_j\bigr)$$

where $f(p, u_j)$ is performance in scenario $u_j$, and $q_j$ is the threshold.

Proof-Accumulation Score (SAPIGER Procedure)

For cluster/project selection, each of 22 criteria is scored as present/absent. The stage-wise total is: $$S_{\text{stage}} = \sum_{i\in\mathcal{I}_{\text{stage}}} w_i s_i$$ where $w_i$ reflects criterion importance; projects above a threshold advance.

Concept-to-Value Metrics (PSK-Value, Airbus)

For each solution $s$:

$\text{Global Value}(s) = \sum_d \alpha_d V_d(s)$

where $V_d(s)$ is the stakeholder's appraisal of $s$ on value dimension $d$, and $\alpha_d$ is weight. Distances between strategies and solutions can be measured in PSK space via cosine similarity or weighted deltas.

5. Empirical Applications

RID principles have been assessed in several organizational and experimental settings:

A. University Experiment

• Nineteen radical innovation projects guided by RID revealed via Bayesian analysis that quality of the problem setting phase (specifically, proper definition of Ideal Need, stakeholder mapping, and usage contexts) was the principal driver of ultimate concept quality.
• Teams neglecting this phase, regardless of idea generation intensity, consistently produced weaker, less deployable outcomes.

B. SAPIGER Innovation Cluster

• In an eldercare innovation cluster of 70 organizations, application of a two-stage jury with 22 proof-evidence criteria (Proof of Value, Concept, Innovation) substantially increased juror consistency and transparency.
• The share of “Chosen” projects reaching market trials increased to 60% (from 25%), suggesting improved filtering and project maturation.

C. Airbus Concept-to-Value

• Adoption of RID in Airbus’s conceptual design phase led to a unifying ontology (PSK-Value) shared between Engineering and Marketing, facilitating collaborative value modeling.
• Practical outcomes included a 30% reduction in stage-1 reviews cycle time and robust alignment of concept architecture with strategy, leading to broad adoption in new programs.

6. Critical Insights and Lessons

Consolidated findings include:

1. Primacy of Problem Setting: Meticulous analysis and definition of needs, contexts, and stakeholders in early stages more than doubled the likelihood of generating company-viable concepts.
2. Contextual Modulation: Optimal configuration of the RID process varies by project type, skill mix, and company environment. No universal prescription exists.
3. Efficacy of Proof-Based Gates: Regular, evidence-backed gating processes direct resources to concepts with tangible traction, suppressing superficial or transient trends.
4. Agility Requirement: Effective implementation tailors depth and extent of stages to budget and risk—structural rigidity hampers, while insufficient structure allows drift.
5. Benefits of Shared Language: Adoption of PSK or proof-based criteria fosters cross-disciplinary clarity and enables efficient, consistent reviews.
6. Danger of Shallow Assessments: Superficially attractive presentations may obscure weak foundations. Structured pre-read and score-driven assessments are essential for robust selection.

7. Significance in Company Innovation Practice

RID transforms innovation processes in industrial and cluster contexts from loosely organized ideation to explicit, value-centered investigations, fusing design, strategy, and engineering. Its empirical impact demonstrates measurable advances in innovation selection, project maturation, and organizational alignment between strategy, technical feasibility, and market potential, as evidenced in university-experimental settings, cluster-level incubators, and deployment at Airbus (Yannou, 2013). The approach exemplifies the integration of design research theory and systemic, practice-oriented methodology in industrial innovation management.