How to Choose Between Competing Concept Designs
Early product development decisions—especially during concept selection—have a significant impact on the final outcome.
June 4, 20258 min read

Written by Konstantin Dolgan, Ph.D., NPDP
Founder & CEO, Product Development Engineer
Published June 4, 2025Updated September 2, 2026
Introduction
After successfully exploring product ideas and generating concepts, teams often find themselves overwhelmed by the many potential directions their organization could take. In today’s highly competitive market, businesses must consistently develop high-quality innovations that meet customer expectations while ensuring sustainable profitability.
Early product development decisions—especially during concept selection—have a significant impact on the final outcome. As a result, this phase has drawn considerable interest within the field of design science.
Importance of Concept Selection
Concept development is widely considered one of the most challenging and crucial stages in the product creation process, shaping the cost, manufacturability, reliability, and development timeline.
It’s a well-established principle that engineering changes made later in development cost exponentially more. Therefore, the concept selection phase—where designers evaluate options against customer needs and design objectives—is essential. This phase includes comparing alternatives, assessing strengths and weaknesses, and selecting candidates for further refinement and testing.
Challenges and Decision-Making Tools
Designers often must make critical decisions with limited information. To support objectivity and accuracy in concept selection, various methodologies have been developed, including:
- Pugh’s Concept Scoring Method
- Weighted Rating Method
- Analytical Hierarchy Process (AHP)
- Fuzzy Set and Fuzzy AHP Methods
- Flexible Design Concept Selection
- Hypothetical Equivalents and In-Equivalents Method
- Quality Function Deployment (QFD)
- Axiomatic Design
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Best Practices for Applying Concept Selection Methods
To ensure effective use of these methodologies, consider the following strategies:
- Start simple – Use fundamental approaches like Pugh’s method or Weighted Rating for initial evaluations. If results are unclear, apply more detailed methods like AHP.
- Cross-validate – If weight factors are uneven or if there are significant differences in performance scores, use another method to confirm findings.
- Trust clear outcomes – When one approach yields a decisive winner, it’s likely that others will support the same result.
- Resolve ambiguities – If results are too close to call, adjust the comparison method or refine resolution to gain deeper insights.
- Analyze data thoroughly – Don’t rely solely on scores—carefully review key criteria before making a final selection.
Spotlight on Two Essential Methods
- Pugh’s Method (Pugh Chart)
The Pugh method is a comparative analysis tool that evaluates concepts against a baseline option. Rather than choosing a final concept outright, this method systematically refines potential solutions by eliminating weak aspects and enhancing strong ones.
Steps for Creating a Pugh Chart:
- Define evaluation criteria
- Develop a decision matrix
- Clarify design concepts
- Select a baseline concept
- Populate matrix entries (+, −, 0)
- Analyze results
- Change baseline and reassess
- Improve the selected concept
- Weighted Decision Matrix
This method ranks concepts against weighted criteria, converting diverse values into a consistent numerical scale.
Steps:
- Assign weights to criteria based on importance
- Score each concept’s performance for every criterion
- Multiply weights by scores to determine total scores
- Select the highest-scoring option or explore hybrid solutions
Additional Considerations for Concept Evaluation
Minimum Requirements for Evaluation
- Clearly defined evaluation criteria
- A shortlist of viable alternatives
- A way to compare each alternative across all criteria
Evaluation Based on Absolute Criteria
Concepts can be assessed using:
- Functional feasibility (Feasible, Not Feasible, Likely to Work)
- Technology readiness (avoiding excessive R&D during product design)
- Threshold constraints (e.g., size, power, cost)
Role of Models in Concept Evaluation
- Iconic Models – Physical, scaled-down prototypes
- Analog Models – Use of similar processes (e.g., modeling heat flow with electrical current)
- Symbolic Models – Mathematical or symbolic abstractions of product characteristics
As product development progresses, models become more complex:
- Conceptual Design – Sketches, rough models
- Embodiment Design – Detailed geometric and tolerance specifications
- Detail Design – High-fidelity prototypes, optimization models
Widely Used Frameworks for Concept Prioritization
- MoSCoW Method
Classifies product features into:
- Must-Have – Essential for viability
- Should-Have – Important but not critical
- Could-Have – Nice-to-have additions for future iterations
- Won’t-Have – Features that are not currently prioritized
- Jobs-To-Be-Done (JTBD)
Focuses on customer motivations—understanding why users “hire” a product. Ensures that features align with user expectations, improving satisfaction and retention.
- RICE Framework
RICE prioritizes ideas based on:
- Reach – Number of users impacted
- Impact – Value delivered
- Confidence – Certainty of estimates
- Effort – Development cost and time required
Strategic Questions Before Finalizing a Concept
Before making a decision, consider:
- Does the design align with company values and vision?
- Does it stand out or blend in with competitors?
- Will it resonate with the target audience?
- Can it scale across different media and formats (e.g., online presence, packaging, merchandise)?
Additional factors to evaluate:
- Market opportunity
- Development cost
- Competitive advantage
- Risks
- Time to market
- User value
- Alignment with company strategy
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Conclusion
Regardless of which framework or method a team adopts, structured, evidence-based, and iterative concept selection is crucial. It helps teams make informed decisions, mitigate risks, and ultimately create products that meet user needs and succeed in the market.
Concept Prioritization Frameworks
Framework | Primary Focus | Key Elements |
|---|---|---|
MoSCoW Method | Feature Classification | Must-Have, Should-Have, Could-Have, Won't-Have |
Jobs-To-Be-Done (JTBD) | Customer Motivations | Understanding why users 'hire' a product |
RICE Framework | Idea Prioritization | Reach, Impact, Confidence, Effort |
A worked weighted concept selection matrix
The matrix earns its keep only when the weights are agreed before anyone scores. Set the weights against the product requirements document, not against the concepts on the table — otherwise the weighting quietly becomes an argument for the concept someone already liked.
Score each criterion 1 to 5 against a defined datum concept, multiply by weight, and total. The example below shows three concepts for an enclosure program where cost and tooling risk dominated.
Criterion | Weight | Concept A | Concept B | Concept C |
|---|---|---|---|---|
Unit cost at 25k volume | 30% | 4 | 3 | 5 |
Tooling risk and lead time | 25% | 3 | 2 | 4 |
User task completion in testing | 20% | 4 | 5 | 3 |
Serviceability and repair | 15% | 2 | 4 | 3 |
Manufacturing partner familiarity | 10% | 5 | 3 | 4 |
Weighted total | 100% | 3.55 | 3.25 | 4.00 |
Where concept selection matrices go wrong
- Scoring after the decision. If the matrix is built to justify a choice already made, it produces confidence rather than information.
- Too many criteria. Past roughly seven, weights get diluted and every concept converges on the same score.
- Mixing requirements with preferences. Hard requirements are pass/fail gates before the matrix, not weighted rows inside it.
- One scorer. Have engineering, design and commercial score independently, then discuss only the rows where they disagree by two or more points.
- Ignoring the spread. When the top two concepts land within 5%, the honest answer is that you need more evidence — usually one more round of prototypes or user testing — not a tie-breaker vote.
What to do when the matrix does not decide it
A close result is information, not a failure. It usually means the concepts differ on dimensions you have not yet measured — manufacturability at volume, real-world grip and handling, or how the product ages after a few hundred cycles.
The productive response is to name the single assumption that would flip the ranking and go test it. That is normally cheaper than it sounds: a printed handling model, a short round of five user sessions, or a quote from the likely manufacturer will usually resolve a 5% gap in a week or two.
- Identify the deciding unknown. Write it as a testable statement, not as a preference.
- Pick the cheapest test that could change the answer. Printed model, quote request, or a five-person usability session.
- Re-score only the affected rows. Do not rebuild the matrix; that invites re-litigating settled criteria.
- Record the decision and the evidence behind it. Six months later, at tooling, someone will ask why this concept won.
- Carry the runner-up forward as a documented fallback, including what would trigger a switch back to it.
Concept selection is the last cheap decision in a hardware program. Every choice after it — CAD detail, prototypes, tooling — multiplies the cost of changing direction, which is exactly why the extra week spent resolving a close call is the highest-return week in the schedule.
Frequently asked questions
Why is concept selection important in product development?
Concept selection is crucial because early product development decisions significantly impact the final outcome. It shapes cost, manufacturability, reliability, and the development timeline. Changes made later in development cost exponentially more, making this phase essential for evaluating options against customer needs.
What are some common challenges in concept selection?
Designers often need to make critical decisions with limited information. To address this, various methodologies have been developed. These tools help support objectivity and accuracy in the selection process. Key challenges include comparing alternatives and assessing strengths and weaknesses.
Which methods can help in choosing between competing concept designs?
Several methodologies can help choose between competing concept designs. These include Pugh’s Concept Scoring Method, Weighted Rating Method, and Analytical Hierarchy Process (AHP). Other options are Fuzzy Set and Fuzzy AHP Methods, and Quality Function Deployment (QFD).
What are the first steps when applying concept selection methods?
To apply concept selection methods effectively, start simple. Use fundamental approaches like Pugh’s method or Weighted Rating for initial evaluations. If results are unclear, apply more detailed methods like AHP. Cross-validation can confirm findings if weight factors are uneven.
What is the purpose of Pugh's Method?
Pugh's Method is a comparative analysis tool. It evaluates concepts against a baseline option. This method systematically refines potential solutions. It eliminates weak aspects and enhances strong ones, rather than choosing a final concept outright. A decision matrix is used.
Sources and standards
- Industrial Designers Society of America — Professional body for industrial design practice in the US.
- Nielsen Norman Group usability research — Evidence-based usability findings applied to product interaction.
- USPTO — patent basics — Official guidance on provisional and non-provisional filings for new products.
Building a concept selection matrix that survives scrutiny
A concept selection matrix converts an argument into a calculation, but only if the criteria and weights are agreed before the concepts are scored. Setting weights after seeing the concepts is how a matrix becomes a way of justifying a decision someone already made.
Example weighted matrix
Criterion | Weight | Concept A | Concept B | Concept C |
|---|---|---|---|---|
Meets core function | 25% | 5 | 4 | 5 |
Manufacturing cost | 20% | 3 | 5 | 2 |
Development risk | 15% | 4 | 5 | 2 |
Usability | 15% | 4 | 3 | 5 |
Time to market | 15% | 3 | 5 | 2 |
Serviceability | 10% | 3 | 4 | 4 |
Weighted total | 100% | 3.85 | 4.40 | 3.50 |
Run a sensitivity check afterwards: change one weight by ten points and see whether the winner changes. If it does, the concepts are effectively tied on the evidence you have, and the right next step is a test that separates them rather than a longer meeting.
Matrix discipline checklist
- Agree criteria and weights before scoring anything.
- Score with a mixed group, not a single function.
- Use the same evidence basis for every concept.
- Run a sensitivity check on the weights.
- When results are close, run the test that separates them instead of debating.
Key takeaways
- Set criteria and weights before the concepts are scored.
- Sensitivity-check the result; a fragile winner means a tie.
- Close scores call for a discriminating test, not more discussion.
Running the review session itself

A matrix only works if the session around it is disciplined. Distribute the criteria and weights before the meeting, and never in the same document as the concepts — otherwise weights get tuned to favor a preferred design.
Have each reviewer score independently, collect the sheets, then discuss only the criteria where scores diverge by two points or more. Those divergences are where the real information lives: they usually mean the criterion is ambiguous or the concept data is missing.
- Independent scoring first. Group scoring converges on whoever spoke first.
- Debate divergence, not averages. A two-point spread signals a definition problem.
- Record the unknowns. Any criterion scored on a guess becomes a test in the next sprint.
- Re-run after new data. A selection made on assumptions is provisional by definition.
- Archive the sheet. Six months later, the matrix is the only record of why the losing concepts lost.
What happens to the concepts you did not pick?
Losing concepts are assets, not waste. Individual features often outscore the winner on a single criterion — a better seal, a cheaper hinge, a smarter service access panel. Harvest those features into the selected concept before engineering starts, and keep the runner-up documented as a fallback in case a supplier, cost or compliance constraint kills the leader during prototyping.
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