Concept selection and screening

After idea generation, promising ideas are developed into concepts and then screened so that resources go to the options with the highest potential. This is the screening step of the innovation funnel made concrete.

Three dimensions of a concept

• Benefit: the value for the customer.
• Form: what the solution looks like.
• Technology: how it works.

Generally, at least two of these three dimensions must be clear for a concept to be feasible. An idea for which only the benefit is known ("customers want faster delivery") is not yet a concept.

Why screen concepts?

Before investing resources, organizations screen concepts to compare alternatives objectively, reduce risk and prioritize the concepts with the highest potential. Common methods are checklists, expert opinions, group voting and scoring models.

Scoring models

A scoring model evaluates concepts against predefined criteria. Typical criteria:

Steps in the concept selection process

1. Define selection criteria: identify criteria, assign weights based on importance, create a scoring matrix and select an evaluation team.
2. Rate alternatives: evaluate each concept on every criterion, using reference points to improve consistency.
3. Rank alternatives: calculate weighted scores and compare concepts on their totals.
4. Combine and improve concepts: merge strong elements from different concepts; selection often leads to refinement.
5. Select the best concept(s): choose the highest-scoring concept(s). Sensitivity analysis tests whether the result changes under different assumptions, for example different weights.
6. Reflection and reality check: revisit rejected concepts, check for overlooked criteria, look for evaluation errors or biases and confirm that the chosen concept is genuinely superior.

Step 6 is often seen as the point of no return, because significant investments follow.

Worked example

Three criteria with weights: strategic fit 0.5, customer fit 0.3, technical feasibility 0.2. Concept A scores 4, 3 and 5; concept B scores 3, 5 and 4 (scale 1 to 5).

• A: 0.5 x 4 + 0.3 x 3 + 0.2 x 5 = 2.0 + 0.9 + 1.0 = 3.9
• B: 0.5 x 3 + 0.3 x 5 + 0.2 x 4 = 1.5 + 1.5 + 0.8 = 3.8

A ranks first, but the difference is small. A sensitivity analysis would show that if customer fit were weighted more heavily (for example 0.4 with strategic fit 0.4), B would score 0.4 x 3 + 0.4 x 5 + 0.2 x 4 = 4.0 against A with 0.4 x 4 + 0.4 x 3 + 0.2 x 5 = 3.8. The ranking depends on the weights, which is exactly why sensitivity analysis and a reality check are part of the process. The team might also combine the strong customer fit of B with the strong strategic fit of A (step 4).

Bias and AI in concept selection

Concept selection is vulnerable to personal bias, inconsistent scoring, group influence and overconfidence. Therefore organizations use multiple evaluators and structured scoring systems to improve objectivity. AI can assist in evaluating, comparing and screening concepts.