Generating innovative concepts: the limits of divergence

The success of an innovation project depends on two things: the quality of the initial concept, and the quality of the implementation of this concept.

The problem of generating good ideas

As far as execution is concerned, Lean Startup and Agile have emerged in recent years as the preferred approaches; but we'll deal with that in a future article. What we're interested in today is the first step: finding the right idea, an essential phase in the success of truly meaningful innovations.

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This raises two main questions:

• What's a good idea?
• How do you come up with good ideas?

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The pain point represented by this idea generation and selection phase has been studied for years; it is sometimes referred to as the "fuzzy front end" of the innovation process, to underline its less rigorous and complex nature.

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Faced with these two questions, a number of idea generation methods, generally referred to as "creativity" methods, have emerged in recent years.

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The main aim of these methods is to generate ideas through brainstorming (divergent phase), and then to select the most promising ideas from among those generated (convergent phase).

Creativity methods for generating lots of ideas

How do you come up with a "good idea"? Many creativity methods are based on a simple answer: generate lots of ideas. The most extreme method in this respect, unframed brainstorming, is based on the principle that quantity is quality. Most methods, however, require some prior framing.

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For example, Design Thinking (the best-known and most widespread approach) suggests first observing users and/or non-users, to better understand their issues and problems.

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But in the end, you end up with dozens, if not hundreds, of ideas, among which may be hidden the best possible idea, which you'll have to identify.

The quest for THE right idea

Once all these ideas have been generated, how can we identify which one is THE best idea? As Burkus points out in a Harvard Business Review article, in a context of uncertainty, companies face a serious problem in recognizing good ideas, and tend to reject ideas that could provide them with a significant competitive advantage.

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Some methods attempt to guide the evaluation of ideas. For example, Design Thinking proposes three criteria: desirability (market), feasibility (technical) and viability (economic). However, the assessment of these criteria remains the sole responsibility of those involved in the decision. What's missing is an objective way of identifying which of the ideas generated is the best and deserves to be developed.

Methods that are ultimately ineffective

In the end, how can you be sure you haven't missed the genius idea at any of these stages?

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What's more, let's assume for a moment that the right idea is not only generated, but also correctly identified. The resources required to achieve this result are significant: the time and people needed to generate the ideas, then to determine the selection criteria, and finally to evaluate all the ideas generated. Remember, most divergent methods rely on a large number of ideas being generated, multiplying the resources needed to evaluate them.

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Couldn't there be a more efficient approach, increasing the probability of generating THE right idea without wasting resources?

Towards a new approach: the impact model

We believe that such an approach does exist. To overcome the limitations of divergent methods, this approach is convergent in nature. By convergent, we mean that it first defines what characterizes THE good idea, before moving on to the ideation phase.

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This approach, developed by Dynergie R&D over the past 3 years, is called theImpact Modeland has already been used for dozens of projects. We'll tell you more about this approach in an upcoming article!

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Sources:

On the complexity of the idea generation phase:

^{1. Felin, T., Gambardella, A., Stern, S., & Zenger, T. (2020). Lean startup and the business model: Experimentation revisited. Long Range Planning, 53(4), 101889. https://doi.org/10.1016/j.lrp.2019.06.002}

^{2. Khurana, A., & Rosenthal, S. R. (1998). Towards Holistic "Front Ends" In New Product Development. Journal of Product Innovation Management, 15(1), 57-74. https://doi.org/10.1111/1540-5885.1510057KeuppM. M., Palmié, M., & Gassmann, O. (2012). The Strategic Management of Innovation: A Systematic Review and Paths for Future Research: Strategic Management of Innovation. International Journal of Management Reviews, 14(4), 367-390. https://doi.org/10.1111/j.1468-2370.2011.00321.x}

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On the limitations of current methods to generate and select the "right idea":

^{3. Burkus, D. (2013). Innovation Isn't an Idea Problem. Harvard Business Review, 23, 2014. https://hbr.org/2013/07/innovation-isnt-an-idea-probleChulviV., González-Cruz, M. C., Mulet, E., & Aguilar-Zambrano, J. (2013). Influence of the type of idea-generation method on the creativity of solutions. Research in Engineering Design, 24(1), 33-41. https://doi.org/10.1007/s00163-012-0134-0}

^{4. Chulvi, V., Mulet, E., Chakrabarti, A., López-Mesa, B., & González-Cruz, C. (2012). Comparison of the degree of creativity in the design outcomes using different design methods. Journal of Engineering Design, 23(4), 241-269. https://doi.org/10.1080/09544828.2011.624501}