How to choose the best ideas in innovation
Picking the winners from the losers using evidence, not opinions
Generating great ideas for new innovations is hard work. Selecting the right ideas is even harder. How do you separate the winners from the losers; how do you structurally weed out the bad ideas? The key principle of good idea selection is gathering the right information to enable evidence-based decision making, using a well-tested and iterative approach to uncover insights that enable you to transform ideas into a solid value proposition, bolstered by a winning business model.
In our practice we see many companies struggle to come to good, fact-based decisions on which ideas to develop further and which not to pursue. The main reason for this struggle? Lack of good information. As at the idea’s inception a lot is pretty much unknown, it is difficult to determine when you have sufficient information to make the right selection.
Why should we select ideas?
Before diving into the details on what information we need to make a selection, let’s try to formulate what the business value is of idea selection? The main contribution is that it delivers attention and focus.
When we do not select and prioritize ideas, we are simply spreading our attention, our scarce resources (people and budget), over too many ideas, and thus starving the most promising ideas from the necessary attention to bring them to fruition.
If we try to do too many things at the same time, the development cycles for all ideas will get longer, increasing time-to-market, leading to disappointing sales and profit figures.
On top of that, bad and mediocre ideas of limited quality that are ill-aligned with your company’s strategy, lead to bad and mediocre products that won’t the create incremental organic growth that the return on innovation investment should bring.
Why is it so hard to select the right ideas?
As stated above, at the onset of the innovation process many things are unknown. Often ideas are selected for development using scorecards that rely on someone’s expert opinion, in most cases a few nominated experts in the company. This is fine for the very first quick and rough selection.
If you have a good idea generation process, you will have very many ideas to start with. Even after clustering and screening the ‘impossible’ ones there will be many ideas. Therefore such a first scorecard based expert selection is needed. However many raw ideas have unknowns and often differ much in maturity and specificity. This is a too feeble basis for conscious ‘go or no-go’ decisions and to start spending development money on it.
For such a decision, an underpinned evidence-based evaluation is needed that goes beyond opinion based scoring. And yes, this means that time and resources (i.e. attention and focus) should be dedicated to the further development and validation of the most promising ideas that passed the first screening. An investment that leads to the desired focus on only the most promising ideas.
Our approach in idea development and selection
The key principle of good idea selection is gathering the right information to enable evidence-based decision making. In our practice we use a well-tested and iterative approach that lets you uncover insights (the real unmet needs of the customer) that enable us to transform the idea into a solid value proposition bolstered by a winning business model. You can find more on this approach on: Developing innovations with winning business models
The essence of this approach is that the key assumptions of the ideas are validated with key stakeholders as fast as possible. The validation can be done in short sprints, by gathering further information about the ideas and validate the ideas with the customers.In this proven approach we focus on three types of validation areas (see also image above):
- Customer & Ecosystems area
To get real insights on market acceptance, ideas are validated as early as possible with customers and other ecosystem partners. This a crucial part of our approach and in line with the lean start-up method. In this area, we not only look at the customer or consumer needs and insights, we look also at insights and needs of the ecosystem partners and stakeholders, as well as competitive offerings and alternatives.
- Solution area
In this area the propositions are tested on the most critical (technical) hypotheses, e.g. can we really bring the proposed solution to the market, do we have the capabilities to develop it? Is our technology mature enough? Is the cost price within an acceptable range? Does it generate the benefits the customer gets excited about? In this part you can also source solution insights from (new) technologies, from start-ups, universities, suppliers or other industries.
- Business area
Also the business elements get evaluated early to determine if we can turn the idea into a viable business. Key hypotheses concerning the business model, strategic fit, and market size of the idea need to be validated as soon as possible. This includes a check on the strengths that we as a company can leverage, like our assets, technologies, channels, relationships, etc.
With these three areas, all key assumptions and hypotheses of the ideas are validated and (qualitative) data is generated to enable an evidence-based decision.
Final selection of ideas
Once the process described above has been completed, we need to establish if our idea has matured and has been validated sufficiently to be a candidate for final selection. Do we have enough (quantitative) underpinning of the idea? As always, this will differ case by case, but most data should by now be available to underpin the most critical assumptions.
The final step is to score all validated ideas and select the most attractive ones. To do that, a scorecard needs to be developed to determine the attractiveness of the ideas. This scorecard differs per company, and can even differ per business unit or product category within a company. Our recommendation is however to define differentiating criteria in all 3 of the validation areas: Customer and Ecosystem, Solution, and Business. Traditionally, many scorecards used innovation portfolio management practices comprise solution and business criteria, yet often lack criteria on the customer validation.
Once you have developed such a scorecard, test it first with actual and old ideas using historical data. This validates it serves its purpose: discriminating between good and not so good ideas. After the scorecard is adequately fine-tuned, the actual scoring of your ideas can start. Allowing you to select the most attractive ideas for your scarce resources to focus on.
Selecting the best ideas is not an easy process. By combining the validated learning approach from Lean Start methodology with proven selections methods used in portfolio management practices, you combine the best of two worlds. You will get more (quantitative) evidence about your idea through structurally validating the most critical assumptions. This elevates the scoring process from an opinion based exercise to an evidence-based method.
Looking forward to your comments, and let us know in case you want to learn more about this topic.
Want to learn more?
Want to learn about our approach to Developing innovations with winning business models or want to learn more about portfolio management?
For further information
Jeroen de Kempenaer
Value proposition, business modeling, business case, road mapping, portfolio management
Looking for digital business model development?
Find more information about developing innovations with winning business models, one of the focal areas of Industry Consulting, and check out our services in innovation management: