In new product concept development, iteration is a well known and frequently practiced technique used by many companies in their new product development process. Small teams typically build concepts, get qualitative or quantitative feedback from consumers, refine concepts, get another round of consumer feedback and so on, until they arrive at a “winning” concept.

This technique works well enough getting periodic consumer feedback and constantly refining concepts does improve their appeal―hence, it’s popularity and adoption throughout the new product development community.

Product Innovation and the Future of Iterative Development

However, the future will most likely be different―and with better product innovation. It will consist of not just iteration, but “iteration at scale.” Iteration at scale means developing and testing not just a few concepts, but tens or hundreds of thousands of them.

To iterate at scale, you need three things:

  • More people developing concepts.
  • More functions involved in their development.
  • Many, many more concepts.

With these three things in place, results are dramatically better. Why?

First, we know through experience that diversity and collaboration yield much better results in concept development, all things equal. The larger the development team and number of functions building concepts, the higher the concept scores.

Second, finding a winning concept is a numbers game. The more concepts tested, the more likely you’ll find a winning, high scoring concept. Sports provide an apt analogy: more at bats yield more hits, more shots mean more baskets, etc. The key to this product innovation is simply developing lots and lots of concepts.

The Challenges of Iteration at Scale

Iteration at scale today is hard for several reasons:

First, it’s hard to involve large parts of the organization in creating and building concepts. Typically, concept development is handled by a team of only two people in a single function. In a recent Nielsen industry survey, two out of three “front line” CPG professionals ranked collaboration as a top five critical factor to product innovation success, yet one in three lacked confidence in their company’s approach to collaboration. Collaboration is hard because people are pressed for time, it’s a burden to incorporate everyone’s input, people often disagree (which creates conflict), and no project leader likes to yield control to people with less perceived experience or expertise.

Second, there is a very real limit to how many concept iterations can be done―in both time and money. The sequential nature of the typical iterative development process creates its own bottleneck. For example, if a small team creates 10 concepts in a week, and gets consumer feedback a day later, you can only test and refine about 40 concepts in a four-week period. While forty concepts may seem like a lot, we know from experience that the more concepts tested, the better the results. If forty is good, 400 will be better, and 4,000 even better than that.

The ingredients of concept success are clear. You need to dramatically:

  • Increase the number of people building concepts.
  • Increase the number of functions involved in building them.
  • Increase the number of concepts created.

A New Product Innovation Approach Utilizing Technology and Math

But how? With collaborative technology platforms and evolutionary algorithms.

Collaborative Technology Platforms―Technology is enabling collaboration at scale. Product development teams anywhere in the company or the world can collaboratively create concepts. New platforms enable a single “owner” to incorporate input and feedback from many people across many functions.

Teams input concurrently and feedback is not dependent on linear email or document review. Contributors can input right into the system―which means the project lead gets out of playing middle-man. The project lead controls who can be a collaborator, has the ability to accept or delete comments and suggestions, and decides when the creative process is “locked.”

Collaboration becomes fast, easy, and simple.

Evolutionary Algorithms―The concept of Darwinian evolution and the survival of the fittest can be applied to concept development and product innovation, too. It starts with a different approach.

Instead of building discrete, integrated, and complete concepts the old fashioned way, teams spend their time developing an expansive range of concept “component parts.”

Rather than arguing and debating which concepts to test, teams simply let an evolutionary algorithm construct the optimal concepts. And not just forty or 400 or 4,000, but 400,000 or more. The algorithm exposes all possible combinations of accepted consumer beliefs, benefit statements, reasons to believe, etc., to consumers via a choice method. It sifts through all possible combinations of concept options, discarding the weaker ones, finding the stronger ones, until, at last, you have two to three fully optimized concepts against several target audiences.

The Benefits of Collaborative Platforms and Evolutionary Algorithms

All of this sounds like good product development, but the proof is in the volume potential of concepts built with “iteration at scale” versus those built the traditional way. Data from Nielsen shows that taking full advantage of collaborative technology platforms and evolutionary algorithms yields concepts that, on average, yield 38% more volume potential. And for an industry with a new product success rates of 15% to 20%, that’s a much needed iteration in how to be more successful.