- Written by Juan Antonio Solares
Many people think that innovation is about generating ideas. In our previous articles we discussed how structures must exist that allow ideas to reach decision-makers, but it is not enough to merely come up with new ideas—this is only the “front-end” of innovation. Since ideas must be executed in order to generate value, a “back-end” of innovation is required to test and refine the ideas and make them a reality. The unit of execution of innovation is not the idea itself, but a project derived from the idea. Many people can claim to have innovative ideas, but only the ones who actually implement them can claim to have innovated.
Not all ideas can be implemented though, because there are limited resources. Organizations must choose wisely which ideas they will focus on, given the resources they have. Ideally, they should focus only on the ideas that will succeed and have a large, positive impact, but without a crystal ball it is difficult know which ones to place the bets on. Despite the best predictions, when ideas are put into practice, they collide with many unforeseen variables, and can turn out very differently from what was expected. This is where the “back-end” of innovation plays a crucial role: ideas can be tested and refined before they are executed, either increasing their likelihood of success, or proving early on that they will fail so as to avoid costly investment losses. This testing and refining is done through lower-cost experiments that prove (or disprove) feasibility, demand and profitability.
Creating this “back-end” of innovation has two components to it: first, organizations must create a culture of experimentation and learning, and second, employees need support in designing and executing experiments. The first key component is creating an atmosphere where experimentation is encouraged and failure is seen as a lesson learned rather than a finger-pointing opportunity. Many organizations want to avoid failure at all cost—creating a culture where ideas are not executed unless all possible risks have been eliminated. But in the world of innovation, lessons learned from failures are critical to building successful breakthrough businesses. This makes failure more of an asset than a liability, especially in the early stages of idea implementation.
Dr. Patel from IXL Center, explains that "leaders have to tolerate failures and employees have to take risks. We need to create a culture of learning similar to that seen in kindergarten – or, in a research lab. In either place, kids or scientists learn by experimenting, by trial and error. They are passionate, patient and persistent. Out of ten tries (experiments), they may both find one success. But neither the kid nor the scientist would say that they had nine failures. Instead, they say that they had nine learnings that allowed them to get the one success."
A great example of such a culture is Alcoa. Paul O’Neill wanted Alcoa to become a safe company. For this he created a culture that emphasized learning and experimentation: even though they wanted to become the safest company, when employees made mistakes it was more important for them to report them so that the rest of the company could learn how to avoid those mistakes and others as well. In one instance, O'Neill fired Alcoa's best division president because "one hundred fifty people [...] succumbed to carbon monoxide fumes and had to be treated at an emergency clinic. The incident was never reported, so others at Alcoa were not informed nor able to learn from the accident" (Paul O'Neill: Values Into Action, HBR Working Knowledge). Alcoa managed to fulfill its goals because of this culture that placed great value on learning and experimentation. It is in this environment where ideas can flourish and become a reality.
Even with a culture of experimentation and learning, employees still need support in knowing what kinds of experiments to run, and often need resources to run them as well. A good place to start is with the aspects of the idea that are most uncertain. For some ideas, there will be a lot of uncertainty around their feasibility: Can it be produced and are we the best ones to produce it? For other ideas, the uncertainty may lie more around demand: Is there are a market for this and are they willing to pay for it? Other ideas may have uncertainty around the profitability: Can we produce it cheap enough and sell it at a high enough price to make it worth it? Employees must be able to determine the biggest uncertainties, and design experiments that will address those uncertainties.
Experiments can range from simple phone calls to lead customers to sophisticated working prototypes. A good place to start for reducing uncertainty around feasibility is making mockups and prototypes, getting feedback from others on the look and feel, signing NDAs with potential partners, and running demonstration projects that show that certain expectations were achieved. A good place to start for reducing uncertainty around demand is making a brochure that clearly states what you offer and what the advantages are, getting feedback from lead customers, and getting advanced purchase orders from clients. A good place to start for reducing uncertainty around profitability is getting cost estimates from producers, margin estimates from distributors, and feedback from potential customers on what it currently costs them to solve the same problem through alternate methods.
Increasing the likelihood of success of ideas is an iterative process in which rapid feedback from small successes and failures is used to transform the idea into something that has high feasibility, strong demand and will have a positive impact on the organization’s bottom line. It is important to give failure the value it deserves—a tremendous source of insights that will ultimately lead to success. As Henry Ford once said: “Failure is simply the opportunity to begin again, this time more intelligently.” Innovative organizations need to create space and provide resources for their employees to experiment with ideas, take risks, fail fast, learn from mistakes, and iteratively refine ideas until they are ready to go to market.