Point: Fast-cycle experiments let companies create the best product/service offering with the least risk.

Story: At the World Innovation Forum, Scott Cook, co-founder of Intuit, described his company’s culture of high-velocity experimentation. Intuit uses an experiment-driven decision-making process throughout the organization. Rather than expect executives and managers to know all the answers, Intuit uses large numbers of low-cost experiments to test new product, service, and marketing ideas.

To illustrate how high-velocity experimentation works in organizations, Cook described how the concept works in Intuit’s 20-person online TurboTax unit.  In the past, this unit ran about 7 experiments during the annual three-month tax filing season.  Now they run 140 experiments.  Not only do they run more experiments, but they run each experiment on a fast cycle so that they can accumulate results and grow more knowledge during each season. Intuit created a weekly cycle for developing, testing, and analyzing experiments that lets each experiment create new information that feeds into the next set of experiments the next week.

Fast experimentation also improves employees’ sense of engagement and ownership.  In the past when the 20-person team did only seven experiments per year, the average team member might only have one of “their” experiments run once every three years.  But with new high-velocity approach, each employee creates and tests a new idea once every two weeks.

Paradoxially, running more experiments and getting more failures lowers the fear and cost of failure.  When a company runs only a few experiments — and every change or new product really is an experiment — then each experiment matters a lot more to the company and to the employees working on that experiment.  If an employee works for more than a year on a single big experiment, then the failure of that experiment surely has an impact on the employee’s career, even if the company professes to permit failure.  But if an employee works on many quick experiments that steadily improve organizational performance, then the success or failure of individual experiments matters little.

In Intuit’s case, 89% of experiments fail, and yet the online TurboTax unit increased conversions by 50% and successfully created a widely-lauded smartphone app that lets people do their entire tax preparation — from taking photos of tax documents, to automatically putting numbers in the right boxes, to electronically filing their forms — all on a smartphone.  The hundreds of tiny experiments let the TurboTax unit tweak and test many variations to come up with the best offering.

Action

• Trust experiments rather than experts to find the truth in a dynamic and volatile business environment.
• Teach individuals how to perform cheap experiments by finding and testing the key assumptions behind every new idea rather than building one big new product.
• Use large numbers of low-cost experiments to both grow knowledge and improve employee engagement.
• Create an accelerated cycle of experiments to reduce time-to-knowledge and time-to-market.
• Coach executives to become experiment-seekers — to use experimentation as a key decision-making tool.

Point: Exponential trends in technology make the future more —  not less — predictable.

Story: At the World Innovation Forum in June, Ray Kurzweil, inventor of the first CCD scanner and author of The Singularity is Near, talked about the ease of predicting the future by spotting and extrapolating exponential trends.  Although Gordon Moore uttered his famous Law around 1970, Kurzweil found that the exponential trends in computation and data transmission predate Moore’s Law by many decades.  Moore spoke of the rate of evolution of semiconductor chips, but the trend started in earlier generations of computing and communications technologies including mechanical relays, vacuum tubes, and the first transistorized devices.  Even wars and depressions failed to halt the exponential progress in performance.  Trends in miniaturization and mass production meant information technologies improved at a steady pace across the decades.

Kurzweil noted that many people don’t understand the basic math of exponential trends.  When the Human Genome project had sequenced only 1% of the genome after seven years of costly labor, many cited the lack of progress as evidence that the project was doomed.  Yet the sequencing project was riding an exponential trend in the performance DNA sequencing methods.  Instead of taking another seven years to sequence a second 1%, they reached it after only one year. Then they reached 4% in about another year, then 8%, 16%, and so on.  It took about as much time to sequence the last 99% as it took to sequence the first 1%.  That’s the nature of exponential trends — they seem to start glacially slowly but finish lightening fast.

This trend continues unabated.  Along with exponential performance improvement comes an exponential drop in cost and an exponential rise in use.  What once took a billion dollars per genome is now costing a few thousand dollars per genome. Soon, scientists expect to have one million human genomes sequenced.  If genome sequencing is cheap enough, it can be used on every person, every cancer cell, every agricultural product, every bacteria, every virus, and even every pet. As performance hits key thresholds or cost drops below key thresholds, new applications can arise at predictable times.

What makes the future predictable with exponential trends is that we can estimate the crossing points when something becomes good enough, cheap enough, or valued enough for widespread use and new applications. Search engines arose from both the growing demand for finding websites in the exponentially growing World Wide Web and the declining costs of computer servers needed to offer a “free” search engine. Likewise, social networking arose as connectivity costs dropped, connectivity increased, and computer prices dropped.  Kurzweil said we may not be able to predict which company will rise like Google or Facebook to dominate some new application, but we can predict that such an application will become feasible and then widespread due to the confluence of exponential trends.

Action:

• Watch for exponential trends in underlying technologies, in which performance steadily doubles every few years or so or prices continually drop every few years or so.
• Look for crossing points where the speed or cost of doing some task — that’s outrageously expensive or abysmally slow today —  becomes affordable and timely.
• Think about new applications that might be possible if something is cheap, fast, and widely available. What happens when everyone is online via a mobile device 24×7? What happens when everyone knows their DNA sequence?
• Convert problems that don’t seem to have exponential performance improvement trends (i.e., healthcare) into ones that do (i.e., genome sequencing, patient databases, mobile app-enabled health sensors, self-care social networking, virtual models of diseases, etc.)

Point: Provide customers with toolkits to help them create new products and services.

Story: I’m looking forward to hearing Henry Chesbrough, originator of the term “open innovation,” speak at the World Innovation Forum tomorrow.

In his latest book, Open Services Innovation, Chesbrough writes about co-creating with your customers, particularly in services where it’s harder for customers to specify what they want because so much of the experience is tacit.  Whereas innovative physical products can excel on objective measurable performance, innovative services often entail a greater degree of subjective perceptions.

What’s exciting for innovators is that precisely because the information is tacit, finding ways to elicit or manage that tacit information will bring strategic advantage.  One way that customers can “tell” you this tacit information is through their behavior, which in most cases is through their purchase and usage patterns. If customers have a good subjective experience, they do it again; if the service was bad, they don’t come back.  Yet passive observation can be hard to interpret, can miss a lot, and is better at providing feedback on existing offers than for creating true innovation.

A better solution is for companies to actively encourage open feedback and ideas from customers.  As Chesbrough says, “When customers tell you – rather than everyone else — their tacit needs, you have a unique insight that can help you differentiate yourself in the market.”  Companies that can find ways to engage customers to co-create — or that can create systems that elicit such tacit knowledge — accrue benefits. LEGO, the building-brick toymaker, is one such company.

LEGO created a software toolkit and online space for customers to create and share new designs that go far beyond what’s possible with the manufactured physical product.   The components of the toolkit and space include “LEGO Digital Designer” software, “My LEGO Network” for children, and a 4.2 million-member LEGO Club.  The social media elements, design contests and customer-created galleries let LEGO fans of all ages build and share ideas.

In turn, LEGO gains tacit information into what customers really want to build, which supports LEGOs product development efforts.  For example, LEGO got the idea to sell kits of leading architectural designs from around the world, such as the Empire State Building, the Taj Mahal or Frank Lloyd Wright’s Fallingwater home. Not only were many of these designs created by users, but LEGO gained entry to a new market — adults — which it had not envisioned nor would have initiated internally.

What Chesbrough is talking about is a kind of meta-innovation — an innovation in the innovation process.  Open services innovation converts innovation from an internal process into an external service.  Providing customers with a toolkit for self-expression not only satisfies customers but also creates an incoming flow of tacit knowledge about customers and about new ideas that may be more widely implementable.

Action:

• Watch the trail of breadcrumbs left by customers to uncover tacit knowledge and subjective performance indicators
• Actively solicit feedback to understand why customers do what they do — and what they want you to do.
• Create a toolkit or sandbox where customers can create their own products and services
• Make innovation an external service your company provides to customers

Sources:
Special thanks to Walden University for sponsoring the May 8, 2012 webinar with Henry Chesbrough as a prequel to his presentation at the World Innovation Forum.