Point: Use visual representations to spur innovative thinking.

Story: Scientific visualization is typically used to communicate data and scientific results, but it can also spark ideas.

Felice Frankel is a scientific photographer who works with scientists across many disciplines — chemistry, biology, oceanography, and so forth. As she sees it, the various disciplines share similar ways to represent data. But, “Unfortunately, you rarely see scientists from different disciplines talking with each other,” she says.

Images can jumpstart communication by creating a common language among different disciplines. What’s more, images can spark new ideas, even if those images are of data which you yourself have been working with for years. Seeing your data presented in a new way can yield new insights. The new depiction gives you a new perspective.

For example, in one project, Frankel was exploring how to show glowing nano-crystals suspended in liquid. She zeroed in on an abstraction that cropped the top and bottom off each glass cuvette of the nano-crystals. The resulting image removed all visual references to the nano-crystals’ containers. After seeing Frankel’s photograph, Moungi Bawendi, an MIT scientist who’d been working with nano-crystals for years, thought of a potentially new application for them because the new image reminded him of a colored bar code. Bar codes are used as a form of labeling. Seeing the nano-crystals arranged like a bar code gave Bawendi the idea to use them as an alternative to fluorescent organic dyes that scientists currently use for labeling, imaging, and monitoring biological systems, particularly in their response to cancer.

In addition, the visual language of pictures and graphics breaks down the barriers of jargon, discipline-related terminology, and language, making it possible for non-experts or non-native speakers to provide input and collaborate. The visual language “allows us to talk to each other about an image, point out parts that are interesting or beautiful, and ask questions without hesitation,” Frankel says.

Similarly, for David Macaulay, drawing is his way to figure things out, to question, clarify and think about things.  Macaulay, bestselling author and illustrator of The Way Things Work and 24 other highly-illustrated books, says: “When you draw something, you really have to look at it. And when you really look at it, you can’t avoid thinking about it.”

Macaulay’s books are primarily images, interspersed with words. “How great is it to have those two languages to work with and pick and choose from?” Macaulay says.

I’m looking forward to meeting Macaulay and Frankel at the Business Innovation Factory’s annual summit on Sept. 19-20, 2012. The summit is almost sold out (it sells out every year), but a few seats remain available as of this posting.

Action

• Look at images from different disciplines to see new ways to present your data or visualize the problems and solutions that you work on.
• Create images with different arrangements, even abstractions, of your data or system to reveal new patterns in your data or ideas.
• Ask people what they see in your images, whether it’s patterns, beauty, or metaphors that can spark new ideas about your area of work.

Sources:

Felice Frankel’s new website: http://visual-strategies.org

Felice Frankel and Angela H. DePace, Visual Strategies, Yale University Press, 2012

Deborah Halber, “Smarter Quantum Dots,” MIT Spectrum, Fall 2011.

Tim McIntire, Felice Frankel: Scientific Discovery Through Visualization

Frankel, Felice. “The Power of the ‘Pretty Picture,’” Nature Materials.

http://www.felicefrankel.com/

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: Experiment with new business models in a “connected adjacency” before committing to them.

Story:  Saul Kaplan, founder of the Business Innovation Factory (BIF), just wrote a new book, The Business Model Innovation Factory.  Kaplan shares 15 business model innovation principles, weaving in his personal experience (from Eli Lilly to Accenture to BIF) as well as experiences from numerous presenters at BIF’s Collaborative Innovation Summits. My favorite chapter in the book was “R&D for New Business Models.”

In the chapter, Kaplan describes how to deal the challenges of testing a new business model.  Organizations can’t easily jump from an entrenched business model to a new one.  There’s too much support for the old model and too many unknowns about the new one.  The solution is to test the new business model in what Kaplan calls “connected adjacencies.” A connected adjacency is like a real-world sandbox or living lab. For example, Kaplan details how Accenture changed its business model from being a systems integrator to being a business integrator.  Accenture (Andersen Consulting at the time) started to rapidly build a strategic capability alongside its existing systems integration business. As Kaplan writes,

“It was a connected adjacency that was given the autonomy and resources necessary to scale a rapidly-growing strategy practice from scratch – right next to the huge systems integration practice.  We were an entrepreneurial business unit within the context of the behemoth. The emergent strategy practice would never have worked if it had to live by the rules of the core business model at the time.  If not protected, it would have been swallowed alive by line partners from within the core business model. The new business model needed to be shielded, at least temporarily, within the relative safety of a connected adjacency.”

Part of the success of experimenting in a connected adjacency is letting employees self-select to participate.  In Accenture’s case, the company went so far as to hire partners directly from outside the company – something the company had never done before in its “promote from within” philosophy of the past.  The connection between the existing business and the innovation sandbox is vital, however, because it lets ideas and experiences be transferred between the two spheres.

In another example, Kaplan describes Babson College’s creation of Babson Global, an entity separate from Babson’s core business model that serves as an R&D platform for creating, prototyping and testing new approaches for teaching entrepreneurship and creating entrepreneurial ecosystems in communities worldwide.  The entity is separate from the college but adjacent to it – faculty and staff from the college self-select to participate.

Action:

• Nurture the new business model in a “connected adjacency” — a sandbox, living lab, or side unit of the main business.
• Protect the developing new business model effort from the old model’s metrics and pressures.
• Allow staff to self-select or volunteer for the new model, or hire outsiders so that you have open-minded enthusiasts for the new model rather than adherents to the old.