Point: Get quick wins by encouraging small experiments throughout the organization. They’re fast, inexpensive, and reduce the fear of failure.

Story: One of the biggest obstacles to innovation is fear of failure. Rarely do people want to bet their careers or companies on what might — or might not — be the next big thing.  But fear of failure becomes a self-imposed obstacle to success.

As Amazon’s CEO Jeff Bezos says, “Innovation is part and parcel with going down blind alleys. You can’t have one without the other. But every once in a while, you go down an alley and it opens up into this huge, broad avenue. And that’s so satisfying and, from a shareholder’s point of view, so successful, that it makes going down blind alleys worthwhile.”

The key twist isn’t to avoid failure but to avoid high costs from failure.  To reduce those costs, institute and encourage ongoing little experiments throughout your company.  For example, Google does this by testing more than 5000 software changes a year. Amazon does it by continuous A/B testing.  And CEO Scott Cook made experiments common practice at Intuit. In Cook’s experience, 89% of experiments don’t lead to a breakthrough or even to an improvement, but that doesn’t make them a “failure” — the experiments simply provide data on what doesn’t work.

These little bets cost little in terms of time and money. They don’t require weeks of planning; rather, they’re tweaks to an idea that can lead to eventual, substantive breakthroughs.  Ever hear of a company called Odeo? Most people haven’t, because Odeo was a small podcasting company of little distinction until its CEO, Evan Williams, gave employee Jack Dorsey two weeks to develop his idea of a short messaging system. That quick prototype developed into Twitter.

Action

• Don’t use uncertainty of success as a filter — the more you don’t know about your chances, the more you can learn by trying.
• Do consider how you might inexpensively look down a possible avenue to see where it leads.  You might use a A/B testing, co-innovation with a lead customer, or a quick minimum-viable prototype.
• Test fast, test often, but pay attention to the results, especially if the unexpected happens.
• Learn what you can from any failures — not just that the idea failed, but why it failed and what it says about your customers, your markets, or your business environment.
• Use each test of a new avenue to scout for other avenues. Even a blind alley can have a side-passage that leads somewhere wondrous.

For more information:

Dave Gray, The Connected Company

Bloomberg BusinessWeek, “Jeff Bezos: ‘Blind-Alley’ Explorer.”

Peter Sims, Little Bets and “What are Little Bets?“

Point: Presenting data visually reduces the mental resources we expend to understand a concept, thereby improving our productivity.

Story: Humans are naturally visual creatures. “Fundamentally, our visual system is extremely well built for visual analysis,” says Noah Lliinsky, author of Designing Data Visualizations and Beautiful Visualizations. We’re tuned to spot patterns.

Consider the Anscombe Quartet, created by statistician, Francis Anscombe. First, look at the datasets in Figure 1.1.

Figure 1. The x values are the same for the first three datasets.
There seems to be little difference between the datasets. But, when graphed out, we suddenly see differences.

Figure 2. Ascombe’s datasets when graphed.
Not only do humans like images, but we’re more efficient thinkers when we use them.  A study conducted by Mindlab International at The Sussex Innovation Center investigated how office workers manage existing data using traditional software and how efficient that process is. One of the key findings of the research suggests that when carrying out routine, everyday tasks in the office, if the data is displayed more visually, such as through visual maps, individuals are 17% more productive and need to use 20% fewer mental resources. What’s more, teams collaborating on a joint project use 10% fewer mental resources and are 8% more productive when using visualization tools, reports Mindjet’s Nicola Frazer-Reid.

Why is visual information easier to process? Verbal abilities developed much later on the evolutionary scale than visual ones. “We are well-developed in imagery for quick environmental awareness,” writes Steven Kim in The Essence of Creativity.  According to Kim, imagery has two main advantages. First, we can see multiple things in parallel. For example, we can see the body language of four people simultaneously much better than we can track four conversations at a party simultaneously. Second, we can grasp an image’s meaning faster, which accelerates productivity.
Action

• Use visual dashboards to show the status of projects at a glance, such as red/yellow/green indicators
• Use bar graphs and pie charts to show relationships. These visual cues help people quickly grasp the meaning behind numbers.
• Encourage people to sketch out ideas — even very rough drawings help make abstract ideas more tangible and easier for a group to react to and discuss.

Sources:

Source for Fig 1 and 2: http://en.wikipedia.org/wiki/Anscombe’s_quartet#cite_note-Anscombe-1 and Anscombe, F. J. (1973). “Graphs in Statistical Analysis”. American Statistician 27 (1): 17–21. JSTOR 2682899.

http://blog.mindjet.com/2012/05/fact-people-and-teams-work-better-with-visuals-so-what-can-you-do-to-benefit-from-this/

Point: Unlike the diminishing returns of the Experience Curve, Collaboration Curves offer continuous, exponential improvement and innovation through knowledge sharing and interactions among a group of participants.

Story: Most of us have heard about the Experience Curve, which traces how a company’s rising experience in making a product leads to declining cost of that making a product.  On average, the cost declines 20-30 percent each time that a company’s experience in making that product doubles. The Experience Curve, which has been systematically studied since the 1960s, holds true across a wide range of industries.  The sad flip-side of the Experience Curve, however, is that the rate of improvement declines over time because it takes longer and longer for experience to double.  It has diminishing returns.  Can anything be done to sustain the rate of improvement? Is there another way to keep on advancing? There is: Collaboration Curves.

Collaboration — in the form of knowledge sharing and interactions among a group of participants — improves the performance of all.  Before the internet, collaboration took place primarily face to face, along with some letter-writing between participants.  For example, in the 1870s, the art movement that came to be called Impressionism arose.  A group of young painters — Claude Monet, Pierre Renoir, Camille Pissaro and others — started meeting in cafes, talking and visiting each other’s art studios. They became a collaborative group; that is, they’d share their work in progress, talk about painting techniques, experiment with colors, and help each other learn and improve.

For example, the group broke with the tradition of black shadows.  They experimented with shadows painted in purple, deep blue or a mix of other colors.  Sometimes the shadows weren’t even that dark. This was a radical idea — no one had painted shadows in a different color before, but once one of the group came upon it, others adopted it as well.  They also expanded the notions of what could be painted. The subject matter needn’t be a religious icon, mythological scene, portrait of a nobleman or an allegorical landscape — it could be something as simple as a haystack or water lilies, painted over and over at different times or day or different seasons, showing how the light and color changes with the times and seasons.  Combining their experiences accelerated the Impressionists’ innovations in color, composition, brushwork, and subject matter.

Today, these collaborative groups can extend online, enabling people to talk and share with others anywhere, any time, thereby greatly — indeed exponentially — improving the group’s capacity to produce.  In the old model, the experience of any one person (or company) grew linearly with time, which created an Experience Curve with diminishing returns.  But a collaborating group can multiply experiences by combining lessons from the successes and failures of all to create a Collaboration Curve that sustains performance improvement.  The internet, social media, and collaboration platforms greatly enhance the Collaboration Curve by increasing the number of people who can collaborate, increasing the geographic span of people who can collaborate, and increasing the access to the accumulated experience of the collaborative group.

Collaboration Curves were first identified by John Hagel, who heads consulting firm Deloitte’s Center for the Edge in Silicon Valley.  “We’re seeing the emergence of a new kind of learning curve as we scale connectivity and learning, rather than scaling efficiency,” says Hagel in his Harvard Business Review blog (coauthored with John Seely Brown and Lang Davison).  “Collaboration curves hold the potential to mobilize larger and more diverse groups of participants to innovate and create new value.”

So far, examples of internet-enabled Collaboration Curves are more anecdotal rather than rigorous because of their nascency.  But Hagel has found that collaborative environments like the popular online game World of Warcraft offer participants a way to continue improving beyond what individuals could accomplish alone.  In the business world, similar collaboration curves take place on SAP’s software developer sites, and large open source projects such as the Eclipse Foundation.  What’s exciting is that “Collaboration curves may reverse the diminishing returns dynamics of the experience curve and deliver increasing returns to performance instead,” Hagel says.  The opportunity for interactions among the many participants lets performance continue improving through the continuing contributions of ideas by other participants.

Action: Hagel found that there are three prerequisites for these online collaboration groups to work and generate the Collaboration Curve effect.

• Attract Participants: First, you need people. That’s pretty obvious, that you need people to make this work. But what’s exciting is that the people don’t all have to be talking or active all the time – it’s perfectly ok to begin by just being an observer who lurks and learns from others. Indeed, in SAP’s software developer network (SAP SDN), most participants do just that — learning by reading the discussion forums before they contribute anything themselves.
• Interact: to get better results, you start interacting with others, in discussions — in person or online — sharing experiences, making suggestions, giving feedback. The more interactions, the faster the performance improvement.
• A supportive, multi-layered environment: Supportive means friendly and online.  It also means that the technology supports the interaction through discussion boards, archives, live chats, video.  Interaction must be easy not only among peers but among all cross-cutting groups. Digital infrastructure lowers interaction costs, enabling large, diverse groups of people to share information and learn from each other, driving performance improvements for all.