The first is a profile of Duncan Watts from Fast Company. The article looks at the question of whether or not you need to spread ideas primarily through targeting superconnectors, an idea put forward by Malcolm Gladwell in The Tipping Point. Watts suggests that peoples’ tendency to be receptive to new ideas has a greater impact on whether the idea spreads than who starts spreading the idea does. This result is very similar to the findings of our colleague Andrew Stephen.

This has some interesting implications. One is that ‘Influentials’ actually aren’t any more effective at sparking trends than normal people. This leads directly to the second point, which is that ideas spread most effectively when the time is right. Taken together, this makes it very hard to predict which ideas will spread, and it also makes it difficult to develop a strategy to make your ideas go viral.

I think that the best response to this is actually to approach innovation alogorithmically. What this basically means is that the way to innovate is to generate a lot of ideas, figure out ways to try them out cheaply and quickly, and then scale-up the ones that seem most promising. The FC article describes an advertising strategy devised by Watts that functions very similarly to this, and I think that it is the way to go.

The second article that caught my eye was Atul Gawande’s New Yorker piece on health care reform in the US. In assessing the bill that the Senate passed last night, Gawande applauds the way that this experimentation mechanism is built into the bill. It does not specify precisely how the new health care system will function, rather, it provides a platform for encouraging experiments and a path for getting the best new ideas to spread. Gawande describes how this approach worked during reform of the US agricultural system at the start of the 20th century, including the efforts of Seaman Knapp in Terrell, Texas:

Knapp knew that the local farmers were not going to trust some outsider who told them to adopt a “better” way of doing their jobs. So he asked Terrell’s leaders to find just one farmer who would be willing to try some “scientific” methods and see what happened. The group chose Walter C. Porter, and he volunteered seventy acres of land where he had grown only cotton or corn for twenty-eight years, applied no fertilizer, and almost completely depleted the humus layer. Knapp gave him a list of simple innovations to follow—things like deeper plowing and better soil preparation, the use of only the best seed, the liberal application of fertilizer, and more thorough cultivation to remove weeds and aerate the soil around the plants. The local leaders stopped by periodically to confirm that he was able to do what he had been asked to.

In a very poor year for cotton, Porter’s profits jumped substantially. This led him to use the new ideas over his entire farm. Many other local farmers followed suit, and the federal government gave Knapp more funds to expand the program. This was happening all over the country, and it transformed the agricultural industry – first in the US, then around the world.

So, again, try things, figure out what works, then scale up. That’s an innovation algorithm that works.

Note: If you’re reading this and you feel bad about thinking about work in the middle of the holiday season, remember that we’re just doing what Chris Brogan is telling us to do: