The long tail of ideas

It’s not clear how you measure the size of an idea. Is it billions of generated revenue? Is it number of papers published? Number of citations? Brain-ounces (whatever that is)? But, let’s say that based on any or all of these measures, some ideas are big and some are small. The long tail applies here too: a few ideas make it big, but most of them remain small. But how do we find these big ideas?

I’ve heard the following piece of advice several times over the past few years, and more recently in a talk by one VP. It goes something like this: “Find an idea an ask yourself: is the potential market worth at least one billion [sic] dollars? If not, then walk away.” This is very similar to something I read in one of Seth Godin’s riffs, about a large consulting company recommending to a large book publisher that they should “only publish bestsellers.” They would, if they knew in advance which books would be bestsellers. But, in reality, this advice is simply absurd.

For example, who thought back in the 90’s that search would be so important, with search marketing worth about 10 billion and expected to exceed 80 billion within 10 years? Nobody, and perhaps following the above advice, projects such as CLEVER and it’s follow-up (which put a “business intelligence” spin to search), WebFountain, went nowhere. The only thing that went somewhere is the researchers; they moved to Google, Yahoo! and Microsoft.

When I onced talked to someone from WebFountain, two things he said struck me and I still remember them after several years. First, the cost of crawling a reasonable fraction of the web and maintaining an index was quite small (a handful of machines, a T1 pipe and maybe one sysadm). Second, it turns out that back then WebFountain received some flak for “starting small.”

In other words, the engineers seemed to recognize they were starting at the far end of the tail, and decided to put some wheels on their idea and see how to move it up towards the head, growing along the way. But management wanted more to justify the project. Four wheels is just a car, but how about four hundred? “Is this something really big or isn’t it? If it is, then why 10 machines and not 300? Why 5 people and not 50? Why just make 3 features that work, instead of design and advertise 30 or 50?” As far as I can tell as an outsider, this is what happened and such an over-planning (combined, perhaps, with rather poor execution on the development side) did not lead to the expected results.

Perhaps such a mentality would have made sense a few decades ago, when computing power was far from a commodity, barriers to entry were large, and supercomputing was thriving. These days however, instead of asking “how much is this idea worth”, it’s better to ask “how much does it cost to try this idea?” and strive to make the answer “almost zero.” You don’t know in advance what will be big—that was always true. You should not start big because it’s not cost-efficient—that was not always possible, but it is today. Start big and you will likely end up small (like countless startups from the bubble-era); but start small and you may end up big. Google just appeared one day and did only one thing (search) for many years; Amazon sold only books; and so on.

Barriers to entry should not be made artificially high. Some companies seem to recognize this better than others (although this may be changing as they grow), and strive to provide an infrastructure, environment and culture that makes it easy to try out many new things by starting small and cheap. And other companies are enabling the masses to do the same.

I’m not saying that you should try every idea, even if it seems clearly unpromising. I’m also not saying that any idea can become big or that, once an idea becomes big, it will still cost zero to scale it up. But, technology, if properly used and combined with the right organizational structures, allows more ideas from the long tail to be tried out, at minimal cost. You’re expected to fail most of the time, but if the cost to try is near-zero, it doesn’t matter.