Sunday, August 31, 2014

Learning Without Logic

After Napster was shut down in 2001, the brand was reborn in 2003 as a subscription online-music service run by Roxio’s Chris Gorog. Chris and his team quickly amassed a large catalog of songs, enabled radio streaming, established partnerships with online platforms like yahoo, built an entrepreneurial organization, and expanded internationally. As record stores became history, Apple’s iTunes, illegal music downloads, and a few subscription services like Napster offered different visions of the future. But by 2005 the verdict was in. Illegal downloads continued apace, iTunes was a clear success, and subscription services were not. As one Washington Post writer put it (in 2005), Napster’s subscription model was not a viable alternative to music ownership: “When music is good, you want to know that it can’t be taken away from you.” The final nail was Steve Jobs' declaration: "Nobody wants to rent their music." The experiment had been run, and the music ownership model beat subscription services.

But wait. As of 2014, with the explosive growth of services like Pandora and Spotify, the pundits are now saying that subscription models are the future. Even Apple is launching such a service. What about the lesson we learned from the failures of just a few years ago?

The problem here is that a failure is a datum, not a logical argument. Data do not speak for themselves. Failures can have various causes, and so it takes logical reasoning to explain why failures happen. Perhaps the early subscription services were ahead of their time, such that limited bandwidth might have made them less attractive than they are today. Or maybe the smartphone is a necessary complement to such services.  Whatever the diagnosis, logic is required to sort out why firms succeed and fail.

Unfortunately, most observers skip the logic part. It is mentally easier to jump to the “obvious” conclusion: If the business failed, the business model must be wrong. Full stop.  You can easily tell when this skip happens. The person will name an example as if it were a reason. Is online grocery delivery a viable model? No: Webvan. Is internet search a viable business? No: Alta Vista. These examples are data, not logical reasoning. But it is hard to rebut those who argue by citing examples, because you look the fool trying to say that a failure somehow might have made sense. Like Gerald Grow’s cartoon, we replace reasoning with dueling examples: I shout “iTunes!” you reply “Spotify!”


The result? We often “learn” without logic, and so we often walk away from great ideas. The Apple Newton failed, leading many to say that there was no market for smart handheld devices - yet now we all own them. Early attempts at remote alarm systems failed, leading many to conclude that such services could not be profitable; now they are commonplace. Even internet search, possibly the most lucrative business in history, was initially panned after a spate of failures among early movers – Lycos, Alta Vista, Excite, and others. Often firms fail.  But that may not mean, logically, that we should abandon their business models entirely.

To diagnose well, we need to systematically contrast failures and successes - as is done in good academic research. The popular maxim “fail fast and cheap,” A/B testing, agile development, root-cause analysis and similar approaches are designed to show us successes and failures without destroying the firm. These techniques routinely are used in Silicon Valley firms these days, and are making their way into the global business lexicon. Sometimes such techniques are very effective for learning. But keep in mind that these techniques simply provide us with data. It is up to us to explain the data, and that requires logic.


The academic research on this topic can be found in the research of Jerker Denrell.