NOTE: this post and the following are part of an experiement I’m conducting with dictation and delegation. You may find that my writing style is different (more conversational?). I want to know if that bothers you, if you perceive it as a quality dropping. Let me know in the comments!
This is my review of ‘The Myths of Innovation’ by Scott Berkun. If you have been following academicproductivity.com for any amount of time, you know that we really like Scott Berkun’s books. We have reviewed his former book called, ‘The Art of Project Management’ (TAPM). I think this book is important for anyone who is aiming for a good output in academic productivity because the book tries to
answer a very important question, which is ‘how can I be more innovative?’ Since innovation is an important part of science, I think this is an important book to read.
One note though; you may be working on a very basic area of knowledge, and you or may not even consider that your work could produce any applied results. It is true that this book considers innovation in a way that is closer to invention: that is, a finished product that somebody can use. If you are not in the ‘applications possible’ group, I still think that it is a good book to read for you, just because it’s going to treat topics that are important for you people doing basic research.
One of the points of the book is that an idea is not an invention, unless you can actually implement it and get something ‘out there’ with your idea. Berkun covers several inventors like Edison, who produced quite a lot of work in terms of ideas and patents, but they only implemented and managed to produce inventions for a few of them. I think this is interesting, because in today’s world most ideas can be implemented with minor costs, for example in software. You can quickly put together a prototype for a software project, even though it may not be the best implementation, to test your idea.
I think this condition of contemporary science separates it from other conceptions that are captured in history books: there, inventions are difficult tasks. For example, if you wanted to create an apparatus, something that flies for example, the initial costs are very high. But nowadays, most ideas can be implemented in software (debatable, I know, but the space of ideas that can be tested as software is large thanks to people spending most of their waking time on a computer). This is great because software doesn’t have such a high cost for starting the production of something like a plane or a machine that can fly, when nothing like that existed.
I think this is a much better book than the previous one about project management, even though the first one was absolutely great. And Scott himself is surprised because this book being a lot better is not selling more than TAPM. Although this is a wider topic it didn’t outsell the previous book. This is one of the mysteries of writing a book. Berkun has been giving talks about this book and promoting it any way possible for a few months (!).
One of the interesting ideas that I got from this book is that finding a problem, and delimiting what your problem is, is actually more important than solving the problem. Berkun’s example is Newton. He spent quite a lot of his time chasing a completely unsolvable problem: He tried to find the philosophical stone that could turn lead into gold, which is a useless, unproductive scientific problem. I wonder how many of our areas’ hot topics right now will be looked down a few years from now, assimilated to the search for the philosophical stone. All this time that Newton spent trying to solve that problem was completely wasted. Berkun also quotes Einstein, who arguably spent 19 days out of 20 trying to define the problem instead of solving it.
I will cover the main ideas chapter by chapter.
Chapter One is called, “The Myth of Epiphany.” What Berkun says is that there is no such a thing as an ‘Aha!’ moment, a great crazy idea that solves everything. He advocates that work is all that it takes to get to good ideas, which is probably a very comforting thought. In that, he agrees with Paul Silvia, whose book we just reviewed. Paul says that we ,as scientists are not writing poems, we are not writing literature, so we don’t have to wait for inspiration. Our work is sort of easier to schedule and we don’t depend so much on inspiration, which is a great.
Chapter two goes against the myth of our understanding the history of innovation. So Berkun says that we actually don’t understand the history of innovation, and it is not easy to just look back at history and see which innovations have been a success and why. The example he uses is the printer by Gutenberg. Gutenberg didn’t reach fame until well past his time. Unlike Michelangelo and Leonardo da Vinci, he was not considered an important figure in history until pretty late in life; its just due to chance that we keep some information about his personal life, for example.
The history of the printing press is actually a very good example of how much implementation matters. You can have the most wonderful idea in the world, but if you don’t implement it, then nothing really happens. In the case of the printing press, the Chinese had invented movable type long before Gutenberg, but Gutenberg was lucky enough to actually implement it and get it to the point where it was popular enough and effective enough, to actually make him some money. But the point is that, you don’t have anything until you have an implementation – a working implementation. So, the success of the printing press in Europe is due to Gutenberg, not to the Chinese, who actually invented the printing press.
Chapter Three is called ‘There is a method for innovation’. Berkun says that we actually don’t have method of innovation; we chase something completely different and we serendipitously reach an innovation. Sometimes the great innovators are chasiing wealth and money (i.e., Edison). Some other times it’s necessity or curiosity. There are plenty of factors that can affect whether you reach an innovation or not. Berkun lists some challenges for innovation: you need to find a problem, then you need to develop a solution, then build something, and those three are completely important for academics. Then the next few are more about actually implementing your idea and reaching the public.
Another interesting idea of this chapter is that the probability of innovation is really small, just because it is a combination of all the factors that he lists before.
So, assuming that you have a 50% chance of succeeding at each of these challenges, which is a pretty generous assumption, you need to combine all those priorities, so if you have 0.5 priority of succeeding on eight steps, then the total chance of succeeding is well actually pretty much like 0.39%; that is, less than one percent.
Chapter Four, “People adopt new ideas.” Berkun says that this is completely wrong; people have to be pushed away from this status quo before they start liking something new. One example is electricity; when electricity was first introduced, nobody thought that it was solving any problem. So, the main issue was, ‘No one will want this’. Of course, being unprepared for this, the first electric chair was built to demonstrate that electricity had uses.
Another interesting point that Berkun makes is how innovations diffuse. After realizing that it is very difficult to implant any knowledge in a field, Berkun points out five factors that are important. One is the relative advantage of the new idea compared to the status quo. Two is compatibility – how much effort is required to transition from the current thing to the innovation? Three, complexity; find out if you need learning to apply the new idea, if so then people are not going to do it. Four is Trialability, that is, how easy it is to try the innovation? And fifth is Observability; how visible are the results of the innovation? The more visible, the easier it is for people to adopt the innovation.
Chapter Five is about the Lone Inventor. Berkun says that there is no such a thing as a lone inventor, that any new invention is just the end of a change of smaller inventions, and most things are actually invented by teams. For example, NASA didn’t put a man on the moon by just using the talent of one single person, it’s was a huge team who actually achieved this.
Chapter Six, “Good ideas are hard to find”. So, this is yet another nail in the coffin of how important implementation is. Good ideas are a dime a dozen, so what you really need to do to prove that your idea is good is to implement it and compare it with other ideas, and prove that it is a better idea IF it provides a better solution to the problem.
One important point here is that finding good ideas can be done by very different ways. Figure 6.4 is actually a graph of how people find ideas. So this was our recent survey of over 100 self-identified innovators in various fields, and interestingly most people, about 70% say that they look for areas in different fields from their own, this is actually key: so next lunch break, go to the cafeteria with people from a different department
Chapter Seven, “Your boss knows more about innovation than you”, we’d want to skip this one. We have no boss to speak of .
Chapter Eight, “The best ideas win”. So, this is a kind of, a mix here between moral and ethics and how people are used to movies in which the good guys always win and so on. What Berkun proves here is that this is actually not true. For example, Beta was a much better video format than VHS, and VHS won. For example, the QWERTY keyboard design was actually uncomfortable for everybody typing but it’s winning over other designs like the DVORAK alternative. Just because it was designed so the typing machines won’t jam. Another example is Metric systems, like the European Metric system compared to the American system of foot, gallon, mile. Actually the United Kingdom is using this system supposedly now, although most people still use the old one.
Chapter Nine, “Problems and solutions”, it’s again about the point I made before, how finding a problem is more important than solving the problem or it should take a lot more time than actually solving it.
Chapter Ten is “Innovation is always good”. Here, Berkun shows some examples where innovation wasn’t always good. For example DDT actually always terminates on plagues but it ended up being an ecological disaster; same for some inventions like automobiles made by the Internet because we had spent a lot of wasted time reading stupid things.
One last thing that I wanted to say about this book is that it has a very innovative way doing references. It has an annotated bibliography and it has also a ranked bibliography; that is, Berkun ranked books he used by how many ideas he took from each of them. This is actually a pretty interesting idea that we academics should explore.