There has been a lot of talk about the “disruptive innovation debate”. In an article for the The New Yorker, Harvard historian Jill Lepore attacked Harvard business professor Clayton Christensen’s well-established theory of “disruptive innovation”. She claims it “doesn’t explain change”.
The debate, which resulted from this article, might have given you some food for thought about disruption. You way also be wondering who is right or wrong in this debate. Yet, this is not what we will be discussing in this post. There isn’t a publishing company or blog who hasn’t already taken a position in this debate. Most of them are in favor of Clayton Christensen, for good reasons, as I think. You will find references on the discussion at the end of this post.
There is something else to this debate. See, what puzzled me when I followed the debate is why two high caliber academics with top-notch credentials can have so different views on the relevance of a well-established framework. In a way, the views in this debate resemble two types of decision making processes I have seen among investors. As a result, looking at how the approach of two top-notch academics differs can offer us a lesson for our decision making process as investors. A look at football/soccer World Cup Predictions will complement this lesson, as it tells us why one decision making process is more successful in a certain situation.
Before we dive in, let me first give you a very brief background on the debate in case you haven’t been following it. The ‘disruption theory’ explains how new companies enter markets with simpler and more affordable product alternatives. It also explains why existing players in existing markets often miss the opportunity and get replaced. For more details, have a look here. The theory, which is subject of several of Christensen’s books, is supported by a number of case studies, which show how existing players were replaced by innovators. Lepore argues that, since the theory predicts the future, its credibility depends on the quality of the case studies, which were used by Christensen. She then starts to deconstruct each case study with counter-evidence. Her deconstruction of the case studies has been analyzed in a number of articles, which you will find listed at the end of this post. Based on those articles my take is that Christensen’s theory withstands her criticism. However the reliability of the case evidence is not subject of this post.
So let’s return to the question, which we want to discuss here. How can this battle between two top-notch academics emerge? And what lessons can we draw from the two views for our own decision making process as investors?
Clayton Christensen is Professor for business administration at Harvard, where he succeeded the legendary Michael Porter. With his highly successful books on innovation and disruption, Christensen became similarly legendary as Michael Porter. He has been awarded No 1 Management Thinker in the World.
On the other side, Jill Lepore teaches at Harvard as well. She is a staff writer at The New Yorker, which has an excellent reputation; and which wouldn’t be interested in publishing nonsense. Lepore would not get into a battle with one of her fellow academic colleagues if she weren’t convinced of her point.
Lepore thinks, that for the theory to work, the evidence of case studies is necessary. She is looking for scientific proof. The books of Clayton Christensen however cannot be considered academic books. Academic books usually don’t make the bestseller lists. These are books, which are made to help mangers, and investors make predictions and accordingly take decisions under uncertainty.
As investors, we permanently face uncertainty in our decision making process. The better we are at reducing this uncertainty, the better the returns we will generate. However, as businesses and markets are complex, we will never possess all the information we need or would like to have. How can we cope with this? There are two ways in which people tend to handle this. One way is to try to gather all the information that is available on a topic and to try to examine every possible option in order to take a “safe” decision. The other way is to take a decision based on good enough information and put intuition into play. People who take the first approach are called “Maximisers”. People who take the second approach are called “Satisficers”.
I have seen these differences manifest itself in investment committees. Some of the decision makers requested to obtain all the financial data of a company before taking a decision, while others decided based on their assessment of the management team and the business model. Personally I believe that, in principle, it’s of advantage to have both types of personalities add up as part of a decision making team. They balance each other and they bring different views to the decision-making.
However I have realized an interesting pattern here. In slow changing, mature markets we may have all the information available to make decisions. So the maximiser approach works fine here. The problem is, this does not apply to areas where rapid innovation happens and where new markets are created. In these fields, which are subject of Christensen’s books, we will never have all necessary information available.
In dynamic markets we have to combine information with intuition.
In those areas it is more important to develop an understanding of the market. This understanding is developed through experience and by getting out of the office and talking to customers. Venture Capitalists for example don’t assess founding teams by looking at case studies. Talking to customers of an industry is the way to develop an understanding for what is going on in a market. Once we have the solid experience and understanding of a certain market we are able to take decisions based on intuition. This experience and understanding will also enable us to recognize patterns, trends and connections.
“A new idea comes suddenly and in a rather intuitive way, but intuition is nothing but the outcome of earlier intellectual experience.”
The disruption theory helps us by identifying patterns. We can use these patterns as a framework for our analysis.
Now let’s return to the disruption debate and apply these thoughts. As a practitioner, you can either trust the logic of the disruption theory, what I consider the satisficer approach, or you can request case evidence and scientific proof before you apply it. In the context of rapid innovation, the value of that theory doesn’t lie in its scientific proof through case studies. The value of Christensen’s theory lies in the logic of the theory. Christensen used case studies to recognize a pattern of how innovation happens. Based on those patterns he offers us a framework that we can apply to individual situations and which helps us recognize disruption opportunities and threats. In particular, his books give us sets of questions, which help us observe customers. For example he tells us how to spot customers who are over-served by current products and who would be interested to buy from a market entrant who offers more affordable product alternatives. He also tells us how to evaluate whether there is a sustainable business model around these alternative products in the low-end segment. And finally he also gives us a set of guidelines to evaluate the extend to which these alternatives represent a threat to existing players in the market. Once you speak to customers, you don’t need case studies for evidence, you will know whether a framework applies or not. In short, Chistensen’s books develop patterns, which help us better develop an understanding of the customers and ask the right questions. This is the value that it provides.
Focusing too much on the details of selective case studies even carries the risk of missing out on the big picture. We run the risk of forgetting to apply our intuition and what we learned from speaking to customers. In a study, the Insead University examined the success of predictions from maximisers and satisficers by having them forecast the outcome of the 2010 FIFA World Cup. They found out that maximizing tendencies had a significant negative impact on the correctness of forecasts. Maximizers performed more poorly in forecasts than the satisficers. The most interesting part however is the reason why this was the case. The Insead report states that the lower performance of maximisers was caused by their lower consistency in their predictions and a higher variance of their responses. They say, “that involve judgments about exogenous uncertainty, maximizers’ pursuit for the elusive ‘best’ causes them tremendous anxiety and worriment and this then gets manifested in their higher response variability.” Let’s try to translate this into simpler terms. It seems fair to say that higher “response variability” was caused because maximisers focused too much on selective information pieces and accordingly lost the big picture out of mind.
Applying the patterns and structure that Christensen’s framework provides seems more reasonable than looking for selective case studies as evidence. How well we apply this framework is up to us. And – in that respect Lepore is right – we cannot apply it blindly. It is key to make sure to understand the individual situation and what elements of the framework apply to that situation. Not everything that is called disruption is really disruption. Disruption indeed has become a buzzword, as has been frequently stated before.
References to the ongoing debate:
Original Article by Jill Lepore in The New Yorker: THE DISRUPTION MACHINE
Comment by Clayton Christensen in Businessweek Clayton Christensen Responds to New Yorker Takedown of Disruptive Innovation
Tom Tunguz on why the theory is useful as a framework: The Disruption Debate Is Focused On The Wrong Ideas
Bloombergview with clear words: An Incompetent Attack on the Innovator’s Dilemma
The Business Insider with further references : The New Yorker’s Takedown Of Disruptive Innovation Is Causing A Huge Stir
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