Thirty years ago, I was a product manager for a startup company that created high-performance, multiprocessing minicomputers. Powerful, scalable, and based on open standards, they offered exceptional price/performance. In 1988, Electronics magazine gave its Computer of The Year award to the flagship model
As we introduced the system, we described the “ideal” customer: a medium to large organization that used Unix-based systems, and ran large database applications, especially Oracle applications. We trained the sales force, produced some modest direct mail campaigns, and launched.
Then reality set in. In the first three months, we sold about 45 machines to some 30 different organizations. We gathered data about our new customers and looked for correlations that would help us target prospective customers more precisely. We found nothing — no patterns in terms of size, SIC code, geography, application, and so on. The data were almost random.
We were stumped. So, we decided to interview the key decision maker in each account. We created an interview guide and fanned out to visit customers
After our visits, we dug into our findings. Again, we found no useful patterns in the demographic data. Then we started describing the key decision makers. Who were they? Why did they decide on us?
Most of the decision makers were men in their early thirties who had recently been promoted to a position typically described as VP, Data Processing. They replaced an older person who had held the same position for more than ten years. One of our marketers had a flash of insight: “It’s almost like the decision maker is saying, ‘I’m the new sheriff in town. We’re going to do things my way. This is one of my first big decisions … and we’re going to buy a hot new machine from a startup company. I’m going to make my mark.’”
It turned out to be a very accurate description. Nominally, our customers were buying our machines to run large applications. But psychology was perhaps more important. We estimated that roughly 60% of our customers fit the “new sheriff” profile.
We decided to market specifically to new sheriffs. We trawled through organization profiles and identified those that had a new VP of Data Processing. We sent each new sheriff a fairly intense mail campaign coupled with calls by our local sales rep. The campaign succeeded rather well. From the time of the launch, we grew to $300 million in revenue in about two years.
I didn’t know it at the time, but we were practicing an art that today is called, the “jobs to be done theory of innovation.” (Click here for a good introduction). Developed by Clayton Christensen and his colleagues, the basic idea is that demographic information doesn’t reveal why a person chooses to purchase a new product or service. If we misunderstand the job to be done, our innovations will miss the mark.
Our startup company, for instance, positioned around big machines for big databases. We wanted to offer ever bigger, pricier machines. The new sheriff profile, however, changed our thinking. To get in the door, we needed to make it easy for the new sheriff to buy something on his own authority. So, we introduced an entry-level machine priced just below a typical VP signature limit.
Similarly, think about why men buy pajamas. We might think they simply want to stay warm. But men in America typically don’t buy pajamas until they have a daughter who is three years old. Their motivation is not to stay warm but to preserve their modesty. If we misunderstand that, we’ll produce far too many cozy, warm, flannel pajamas that men will never buy.
In my experience, good marketers and salespeople use the jobs-to-be-done method naturally and intuitively. They’re good observers and naturally ask a basic question: why do people buy these products? They dig into the data but, more importantly, they observe how people behave and ask insightful questions. The management guru, Ted Levitt,was a natural at this. He noted that people don’t buy gasoline for their cars. Rather, they buy the right to continue driving.
The jobs-to-be-done theory suggests that the key to innovation is sociology, not technology. Do you want your company to be more innovative? It’s time to add more marketers and salespeople – and maybe a sociologist and anthropologist – to your development team.
My career has been a steady diet of disruption.
Three times, disruptive innovations rocked the companies I worked for. First, the PC destroyed the word processing industry (which had destroyed the typewriter industry). Second, client/server applications disrupted host-centric applications. Third, cloud-based applications disrupted client/server applications.
Twice, my companies disrupted other companies. First, RISC processors disrupted CISC processors. Second, voice applications disrupted traditional call centers.
In 1997, a Harvard professor named Clayton Christensen (pictured) took examples like these and fashioned a theory of disruptive innovation. In The Innovator’s Dilemma, he explained how it works: Your company is doing just fine and understands exactly what customers need. You focus on offering customers more of what they want. Then an alternative comes along that offers less of what customers want but is easier to use, more convenient, and less costly, etc. You dismiss it as a toy. It eats your lunch.
The disruptive innovation typically offers less functionality than the product it disrupts. Early mobile phones offered worse voice quality than landlines. Early digital cameras produced worse pictures than film. But, they all offered something else that appealed to consumers: mobility, simplicity, immediate gratification, multi-functionality, lower cost, and so on. They were good enough on the traditional metrics and offered something new and appealing that tipped the balance.
My early experiences with disruption – before Christensen wrote his book — were especially painful. We didn’t understand what was happening to us. Why would customers choose an inferior product? We read books like Extraordinary Popular Delusions and The Madness of Crowds to try to understand. Was modern technology really nothing more than an updated version of tulip mania?
After Christensen’s book came out, we wised up a bit and learned how to defend against disruptions. It’s not easy but, at the very least, we have a theory. Still, disruptions show no sign of abating. Lyft and Uber are disrupting traditional taxi services. AirBnB is disrupting hotels. And MOOCs may be disrupting higher education (or maybe not).
Such disruption happens often enough that it seems almost intuitive to me. So, I was surprised when another Harvard professor, Jill Lepore, published a “take-down” article on disruptive innovation in a recent edition of The New Yorker.
Lepore’s article, “The Disruption Machine: What The Gospel of Innovation Gets Wrong”, appears to pick apart the foundation of Christensen’s work. Some of the examples from 1997 seem less prescient now. Some companies that were disrupted in the 90s have recovered since. (Perhaps we did get smarter). Disruptive companies, on the other hand, have not necessarily thrived. (Perhaps they, too, were disrupted).
Lepore points out that Christensen started a stock fund based on his theories in March 2000. Less than a year later, it was “quietly liquidated.” Unfortunately, she doesn’t mention that March 2000 was the very moment that the Internet bubble burst. Christensen may have had a good theory but he had terrible timing.
But what really irks Lepore is given away in her subtitle. It’s the idea that Christensen’s work has become “gospel”. People accept it on faith and try to explain everything with it. Consultants have take Christensen’s ideas to the far corners of the world. (Full disclosure: I do a bit of this myself). In all the fuss, Lepore worries that disruptive innovation has not been properly criticized. It hasn’t been picked at in the same way as, say, Darwinism.
Lepore may be right but it doesn’t mean that Christensen is wrong. In the business world, we sometimes take ideas too literally and extend them too far. As I began my career, Peters and Waterman’s In Search of Excellence was almost gospel. We readers probably fell in love a little too fast. Yet Peters and Waterman had – and still have — some real wisdom to offer. (See The Hype Cycle for how this works).
I’ve read all but one of Christensens’s books and I don’t see any evidence that he promotes his work as a be-all, end-all grand Theory of Everything. He’s made careful observations and identified patterns that occur regularly. Is it a religion? No. But Christensen offers a good explanation of how an important part of the world works. I know. I’ve been there.
As Clayton Christensen pointed out more than a decade ago, disruptive technologies are often seen as inferior to the technologies they replace. Leading companies can easily dismiss them as toys and ignore them. That’s when the trouble starts.
We’ve seen two examples of this phenomenon in the last week. The first is BlackBerry. Just four years ago, the company had 51% of the North American market for smartphones. Today, it has 3.4%.
There are, of course, many factors behind the decline, but I’d have to guess that the iPhone is the primary disrupter. Here’s how the New York Times describes BlackBerry’s response to the iPhone, “…BlackBerry insiders and executives viewed the iPhone as more of an inferior entertainment device than a credible smartphone, particularly for users in BlackBerry’s base of government and corporate users.”
In other words, BlackBerry dismissed the iPhone as a toy. In fact, long-time readers of this website will remember that BlackBerry actually used the word “toy” in one of its ad campaigns. BlackBerry users, the ad claimed, needed “tools, not toys”. That’s when I concluded that BlackBerry’s future was dismal.
The second example this week is the Washington Post. The Post used to be one of the most influential newspapers in the world. But somehow it missed the Internet wave. I’m guessing that executives at the Post once dismissed the Internet as nothing more than fluff and entertainment. No self-respecting citizen would get serious news and analysis from such a source. It was a toy. It could be ignored.
Now, of course, Jeff Bezos has bought the Post for $250 million. (Critics say he overpaid by a factor of two or three). I admire the Post and I hope that Bezos can help save it. But I can’t imagine how. The Internet has already thoroughly disrupted the Post’s business model.
In an entirely different arena, I see another disruption looming. In higher education, Massively Open Online Courses (MOOCs) threaten to disrupt the genteel world of higher education. Why pay $50,000 a year for a college education when you can get it virtually free on the Internet?
Some leading colleges, of course, are jumping on the MOOC bandwagon and experimenting with different offerings. Other colleges seem to be dismissing MOOCs as inferior “toys”. Just look at what MOOCs don’t offer: a campus, buildings, athletics, football, school spirit, dormitories, etc. But perhaps that’s no longer what customers want. Brick-and-mortar colleges may not crash as fast as BlackBerry did but, if they dismiss MOOCs as toys, their future is just as dismal.