One of the important points I've heard Clay Christensen make is that incumbent companies often get destroyed (disrupted) by small players not because they're incompetent, or even because they're making bad decisions. Each decision along the way seems perfectly rational. Christensen frames it ultimately as a problem of measurement, that people are measuring the wrong thing, therefore optimizing for or solving the wrong problem.
I think this article correctly points out that Hastings isn't stupid, but he's in a tight spot, just because of the circumstances.
Even more grossly significant than this is the fact that "logical and/or beneficial at small / individual / short-term scale" need not equate to a best solution or alternative for a population at large or long-term timescale.
A classic case in economics is explained very clearly in Mancur Olsen's Logic of Collective Action, which explains why group-based decisions are often at odds with the interests of the group as a whole.
Another is Arrow's Impossibility Theorem, which hods that there is no method for constructing social preferences from arbitrary individual preferences. In other words, there is no rule, majority voting or otherwise, for establishing social preferences from arbitrary individual preferences -- so long as you also require unrestricted domain, non-dictatorship, Pareto efficiency, and independence of irrelevant alternatives. In other words: democracy not only may not, but cannot deliver an optimum outcome.
There are many other such paradoxes and conflicts, many of which I'm becoming increasingly convinced undermine key and manadatory assumptions of a properly functioning free market economy.
What changes might fix these is of course a rather longer discussion....
Winston Churchill was clear in his writing that America could not be trusted as an ally in anything that required steadfast determination over longer timelines. The winds of democracy make America a fickle ally. See 'The Gathering Storm.' Public schools don't often teach any of the shortcomings of a democratic society.
The US has often turned to dictatorships for its "friends indeed", though this doesn't always pay out particularly well.
While there's a limit to the amount of pain a democracy will shoulder, there's also a pretty strong tenacity to its true friendships. Such as, say, the "special relationship" much heralded between the United States and Britain. Once we got over some initial sore feelings, by the late 19th century, economic and cultural ties had pretty solidly cemented the two countries together.
By comparison, the USA' s dictatorial allies have been steadfast ... for roughly the duration of the dictatorship, if that. And the fall of same can leave a very long period of mistrust and poor relations: Iran, and much of Latin America are testament to this.
Public schools are indeed a fairly mediocre source, but fortunately we're not limited to the knowledge spooned out in them. I found university to be rather interesting in this regard, and have made some study of related matters since.
So: I'd take odds with Mr. Churchill's assessment.
Churchill was not speaking in regard to feelings and a relationship with another nation, but rather dependability in mutual long term pursuits. I think what he says remains true and a useful filter at times.
another problem is we might not be judging this companies by the correct metric. maybe the best outcome a company can hope for is dying and making a ton of money while dying but we will often see this as a failure of management. so instead we get companies that fight tooth and nail to stay alive but don't end up creating as much value than if they went gracefully into the night.
E.g.: in an election between La Roge and Grebe Sough, if Handle Parr's decision to run changes the outcome between Roge and Sough, you have a dependence on an irrelevant alternative.
Taking Stanford's Machine Learning course this fall has given me a couple of new analogies to explain the innovator's dilemma. Think of business strategy as the learning hypothesis, and the learning algorithm seeks to increase profits by minimizing the error between what value they capture and the available dollars in the market. Successful companies walk the surface, making stepwise reductions in this error rate. This often leads to a perfectly rational descent to a local optima. These local optima can be very deep and very profitable, which makes it even more difficult to turn attention to steps that will introduce loss and variance in order to find a more profitable (or global) optima.
"Randomizing" the starting points (the effect of hundreds of startups in a market) can increase the likelihood of a better optima being found, as can large companies attempting the same with lots of small bets (e.g., 20% time) which then are cultivated using the proven learning algorithm (i.e., management approach.)
True visionaries are able to hasten the process by scouting out where these new optima are likely to reside.
Or they're measuring or looking at things in the wrong way. It's easy to see the peaks and the valleys in a company but the truly important points are the inflection points.
If a big company waits until a small company has taken away 10% of its business it may still be too late to save the company, depending on how long it usually takes to change momentum. Often the reasons for differing degrees of growth come down to different fundamentals. A big company may not even realize that they've screwed themselves over by evoparating all of the best talent out of the company through boneheaded corporate decisions until revenue growth stagnates and then people start to wonder why they can't execute as well as they used to.
I still think it's the best/most insightful/most useful business book ever. The implications of truly understanding that book and disruptive innovation can be huge if you're a company founder or a CEO, Product Manager, etc. It's not so easy to internalize. I'm sure a lot of CEO's have read it by now, but I can barely spot some that follow it.
Btw, what do you think about Microsoft trying to apply its desktop OS, descendant of Windows NT, to tablets? Aren't tablets disruptive innovation to desktops (in Christensen terms) and therefore the entire plan is doomed? It looks to me they are making classic management mistake like ones the Christensen's book is full of.
I'm sure someone has done a study trying to account for it, but it seems you also have to take into account that the small companies, taken in aggregate, are trying out tons of things simultaneously, most of which will fail: often one big incumbent is being besieged by hundreds of startups who each think they have a new angle. So even though one small company might eventually win and look like geniuses who did it on a shoestring budget, the machine that produced them, so to speak, involved hundreds of companies and a lot of resources all gunning for the incumbent in parallel.
Or to put it slightly differently, the act of measuring a system changes it.
Pretty much any system, but for businesses this is especially true. As you measure, you respond to the measurements, and the response ends up being reflected in future measurements. Sometimes the new system created by this feedback path heads off into the hinterlands like a glider flying off the gameboard in Life.
A real world example was BYTE magazine. They were polling their readers to see what kind of machine they owned, more and more owned IBM PCs, so they started doing more and more IBM PC articles, which attracted more readers who had IBM PCs. But it left out in the cold people who came to BYTE for non-PC articles (who complained loudly). The key was that the metric 'what computer do you own' did not reflect accurately 'why are you reading this magazine' and yet it was driving what the magazine covered.
I'm a big fan of metrics, but I'm also a strong believer in re-assessing periodically how changes in response to a metric have changed the business and measuring that too.
The were defining (implicitly) their target market as their existing market. Unfortunately, this was serving not to expand but restrict the interest areas within their existing subscriber base.
This is a very common mistake. A canonical example would be the "when should we hold this meeting" question ... asked of a meeting's attendees (the answer will almost certainly be biased toward "when we're holding it now").
Yes, another, maybe even more important point that Christensen makes is that smart people get sucked into these metrics not because they haven't been educated well enough in the tools that business school programs give them, but because they fail to think critically, to ask the right questions, and to form the correct narratives.
And this is a criticism that applies not just to business, but to engineering, product development, design, etc. You can be the best problem solver in the world and it won't help if you're solving the wrong problems. And this sort of thinking is something that a broader liberal arts education can at least encourage, which is why I'm still a proponent of the liberal arts, and wish people would find more value in them. (Yes, I was a Comp Lit major.) (Obviously, it has to be a well-executed program in any case, and an unserious student isn't going to learn anything in any case, either.)
I think this article correctly points out that Hastings isn't stupid, but he's in a tight spot, just because of the circumstances.