The Innovator’s Stopwatch. Part 2

The adoption curve has been used to categorize adopters into groups by their behavior: innovators, early adopters, early majority, late majority and laggards. This categorization asserts that adoption is function of psychology, or the likelihood of people to act or react within social systems. [Rogers first edition 1962]

It’s a compelling model and has been proposed as a tool for firms to help with their marketing strategy. As diffusion proceeds through each adopter category, the product is re-positioned to address each group’s presumed behavior. Innovators (first 2.5% of the population) are offered novelty, a chance to experiment and uniqueness of experience; early adopters are offered a chance to create or enhance their position of social leadership; the early majority build imitate the leadership of the early adopters and justify it with productivity gains; the late majority are skeptics but, given a set of specific benefits, join the earlier adopters. Finally the laggards reluctantly agree to adopt as their preferred alternative of not adopting disappears.

The theory suggests that a firm can be successful if they modify their marketing and perhaps product mix to accommodate these adopter categories in a timely manner.

If this is the case however, why is it that those who have access to these data (i.e. who is buying and when) not to do the right thing? Why is it that during a technology adoption curve, there is a high degree of turnover in the firms which capture profits from the products that deliver this technology?

If you don’t believe this to be the case, consider the smartphone market. The data about buyers is easily obtained (even without paying a fee). Shown below is the US smartphone penetration data as obtained by comScore (including teenage survey data from Piper Jaffray).

Screen Shot 2014-12-16 at 5.07.41 PM

Following the penetration data there is a second graph showing the smartphone shipments for the largest vendors as well as the sum of the “others” which make up the difference with the total market. I used vertical registration lines to align the different data sets to the same time scale.

Having observed the market for some time, it’s possible to see a set of “epochs” which show the rise and fall of various platforms/vendors/geographic production areas. I applied these “epochs” as a rough sketch over the production data.

Screen Shot 2014-12-16 at 5.26.11 PM

I define these epochs as:

  • The Windows Mobile epoch from 2003 to about 2010 peaking in 2007. Competitors from Taiwan using Windows Mobile fielded a large number of devices and led that platform to win over proprietary Palm and Symbian.
  • The Nokia/RIM epoch from 2005 to about 2012 peaking in 2010. Nokia’s distribution power takes its platform to global dominance. At the same time BlackBerry surges in popularity peaking at about the same time.
  • The Samsung epoch from 2010 to (probably) 2016 peaking in 2014. Samsung surges from almost no smartphone volumes to double the nearest competitor in a matter of three years.
  • The Chinese epoch from 2012 and ongoing. With a vast number of new competitors doubling or tripling sales over a few short years, “Other” becomes once again the bulk of volumes with additional brands like Lenovo, Huawei, ZTE, Xiaomi, Coolpad adding to the total.
  • The (probable) Indian epoch from 2014. This epoch is not so much of or about India as the “local brands” which begin to have large, even majority, market share in markets such as India, Indonesia, Philippines, Vietnam, etc. This epoch is the triumph of the local over the global and represents the latter stages of adoption.

Now I deliberately left out Apple because, as can be seen in the shipments data, Apple never held a pre-eminent volume position. It is however a competitor with a steady rate of growth. So steady in fact, that it seems to mirror the overall market. Essentially, Apple shows that there is a potential for growth without competitive flux. A type of growth that is “systemic” rather than a function of some rivalry and hence turnover.

But Apple is an exception. As so often it tends to be.

The real puzzle is why are there so many turnovers in leadership in such a short span of time. The idea that five distinct eras can exist in a mere decade seems preposterous. These turnovers are not without economic drama. They are booms as well as busts. They happen in a market where there are literally billions of consumers spending the equivalent of $300 billion/yr. so the stakes are pretty high.

But it’s even more strange. If you super-impose the epochs on the (early) diffusion curve you can observe how a predictable adoption curve[1] results in unpredictable success in the market.

Screen Shot 2014-12-16 at 5.38.51 PM

There must be something about the way companies behave *while* they are watching the evolution of the market. They seem to be running at a cycle time far faster than the market’s overall absorption rate. Is this because competition is forcing them to mis-spend their energies?

Could it be that the behavior of firms is also a function of the psychology and reward systems of managers? That they seem compelled to optimize for a time frame shorter than the economic lifespan of the technology? That this mismatch of phase between lifespans of a technology market and their profit model leads to premature demise of their market position?





  1. I.e. one whose shape can be determined well in advance and updated with very high precision []
  • Sacto_Joe

    “Could it be that the behavior of [these] firms is a function of [mismanagement]?

    You betcha!

    • mfwpnz

      …”a function of mismanagement?” and through misaligned incentives driving misaligned results. Appears to be a repeating pattern with many players tendencies to push short term volume leading to boom and crash.
      This company pattern does not stand alone and requires a combination of company actions and consumer behaviour for the brands to fall out of favour and into a crash. Perhaps rapidly changing jobs to be done though the overlays of geographies suggests other forces may be at play.

    • claimchowder

      It’s not actually mismanagement if it’s the result of managers following their incentives. Then it’s – misguidance?

  • Micromeme

    Hi Horace, Very interesting post. You appear to suggest it is slightly mysterious why companies don’t adapt and penetrate the whole market better. (at least I think you are asking that– correct if wrong.)
    another view might be that at the early phase of any company attacking a broad market (cell phones, cars, whatever, ) they make some strategic choices, principally technology/product definition, sales channel, target margins) and these change in the early phase, but not very easily once they hit scale. that stiffness at scale leads to the peaking earlier than the broad market, because they are only really attacking the niche defined by their strategic approach.

    to make this more concrete,
    choses high end technology with integrated software and hardware, sales channel that is picky and demanding with carriers–(no carrier branding, apps, interference with over the air upgrades) and aims for relatively high margins on each sale.
    chose cloned software (google) with fast follow hardware, the most rapidly accessible carrier sales channel (allowing the carriers to do anything– relying on them to just want an alternative to the iPhone asap), and no requirement on margins (going for growth and scale over margins).
    in an earlier day blackberry
    chose technology with integrated software and hardware-providing over the top email, with a business/enterprise oriented sales channel, and decent margins on each sale.

    but each of the choices has consequences at scale
    a) you don’t get the part of the whole market that your choices are not appropriate for. so the reality is all companies are only oriented to part of the broader market.

    b) you can’t easily (at scale) switch from a high margin to a low margin strategy– or even the other way around. your company is in fact paid and structured partly around the margins it achieves at scale– extremely traumatic to change.
    c) engineering teams don’t really change easily from oriented to copying to developing really new systems or the other way around (if you’ve actually managed engineering teams– those aspects are not easy to change without breaking.
    d) sales teams are the same– a large organization that sells over the web is not convertible to one with high touch aggressive sales forces. in medicine for example a sales division that calls on hospitals doesn’t convert back and forth to one that calls on doctors. (or the other way around)

    FWIW in your figure of corporate growth/peaking all these strategic decisions (or accidents– unintentional decisions) are baked in and stiff by the time one is 25% of the way to the peaks– after that much is momentum (up and down).

    one thought– you could probably make a similar figure for the PC market over its first 20 years as waves of hardware vendors came in and went out.

    • pk_de_cville

      good insights, Micromeme. Interesting.

    • Companies are expected to change, to reposition their products to the market, as Horace says “The theory suggests that a firm can be successful if they modify their marketing and perhaps product mix to accommodate these adopter categories in a timely manner.”
      So strategies should change to accomodate market requirements but they don’t, Horace ask why, you say because at scale you can’t, that’s some sort of tautology.
      Companies should be designed to change, from your examples, if your sale division calls hospitals and is growing fast, a little what’s next analysis should make you think you will soon need to address doctors and make you start a little division to do just that and be able to grow the division as required by market.
      It seems to me that the main strategy is always something like: stick to what you know, to what works, don’t change or try anything else.
      You start throwing a lot of products to the wall, like samsung did, and if one sticks go all in on that and iterate until it dies.
      Apple has a long period strategy, that’s unusual, different, and is greatly rewarded, but they are also flexible and seeking change even in that strategy.
      Take Apple TV, they started high end with a 300$ product and ended low end with a 99$ very simple product that sells more than all the more complex more costly other’s products.

    • Casimir

      Change is difficult. If you define a business model, (using business model canvas as an example), is it difficult to change several parts of the model at one time if you have a larger company. Organisation and incentives as well as capabilies of people and IT are difficult to transform. So when the market changes rapidly is hard to change course.

    • The PC industry analysis is in the works as are a few others.

  • Les_S

    Seems to me that Apple has never been in a hurry to add features to products while others fall all over themselves trying to do so. Waiting to offer LTE or 3G or larger screen has been their MO. They seem to be able to time these upgrades in a way that draws the maximum number of buyers at the time of release.

    • Walt French

      In at least several of those instances, Apple chose to wait because the technology wasn’t something that Apple could control well enough to make for a good user experience.

      E.g., LTE. Early chips burned power like mad, leading some phone makers to offer controls to switch between no data, 3G and LTE. Confusion, plus the opportunity of having your battery die at 1pm if you forgot your choice, even after a full overnight charge.

      The job was not to provide a high-speed capability, that only obsessives could manage properly, but one without any sharp edges on it.

      • Les_S

        And it’s that patience to only release a technology when it’s fully baked which might lead to a brand affinity which has long-term implications rather than the short-term infatuation that burns hot and then cold for other brands.

  • Jonorom

    I don’t see a mystery. Consumer preference in this segment is eminently fungible. The smartphone purchase is more like buying tickets to a Broadway show than buying a vacuum cleaner. For what reason would a person go back to the same show?
    – Smartphones are a new consumer product.
    – Smartphones are replaced every two years and often more frequently.
    – The product appeal is heavily influenced by novelty and fashion.
    – Mobile phones are a rapidly evolving technology so that today’s products are massively more capable (and different from) the previous generation that the consumer is likely replacing.
    – Smartphone capabilities and quality are opaque to the consumer.
    – in some major markets the consumer is insulated from the cost of the device.
    – Manufacturers over-promise and under-deliver on the jobs to be done. If a consumer is replacing a device who’s capabilities are massively less than what is being offered today, and the consumer’s current device is a source of disappointment and/or frustration, it is unlikely that the consumer’s next device will be from the same manufacturer.
    – There is little brand loyalty – my dad didn’t own a Samsung anything.

    • Walt French

      It’s good to think of an analogue but the Broadway show model seems especially wronger than Horace’s.

      In fact, turnover is much less than the nearly-100% suggested by the fact that few people see the same show twice. The “epochs” above were not just when “Equus” was popular, but were driven by a set of functions besides novelty that other phones better captured, as well as new jobs. I.e., “Proof” made me think about fathoming the depths better than some shows (“Doubt,” “Curious Incident”) did subsequently, yet I enjoyed the newness of the later shows. Meanwhile, I haven’t bought the book for Proof, despite having enjoyed it and thinking it’d be nice to go over it again.

      About 40 years ago, financial economists observed that stock prices could be modeled as a particular random walk… not that the prices had no connection to reality, but that ups and downs arrived without predictability, with the (log) size of moves drawn from a Gaussian distribution. If you put in some network—self-reinforcing for “buzz” or self-canceling for worn-off novelty—you might be better able to see how these epochs are driven. Even more, you’d see some abiding features that, as Horace noted many months ago, competitors see, but do not try to imitate.

      Maybe Horace will link to that old post, which surely was in his mind as he wrote this (very fine) post.

  • Mark

    Fascinating post and comments. I want to consider some more the issue of incentives.

    In the work I’d do I look at how to incent appropriate behaviours at the input (e.g., getting better skills and proficiency); throughput (e.g., being a good team player, having good work habits); outputs/results (delivering on ones commitments). But there is a fourth level for inventing: outcomes (did what did make the desired difference?

    Organizations that focus on the first three levels of inventing will in my mind always have a short term focus. It would seem reasonable that the focus would be on doing what has been working well for you so far. This suggests to me that we introduce (self indlicting) risk of shifting market behaviours which in the beginning will be subtle, nuanced and often appear as outliers (I.e., easily discounted and ignored). I am thinking that the different adapting categories described in the “S” curve by Horace would be reflective of this situation of changes that are easy to ignore (discount).

    Outcome oriented incentives focus on what difference does what you are doing do for the the customer, hence the ability to sense and respond to differing customer categories is easier to do: you are actively looking for these shifts in potential adoption patterns.

    The value of an organizarion’s vision and mission here can be significant it would seem. Apple’s includes the notion of “enriching people’s lives”. It has already been described here how enrichment can appear for innovators, early adopters, etc.

    I have always been fascinated by the paucity of of insight and appreciation for outcome oriented perspectives in performance management and I wonder if what Horace is questioning too is in part explained by this “outcome” absence/minimization in many firms?

    • Walt French

      Mark, I don’t quite understand your comments, but sense that you’re onto something. Could you have a friend who writes well, act as an editor & resubmit your comment?

      • Mark


    • David Leppik

      Another way to look at it is that Apple values its reputation with consumers far more than most companies. Shortly after Steve Jobs came back to Apple from NeXT, but before he became CEO, he gave a talk to developers at Apple that you can find online. Much of what he talked about was restoring trust, and how it would take years.

      Apple has brand loyalty in large part because it guards its reputation jealously. If you have a broken Apple device, you take it to the Apple Store, and you can be confident that they will go farther than their competitors to make it right with you. It took years for Apple under Steve Jobs to establish that level of trust.

      Luxury brands know all about this. So does McDonalds, which won’t serve you a fantastic Big Mac one day and and an okay one the next, because they want you to get exactly what you expect. For McDonald’s brand promise (i.e. reputation), consistency is more important than greatness.

      When companies listen too much to their investors, they optimize for variables they can measure. Reputation is hard to measure, and it doesn’t improve quarter-by-quarter. So they throw in features at the expense of quality, or see customer service as an expense rather than part of the package.

      As a result, customers see HTC phones as replaceable with Samsung phones. Whereas Apple phones are in a different category. And the real difference isn’t something Samsung or Wall Street can track, because it isn’t something they can quantify.

  • Sacto_Joe

    I’m not sure that we can compare the smartphone phenomenon so directly with things like the VCR, because the potential markets are not close to being on the same scale. The smartphone is literally computerizing the world. And the “jobs to be done” for computers is almost limitless.

  • stefnagel

    JTBD: It’s also about the job you get to do. Both orgs and folks have trajectories that put them on track to take on certain jobs. And, irreversibly, not others.

    Way back, Sports Illustrated described how few people fit the profile, physically, mentally, and emotionally, to play specific NFL positions.

    Apple was groomed for its trajectory, just as Microsoft and Samsung were for theirs. It’s not enough to be lucky … the right place at the right time … you also need to be the right person for the job.

    Robert Frost said it: it’s hard not to be king, when it’s in you and in the situation.

  • Walt French

    @Jonorom:disqus , surely the Broadway show model is worse than Horace’s.

    Turnover in that model is nearly 100%; almost nobody sees the same show twice. But I’ll guess there’s a high repeat-purchase rate of some franchises, e.g., the Disney shows, with some consumers strongly preferring musicals from them—more like the phone models’ high repeat-purchase numbers. (And my repeat-purchase of them is also about 100% serially correlated at zero.)

    About 40 years ago, financial mathematicians noted that a particular random walk generated VERY believable stock price charts, over 5 minutes or 30 years’ data. Not that the prices have no connection to reality; rather, “news” arrives unpredictably, and the impact of that news is distributed per a Gaussian distribution, up or down in (log) prices. Predictable periods of stocks being in favor or out of favor are extremely difficult to observe, because there is such a high payoff from seeing that e.g., a price is supported mostly by sentiment that will fade. Just sell (short if necessary, or buy puts) a day before the others will. You will often be wrong if some good news happens to come out, but if your costs are low enough (and institutional investors’ costs are EXTREMELY low as a percent of the trade in reasonably large companies such as Apple), you will be richly rewarded with even crummy diversification.

    Oops! You have to sell before *I* do, because I have access to all that same information about Apple (or Stock X) and I have just as much speculative capital and just as much appetite for wealth. You need to sell a day before I do, and *I* in turn need to sell a day before the other investors who see a predictable decline. The “news” degenerates into guessing about what deep-pocketed investors might soon do, a fool’s game of the first order.

    Smartphone purchases, OTOH, are much more likely impacted by herd effects, innovations that others don’t copy, customers’ inability to diversify and many other reasons that are NOT simply about novelty. Most companies try to cultivate these unique features and hope to hold on to a loyal customer base while they figure how to respond to (copy) competitors’ new features. BlackBerry rose and fell, not because it was cool and then suddenly was not, but because the valuable fast/secure communications job it did—still does—extremely well actually over-served most of its customers, while becoming too expensive (both cost and absence of other desirable features in the place of honor in one’s pocket).

    This is just a simple example of disruptive innovation; what’s relatively new is the timeframe being crazy (and why methinks Horace had his tongue firmly in cheek when he chose “epoch” for his labels). But if you look at the features that apparently drive brands’ successes (and features of others that displace it), you’ll see that they may take many months or even years to build/replicate. Multi-tasking, for example, was part of OS X that iOS was based on, yet had to be painstakingly re-created to deal with the unique power demands of mobile. Few smartphone firms have a dedicated OS group. Apple spent literally YEARS getting synchronization to the point that they could offer it to developers as a program feature. Secure inter-process communication: ditto. Occasionally we see notices that Apple is doing X because they have a job listing for it, and inevitably it’s 18 months or more before the feature manifests.

    Meanwhile, most companies are under very real pressure — not just from Wall Street — to keep sales strong quarter-to-quarter. Very few can afford to think in terms of the next 5 years because every such body dedicated to that reduces the probability the company will be successful enough to be around in 3 years.

  • Walt French

    @Asymco wrote, “If you super-impose the epochs on the (early) diffusion curve you can observe how a predictable adoption curve results in unpredictable success in the market.”

    Methinks this is backwards causality. The adoption curve is the sum of individual companies’ (regions’; OSs’) successes.

    See Wikipedia’s Central Limit Theorem entry. Even if a given measurement is QUITE ill-behaved (e.g., payouts from lottery tickets), the averages of individuals’ results will tend to be distributed according to the bell curve, if you take enough repeats of averages across enough individuals.

    In this case, if there are enough competitors, each with not-too-lopsided competitive benefits(†), individual competitive benefits will have little impact on the overall curve, while the technology’s benefits will determine the adoption.

    † One of those benefits is availability. Some of the bumps in the overall curve are just reporting noise; others are from a surge of new entrants at roughly the same time; similar responses to similar economic forces.

  • Walt French

    A last note before I go back to work… Horace, some months ago—maybe at the time of Microsoft’s CEO transition?—you asked why so few companies copy the organizational structure, etc of Apple. Surely you had that in mind when you wrote this post and could amplify on how it bears on the question. It seems like a simple answer is that few companies afford to invest the resources, build the processes or even have the values that Apple does.

  • mark

    In reply to Walt French’s request to my post below:

    Horace talks in part about how much churn there is in those producing and selling smart phones and raises the question on how organizational incentives might play out in this churn.

    When I think and discuss with clients incentives (aka performance management) I ask that they look at how we can effectively invent at four levels:
    1. At the INPUT stages: are we inventing quality inputs into our business processes? In the area of information are we encouraging quality and useful information into our decisions? Are we encouraging people to become and sustain superior skill areas that interest us, etc.
    2. At the THROUGHPUT stage where we are interested in how we process inputs into useful results we can use incentives to encourage effective teamwork, processing of work, effectiveness of “just in time”, etc.
    3. At the OUTPUT/RESULTS stage we are interested in did we deliver on our commitments? Was the project completed on time, within budget and meets performance specifications? Did we produce enough phones to meet market demand? etc.
    4. At the OUTCOMES stage we are interested in whether all our previous great efforts made an appropriate difference. For example, Samsung may have done everything right (in terms of inputs – results) in producing its Galaxy S5 product. Yet it did not really succeed by all reports I have heard. We all have had experiences where our best efforts to make something better turned out quite the opposite.

    Back to Horace:

    When Apple says that its passion is to make great products that “enrich peoples’ lives” this is an outcome perspective. One of the practical values of having an outcome perspective is I believe you are more likely to see, consider and take heed of subtle market shifts, namely outliers. In an “S” curve I think that they can begin from an outlier. Something small becomes significant. How do we recognize this possibility? An outcome perspective question addressing this might be: “Why is this happening, and if it continues, what might it signify?” Similarly, when we shift from different adapting groups within an adoption curve how do we begin to recognize that new entrants are arriving with different expectations (jobs to be done?)? Personally, I have always framed my inquisitiveness when seeing anomalies, curiosities, oddities, out of pattern incidents, etc. phenomena from an outcome perspective: “What difference will this make it it persists or even grows?”

    We often are cynical about vision statements for good reason. But I suspect that if we talked to any engineer in Apple about why they did what they did they will be able to connect the explanation back to the “enriching peoples’ lives” notion. Somehow (and I could be very wrong) I suspect that this would not be the case in Samsung.

    In fact we can more easily say no to an option if we are clear about this: “If we do this this way, how will it better enrich peoples’ lives versus an alternative before us?”

    Outcomes, are the “pole star” in setting up effective incentives.

    Walt, sorry for the length of this, hopefully helpful, explanation.

    • Eric Gen

      I replied to your earlier post, but like Walt said in one of his posts, strange interactions ate my reply! 🙂

      I like your notion of ‘outcome’ incentives. I would guess that you would still need some of the other 3 incentives that you list, if for nothing else, to help retain staff. But, it would seem to me to be in the best interest of the organization to weight the ‘outcome’ incentives the heaviest.

      I have worked in large multi-national companies where products shipped on the 75th day of the month and where multi-million dollar purchases of known inadequate software was purchased just so those involved would meet their objectives and get their performance bonuses. A heavier-weighted outcome objective would have helped alleviate some of these issues.

      Again, I’m just speculating, but I would guess that the sorts of things that I have witnessed occur frequently across most large organization and, as such, have an aberrant effect upon being able to sustain successful outcomes. If properly done (which may be difficult to specify), rewarding actual outcomes might help correct the course that the current incentive structure causes to deviate.

      Hmm! I just had a counter-thought. It seems like the incentives in the last financial meltdown (2008) were outcome incentives. Was this just that the outcome was specified poorly with regards to everyone outside the financial community?

      • Mark

        Eric, yes we would need incentives for all four levels.

        I do not know enough about 2008 financial meltdown to appreciate the role of outcome incentives. In ignorance, I would speculate that most incentives were targeting results/outcomes (making deals) and trusting to automated like throughput incentives (like computer based algorithms on risk assessment without human “sniff sanity testing).

        As a historical note, I became interested in outcome oriented perspectives and attendant incentives when I was dealing with clients who were very successful operationally ( what the first three levels look at) while being less successful in the the external sense (sales, good will, reputations, public relations issues, being outflanked competitively, etc.). This customer and broader stakeholder perspective in terms of differences in their lives enabled some of them to see opportunities and threats (mainly through picking up on outliers more insightfully) more effectively. The theory they bought into is that opportunities and threats first show up as outliers in their business activities.

    • Accent_Sweden

      Your thesis strikes a strong chord and I would very much like to explore this idea of outcomes as incentive. Could you recommend some background reading?

      • Mark

        I appreciate your thought about my tentaive thesis. I have not done any literature research in this area so I do not have any sort of list of useful literature to read.

        I came to this perspective when I worked to help clients think about how to identify and set up leading indicators for their strategy. This is how I gravitatedto the four level view of measurement. My interest in leading indicators is based on the claim that getting early insight on possible threats/opportunities gives us time to best respond. My more recent thinking focuses on how we can use measurement to anticipate what can go wrong in the future and in this sense move some of our uncertainties and make them more risk like.

        Your question gives me some homework in the new year. All the best to you and yours.

      • JerryL

        small step back from looking directly at outcomes – it’s instead supposed to identify and concentrate on those elements of what is produced that actually matter to the ultimate customer. These in turn are assumed (correctly or not; there are plenty of ways to get this wrong) to determine the actual outcome.

        I think the largest difficulty with all these ideas is the long time lag between decisions made and feedback concerning outcomes. (This is particularly noticeable in Six Sigma, which at its origins was about control of manufacturing processes, where the feedback loops are typically quite short.) But then it’s been my observation that pretty much all difficult questions come down to striking the correct balance between the short and long term.

        — Jerry

      • JerryL

        Hmm. The top of my note got cut off. Here’s how it was supposed to go:

        The closest thing I know of your notion is “the voice of the customer” in Six Sigma methodologies. It’s a
        small step back from looking directly at outcomes – it’s instead supposed to identify and concentrate on those elements of what is produced that actually matter to the ultimate customer. These in turn are assumed (correctly or not; there are plenty of ways to get this wrong) to determine the actual outcome.

        I think the largest difficulty with all these ideas is the long time lag between decisions made and feedback concerning outcomes. (This is particularly noticeable in Six Sigma, which at its origins was about control of manufacturing processes, where the feedback loops are typically quite short.) But then it’s been my observation that pretty much all difficult questions come down to striking the correct balance between the short and long term.

        — Jerry

      • Mark

        I understand that long term outcomes are just that. Yet some outcomes that matter to us (as providers and/or users can be shorter term. Great design may help customers deal with historic frustrations in use of comparable products. Also, we can see that customers arable to use pour products in ways that we (and they) never envisaged. Apple in its advertising and general marketing reinforces the notion that use of their products makes a meaningful positive difference in peoples’.

        The way I have used this notion in my own life and in conversations with others is to examine what positive differences might/hope to observe in relatively shorter time frames. Looking at how historic frustrations may be dealt with can be a useful place to begin to identify such measurable/observable outcomes.

  • berult

    Just as classical physics bounces out of the uncertainty principle on a one-off deterministic binge, iPhone transmutes computing from a random, gaseous state to a vectorized flux. The probability of such events ever happening is one.

    How is this relevant?

    Well, you have to refer to a deterministic model in order to gauge the uni-verse of the model’s very own substrate. In other words, information-theory wise, iPhone’s very existence, as though the arrow of time…on a certainty’s whim…pointed suddenly in a reversed direction, lights up and emulsifies the perfect…minus a probability of one… entropic state from which it originates.

    The effect shoulders henceforth the burden of cause. iPhone informs computing randomness, just as classical physics informs elementary particles’ randomness. After all, that is essentially what they are there for; to let the Universe unfold in running awareness towards the period underpinning the question mark.

  • Is this quick rise and fall the fate of low-end providers naturally? It’s really hard to sustain a price advantage in this way. Few companies have lasted long when targeting the low-end. It’s much easier to sustain an advantage as the premium provider, as evidenced by Apple’s decade+ long dominance of computers, tablets and phones.

    • Walt French

      Except that these aren’t low end in the context of the market before Apple arrived and it doesn’t seem that premium pricing guarantees long life in other consumer markets such as TVs, stereos, …

      I’d say the way a company survives and prospers is in having both financial reserves AND enough differentiation/identity to keep rolling thru the errors, occasional dud products and other hiccups while it keeps finding new ways to please its customers.

      • I can’t speak to other consumer electronics, but did you use any of those devices before iPhone? I would argue not a single one of them were competing at the high-end of the market. There was no high-end provider in those days.

      • Walt French

        I took a good look at a Nokia pocket phone-cum-computer before deciding it wasn’t for me—too pricey for the value.

        You might well argue that it wasn’t high end, but I don’t see how you can say it was low end.

  • Ian Ollmann

    Waiting patiently for Horace to synthesize Jobs to be Done with early / middle / laggard market segmentation and tie it up with a neat little bow.

    • Walt French

      iPhone is a platform and the JtbD doesn’t appear to need a lot of new iPhone-specific stuff. Software—apps and system goodies such as extensions & synchronization is the new commodity module. Christensen’s belief that all disruptive innovations become commodity (zero excess profits) goods, is coming true in apps, which developers are finding hard to translate into major businesses. There’s certainly less difficulty finding somebody who can write an app; many fast followers for any new app category.

      Meanwhile, Apple enjoys quite a moat around its hardware, and will probably manage its market share / profit margin tradeoff much the way it has done with its entry into the laggard-phase PC business, the Mac: gradual increases in share while protecting its profitability.

  • JerryL

    Not mentioned anywhere here is the power of the carriers in determining market success, certainly at the beginning of the period covered and in the US (though much less so now).

    The carriers controlled access to the customer, and built a business model centered on frequent replacement, hence on novelty. Indirectly, they also favored playing one supplier off against another, as that prevented any one supplier from becoming strong enough to challenge them. How much of the resulting churn could then be explained as “by design”?

    — Jerry

    • Walt French

      I dunno when I first encountered the idea that the carriers like the OEMs “barefoot and pregnant,” but it’s quite apt. But it seems almost as if the carriers worked to keep Nokia out of the US, a stronger version of our views, to ensure the telcos maintained control of the value stack.

  • boxingday

    “They seem to be running at a cycle time far faster than the market’s overall absorption rate.”
    Steve Jobs: “Stay hungry.” This may explain the frustration of consumers and commentators that Apple is not bringing in new features fast enough, which we get with every product cycle. But Apple seems to have a good idea of just the right pace of change needed. Like baby bear’s porridge, neither too hot nor too cold.
    OT: I was looking for a present for my brother in law on Christmas Eve. Obviously gifts between men are difficult and can be embarrassing for both parties. I nearly bought him a scarf (I was in a chic boutique getting stuff for the girls), but that just seemed too girly. So I ended up in the mall looking at books and electronics. But he doesn’t read much and though he like motorbikes I couldn’t give him a book on bikes, it just seems pointless and I don’t know what I’m giving him. So electronics. We’re both Apple fans and have pretty much everything out there already. Can’t give a phone, already has various ipads, go pros, hovercopter, multitudes of wireless speakers, MacBook Air etc etc. Anyway there’s no Apple shop where I live, so although Beats headphones were prominently displayed, there were no other decent gadgets. So basically I went away empty-handed and gave him nothing! Not a problem because we generally don’t give each other anything anyway. But it did occur to me, there is a huge gap in the market here for more useful, high quality gadgets by Apple, along the lines of Withings or Nest, neither of which were available here.