Disruptive Leadershipis a nifty little book about Apple and organizational leadership from the lens of Jony Ive’s caring deeply. Tracing nine keys through the three stages of eruption, construction and disruption, the book provides a paradigmatic look at organizational effectiveness and impact.
At just 150 pages, it’s a compact resource for personal improvement, teaching business classes, and building one’s leadership library. Digestible in one or two sittings, it’s a great read for airplane flights or commuters rides, as well as reflection for deeper thought.
Drawing from popular press articles, case studies, and the academic literature, the book weaves a compelling narrative on how caring changed the world as it flourished at Apple.
It’s common knowledge that sell-side analyst price targets for stocks are not taken seriously. The evidence is simply that no public accounting exists for their historic performance. It would be trivial to grade performance but it seems nobody bothers to do it.
It seems strange given the attention paid and repetition of these targets in financial media. When a “note” is published with an opinion and a target price the stock price can and does actually react. But why should it if there is no accountability?
Well, not quite zero accountability. Philip Elmer-DeWitt publishes analyst estimates (example) diligently. These estimates are presumed to be 12 month targets, meaning that at the time when the estimate is published the target price is assume to be reached 12 months hence. He does grade the performance of these same analysts (and more) in predicting quarterly earnings and revenue estimates for the just-ended quarter.
But an estimate for what *just* happened in the last 90 days is a lot easier than predicting how markets will react to all the information about a company 12 months into the future.
So how hard can it be to measure performance on price targets vs. just-ended quarterly estimates?
Here is my modest attempt: I note that Apple’s share price today is trading around $298 per share. I also note that we can recover the estimates from analysts exactly a year ago. At that time Apple issued a rare warning that its own estimates for the fourth calendar quarter 2018, issued about 60 days earlier would be quite a bit different than what will be released (in 3 weeks).
This compelled all the analysts to re-set their targets at the same time. What we ended up is a whole batch of January 3rd 2019 estimates for, presumably, January 3rd 2020.
Well, January 3rd 2020 is tomorrow. How did the estimates hold up?
The following graph tells the story:
The green line in the graph represents the closing share price at weekly intervals (from about October 2016 until last week.) The blue dots represent various estimates. Note that they are 12 months since their issuance and that since estimates can come at any time the are not easily clustered.
That is except last year and the “big reset” when the estimates all were issued on the same day. I highlighted the range with a vertical line. Note that the closing price last week was well above the highest estimate and that the lowest estimate ($140 is less than 50% of the current price).
This is quite a big fail. Errors of 50 for a 12 month time frame are egregious.
A few additional observations:
The spread or variance of estimates is enormous. Far wider than what was the case 3 or 4 years ago. (I look forward to getting more data to perform this variance analysis). It’s peculiar to me that a larger, more stable business, as Apple is today, is more difficult to predict. To see even today a range in targets between $150 to $350 is bizarre.
Another observation is that very, very few targets were “accurate”. That is anywhere near what actually happened. To find these rare successes, look for blue dots placed directly or near the green line. The chances of a correct target is less than what can be attributed to chance. Again, I look forward to a larger data set to see if there is any set of analysts that perform particularly well or particularly poorly.
Again, we’re not describing here predictions about the stock market in general, or of macroeconomic indicators. We’re talking about predicting one single company’s stock price in a 12 month period. A company that receives a great deal of scrutiny and which publishes a surprisingly large amount of data about itself.
Now I don’t want to suggest that there is a better way to predict share prices. I will not try to do so because although it might be easy to predict earnings based on overall company strategy, processes and team (all well known) the share price is that data multiplied by a random number called “sentiment”. That sentiment can be summarized as the P/E ratio which wanders around aimlessly. I don’t think I have any way to predict sentiment one second into the future, never mind one year.
But even if I don’t think there is a method to the madness of sentiment, it seems dozens of people find it necessary to claim that there is one. But if you do, then analyze yourself. What did you learn from the mistakes? What is the theory you’re employing?
And if you don’t analyze yourself, then don’t expect to be taken seriously.
There is no such thing as a free internet. If you engage online you are being monitored and someone is looking to extract data from your actions. Your online life is under constant surveillance from social networks, data brokers, ad companies and others looking to “monetize” your actions. You don’t have to accept this.
IVPN was built by a team of security experts and privacy activists as a tool of resistance against constant online monitoring. When using IVPN on your personal devices, an encrypted tunnel prevents the logging of your browsing history, while web trackers and ads stop following you around.
IVPN was the first VPN provider to integrate the WireGuard protocol to their Android, Windows, macOS and iOS apps, helping you achieve lightning-fast connection speeds on any platform.
In addition, unlike most VPN providers, IVPN has strong ethical standards and rejects targeted advertising, paid reviews and misleading affiliates. Remember, you get what you pay for.
At time of writing (December 12, 2019) AirPods Pro delivery wait time is over 4 weeks. It’s been like this since they shipped. I tried stores in several countries and although units can make an appearance on a shelf, they sell out immediately.
AirPods are part of the “Wearables & Home” category for Apple which used to be called Other Products and include also the Watch, iPod, Apple TV, Beats and HomePod (among other items.) iPod revenues were broken out as recently as 2015 but as the graph below shows, there have been no specifics on any product in “Wearables & Home” since then.
It therefore falls upon us to estimate how much of the entire category is any one product. It’s been very difficult as the only clues lie in growth rates, sometimes cited for the Apple Watch and sometimes for “Wearables” alone. As far as I can tell from the available clues, the split is roughly as shown between the Orange and Green areas. Orange reflects estimate for Watch and Green everything else.
This analysis helped me conclude the Apple Watch overtook the historic “peak iPod” which occurred in the fourth quarter of 2007 at $4 billion. My Watch revenue estimate was $4.2 billion in the fourth quarter of 2018. This conclusion was confirmed by statements from the Company.
The problem lately has been that AirPods have become huge unto themselves. There is literally no information about AirPods sales as a product category. The only option is to guess Watch and subtract it from Wearables and then guess again the portion of “non-Watch Wearables & Home” that is AirPods.
Looking forward to the next quarter, I am expecting a 51% increase y/y for Wearables and 24% growth in Watch. This results in a Watch revenues about $5.2 billion and non-Watch $5.7 billion. Now if we assume $1.7 billion for non-Watch-non-AirPods (i.e. Apple TV, HomePod, Beats, iPod, other) then this quarter AirPods will have overtaken peak iPod.
Remember that iPod was the phenomenon which reset all expectations for Apple. It caused Apple to cease calling itself Apple Computer. It (at least psychologically) laid the foundation for iPhone and everything else that followed. In 2005 and through 2007 Apple was “the iPod company”. I remember people working in a large search engine company calling Apple “that media company” as a result of over-intellectualizing iTunes.
(One more footnote on the AirPods Pro is that at $250 a pair and $300 for Apple Watch, throwing in a case puts these attached accessories for an iPhone at roughly the same average selling price for the iPhone of a few years ago.)
For the AirPods to overtake the iPod highlights just what a phenomenal category Wearables has become. In combination with Home and other accessories the category is going to decidedly overtake the Mac, having already passed the iPad.
And so it goes, something dismissed as inconsequential–”does not move the needle”–ends up becoming a massive force of change. The iPod was that, the original Apple II, the Mac and yes, also the iPhone. It’s the asymmetry of humility that this happens over and over again.
To hear more about the profundities of AirPods Pro tune in to the next Critical Path podcast.
We love Gmail and Calendar, but we believe multitasking kills productivity. That’s why we’ve built the most minimal, yet powerful Gmail and Calendar apps for Mac. We’re partnering up with Asymco to give you an exclusive 30% discount: click here to get it.
Instead of a list of features, here’s what our users say about Boxy Suite:
Framer co-founder Jorn van Dijk: “Boxy Suite is the best way to use Gmail and Google Calendar on your Mac. I use it every day and love it.”
Zee M Kane, former The Next Web CEO: “Boxy makes G Suite beautiful and gives it those extra priceless features that should have been there from the start.”
Ryan Kulp, founder of FOMO: “Just downloaded Boxy Suite and already in love. Killed ~13 permanently open tabs with their suite of native clients.”
During 2016 Apple services revenues were $25.6 billion. In January 2017, just after the end of that year, Tim Cook said “We feel great about this momentum, and our goal is to double the size of the services business in the next four years”.
If Apple were to hit that target, during calendar year 2020, Apple’s services revenues should exceed $50 billion. In 2017 they were $32 billion, in 2018 they were 41.5 billion and so far this year they are 23 billion. If, as has been the case during 2017 and 2018 (see graphs below,) Apple were to maintain 30% growth in Services during the rest of this year they will have revenues of $51 billion in 2019; reaching the doubling tarted a year sooner than predicted.
Apple will have doubled Services in 3 years to a level equivalent to a Fortune 63 company (right behind Goldman Sachs).
Keep in mind that the reported revenues are not billings or what consumers actually spend. That figure is at a run rate of over $71 billion. You can see the difference between billings and reported revenues in the graphs above.
So what made this possible and what is the source of growth in the future?
As my estimates above show, the growth came from apps and licensing and other revenues. Apps include many third-party subscriptions and licensing includes Google TAC and other income includes Apple’s own subscription services and a few additional items like Apple Pay, AppleCare and iCloud.
What Apple is launching this year will boost this even further with TV+, Card, Arcade and News+. These are a new set of specific services that, apart from Card, will require subscriptions and will deliver Apple-specific content. Unlike previous Music and TV offerings, what Apple has embarked on is a high degree of involvement in the content creation process. These will be Apple TV shows, Apple video games and Apple-directed News feeds.
This is quite the watershed moment. Apple, a company dedicated to providing tools to content makers and content consumers, choosing to be involved in the lottery-like game of choosing and backing winners in creative works.
Can a company with good taste about devices and software successfully extend that capability to content? That seems to be the question many are asking: How good is Apple at creating hits? The process of hit creation is difficult but it’s not completely random. There are many individuals who have skills or taste. And Apple’s approach seems to be to hire people with such skills. These “executives” then proceed to attach people with great track records in hits and who may have the star power to attract audiences. It’s not a matter of complete guesswork. It’s actually the approach most “streamers” have: They hire studio executives, attach talent to projects and spread bets.
This is why there has been a rush by streamers to secure programs and A-listers. There might be a variety of subscriptions users are likely to pay for but there is a fixed number of bankable names in the business.
But let’s pause here to think more deeply about what is happening. Without much notice, we are seeing a content world where distributors are locking up talent and creating a studio model where production, talent and distribution and display are under one roof. This is exactly where the movie industry was in the so-called golden age of Hollywood. The era of the studio system. An era that ended with divorcement—the complete separation of exhibition interests from producer-distributor operations or the forced divestiture of theaters by production/distribution.
Another observation to be made is that the bundling and binding of content into specific distributors creates a walled garden effect. This extends beyond video content to games (a larger business than film, at least at the box office, see below) and to apps. Arcade games are Apple-exclusive. Many apps which depend on Watch, AR and other unique technologies become exclusive, and of course unique titles.
As far as consumers are concerned this might be just fine. There are very implicit lock-in effects of ecosystems, from UX muscle memory, switching costs for data, network effects from friends/family/co-workers in the same system. The extension of this to cultural content, news curation, music curation and privacy curation could be the comfortable default for many.
In this world-view the proposition Apple offers is very attractive. Look at the preference vacationers have toward packaged experiences. Look at the popularity of cruises. Look at the way features are packaged in cars. Look at meal delivery and the packaging of ingredients into something you can cook at home. Look at fitness and the packaging of instruction with the exercise venue. The examples are plentiful.
A garden is lovely after all. The walls are there to keep danger and chaos away as much as to keep you in it. The constraints simplify as much as they restrict. Though it may be contrary to some modular and interoperable utopias which paralyze with choice, we might well be experiencing a triumph of the walled garden.
InstantDomains.com is the fastest domain search tool ever built, you can search domain availability for all 500+ domain extensions in milliseconds. Results load instantly and with an incredibly friendly user interface it’s easy to scan through which domains are and aren’t available.
A domain name generator additionally suggests alternative domains to the one you’ve searched for and you can filter results by 55 different industries to make results even more relevant.
Instant Domains works in 32 different languages and will display the most relevant and popular domain extensions based on your location.
If you’re in the market for a more premium or brandable domain you can search domains for sale with results in milliseconds.
Instant Domains will quickly become you’re favourite tool of choice for domain name searches and availability checks. Try it out now.
The old cliche is that we were promised flying cars but ended up with x where x is something trivial or mundane. Perhaps the best “x” is “140 characters”. This statement is meant to de-value the technologies developed in the last few decades. Instead of building grand things, we build trivialities. The irony is that x is often wildly popular and ubiquitous. x also generates a lot of profits and is likely to change behavior. Indeed, the flying car alternatives are almost always better ideas.
Flying cars are an example of “extrapolated technology” where we take a trajectory of improvement and expect it to continue forever. x are examples of “market creating” technologies which create new behaviors and which allow more people to do more things that they could not do before.
The flying car dream comes from a century of improvements in cars, and airplanes. The idea that cars must continue to get better and flying must come to personal transportation. When they are faster than what roads and human reaction times can allow and when they have more space than we can fill and when they have more cupholders than we can drink from it’s time to look for a new domain–the sky–for them to enter.
The alternative is literally unthinkable to the extrapolator: that we might drive less or not at all.
The promise of super-fast computers on every desktop and every living room of the 1990s is countered by an acceptance of a computer in every pocket and a tablet in every living room in the 2010s.
So in many ways the grandest technological revolutions are a study in humility rather than ambition.
Humility as a business model or as an operating principle is one of, if not the most most powerful tools for a manager . The queen of the virtues is most elusive but most enabling.
And so here we are, the Apple Card has arrived. And the Apple car hasn’t. The contrast is deliciously ironic. The cynics are out and having their fun. The users are out ordering the product. The cycle repeats.
Except the Apple Card demands explanation. It’s not explained by Apple sufficiently. It sounds like a slightly easier credit card. Perhaps a bit easier to keeps tabs on, perhaps a bit easier to manage payments and easier getting bonuses. It sounds, well, easier.
But easier doesn’t rock anyone’s world, they say.
It’s just another card, they say.
How can this change anything?
Here’s the thing: follow the integration. First, Apple Card comes after Apple Pay, more than 4 years ago. Apple Card builds on the ability to transact using a phone, watch and has the support of over 5000 banks. Over 10 billion transactions have been made with Apple Cash. Over 40 countries are represented.
I am quite sure Apple considered their card entry at the same time they considered Pay entry. The extension to a credit instrument is only logical as an addition the the Wallet.
The emphasis is on convenience, ease of use, integration and assistance. It’s what a credit card should be if you invented it today.
The application process is easy. It’s designed for the iPhone. No delays, no paper, no signatures.
It promises “A healthier financial life” through help in understanding your spending and acting on it. The goal is not to keep users in debt but to keep them loyal. Think about the asymmetry here.
The partner, Goldman Sachs, is chosen for their willingness to also align on incentives.
But more than anything the release of the Apple Card brings into question what could be next. The Card may not have been on everyone’s mind four years ago when we first saw Pay.
Now the die is cast. Apple’s goals seem to include enhancing financial and physical health. These are mundane goals, perhaps.
“The essence of ultimate decision remains impenetrable to the observer – often, indeed, to the decider himself.”
John F. Kennedy
The fact that we ourselves don’t know how we make decisions has not stopped us from proclaiming, loudly, that we know how everyone else decides. Such proclamations about others’ decisions are especially confident and assured the more important, or highly visible, the decision.
This is at the heart of analysis for large companies, especially Apple. The premise that decisions on product, positioning, investment and a myriad other necessary functions are guided deliberately through the will of single individuals in positions of power; rational single Actors that are directed by some rational, typically economic, calculus is pervasive. Without pause, we assume that analysis consists of de-compiling the calculus of that single Actor.
The diversity of opinion on Apple stems from disagreements about whether the calculus is purely economic or some other—aesthetic, virtuous or greater good, “satisfaction maximization” or something else that motivates the Actor.
However this is not the only decision process. It is in contrast to two other decision making processes: the bureaucratic model where decisions are the result of analysis of constraints, resulting in a “best compromise” between multiple sub-problem solutions.
Or the “political model” where maneuvering between factions with fractional power results in a consensus decision based on a political (zero-sum?) calculus.
One could classify these decisions processes as Graham Allison did in “Essence of Decision: Explaining the Cuban Missile Crisis“: The Rational Actor, The Organizational Process or the Governmental Politics models. That landmark work opened our eyes to the variety of ways organizations—not just governments—decide. It clashed with, to the point of refuting, the economic rationality model typically attributed to Milton Friedman.
When reading commentary on Apple decisions I almost always hear the causality ascribed to the “Rational Actor” model where the Actor is a person of great importance. The importance imparted upon them implicitly by being a “visible” person. That visibility comes from having been put forward by the company itself. We know of the Apple Actors as those whose names are revealed and we assume that those not visible are not Actors.
But, of course, visibility is a design. The company, known for its design, takes that ethos to its communications, and communicating who is visible and thus who is “an Actor” is a design decision. So we are led to believe that decisions are made by the Actors and who the Actors are is determined by the very entity we are trying to analyze.
Do you see the problem?
Rather than take the comfortable road and analyzing Apple by the surface that is exposed, the better approach might be to toss the Rational Actor model and think about the Organizational or the Political Models.
How does the company process information? How does it generate consensus? How does it deal with motivating employees? How does it allocate resources? How does it evaluate productivity? How does it balance morale and turnover? These are what Clay Christensen classified as “Processes” rather than “Resources” questions. The Actor model assumes all decisions come from individuals who are, in a large organization, Resources. They come and go. They can be hired and fired.
The Political model asks further if the decision came from maneuvering between visible and invisible Actors. I would argue that the political dimension is prevalent in most large organizations and it is corrosive to the overall health of the organization. I would also argue that Steve Jobs designed Apple specifically to avoid the Political process. But we must still assume that it’s at work to some degree. It’s like entropy.
When hearing about big staff changes at Apple, take a moment to reflect what decision processes are at work. How did that one (visible) Actor really influence the decisions made? Are you ascribing too much to them because they are visible? Are you assuming that tens of thousands of other individuals are not influential? That they are minions hired to act and not to ask questions? Doesn’t Apple also say they hire people to tell Apple what to do?
Allison did not say which model applied to the Cuban Missile Crisis. He left it to the reader to decide.
I will do the same when it applies to any particular Apple decision.