The Most Important iPhone Ever

Just recently, the 2 billionth iPhone was sold. Unlike the 1 billionth, there was no announcement, no celebration. Partly this is because Apple stopped reporting unit shipments, but partly it’s because it’s not as interesting to talk about 2 billion as it is about 1 billion. There is a desensitizing when numbers get that big. What happens after you achieve the status of the most popular and valuable product of all time? How much more better can the world absorb?

Before we answer, let’s reflect on how it’s going. The iPhone is doing better than ever.

There are more than 1 billion iPhone users. The total number of users has been rising steadily. iPhone users make up about 26% of all smartphone users (3.8 billion is the current estimate). The share of users in the US is about 60% (or soon will be.) The share in UK is close to 50%. All these share numbers are higher than ever. Over 14% of US and 10% of UK survey respondents have switched to an iPhone in the past two years. The following graph shows how churn is boosting iPhone market share in terms of users.

Source: Piplsay

There are more iPhone configurations. As the following graph shows the spread of phone price points is wider than ever. Reaching $1600, the range still starts at $399 in the US (excluding taxes.) The total range (number of lines in each year) is increasing also, now 24 mainly due to the addition of a 1TB storage option. NB: There are now two iPhone minis (12 and 13) and one SE bringing up the rear.

Carrier incentives are picking up again. There are tremendous trade-ins and incentives for financing new iPhones which is bound to create retail traffic. Also with the opening of more economies, there is likely to be a surge in shopping. Bear in mind that around 400 million users have iPhones older than 3 years. Trade-in values are as high as $1000. Which leads to…

A thriving secondary market. The used smartphone market is dominated by iPhones and this drops the floor for entry into the iPhone ecosystem to essentially $0. The following graph shows price drops across 2019 for Apple and Samsung smartphones (for various models by date of initial release).

Most importantly, the specification of the iPhone continues to push the boundaries of what consumers demand from a phone. The camera performance for the latest iPhone 13 enables a set of new behaviors beyond the selfie, the snapshot or 10 second video. Apple is putting cinematographic power in the hands of amateurs. It’s not so much about replacing professionals but enabling amateurs to look better to each other. Be sure to listen to the latest Asymetric podcast to hear from John J. Connor, accomplished film industry camera operator and cinematographer on the power of iPhone cameras.

The new cameras are for the new generation of YouTube, Instagram and TikTok influencers. Ordinary people with extraordinary tools can do extraordinary work.

The latest iPhone 13 is, in my opinion, the most important iPhone ever. It creates the perception of what a phone should be and it sets up the trajectory for demand that did not yet exist. It’s facile to think that the utility of an ok older phone is good enough. That assumes that we are satisfied with ok messaging and ok apps. With ok photos and ok video. With no wide angles, no nightmode and no macro photos. What the iPhone has shown however is that the demand for performance can be nudged up.

We did not ask for rack focus, post-production focus (!), night mode, macro photography and portrait bokeh. But once we have these features we begin, ever so slowly, to use them and then we start demanding them. Conversely it seems that what people mostly ask for—that is what the critics ask for—are extrapolations of existing features. The “faster horse” dilemma.

What makes the iPhone and perhaps Apple special is that it seems to deliver things that nobody asks for but then everybody wants while eschewing overshooting a performance dimension that a few demand but most won’t use.

The tragedy of overservice and disruption is that if you don’t shift the definition of performance eventually you run out of demand at the top of the performance curve. That opens you up to “good enough” competition from below. Instead you need to re-define the notion of performance: compete on a new basis, reset expectations. That the iPhone can find new dimensions of performance and hence demand is effectively a solution to the innovator’s dilemma.

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Forecasting The Past

The last quarter of 2020 was a remarkable quarter for Apple. Every line in the income statement increased by double digits. Net sales up 21%, iPhone sales up 17%, Mac sales up 21%, iPad up 41%, Services up 24% and Earnings Per Share up 30%. This had not happened in over 10 years. The last time being the first quarter of 2010.

Take a look at the table below which color-codes each line based on the rate of growth. The darker the green the faster the growth (blue being above 100%).

A shockingly good performance is made all the more remarkable by its happening in a time of uncertainty. The company has refused (rightly) to issue guidance as long as a pandemic is raging world-wide. The disruptions in supply chains, demand and changes in behaviors due to new limitations on mobility and interactions between people are unprecedented and consequences are still to be estimated.

The growth surely, you say, is precisely because of this disruption. The “work and study from home” and lockdowns have forced people to buy more technology. Phones, Laptops, tablets are not just tools but lifelines for a society denied other forms of contact.

But this was not at all obvious at the beginning of the crisis. The months leading to pandemic caused the share prices of most equities to fall, and tech was not immune. Apple’s shares fell in March 2020 to $57/share. I heard comments suggesting that Apple would collapse as a business with unemployment reaching 25% and nobody willing to pay for luxuries like iPhones.

The crisis has proven that technology is not a luxury but a necessity, and technology that works better is far more valuable than technology that works barely. Spending on better machines has increased.

Some of that is of course helped by stimulus programs but growth was not only in countries which gave out cash. The growth for Apple was in all regions of the world, breaking new records even in poorer countries.

Far more likely, the economic fuel for Apple’s growth came from disposable income being unspent on other high-ticket items like dining, vacations and entertainment. Much cash sloshing around the economy surely ended up in an Apple cash register.

But this is all old news. The question into 2021 is what will this year look like. The first quarter already ended and the data is dribbling in: Apple has 1 billion customers, 88% of US teens have an iPhone, 70% have AirPods, China is growing at crazy rates, Foxconn reporting 40% growth, production of next generation iPhone chips starting early (May), etc.

There does not seem to be a let-up in growth, despite some component shortages postponing some non-iPhone product introductions. Apple’s cautious comments 3 months ago are probably moot now.

We are providing some directional insights assuming that COVID-related impacts of our business do not worsen from our current assumptions for the quarter. For total company revenue, we believe growth will accelerate on a year-over-year basis and in aggregate, follow typical seasonality on a sequential basis.

At the product category level, keep in mind two items: First, during the March quarter last year, we saw elevated activity in our digital services as lockdowns occurred around the world, so our services business faces a tougher year-over-year comparison; second, we believe the year-over-year growth in the Wearables, Home and Accessories category will decelerate compared to Q1.

As you know, we were chasing demand on AirPods last year as we expanded channel inventory from Q1 to Q2. This year, we plan to decrease AirPods channel inventory as is typical after the holiday quarter. We expect gross margin to be similar to the December quarter.

We expect opex to be between $10.7 billion and $10.9 billion. We expect OI&E to be up around $50 million and our tax rate to be around 17%.

Luca Maestri

Given this, I am tentatively projecting top line growth of 15% (vs. 1% a year ago and 21% last quarter) and EPS growth of 11% (vs. 3.8% year ago and 25.6% last quarter.) A goldilocks quarter.

More details will be forthcoming.

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Significant Contribution Again

Five years ago I used the Cook Doctrine (put forward 12 years ago) to assess the possibility of Apple’s entry in the car market. That doctrine states, among other things:

We believe that we need to own and control the primary technologies behind the products we make, and participate only in markets where we can make a significant contribution.

Tim Cook

I concluded that it was not a question of if, but of how and to what degree Apple could make a significant contribution. How in terms of control of the technology and to what degree in terms of significance of contribution.

It was a tough call five years ago and it’s still a tough call today. Arguably the failure of initial efforts to meet the Cook doctrine have caused resets and reboots and pivots which means no entry is visible in the near future.

But there is another effort that Apple has undertaken in the automotive space which might be indicative of their intentions and capabilities.

This is an effort that hardly gets mentioned and was dismissed as immaterial a long time ago but I would argue it has made a contribution. It’s also unique for Apple in being a licensed software technology made available to hundreds of licensees and extending a software and services strategy to non-Apple hardware.

I am speaking, of course, of CarPlay.

CarPlay was announced almost exactly 6 years ago. It implements a unique division of labor between the iPhone and the on-board hardware. A division that keeps most of the computation and data on the phone but displays and allows inputs through the car. As a result it can evolve with new versions of iOS while keeping car inputs and outputs functional even when they age well beyond the lifespan of several iPhone generations.

It can be argued that CarPlay is a necessary “connector” for the iPhone for that one hour a day that many iPhone users spend in their cars. It is effectively a better way to control the iPhone and have it be the “brains” of the infotainment system. In that regard it’s very similar to Apple TV: controlling the “dumb” TV without having to be a screen. The difference here is that CarPlay does not need an Apple remote.

But how is this significant? It improves things, sure. It improves most in-car experiences related to making calls, music, navigation, calendar, messaging, podcasts and news. It also seems to have traction.

The measure of any product introduction should be adoption and in that regard CarPlay could also be seen as significant in its departure from the Apple play book.

Because the adopters are not users but carmakers, the decision to deploy it depends on it being licensed and put into cars that are produced and made available. Quite a different set of hurdles, these are the “orifices” that Steve Jobs famously riled against.

One of the aspects of adoption by institutions vs. adoption by consumers is that whereas consumers are influenced by an early adopter calculus followed by the observation and imitation of others, for institutions there is a long delay with indecision followed by a rush to do adopt in unison with competitors. In other words, the adoption curve for consumers is a continuous gradual uptake whereas for institutions it’s a flat line followed by near-vertical step function.

We can see this with the following graph showing the number of car models supporting CarPlay for the model years they represent.

2014 and 2015 were very tepid but 2016 and 2017 saw huge leaps in adoption. Since then there has been a steady filling out of support. At this point in time about 600 car models support CarPlay which is very nearly all the models available in the US market and a substantial number for the markets where the iPhone is widely used.

So is CarPlay significant and can it provide control? On the control side the answer is a tentative yes. CarPlay creates an iOS bubble in the car and it sustains the iPhone ecosystem with no incursions by alternatives likely. [Android Auto which seems to have a similar degree of adoption does the same for Android but there is no “pull” of switchers from one to the other.] Anecdotally, CarPlay support has become a hygiene issue with carmakers. Having it offers few advantages but not having it may repel users.

On the significance question, the answer should be “it depends”. The support seems substantial but it’s hard to assess market share of models as a complete list of car models available is not easily obtained. Apple has effectively injected software in a lot of cars and done so relatively quickly. By licensing it has amplified its reach much in the way Microsoft did with Windows and the Intel PC in the 90s. The speed is remarkable because everything in the car industry happens very slowly.

More than 1000 licensed car models in 4 years. This is quite a feat.

But the software touches only a fragment of the car. Infotainment is important, perhaps more than anything else the user perceives about the car experience. But it has not changed what the car is. It has not made driving safer nor more productive or more efficient.

Messaging and calling and mapping/navigation notwithstanding, significance needs to be measured in more important terms. The iPhone is significant precisely because an iPhone is not a Phone. The Apple Watch is significant because it’s not a Watch. AirPods are significant because they are not just acoustics.

CarPlay would be significant if it made the car something it isn’t and not keep the car being what it is. We know it should be something else and that is what we are all waiting for.

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The Car Bundle Paradox

The EV car market is booming. The graph below shows the global market for plug-in electric cars (plug-in hybrid (PHEV) and battery (BEV)–BEV are about 70% of total). The data is split between 2019 and 2020 with further distinction between the main regions.

EV (PHEV+BEV) units sold 2019, 2020 by region.

There is an additional detail in the delineation of Tesla’s shipments into these regional markets. To that point Tesla’s market share of all EV cars has remained roughly equal from 2019 to 2020.

Tesla share of EV car market and share of all cars.

The big story of 2020 was the growth of European EV shipments. Those who follow the market know that new EU penalties for CO2 emissions have come into effect, causing much of this increase. Indeed, previous surges in the US and China have also been driven by new incentives and/or disincentives.

As an aside, it should be noted the absence of Japan from this EV story. It’s quite a shock, really. Japan is responsible for a large percent of all cars sold through its national heroes Toyota, Nissan, Honda, Mitsubishi (and Subaru, Suzuki, Mazda, Isuzu) and has been a driving force for innovation. The absence of a local market for EVs is a glaring indicator of lack of industrial policy. Unlike the US, Japan does not even have an oil industry, importing all its supply (while the US is a net exporter.) Yet the US produces and consumes far more EVs than Japan. This should give pause. One wonders what would happen if Japan followed Europe in providing incentives for EVs in the “JDM” market.

Japan and “Other” countries aside, there was growth. But much remains to be done. The overall industry is far larger, as shown in the following graph.

EV growth and global light vehicles 2019, 2020.

Nevertheless, optimism abounds. With an increase in market capitalization of about 648%, Tesla is now the most valuable automaker in the world.

Tesla, the champion EV maker has taken 17 years to reach 0.65% market share.

Market capitalization of the auto industry (top 25 firms) and the market size (in units delivered).

Actually, as the graph shows above, Tesla is now almost as valuable as the entire auto industry was a year earlier. But the rest of the industry did not collapse. The top 24 companies (i.e. apart from Tesla) increased their market capitalization from $901 billion to $1266 billion during 2020. That’s a 40% increase during a year when sales fell by 15%. Quite an achievement.

Overall the market capitalization of the top 25 automakers more than doubled from $1.0 to $2.1 trillion. This begs many questions, mainly, how would such profits ever be generated.

To put a finer point on it, if we divide the market capitalization by units produced we get a figure of value that allows a historic perspective.

A measure of valuation by units of production.

Historically car companies were valued at $8,000/yr. 2019’s value was about $10,000 which makes sense given some inflation. But the drop in volumes coupled to increase in valuation brought the ex-Tesla cap/unit to an eye-watering $16,400, a 64% increase in one year.

Tesla’s valuation is on a different level. It went from $291,361 to over $1.6 million/car sold. Roughly this is 100x rest of industry.

But if we continue to pull the thread there’s yet another story to consider. The car industry (i.e. making and selling and servicing cars) is not the only way to deliver “miles” to citizens. There are multiple “modes” and services that deliver transportation.

There are also the ride hailing and micromobility which are positioned on different “jobs-to-be-done” than cars. The market capitalizations of ride hailing and micromobility are shown below

Adding the value of ride hailing and motorcycles and bicycles.

Note that micromobility is only measured by the value of motorcycles and bicycles whose markets are measurable and applying a 1.1 multiple to those sales yield a rough estimate of market cap.

It’s hard to get a measure on these jobs but I’ve taken to heart the idea that what you measure is most important in seeing what’s next and have been dividing the “market for miles” into short, medium and long distance trips.

The “Car Bundle Paradox”: The demand for travel vs. value of modes for travel by trip distances.

In the view above we get a sense of the scale of perceived value for businesses serving various trips. The inverted nature of valuation positioned on trips is, I believe, worthy of further analysis.

As the car today is a bundle, the design and engineering efforts are directed at serving the longest of long trips (with the largest payloads.) But the demand is for short trips.

If the car is to be unbundled (as the Personal Computer was into laptop, tablet, phone, wearables) then one can imagine that devices designed for short trips would accrue the value of those trips (and their popularity).

The absence of value in short trips is a paradox. Or perhaps it’s just an opportunity.

Apple Pay’s Pay Day

IN a recent release, Apple reported that “more than 90% of stores in the US, 85% of stores in the UK, and 99% of stores in Australia accept Apple Pay.” This is encouraging but a very small view for the global Apple Pay picture. How can we assess where Apple Pay is and how do we even measure success? My expectation six years ago was that Apple Pay would be a “$1 billion business” by 2020. Now that 2020 has ended, how was my six year prediction?

I always recommend counting customers rather than (or before) dollars so let’s begin with that. According to one source Apple pay users worldwide reached 507 million by September 2020. This is about 50% of iPhone users and therefore a decent adoption rate (starting as it did six years ago.) The data shows a growth rate of about 66 million in 2020 but a deceleration from 150 million the previous year. This data is obtained through surveys as there is no reporting from any participants.

There is a smattering of other samples about transaction volumes, mostly behind pay walls, but the overall story of adoption is typical: an s-curve where we are either at the point of inflection or slightly after it. If we are half-way then perhaps saturation will occur in another six years.

More concerning is the distribution of these users. A lot of the data that is collected on mobile and online payments (and mobile wallets) is US only. Historically the US was a good place to measure technology adoption as the US was usually the leader. The automobile, PC and many other consumer technologies saw their market defined by the US.

But not so much anymore. The digital mobile phone broke the rule. Today mobile payments is breaking it again. Note that although the iPhone is over-represented in the US (as share of all phones) Apple Pay point-of-sale support is under-represented in the US.

According to one survey, in mid 2018, there were an estimated 38 million Apple Pay users within the United States, and 215 million outside (5.5 times more!) Outside the US mobile payments are nearly 100% accepted by default but in the US the support is patchy and characterized by active intervention to deny.

I’ve used Apple Pay everywhere in Europe without friction. From vending machines to highway tolls to drive-throughs, public transit and parking meters. I can recall one failure to do so in the last six months (a state-owned gas station).

The same cannot be said of the US. Where at WalMart and Home Depot there is the capability of support but an incomprehensible refusal to do so. One rumor about why Home Depot denies it is because they were hacked once and are paranoid about any technology. Walmart may be spiteful due to margin/cost, valuing a few basis points over customer satisfaction, convenience, hygiene and employee productivity. These holdouts are the laggards. Perhaps there is some pride in denying their customers a basic convenience but there certainly isn’t profit in it.

It gets even weirder when it comes to banks. In the US almost all banks immediately supported Apple Pay as an extension of their bank cards. In Europe the banks became the holdouts, rolling out support slowly and perversely.

So when you consider the dependencies of Apple Pay:

  • Sufficient number of users with iPhones/Watches (check)
  • Support from Banks (great in US, spotty outside)
  • Willingness of retailers to accept (sluggish in US, perfect outside)
  • Availability of points-of-sale equipment (universal by now

It’s an impressive achievement.

My expectation six years ago was that Apple Pay would be a “$1 billion business” by 2020. This was based on a take rate of 15 basis points ($15/$10,000 in transactional value). Juniper Research, which regularly examines payment transaction markets, now expects that Apple will see global Apple Pay transactions of $686 billion by 2024.

At that 15 basis point rate it amounts to $1.03 billion. Thus this particular research suggests that I was off by 4 years, making the $1 billion pay day a 10 year target rather than six.

But maybe that is no fault of Apple’s. The transaction volume is also equivalent to 52% of the proximity mobile payment market. Half the addressable payment market is a pretty good market share for a company holding 25% of the smartphone user base.

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Analyst, analyze yourself

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:

Apple Share Price vs. a sampling of Analyst Estimates, Past and Present.

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.