Disrupting the Innovator's Dilemma

It seems Clayton Christensen has become the Michael Porter of the third millennium, having his book, The Innovator’s Dilemma (TiD), quoted in all sorts of articles, talks, and even other business publications. You can’t read a single WSJ or NYT article without seeing the word disrupted. Companies go out of business because they are disrupted by more innovative businesses. Products and services kill other products and services because they are so disruptive to them. A company even disrupts itself when it releases a new product that improves on the old one. Everybody is being disrupted everywhere, all the time.

Some Background

If you aren’t familiar with Christensen’s law, it is this. There are two types of technologies defined in his framework: sustaining technologies and disruptive technologies. In order to be as accurate as possible, I will quote his own definitions for these technologies.

“Most new technologies most improved product performance. I call these sustaining technologies…What all sustaining technologies have in common is that they improve the performance of established products, along the dimensions of performance that mainstream customers in major markets have historically valued.”

From the next paragraph…

“Occasionally, however, disruptive technologies emerge; innovations that result in worse product performance, at least in the near-term…Disruptive technologies bring to a market a very different value proposition than had been available previously. Generally, disruptive technologies underperform established products in mainstream markets…Products based on disruptive technologies are typically cheaper, simpler, smaller, and frequently, more convenient to use.”

So now you have a basic understanding of Christensen’s ideas. I still encourage you to read The Innovator’s Dilemma, since it shares many interesting ideas, but for our purposes, you are ready. 


Opportunity Cost

One of Christensen’s fundamental contributions is quite profound. To summarize, it goes something like this. Management of a company doesn’t think about the disruptive, low margin technologies nearly as much as they do about higher margin technologies, since by definition, low margin products are not as profitable. 

As Christensen himself admits, a company becomes successful in the first place from the processes, values, and ultimately products it created in the past. Since the goal of most companies is to be profitable, they must create profitable products. Profitable products are usually more expensive, provide more features (value) to the buyer, and/or carry with them an element of prestige. According to TiD, these very same products are ripe for disruption. Thus, companies should avoid being disrupted by instead investing in disrupting themselves, before somebody else can disrupt them. 

This all sounds great until the realities of the real world come in. Say you are a car company, and have $1B to invest. You can either invest in your current best-selling model in order to improve it, or you can invest in R&D for a cheaper, more economical car that you think would do well in developing nations. Absent other information, TiD would urge you to invest in the cheaper, low margin car, since it may become a disruptive technology in the future. So you go ahead and invest the $1B in this low margin car, and it becomes an international hit! Drivers in India, China, and Brazil are buying them in droves, and your production lines are busy churning out more and more vehicles. You smile at your production volumes, but then you look at your income. Turns out, the margins on these little guys are so low that you’re actually barely making any money on all of those sales! You tell yourself, don’t worry big guy, since you still have your high margin car available for sale, and you’ll make the profits that way. You open your trusty spreadsheet to check the latest sales figures, and lo and behold - the sales dropped! Immediately, you call the director in charge of the high margin car and ask him what went wrong. “We didn’t invest much in improving this model since we spent everything on the low margin car. Meanwhile, our competitors vastly improved the engines, their navigation system, and MPG of their cars, which stole away from our sales”. But you read The Innovator’s Dilemma, you say to yourself. How could everything have gone so wrong?

Now imagine that instead, you invested the high margin vehicle, which was already beloved by your customers. With the extra $1B in R&D, you were able to improve on the features you already offered, thus overpowering the new features your competitors offered. 

For a business book, it is astounding that TiD fails to mention the opportunity cost of investing in a potentially disruptive technology. The costs of investing in disruption do not guarantee results. For large corporations with piles of cash, the opportunity costs of investing extra sums in finding a disruptive technology may be worth it. But large companies with limited cash may find themselves in an odd predicament, and disruption may be the last thing they need.

Sample Size

Christensen gives us examples disruptive technologies in action through the following industries: disk drives, excavators, and steel. 

Acquiring large amounts of sample sizes for a business book of this nature is unfeasible for one person, especially in 1997, when TiD was published. You would have to get access to data from thousands of companies, explore each industry they are in, and find the products and companies being disrupted or disruptive. Instead, TiD gives us examples from a sample size of three, “proving” that disruptive technologies come in two varieties and are indeed what make or break companies. I’m sure you can see the ludicrousness in the preceding sentence yourself. A sample size of three is not enough to base a whole book on. TiD also implies that every industry gets disrupted in the same way, since it doesn’t say otherwise. Does the luxury clothing industry get disrupted by cheap knockoffs? What about expensive Swiss watches that are undercut by low cost Chinese fakes?

As an example, evidence of disruption is found only in five industries (1, 2, 10, 22, and 25), three of which were sampled by The Innovator's Dilemma. No evidence of disruption is found in the other industries.

As an example, evidence of disruption is found only in five industries (1, 2, 10, 22, and 25), three of which were sampled by The Innovator's Dilemma. No evidence of disruption is found in the other industries.

Known-Unknowns and Known-Knowns

TiD is backed by a lot primary evidence. Christensen was able to speak to managers and CEOs to ask them what went wrong, and more importantly, what they did to fix it. Often times, the fix came in the form of a new, but internal venture, backed by the full faith and credit of the company CEO. This, in turn, allowed the company to create disruptive products, since the internal ventures were unshackled from the unyielding forces of resource allocation. 

I will turn to former U.S. Secretary of Defense, Donald Rumsfeld for my next comment. 

“There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.”

We attribute our performance to our behavior - that is, we take credit for what we can measure and see. If a new CEO joins a company, and the sales figures go up, we ascribe the results to the new CEO. That is, after all, the only thing that changed from before to now. Unfortunately, this isn’t entirely true, and we attribute the increase in sales to the CEO because that is the only known we can identify. Many changes may have taken place, but none of these changes are visible or measurable by us. Continuing with our car analogy, perhaps the demand for low cost vehicles increased, which itself is the result of shifted consumer tastes. Consumer tastes were themselves influenced by something else. Perhaps the negative impact large vehicles have had on the environment led consumers to feel bad about their oversized vehicles, opting them over time to prefer smaller and cheaper alternatives. Is it possible to link the increase in sales to the change in consumer taste for smaller vehicles? Sure is possible, but it is much harder and considerably less obvious. Instead, you might attribute the increase in sales to the new CEO, who is a very obvious change. 

Similarly, TiD substitutes unknowns with knowns in order to explain many of the strategies used by companies and their CEOs. A CEO may say the increase in sales would not have been possible if not for the newly funded internal venture, but how can he be so sure? Many of Christensen’s interviews were conducted before the advent of powerful computers that process terabytes of data, which makes the results even more dubious. Could it be that disruption is simply a known-unknown, rather than a known-known as TiD establishes it to be?

We know about the known-knowns. We know about the known-unknowns, but we cannot explain them. We don't know about unknown-unknowns, and therefore cannot explain them. TiD confuses the purple triangles with the green circles. 

We know about the known-knowns. We know about the known-unknowns, but we cannot explain them. We don't know about unknown-unknowns, and therefore cannot explain them. TiD confuses the purple triangles with the green circles. 

User Experience, Prestige, and Other Intangibles

You will have to use your prior knowledge of sustaining and disruptive technologies for this next passage, so if the definitions escape you, read them once more at the start of this post. If you remember them, let us continue. iPhone - is it a sustaining or disruptive technology? For starters, it came bundled with a web browser, a phone, and camera, none of which were wholly new technologies. The PocketPC, which came known to be as Windows Mobile, also offered all of those features. Thus, the value proposition of the PocketPC was the same, on paper, as that of the iPhone. The PocketPC flopped, while the iPhone prospered. Would that mean we could call the PocketPC a sustaining technology, and the iPhone a disruptive one? What makes the iPhone any more disruptive than the PocketPC? Playing devils advocate with myself, I would say the user experience of the iPhone was monumentally better, making it much more convenient to use. But as far as the value proposition - it was almost the same as that of the PocketPC. 

When I was a young, puerile kid, my grandfather gave me a Casio calculator watch. I though it was the epitome of cool, and I wore it everywhere. My grandfather gave it to me because it looked futuristic, but also because he knew I would never wear a mechanical at that young age. My Casio checked off all the typical characteristics of a disruptive technology: it was in most cases cheaper than a mechanical watch, it was simpler to read time with, it weighed less, and it even provided me with the unprecedented value of having a portable calculator with me everywhere I went! Many years later, however, the mechanical watch industry is alive and well. 

The above are only two examples that illustrate the shortcomings of TiD. The first example with the PocketPC and the iPhone attempts to show that despite the fact that both products are on paper disruptive technologies, that alone did not make them successful products. Much more is needed than just a new value proposition or a cheaper price. As Apple has shown through the years, a great user experience goes a long way. My Casio calculator watch also fit the bill to be labeled a disruptive technology, even though in retrospect we know there was nothing disruptive about it. Watches are often luxury goods that carry an element of prestige and social class with them. It may very well be that smartwatches will in the future provide so much value as to overpower that element of prestige, but the point remains - disruptive products may be disruptive in ways TiD did not foresee.

Performance Oversupply

Performance Oversupply (PO) is exactly what it sounds like: it is when a product gets packed with so many features and performance enhancements that it becomes more powerful than is required by the consumer. Thus, the consumer experiences diminishing returns from the performance of the product, since he can’t make use of it. A great example of PO are the latest computers that are being released. The average consumer doesn’t need all of the power that is packed into the machine, since all they will be doing is watching YouTube videos, browsing the web, and using some sort of word processor. In effect, the computer is more powerful than the power an average consumer needs from the computer. If we made a hypothetical power scale, the computer would be an 8, while the needs of the consumer would be a 5. The difference (8 - 5 = 3) is the Performance Oversupply.

Performance supply is an 8. Performance demand is a 5. Performance Oversupply = 8 - 5 = 3.

Performance supply is an 8. Performance demand is a 5. Performance Oversupply = 8 - 5 = 3.

TiD contends that when a PO occurs, the technology is ripe for disruption. Going by the preceding case, you could argue the iPad/Chromebooks/Ultrabooks are the form of disruption Christensen was talking about, since they’re less powerful, cheaper versions of the PCs they replaced. These less powerful, “disruptive” technologies provide exactly, if not slightly less power, than the consumer desires. On our hypothetical power scale, they would score around a 4.8. 

This all makes perfect sense - but there is another side to every coin. What if the needs of the consumer increase to match the PO? I find it best to explain through example, so let’s turn to one. YouTube is becoming television for the masses. More and more people are watching YouTube (or some other type of online video) every year, and as a result of technological improvements, the quality of these videos improve tremendously. YouTube now supports 4K UltraHD video, which requires much more processing power to consume. Not only is the world watching more videos, but a greater number of people are now editing and uploading their own videos. These content consumers and content creators are bridging the gap between the power demands of the consumer and the PO. Instead of a ranking of 5 for consumer needs, these consumers now rank a 7. Thus, the PO is reduced to (8 - 7 = 1). This suggests there might be room for Performance Oversupply, and disruption in this market may not happen after all.

Performance supply is an 8. Performance demand is a 7. Performance Oversupply = 8 - 7 = 1. The point of this illustration is to show that performance demand can increase, which in turn decreases Performance Oversupply.

Performance supply is an 8. Performance demand is a 7. Performance Oversupply = 8 - 7 = 1. The point of this illustration is to show that performance demand can increase, which in turn decreases Performance Oversupply.

For this example, the performance of the PC is kept stable at 8, since the rate of progress on processor technology has been slowing considerably in recent years, while consumer demands have been growing.

The Randomness Factor

This next commentary is similar to the Known-Unknowns and Known-Knowns point we touched on earlier, but it ventures a bit further, into new territory. The question I ask is as follows: does the whole of a disruptive technology come from what a company does in terms of productive effort (R&D, employees, management, etc…), or can a certain percentage of the technology be attributed to luck or randomness? In fact, TiD does make one brief reference to the element of luck in the success of a company, but it then proceeds to dismiss it almost entirely. Here’s what Christensen writes on the subject of luck:

“One might be to conclude that firms such as Digital, IBM, Apple, Sears, Xerox, and Bucyrus Erie must never had even well managed. Maybe they were successful because of good luck and fortuitous timing, rather than good management. Maybe they finally fell on hard times because their good fortune ran out. Maybe. An alternative explanation, however, is that these failed firms were as well-run as one could expect a firm managed by mortals to be - but that there is something about the way decisions get made in successful organizations that sows the seeds of eventual failure….The research reported in this book supports this latter view.”

Christensen is essentially saying that luck is not as important a factor as the processes for decision making. And he’s right in the grand sense - a company cannot attribute its success only to the element of luck, because it would have to consistently produce “lucky” products, which by definition, does not happen often. But in regards to disruptive technologies, which is precisely what the book is centered upon, luck is a crucial element. To better illustrate this point, let’s use a quote from Ed Catmull’s (the President of Pixar) book, Creativity, Inc.:

“When companies are successful, it is natural to assume that this is a result of leaders making shrewd decisions. Those leaders go forward believing that they have figured out the key to building a thriving company. In fact, randomness and luck played a key role in that success.”

So who are we to believe; the intelligent Harvard professor with years of experience, or the creative genius who helped spawn many of the worlds greatest animated films? I, for one, believe both are right…partially. Most people read TiD and treat it as the bible. I recommend reading it with a grain of salt. The processes of a company do indeed make-it-or-break-it, but luck is undeniably a critical factor too. The iPhone was a great product, but it also had fortuitous timing (luck), which is what made it so disruptive. 

Luck and randomness is what happens in the dashed circle. Everything else in the larger circle is attributed to the productive efforts of the company. The size of the luck and randomness circle is arbitrary and used only to illustrate the idea.…

Luck and randomness is what happens in the dashed circle. Everything else in the larger circle is attributed to the productive efforts of the company. The size of the luck and randomness circle is arbitrary and used only to illustrate the idea. 

No Book is Perfect

The Innovator’s Dilemma would have been a fantastic blog post, but as a book, it is extremely light on ideas and data points. As I have attempted to show through the above examples, there are a lot of points that TiD fails to explain. Basic economic concepts such as opportunity cost are left untouched by Christensen. Moreover, the sample size for the book is highly questionable. It often substitutes unknowns with knowns, and randomness with good decisions by managers. Intangibles are also oddly missing from TiD. Finally, while Christensen clearly shows how Performance Oversupply is a sign for an upcoming disruption, he keeps the power needs of consumers a static variable, which is demonstrably not a realistic assumption.

A disruptive product has become a business buzzword for good product which steals sales from the status-quo product. It is a word that explains the effect a product has had on the market, but not how that effect took place. It is an umbrella term for everything and nothing, all at once. While The Innovator’s Dilemma raises many excellent ideas, no book is without its faults and deserves to be read without skepticism. I will end this essay with a quote from Samuel Lee, an Assistant Professor of Finance at NYU. 

There are two ways to validate an economic or financial theory: wait 100 years and collect new data, or look at a fresh new data set, such as another time period or different markets. It can take decades before someone’s held accountable for a bunk theory.

Since 100 years have not passed, I took the second approach.

1Q 2015 Apple Results and Other Miscellaneous Musings

Sometimes a company does so well that it even surprises itself. This is what happened with Apple in Q1 2015. In three months (October, November, and December), Apple made $74.6B in net sales. The earnings were so good, in fact, that they exceeded the expectations of even the most bullish analysts. Below is a chart from Philip DeWitt of Fortune that summarizes analyst predictions prior to the posting of the results. 

Source: Fortune

Source: Fortune

Apple also posted the largest corporate quarterly earnings of all time (Fannie Mae still tops the list, but it's government sponsored and thus disqualified from this contest). Here's a nice chart from Wikipedia that puts Apple earnings in perspective. Apple is competing only with Oil and Gas companies which are in an industry of their own.

Source: Wikipedia

Source: Wikipedia


Now that we've established the astronomical scale of Apple's 1Q 2015 results, let's make my Accounting degree useful and jump into the financial data, starting with net sales.

Apple Sales Growth

As mentioned earlier, net sales in 1Q 2015 were $74.6B (+77% sequentially, +30% YoY). This chart is great because it shows just how seasonal Apple's sales truly were in the past few years. Every December, sales spike in terms of dollar and percentage growth, plummeting precipitously in the March quarter. They then rise slowly in June, continue rising into September, and reach their apex again in December. 


Apple Gross Margin

Many analysts have written that Apple's gross margin's will decrease in the future, due to competitive pressures from the low end market. While it's true that margins haven't exceeded 40% since September 2012, they haven't exactly ebbed either. 

As the chart above shows, gross margins were on the decline from March 2012 - June 2013, but have since been either stable or slightly increasing. Apple is not the type of company that deeply and truly cares about margins - Apple cares about the product. For that reason, I don't think there is much to be said here. In some periods margins will rise, in some, they'll fall. That said, I doubt margins will ever fall below 35%. Premium brands require premium materials. 


Apple ASP

Continuing our financial analysis, let's now turn to the average selling price (ASP) of Macs, iPhones, and iPads. (For the unaware reader, ASP is calculated as Product Revenues / Product Unit Sales). 

  • You would think that PCs are going through tough times, and you would be right. Industry sales are decreasing, and so are the prices manufacturers can charge. Since Apple competes on differentiating itself through hardware and software, however, the company is somewhat insulated from the overall PC market woes. Mac ASP's have remained steady in the past few years, settling on $1,258 (+5% sequentially) in 1Q 2015. It's likely Mac ASPs will stay within the $1,100 - $1,300 range for the next few years.
  • iPhone ASPs went up to $687 (+14% sequentially) in 1Q 2015 for two main reasons. The first reason is due to Apple's new iPhone storage structure, offering phones in the 16/64/128GB capacities. Going from 16GB > 64GB and from 64GB > 128 GB costs the consumer an extra $100, but that's not what it costs Apple. Lots of easy money was made here, but the long-term ramifications of such pricing tiers is questionable. Reason two for the increased ASPs is the introduction of the iPhone 6+, which sells for $100 higher than the iPhone 6 and all previous iPhone models. Just so you could see how expensive an iPhone can get (and by how much it can boost ASPs), a 128GB iPhone 6+ retails for $949 unsubsidized. How much more do you think it costs Apple to make than a regular iPhone 6? Answer: not much.
  • For many reasons, iPad ASPs have been on a steady decline. The average selling price of an iPad today is just $419 (-3% sequentially). People just aren't willing to pay out of pocket for tablets. I would wager much more money is made (on average) on iPad accessories and apps than on the iPhone counterparts, which makes the ASP decrease a bit of a moot point. The iPad Pro could change this. During the investor call, Tim Cook made a slight reference that iPads are great in enterprise, and the recent partnership with IBM can further strengthen the iPad in enterprise. If an iPad Pro is indeed a real product, and if enterprises begin purchasing them, ASPs will certainly increase.

Miscellaneous Musings

  • Apple is no longer reporting iPod unit sales or revenues, since the product is becoming more irrelevant by the second. I'm honestly surprised it took this long for Apple to stop giving us breakdowns. Average iPod revenues over the past year have been a measly $572M per quarter (which is negligible for a company as large as Apple).
  • Sales revenues are also no longer broken down for accessories. My thoughts on why are below.
  • There is a new product-level category Apple introduced this quarter, mysteriously called Other Products. According to Apple's 10-Q filing, this category includes "sales of iPod, Apple TV, Beats Electronics and Apple-branded and third-party accessories". In short, Other Products is the combination of the aforementioned product-level categories iPod and Accessories, both of which were killed of this quarter. While this may seem like a small change, I believe it foreshadows the Apple Watch accessory market. A huge selling point for the upcoming Apple Watch are the heterogeneous bands you can wear with it. Disclosing the revenues from these watch accessories may not be in Apple's best interest because the competition may learn far too much from it.
  • Also gone is the Retail Sales operating segment. Instead, retail sales are now distributed by geographic region (Americas, Europe, Greater China, Japan, and Asia-Pacific). The driver for this change is again the Apple Watch. Unlike most of Apple's other products, the Watch will be a product that will need to be tried on and physically played with before purchase. This is because the Watch is not only a tech device, but also a fashion accessory (would you buy an expensive watch online without first seeing it in person?). Continuing with this line of reasoning, the Apple Watch will be sold mostly through Apple retail stores (I think luxury boutiques and outlets will carry it as well, though). Disclosing retail sales would provide too much data into Watch sales, and that is likely the reason for the disappearance of the retail segment.

Postscript: I'm doing a new thing starting with this post, and will be including a gallery of all my charts. They're free for you to peruse and share.

Apple Financial Performance and 2015 Outlook

This post is divided into two sections: we start with a brief analytical look at Apple's historical financial data, followed by a narrative to describe the new products Apple will release in 2015. Companies cannot be analyzed solely by what's in a spreadsheet, which is why we will have to look at the big picture story of Apple too.

Net Sales and Profit margin

Net Sales and Profit margin

  • Every December (Q1 for Apple), we see revenues spike considerably. These sales spikes are helped by the holidays (October, November, and December are holiday months), but perhaps their most strongest contributor is the release of the latest iPhone every September.
  • The iPhone 6 was the most popular iPhone yet. It finally appeased consumers who wanted larger screens, leading many Android users to switch to iOS. In December of last year, Apple had sales revenues of $57.5B. For this December’s numbers, I expect to see sales revenues increase to $67B (+17% from Q1 2014).
R&D as a Percentage of Net Sales

R&D as a Percentage of Net Sales

  • There is a pretty clear trend with R&D spending. The lowest spending is in quarters ending in December, and the highest is for quarters ending in June. Given that Apple’s developer conference (WWDC) is in June, this makes a lot of sense. Apple is spending billions of dollars every year to announce its latest products in June so that developers can start getting ready to support the latest software and devices.
  • As a percentage of sales, R&D spending seems to be slowly increasing. It hit highs of over 4% of net sales, with an average of 3% over the last five or so years. Compared to Google and Microsoft, Apple spends very little on R&D. It’s hard to criticize Apple, however, since they keep releasing great products every year. Apple is not the type of company to release experimental technology to the public, which is likely the main reason for relatively its low R&D costs. For example, Google sells beta products like Google Glass and Android TV which are expensive to develop, and are unlikely to become profitable products in the near future. Apple, on the other hand, has a history of releasing products ready for the consumer market which go on to become highly profitable.
  • Profit margin, which is calculated as Net Income divided by Net Sales, is quite stable at 20%, bringing Apple roughly $20 in clean profits for every $100 they make. Behaving similar to net sales, profit margin usually peaks in Q1 (quarter ending December), since it is being aided by the excellent margins of the iPhone. I expect profit margin to increase in Q1 2015 since the iPhone 6 was offered in 16/64/128GB variants, opting many buyers to spend more for extra storage, resulting in even greater profits for Apple.

Going Forward

Revenues. Apple will post its highest revenues ever this quarter, but success hides problems. Most of the revenues Apple makes comes from the iPhone, distantly followed by iPad, Mac, iTunes/Software/Services (I/S/S), and finally, iPod. iTunes/Software/Services and iPod contribute only a sliver of those revenues, and I don’t expect either segments to grow rapidly (I/S/S is growing unlike the iPod, but it’s not a primary revenue driver for Apple). Next, we have the iPad. As I’ve written before, the iPad did not take over the world as many expected, and it is dwarfed by iPhone revenue and sales volume. This leaves us with the iPhone, which is increasingly Apple’s strongest revenue-driver. This means that the revenues of Apple are predicated upon one product. In the investing community, it is a well-established axiom that diversification is key in order to “diversify away the risk”. I don’t believe the Mac, the iPad and I/S/S are enough diversification, since their combined sales are still lower than those of the iPhone. As a percentage of revenues, the iPhone ranges from 50–57% (it changes quarterly), while the iPad+Mac+I/S/S ranges from 39–42%. What will happen when the market for iPhone becomes saturated? Of course it is possible that the iPhone will continue selling admirably for years to come, but more likely than not, another product will enter the market and take away from iPhone (or all smartphone) sales. Apple should aim to be the creator of that future product, or diversify away the risk of being disrupted through additional products and services.

New iPad and Mac? According to the credible supply chain leaks, we are likely to see an iPad Pro and a new Mac. I expect both of these products to be great, but it’s doubtful they will bring as much in as the iPhone does. The economics of the PC and tablet markets simply don’t allow for the immense subsidies that smartphones have. Moreover, smartphones are practically necessities all over the world. I challenge you to find a large portion of people who own a tablet but no smartphone. In short, these new products may boost revenues, but they won’t drive them. 

Apple Watch. I approach talking about the Apple Watch with caution. For a full analysis of it, read my piece from before. For this post, I will discuss only its effect on revenue. The reason for my caution is that nobody knows truly how large the market for smartwatches is or will be. Will people who wear watches now substitute them for the Apple Watch? What about people who don’t wear watches at all - will they buy one? Margins on the watch remain a mystery as well. We know that Apple will offer 3 tiers: Watch, Watch Sport, and Watch Edition. The cheapest model starts at $349, but the prices of the other two models is unknown, which says everything about my hesitance. From all accounts, the initial model of the Apple Watch will require an iPhone to connect to, further limiting its market. If you recall, however, the iPhone also needed a PC (Mac or Windows) to connect to, but it eventually became a standalone product. The Watch can plausibly take the same trajectory, and be the next revenue driver for Apple. 

Pessimistic Optimism. Apple is doomed is a cute aphorism to mean Apple isn’t growing as fast as before. While my thoughts from above may seem pessimistic, Apple is still a hugely successful company with great future potential. If I had to give this post as an elevator pitch, it would sound something like this: When you become as big as Apple, it’s hard to find markets that are large enough to make a a meaningful difference on revenues. That leaves Apple with two choices. Either find a large enough market, or diversify into a larger number of smaller markets. Which will it be?

Industry Analysis of Fintech Startups

Financial technology (fintech) startups are trending topic in recent years. The financial industry can be a sloth-like creature, with banks just recently adding support for decent mobile apps and more advanced capabilities such as spending trackers and remote deposit support. There are still many gaps left between what consumers want and what banks provide. This gap is currently being filled by fintech startups.

As I see it, there are currently three major categories of fintech: Payments & Money Transfer, Spending Trackers, and Investments. The order in which these categories are listed is not random: each category becomes easier to enter, in terms of the capital (human and financial) and barriers to entry. To be abundantly clear, let me further define the first category. The Payments & Money Transfer encompasses companies that allow you to pay for goods and services through them, or transfer money to anyone you wish. I lumped payments and money transfer together because the distinction between the two is not always clear (are you transferring money to pay someone?). This category includes companies like Venmo, Square, TransferWise, Stripe, and PayPal. It also includes Apple Pay and Google Wallet, but these services are provided by established companies and do not fit the bill for this analysis, which focuses on smaller companies. To be comprehensive, however, I have added them to the graphics below. You may even argue that Square and PayPal are too large to include here, but I feel they are not large enough to eschew. 

1) Payments & Money Transfer

As I briefly mentioned earlier, the Payments & Money Transfer category is most difficult to enter. It is extremely expensive to process payments due to the risks involved for each transaction, fraud, required security measures, governmental requirements, and a slew of other difficult problems that need solving. It’s not impossible, and we’ve seen some startups attempt to solve these problems, but on the whole, these startups are much larger in size and rarer in quantity. While I think a few may thrive on their own and even become public (Square, Stripe), the most likely scenario is for them to be purchased by the tech giants (Apple, Google, or Microsoft). For this scenario to be avoided, this category of services must find new ways and markets to monetize - an extremely hard proposition (Square is currently paying users $1 - $5 to use their Square Cash app!). 

Category 1: Payments & Money Transfer

Category 1: Payments & Money Transfer


2) Spending Trackers

The Spending Tracker category is exactly what it sounds like. It is a service provided by startups that allows you to monitor your income, expenses, bills, and everything else that measures your cash flows. This category includes startups like Mint, Mint Bills (formerly Check and Pageonce before that), Level Money (as if to prove my point, acquired by Capital One at the time of this writing), and a few others. Unlike Payments & Money Transfer, the barriers to entry here are lower. However, it is costly to partner with banks to allow for a historical list of your transactions. The very same risks are present here as for Payments & Money Transfer, but they aren’t as demanding. The reason we see relatively few companies compete in this category is because there is very little money to be made. Spending tracking apps and services provide a value-add, but most consumers are not willing to pay additionally for it. Consequently, these types of apps are best when used as gateways to other products, or when they are bundled with an existing product. 

Category 2: Spending Trackers

Category 2: Spending Trackers

To illustrate, let’s look at Mint, which is the largest and most popular Spending Tracker. The company began as a startup, and was soon purchased by Inuit, which sells personal finance and small business software. Although Intuit could have certainly charged users to use Mint, they smartly did not, because Mint is a gateway product to other Intuit software, most of which is not free. 

Just this week, Capital One purchased Level Money, a spending and budget tracking app. The reasoning behind this purchase is likely to acquire Level’s infrastructure, team, and technology. I expect to see Capital One’s apps to improve in the next year as a result of this acquisition, either by incorporating Level into its existing apps or keeping it standalone and adding features. 

It’s becoming increasingly difficult for banks to compete solely on savings and checking accounts, so they began to compete in mobile and online services. If Capital One’s mobile app are superior, for example, to Chase’s mobile app, it is more likely that a consumer will open an account with Capital One. Spending Tracking startups, of which not many remain private, will not survive on their own. They will either close shop or be acquired by larger financial companies. 


3) Investments

Investment startups (aka Robo Advisors) are the final major category of fintech companies which I have identified. They are also the most common. This includes huge startups like Wealthfront and Betterment, in addition to smaller companies like Acorns and Robinhood. They are all companies which aim to help you invest (long or short term). These startups compete with the established financial advisory and investment firms (Vangaurd, Schwab, TD Ameritrade). I listed this category last because I believe the barriers to entry are lower than for the above two categories, but I’m not against rearranging this category with Spending Trackers either. They have very different barriers to entry, and it is difficult to say which is harder to break into. Do not get too preoccupied with the order of the categories, as the order is more for academic than hierarchical purposes. 

Category 3: Investments

Category 3: Investments

This category of startups may actually succeed on its own, because they take a percentage fee or a flat cut of your investment. As I have written previously, these Robo Advisors face the majority of their challenges from huge traditional institutions, which have a lot more capital and consumer trust. The startups, however, have vastly better apps and sometimes provide more features than the traditional firms. 

I see this category playing out in one of three ways. First, the less disruptive startups will simply flounder, since they won’t be able to get consumers to invest with then. 

The second scenario concerns the innovative, but smaller startups like Acorns and Robinhood. They do not have the resources to compete effectively on their own, since investing is a capital intensive business. Consequently, most of these startups will go the way of Spending Trackers, and will be acquired by larger financial institutions for the same reasons: infrastructure, team, and technology. 

The last scenario involves the larger Investing startups, such as Wealthfront and Betterment. They have much more capital to work with, and can hire the best people. Additionally, the more assets under management (AUM) they have, the more consumer confidence they will get, which will result in even more signups. It will become a virtuous cycle, to the point where these companies become large enough to stand on their own or otherwise go public. Not all of the larger firms will succeed, however, since there is a limited market for such services. The unsuccessful ones (success is measured by profitability) will either close shop or also be purchased, at a bargain, by the larger institutions. 


In summary, due to the current unprofitability of fintech startups and the psychological aversion to risk that most consumers hold, most fintech startups will not succeed on their own. I see two emerging trends that effect the three fintech categories.

The first is for larger, established and traditional financial institutions to purchase fintech startups (i.e. Simple was acquired by BBVA, Mint by Intuit, Level Money by Capital One). This is a win for both parties; the startup gets the capital to create disrupting technologies, and the banks get the best technology, infrastructure, and human capital. Finally, consumers trust their money to the banks, and are more likely to make use of new technologies. 

Second, fintech companies can go public to raise capital. We’ve seen this most recently with LendingClub, but this will become a trend in the future. For example, Square and Stripe seem ripe for an IPO (unless they get acquired). If Wealthfront continues to grow and steal market share from Vanguard, it too can look into an IPO. Again, this will provide them with the additional capital needed to succeed in the financial industry, and it will reinforce consumer beliefs in the long-term health of the company. 

Not a trend but a reality of business, the unsuccessful startups will fail. This is a sad, but true reality of any business. Most businesses fail, and startups are businesses. Not all fintech startups will be able to become profitable businesses, and some will inevitably lose funding and exit the market. 


Postface: This analysis did not include every startup in the fintech industry - there are simply too many to include. For this reason, I have chose to include only the largest and most well-known fintech startups.

Spotify's Temporary Growth Spurt

Spotify released their latest subscriber numbers yesterday, announcing they have 15 million paying subscribers (up from 12.5 million in November), and 60 million total users (up from 50 million). 

I have updated all of my Spotify models, and below is my latest chart showing user growth.

Spotify Growth

While month over month growth rates seem to have increased (temporarily), the new subscriber data is likely an outlier. By outlier, I mean these rates shouldn't be used to make stable projections of future Spotify growth. Let me explain why. 

In December, the company held a promotion that let users sign up for a three-month Spotify Premium subscription for $0.99, instead of paying $9.99 per month. Great deal, right?

Right. But how many of those users who signed up for this promotion will actually stay with the service after the three months are up? My guess is 15-25% (25% is the current paying-to-free user ratio, and 15% is the more realistic rate, since users who signed up for this promotion are less likely to keep the subscription active). 

In addition, December is the holiday month, so it's very likely Spotify gift cards and subscriptions were gifted by friends and family. This further inflated the latest Spotify figures. 

It's never a good sign when companies inflate their numbers to proclaim better than expected results, but you will be hard-pressed to find companies that abstain from this practice. Especially in the world of startups. Fortunately for us, Spotify's number-inflation was easy to spot (sorry, I had to). Unfortunately for Spotify, it was caught.