Tech Stack Trees

Every product is built on and enabled by one or more technologies.

Understanding where a product fits on its higher-level tech stack is an important part of any long-term strategy or investment thesis.

The following is an exploration of tech stacks: what they are, how to model them, and what roles their components play. I also discuss what insights can be gained, such as potential opportunities to expand the business.

Stack Trees

Typically, a tech stack shows what infrastructure a technology is directly built on or requires. A SaaS startup for example could have a front- and back-end software stack with a cloud provider like AWS under it. The tech in focus is on top of the stack, with the supporting layers below it.

A tech stack tree is a higher-level version, branching both above and below the “layer” in focus. It shows both what the technology directly relies on and what relies on it. Stacks are fractal in nature, just like trees. An innovation spawns many others that use it, which further enable others, and so on.

A stack tree shows the relevant “slice” of the full dependency graph, going only a few nodes out. It looks something like this:

How to model a stack tree

Step 1: Determine the core tech. The first step is to decide what the actual technology in focus is. A technology in this case is a physical tool, process or system of other technologies that combine to do a job. It does not include businesses or social innovations. (A “business” is just a group of physical and social technologies united under a strategy — but we’re only concerned with the physical part here.[1])

Examples can range from the simple: hammers, glass, newspapers, or an assembly line process; to the more complex: CPUs, streaming video services, blockchains, smartphones, or nuclear reactors.

Step 2: Layers below. What are the primary technologies and processes needed to create and maintain the core tech? What does it need not only to function but to be sustainable? Clues can be found in:

  • Why now: What enabled the tech in the first place? Why wasn’t it widely used 20 or 50 years earlier?
  • Suppliers & major cost centers of businesses producing the tech. (Infrastructure, manufacturing tech, service networks…)
  • Supply chain & logistics: What gets the product/service to customers? (Transportation, shipping, internet…)
  • Distribution tech: What gets the customers to the product? (Retailers, advertising, search engines…)

Step 3: Layers above. What does the tech directly enable? It’s possible there are no layers here. Many well-known innovations don’t directly enable other tech, like Netflix.

  • What do other businesses use it for? Who is it a supplier to?
  • Is there anything in-between the technology and the ultimate end-user?
  • Is it a marketplace or multi-sided network that connects many groups of users?

Stack tree examples

Here’s a few examples of stack trees from the tech industry, although they can be drawn out for products any industry:

(The Amazon “Vampire Squid” is the best example I can think of traversing the stack, starting as an online marketplace and expanding outward in all directions: up, down, and sideways (I left out Prime, Music, Video, etc.).

What insights can be gained?

Companies are embedded in value networks because their products generally are embedded, or nested hierarchically, as components within other products and eventually within end systems of use. — Clayton Christensen

A tech stack tree is one way of looking at a company’s value network. This can lead to insights into where value flows, who captures it, and potential opportunities to expand the business.

What layers in the stack capture the most value?

Which technologies accrue most of the value depend on many things: how much value (productivity) created relative to alternatives, availability of potential substitutes, the size of the overall need, or other competitive advantages inherent to the business model.

One of the models Clayton Christensen uses makes sense to apply here: Where is the bottleneck in demand? In other words, where in the stack is the biggest difference between performance demanded and performance supplied? What needs to be better?

Nvidia is a good example here. They keep churning out GPUs with higher capabilities and the market keeps needing more. Supply hasn’t kept up with demand and that’s likely to continue for some time. This bottleneck (along with other factors ) allows the GPU layer to capture a lot of value.

Are there opportunities to expand into adjacent technologies?

Amazon (see stack above) is the prototypical example here. They started as an online marketplace with some fulfillment operations, and over time have expanded in all directions.

In more traditional business thinking, you consider expanding vertically into suppliers and customers or horizontally across industries. Traversing a tech stack is similar, but to me more focused on the true technological and needs-based relationships. Traditional business thinking would have never led to Amazon expanding into internet infrastructure via AWS.

Of course, expanding for the sake of it is never a good strategy. You have to ask:

  • Do our current products or processes give us an advantage here?
  • How much value does the layer capture? (Is it a bottleneck in demand?)
  • Are there existing barriers to entry, and if so, does our position in other stack layers help overcome them?
  • Does this improve the outcomes for our current customers?
  • Will expansion endanger our relationships with partners or customers?

Short case study: Food delivery apps

The core tech here is a mobile or desktop app where you can order food from many local restaurants and get it delivered within ~1 hour. DoorDash, UberEats, Postmates, etc.

Layers below: What are their major cost centers? Restaurants and delivery drivers. What enabled delivery apps? Primarily ubiquitous smartphones and access to GPS-based navigation. Restaurants also need to have some way to communicate, whether by phone or Wifi-based tablets, and be able to package food in proper take-out containers (plus potentially many others to manage operations).

Layers above: What needs delivery apps to run? Cloud kitchens, which operate large strategically located kitchens that can make food for many different branded “restaurants”. Recently a further layer was added with the concept of pop-up branded chains, which uses the cloud kitchen & delivery infrastructure.

What captures the value? In the stack above, smartphones capture far more value than any other tech — but they’re a platform with thousands of other use cases. In this case we just want to focus on value flow within the food delivery market. It may not be clear at first who captures more value: the delivery apps or the restaurants, given companies like DoorDash are losing so much money. But it’s clear that restaurants are not a bottleneck in demand — so it’s likely the apps that capture more value. And it seems their unit economics bear this out.

Opportunities for expansion? The clearest opportunity to expand within the tech stack is into cloud kitchens. This could potentially alienate some restaurant partners, but restaurants are so fragmented it shouldn’t matter. I think this has a lot of potential given: captive customers, synergies with delivery app, and lower costs with economies of scale and not having to operate normal restaurant ops.

Functions in the stack

How would you classify technologies in the stack? I think it’s most informative to categorize by what pattern (or archetype) they match in the greater ecosystem. These are functions that can exist in any industry or stack tree: Platforms, protocols, etc.

I’ll follow up with another post including examples of different tech functions and stack patterns.

To be continued…


Thanks to Leo Polovets and Jake Singer for helpful feedback on this post. Header photo from veeterzy on Unsplash.


Footnotes

  1. Physical technologies are “methods and designs for transforming matter, energy, and information from one state into another in pursuit of [goals]“. There are also social technologies (organizational processes, culture, values, incentive systems, memes, etc.) that evolve and build off of each other over time. (Definitions from The Origin of Wealth, by Eric Beinhocker.) ↩︎

The Scale of Large Projects

$100 million +

  • Midsize commercial airplane — $120m ^
  • Big budget video game — $150m ^
  • F-22 Raptor jet — $157m ^
  • iPhone R&D (2007) — $185m ^
  • Titanic (1912) — $190m ^
  • Big budget movie — $250m ^
  • SpaceX Falcon 9 v1 R&D — $350m ^
  • Empire State Building (1931) — $400m ^
  • Modern cruise ship — $750m ^
  • Hoover Dam (1936) — $863m ^

$1 billion +

  • Modern sports stadium — $1.3b ^
  • Modern skyscraper — $1.5b ^
  • Space Shuttle launch — $1.5b ^
  • Erie Canal (1825) — $4b ^
  • Human Genome Project (2003) — $5b ^
  • Panama Canal (1912) — $9b ^
  • Hubble Space Telescope (1990) — $9b ^

$10 billion +

  • Global Positioning System (1989) — $10b ^
  • Large Hadron Collider (2009) — $13b ^
  • Great Pyramid of Giza (~2500 BCE) — $20b ^
  • Three Gorges Dam (2009) — $25b ^
  • Transcontinental railroad (1863) — $30b ^
  • Manhattan Project (1945) — $30b ^
  • F-22 Raptor development (1997) — $42b ^
  • Great Wall of China (220 BCE) — $50b ^
  • SR-71 Blackbird development (1964) — $90b ^

$100 billion +

  • International Space Station — $150b ^
  • Apollo program (1969) — $200b ^
  • U.S. Interstate Highway System (~1980) — $500b ^

Many of these numbers are rough estimates. Figures adjusted for inflation after 1900 that weren’t already. Any figure before 1900 was adjusted via per capita GDP to more accurately reflect the scale of the undertaking.

If it were possible, the best metric to compare the scale of projects would be something like “Man-years + Value of Raw Materials (possibly in ounces of gold)“. This is especially true for projects like the Great Pyramid, the Suez Canal, the Great Wall of China, or the Manhattan Project which used mostly unpaid or low-paid labor.

Related: The Tallest Skyscrapers in the World, Pyramids vs. Skyscrapers

Book Notes: Innovation and Entrepreneurship

As with my other book notes, some passages are direct quotes and others are my own paraphrasing/summaries. Any footnotes or [brackets] are my personal comments.

Innovation & Entrepreneurship (1985), by Peter Drucker

Innovation and Entrepreneurship“The entrepreneur,” said the French economist J. B. Say around 1800, “shifts economic resources out of an area of lower and into an area of higher productivity and greater yield.”

All new small businesses have many factors in common. But to be entrepreneurial, an enterprise has to have special characteristics over and above being new and small. Indeed, entrepreneurs are a minority among new businesses. They create something new, something different; they change or transmute values. An enterprise also does not need to be small and new to be an entrepreneur. Indeed, entrepreneurship is being practiced by large and often old enterprises.

The entrepreneur upsets and disorganizes. As Joseph Schumpeter formulated it, his task is “creative destruction.” They see change as the norm and as healthy. Usually, they do not bring about the change themselves. But—and this defines entrepreneurship—the entrepreneur always searches for change, responds to it, and exploits it as an opportunity.

When shifting resources to a more productive area, there is a risk the entrepreneur may not succeed. But if they are even moderately successful, the returns should be more than adequate to offset whatever risk there might be. One should thus expect entrepreneurship to be considerably less risky than optimization. Indeed, nothing could be as risky as optimizing resources in areas where the proper and profitable course is innovation, that is, where the opportunities for innovation already exist. Theoretically, entrepreneurship should be the least risky rather than the most risky course. [There are “hidden” risks of not being an entrepreneur.]

“Innovation,” then, is an economic or social rather than a technical term. It can be defined the way Say defined it, as changing the yield of resources. Or, as modern economists would tend to do, it can be defined in demand terms rather than in supply terms: changing the value and satisfaction obtained from resources by the consumer. Continue reading “Book Notes: Innovation and Entrepreneurship”

Why Google Continues to be the Best

GoogleAs many have already seen, Google just posted some great third quarter figures. Both revenue and operating income were each up 23%, and Traffic Acquisition Costs (the revenue paid to AdSense partners) were at an all-time low of 25.7% of ad revenue. They also broke out some never-before-released sales figures: $2.5 billion a year for non-text display ads, and $1 billion for Google’s mobile search (driven mostly by use of their Android OS). But one part of the conference call caught my attention:

This is why we’re incredibly proud of Google Instant. Many of you guys speculated that we launched Instant to make more money. Well, let me tell you, that’s simply not the case. We launched Instant because it’s so much better for the user. In fact, from a revenue standpoint, its impact has been very minimal. And from a resource standpoint, it’s actually pretty expensive. So why did we do it? Well, we believe from a user standpoint, Instant is outstanding—and the data that we’re seeing actually bears this out.

The above was from Jonathan Rosenberg, Google’s SVP of Product Management. So, Google Instant was an expensive, non-revenue-producing upgrade to their lucrative search product. They did it, said Rosenberg, because it’s a huge improvement to the user experience. But how can that be measured? This got me thinking about what kind of metrics are truly important to Google in a broader economic sense. In Google’s financial reports they tout improvement in metrics like Traffic Acquisition Costs, Cost-Per-Click, and total number of Paid Clicks. All important to their business, but none that really capture Google’s overall business model. The most important metric to Google, I believe, is Revenue per Unit of User’s Time (or RUUT, for short).

Translating Time into Profit

Time is the ultimate scarce resource. Most businesses capture a portion of their customer’s wallets in exchange for a good or service. But businesses like Google (and TV networks, and most new media/web-based companies) capture a portion of customer’s time first, then translate that time into revenue.

Because time is scarce, when consumers choose to devote their time to a product or service, they are doing it at the exclusion of something else. So that company is literally capturing their customer’s time.  Before Google and other search engines, when people wanted to “find” something, they went about it a multitude of ways: white & yellow pages, classifieds, a library or bookstore, or just plain leaving your house and searching (hard to believe, I know). These things took up a lot of people’s time. Continue reading “Why Google Continues to be the Best”

The Innovations of Apple: Part II

Steve Jobs iPhone
Instead of further examining where Apple’s current (and future) products fit in on the “innovation scale,” in Part II I want to talk about Apple as an investment, and where its products fit in in terms of investment value.

Apple has been a fantastic investment over the past decade. In fact, since April 2003 when they launched the iTunes store (and iPod sales took off), a dollar invested in Apple would be worth over $40 today – an annualized return of almost 70%. That’s a return that would make most venture capitalists blush. Not bad for a company founded 27 years prior.

One more statistic: even if Apple stock had gone nowhere from its IPO in 1980 up to 2003, its annual return over the three decades since going public would be 13%, which still beats the S&P 500 by over 3%. In other words, almost all of Apple’s current value (~$230 billion) was created over the last seven years.

Where did that value come from? For the seven years ending 2009, sales grew from $5.7bb to $42.9bb. Over 70% of that growth came from new products: the iPod, the iPhone, media sales, and other related peripherals. On a net profit basis, even more than 70% of Apple’s growth came from new products (segment margins aren’t disclosed, but overall margins have hugely increased and most of that likely came from new products). Aside from the storied brand name, Apple is basically a startup that was funded with the cash and income from their struggling Macintosh business.

Apple and the Red Queen Run the Hedonic Treadmill

…it takes all the running you can do, to keep in the same place.” – The Red Queen, Lewis Carroll’s “Through the Looking-Glass”

So, clearly, the law of large numbers comes into effect when looking at Apple’s future growth prospects. To double revenues, Apple would have to sell an extra $43 billion a year in products – that’s over 68 million iPhones or 32 million Macs every year. Continue reading “The Innovations of Apple: Part II”

The Innovations of Apple: Part I

Steve Jobs

Apple is an incredibly creative, innovative company, and is usually at the top of people’s minds when it comes to new consumer technologies. So for the rest of this post, I’ll examine if and why Apple’s products are disruptive.

Disruptive Portable Music?

Before MP3 players, the only real option for portable music was a CD player. The first MP3 players were introduced in 1998, and had very low capacities. They could hold at most one or two CDs worth of music. In 2000, Creative released its NOMAD Jukebox, which had a capacity of around 1,200 songs. However, it was expensive and had limited usability.

SongCapacity

The first generation iPod (5GB) was released in 2001 and could hold an average of 1,000 songs, or about 79 CDs at an equivalent quality. The cost of music (content) was low at first: consumers who already had a CD collection could transfer their songs to the iPod, or download them from the (usually illegal) filesharing programs on the internet.

The total cost per portable song for an iPod 1G was $1.48 or $0.39 if users converted old songs. This compares favorably to a CD player’s $1.95 cost per song (assuming someone can carry around a maximum of 10 CDs without it becoming too much of a burden – see notes for details). Despite this ability to carry more music for an incrementally cheaper cost, like earlier players the high total cost of the device—and the lack of convenience to use its capacity—confined sales to “fist adopters” and high-end users who were willing to convert their old music collection.

So at first, the iPod was a sustaining innovation relative to other portable music devices. Although it wasn’t made by a current industry leader, it was a breakthrough improvement upon other portable music devices and the performance metrics that customers valued (quality, capacity, cost per portable song, etc.).

Continue reading “The Innovations of Apple: Part I”

Sustaining, Disruptive Innovations

Although the phrase disruptive innovation is used often, it is best described by Clayton Christensen in his books “::amazon(“0060521996″,”The Innovator’s Dilemma”)::” and “::amazon(“1578518520″,”The Innovator’s Solution”)::.” Most new technologies are sustaining—they improve the performance of current products along dimensions that the market already values. Rarer disruptive innovations result in products that are worse than current offerings in the near-term, but offer a different value proposition and are directed toward a different set of customers.

There are two types of disruptive innovations: new-market and low-end. New-market disruptions create a new value network (the context in which customers and firms within an industry define what attributes are most important), with different performance attributes. They usually serve customers who would normally not be using the product at all (i.e. personal computers, Bloomberg terminals). Low-end disruptions attack the least-profitable and most overserved customers along attributes that the market currently values (i.e. discount retailing, steel minimills). Both types of disruption eventually end up overtaking or completely replacing current offerings as their performance improves.

There are also two types of sustaining innovations: incremental and breakthrough. Most sustaining innovations are simple, incremental year-to-year improvements. Others are dramatic, breakthrough advances that surpass all current offerings (i.e. contact lenses replacing glasses, airliners replacing other long-distance travel). Many people confuse the terms disruptive and breakthrough. Christensen further distinguishes them by pointing out that disruptive innovations usually do not entail technological breakthroughs. Instead, they package current technologies into a disruptive business model.

Continue reading “Sustaining, Disruptive Innovations”

The McDonald’s Success Story

I am currently in the process of researching and writing a long article on the restaurant industry, or more specifically Steak n Shake, McDonald’s, and In-N-Out Burger. I should have it finished in a few weeks or so. In the mean time, please enjoy the following excerpt of the article on McDonald’s:

McDonald's (courtesy of verandaparknews.com)

As Ray Kroc sat in his car, he watched a miracle unfold. The parking lot was full, the lines were long, and customers were leaving with an arm-full of food and a smile on their face. Kroc stopped a few to see what was going on: “You’ll get the best hamburger you ever ate for fifteen cents. And you don’t have to wait and mess around tipping waitresses.” He had travelled the country selling milkshake machines, visiting countless restaurants of all types. But he had never seen a merchandising operation like this. It was 1954; fourteen years after the McDonald brothers opened their small burger drive-in in the town of San Bernardino, California.

Continue reading “The McDonald’s Success Story”

1908 – 2008 – 2108

MrMorgan
The New York Times, 11/4/1907

In October of 1907, financial markets in the United States came to a complete halt. Credit markets froze, major banks collapsed, and the stock market plunged. Heads of industry, like J. P. Morgan, were forced to inject massive amounts of capital to prevent a complete collapse.

The circumstances of the Panic of 1907 are very similar to our current crisis. In both, the economy had experienced huge growth over the preceding decade. Banks lowered lending standards, which led people to take on more and more debt. When bank assets began to decline, depositors panicked, and there was a run on the financial system.

But for the rest of this post, I’d like to focus on the period that follows a financial crisis—not on the crisis itself. (Keep in mind that although I speak in terms of American progress, my point applies to any country around the world.)

* * *

The period following 1907 was monumental in American history. Continue reading “1908 – 2008 – 2108”

Reality Bytes

So I just finished watching the debut of Dancing With the Stars. I saw a bit of the last season, and I really didn’t like it. But as far as reality shows go, my dislike was nothing out of the ordinary.

However, I have two reasons for watching this season: the first being Mark Cuban. Cuban is an interesting guy. I don’t follow his adventures in the sports world, but I like his blog and think some of his posts are right on the mark (no pun intended). Obviously, I don’t agree with everything he says but I like alternative points of view. It will be interesting to see him on the show. He certainly doesn’t fit in with the other male contestants — but I guess if he enjoys himself that’s all that matters. The second, being Josie Maran — for obvious reasons.

Bureaucratic Innovation

I think the biggest problem with reality TV at the moment is lack of originality. Every show is either a direct copy or a “rhyme” of another (usually successful) show. Is it because the networks are too afraid to take a chance on something new? Or have the creators/writers truly run out of ideas? I have the tendency to believe it’s the former rather than the latter. And that’s just one reason why eyeballs are moving away from traditional media sources and on to new media. More original, more creative content. If and when the big guys do get it right (it happens every once in a while), they have the talent and the resources to do a fantastic job.

Outside the bureaucracy of the large content generators, it’s easy and cheap to try new things. Throw it out there, quickly gauge the public’s response, and either make the necessary adjustments or continue to expand the content. Maximum tinkering and survival in small niches of content on The Long Tail. In my opinion, a combination of both these features — being nimble/innovative and having the resources of a large content generator — would produce the best results (another reason why Google (GOOG) is so successful).