Apple's $3 Trillion Valuation

Apple just released impressive quarterly results: $57.8 billion in revenue, 51 million iPhones, 26 million iPads, 4.8 million Macs, and 6 million iPods sold. So how should we value Apple? How much is a share of Apple really worth?

Let’s combine a few things to value Apple: (i) Warren Buffet’s intrinsic value model, (ii) market disruption theory, and (iii) jobs-to-be-done innovation theory. 

To read the headlines, you might think Apple is, again, doomed: “Apple’s Shares Slump on Weak Forecast” and “Apple iPhone Shares, Outlook Come Up Short” are just two examples. These headlines always encourage people to tell Apple what they must do. Here is a great list of past examples of “Apple must do…” (via John Gruber). 

If you look at any valuation number for Apple (for example, a P/E of 12.6, an EBITDA multiple of 8.4) it is remarkably low relative to its competitors (for example, Google has a P/E of 32.2 and an EBITDA multiple of 18.6).

To put this into perspective, if Apple had Google’s P/E,  it would be worth $1.2 trillion (yes, trillion with a “t”) instead of the $452 billion it is worth today. So why is Apple valued with a multiple so much lower than Google?

The Buffet model is important because it will tell us what assumptions we should analyze to determine Apple’s value and ultimately its multiple. The model is straightforward: a company’s value is based on its ability to generate future cash for its owners (what Buffet calls “owner earnings”). We can analyze Apple’s owner earnings by taking its net income plus depreciation and amortization less capital expenditures. This number was $34.7 billion for the 2013 fiscal year. 

The key to the Buffet model (and any valuation model, really) is projecting the growth rate of this owner’s earnings number. If we assume a future growth rate we can determine the company’s value. All of the future owner earnings are discounted back to today’s dollars to determine the value of the company. The trick, of course, is being accurate about these growth assumptions, which is where disruption theory and jobs-to-be-done theory can help us. 

If we assume that Apple will grow its owner earnings at 5% for the next 10 years, and then 2% for all years after that (with adjustments for cash and debt), Apple’s market cap wouldn’t be $453 billion. It wouldn’t even be $1.2 trillion. It would be $3 trillion. This is a share price of $3,275 in contrast to today’s share price of $506. At just 5% annual growth for Apple. 

Here is the math behind this valuation:

Intrinsic Value AAPLLet’s put this in perspective: from 2004 to 2013, Apple grew at a compound annual growth rate of 74% (meaning it grew owner’s earnings basically 74% every year, see the chart above). That is impressive, but not likely to continue forever. So how do we determine if this historical growth rate will slow to 5% then 2%? As Horace Dediu and Jesse Felder have noted, the market is undervaluing Apple’s ability to produce future cash flow, so understanding this growth rate assumption is critical to our assumptions.

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Happy Birthday Mac

Happy birthday Mac. My Apple products, starting in 1979:

Apple II+, Macintosh Plus, Macintosh IIfx, Macintosh QuadraAV, PowerMac G4 Quicksilver, iBook Dual USB, Newton 100, Newton 110, Newton 2000, PowerBook G4 17 inch, iMac G5 20 inch,MacBook 13 inch, iMac G5 20 inch, iMac 24 inch, MacPro, iMac 27 inch, MacBook Air, iPod (v2), iPod Classic, iPod Shuffle, iPod nano, iPhone, iPhone 3GS, iPhone 4 ATT, iPhone 4 Verizon, iPhone 5, iPad, iPad 2, iPad 3, iPad mini.

Thanks to my Dad for getting me started with Apple II+.



The Facebook Segmentation Problem

Facebook is about to go public, so obviously the company is getting a lot of attention and focus on its business and long-term prospects. I am not a frequent Facebook user, but I have enormous respect for fellow entrepreneurs and Mark Zuckerberg has done an outstanding job of building a product that people love to use and a very successful company. So congrats on the upcoming IPO. 

The big question, of course, is what is Facebook worth? It is an interesting discussion not only because so many people use Facebook, but because it is going public at an extraordinary valuation. Since Facebook provides a service that is free to users, it has to make money from its customers, advertisers. 

This is the interesting long-term question: can Facebook create more value for its customers (advertisers) than competitive solutions. If it can, it will continue to thrive, if not, it is a serious risk for any investor. Its users might be happy, but its customers won't be. 

Today, there is a story in the NY Times that points out this potential problem:

On Tuesday, General Motors, the third-largest advertiser in the country, shut down its Facebook budget, about $10 million, saying that those ads were simply not doing enough to sell automobiles.

In our language, the job that Facebook is helping its customers execute is to acquire customers. All advertising is about customer acquisition. You might argue that advertising also provides "branding", but this is just a step in the customer acquisition process. No company needs branding without customers, but all companies need to acquire customers, whether or not they decide to build a brand. 

Of course, Google has been extremely successful because they got the customer acquisition job done much, much better than alternatives, and they made it measurable and quantifiable. Google satisfied the unmet customer acquisition needs of all companies, big and small, and they have been rewarded with a very defensible model that is exceptionally profitable.

So will this be the case for Facebook? Perhaps, but another part of the same NY Times story is very revealing: 

Facebook currently allows marketers to buy audiences, say women between the ages of 18 and 35 who live in a specific neighborhood. But Facebook is essentially a walled garden, so what users may do on the Web beyond Facebook — where they shop, what they read — isn’t available for advertisers who want to home [sic] in on people’s behavior. [Emphasis added]

Facebook's product - how it generates revenue - is very traditional. It allows advertisers to target users based on demographic segmentation, for example, women between the ages of 18 to 35 who live in San Francisco. 

So why is this a problem? Because demographic segmentation has failed companies for decades. We have seen this in every type of market from consumer markets, to business markets, to medical devices, to software, and services. Over the long-term demographic segmentation will be viewed as an ancient relic for customer acquisition because demographics create phantom segments. They aren't real.

This makes perfect sense if you define markets based on the customer's job-to-be-done and not a product. Let's look at an example. 

Suppose you wanted to acquire customers for a new music service. The underlying job your service satisfies is to listen to music. The job is stable and will never change, but the products and services will continue to evolve as they have in the past from records, to CDs, to iPod, to Pandora. 

So how should you target customers to acquire? The obvious answer is to target customers who are unsatisfied with their ability to listen to music successfully. And let's say the part of listening to music they are unsatisfied with relates to discovering new music. Your potential customers are tired of their music collection and they really want to discover new music better. 

So you launch a new ad campaign on Facebook. And you select 18 to 35 year-old women in San Francisco. Will this get you the new customers you want? Probably not. So why is this?

Because the people who are unsatisfied with their ability to execute the job of discovering music don't segment themselves by demographics (e.g. age, gender, income, zip code). They segment themselves by how well they can execute the job. 

Could an 18 year-old woman in San Francisco, a 60 year-old man in Detroit, a low-income mom in New York, and a wealthy man in Seattle all be similarly dissatisfied with their ability to execute the same job, e.g. discover new music? 

They answer, of course, is yes. But these people would absolutely never fall into the same traditional segmentation. And this is the risk for Facebook - its segmentation is inefficient. Chris Dixon points out that Google's revenue per pageview is estimated to be 100x to 200x Facebook's.

This is because a company can acquire customers on Google based on the job the customer is trying to execute, not based on phantom demographic targeting. In other words, it doesn't matter if I am male, female, high income, low income, or anything else when I type a search term into Google. All that matters is that I search for "music discovery" and when I find your new service, I will be a satisfied customer, regardless of my demographics. 

Finally, I found it amusing that the NY Times article points to a possible improvement for advertisers on Facebook: that they could in the future use Facebook's user behavior data to segment. This type of behavoir segmentation or "psychographics" is just as flawed as demographic segmentation. It just came into vogue as computers got more advanced and companies could access and analyze consumer credit card transactions. 

But what I purchased in the past tells you nothing about how satisfied I am with my ability to execute an important job. So the only accurate segmentation is based on a customer's job-to-be-done (and specifically on the outcomes in the job). This is how customers segment themselves. 

If Facebook only offers companies traditional segmentation, their advertising model will be at serious long-term risk. If it can figure out how to get the customer acquisition job done better than Google and others, it could continue to thrive. 


Pivot Away from Pivot

Pivoting is all the rage in startup land. But it is a concept that I believe is extremely harmful to entrepreneurs. Pivoting (and "failing fast") is exactly the wrong approach to launching a new company. 

The problems with "pivoting" don't get enough attention. Venture investors and successful entrepreneurs love to tell the stories of the early days of their startups. 

And this is understandable. I have been there, and the early days are exciting. You start with what seems to be a great idea, you raise venture capital, you start hiring a team willing to take enormous risk to build something new. 

Fred Wilson recently posted about startup creation stories. And there are lots of lessons to be learn from these stories. 

But there are many, many more lessons - and better lessons - to be learned from startup failures. 

And my conclusion from seeing many startup failures is that the entire innovation process for startups (and larger companies) is fundamentally broken. 

So the answer to the innovation problem is absolutely NOT to pivot. Here's why. In the mind of the enterpreneur, this leads to launching before he/she really understands the market opportunity and the customer needs. 

The lean startup movement would seem to be a solution to this and Steve Blank's customer development model is an improvement over traditional product development.

But both lean startup and "customer development" are based on the idea that customers don't know what they want, i.e. they have latent needs.

So if customers don't know what they want, it would make sense to launch quickly, fail fast, pivot, and hope for the best. 

Seesmic is the latest example of the pivot method. And Seesmic shows that pivoting doesn't work

I was amazed at the number and types of pivots Seesmic has taken. From All Things Digital: 

Since it launched in 2007, Seesmic has been a video platform, then made Twitter clients and other social tools, and last year tried to make a go with Salesforce CRM products...  In February, the company announced it would be changing and expanding the free social media cross-posting tools it bought in 2010 into a paid service called “Seesmic Ping.”

This is absurd in the extreme. But it is also very common with startups. In fact, this type of behavior is encouraged by venture investors. 

Ultimately it is harmful to entreprenuers who are dedicating their lives and souls to their startups, often at the expense of their personal lives and their families. 

A much better approach is to spend the necessary time to understand the market, the customer needs, the opportunities and to innvotate only when you know all of the unmet needs in a market.

It can be done


Today was the last day of earthscreen, a project I started with good intentions, like most startups. earthscreen for me was different for two reasons: first, I used a different, extremely lean model without venture investors, and second, it had a social mission.

earthscreen was also important for me because it is the last company I will launch using traditional methods. By traditional, I mean the traditional "innovation method" of starting with an idea, launch, and iterate.

In current terminology, earthscreen was launched using a "lean startup" method, a "fail fast" development process, and a "pivot" strategy. We were lean, we failed fast, and we pivoted. And that was the problem, not the solution.

All three of these techniques are fundamentally broken because they are based on the traditional, ill-defined definition of a market. And these techniques are flawed because they are built on the belief that customers have "latent needs."

Thankfully, it was because of earthscreen that I came discover Tony Ulwick, Strategyn, and Outcome-Driven Innovation. And I can honestly say that my professional life was changed forever.

Tony and Strategyn pioneered a new way to define markets, needs, opportunities, strategy and innovation based on the idea that customers hire products to get a job done, and that all the customer needs in a market can be identified. Customer needs can be identified because customers use metrics (called outcomes) to judge if they can execute the job quickly, predictably, and successfully.

I am extremely lucky to now be part of the Strategyn team and to have Tony as both a colleague and a close friend. 

So, while today is the end of earthscreen, it is the start of a new future of innovation and venturing for me. And my goal is still the same, to use innovation to help make people's lives better and the world a better place.

Hello iCloud, Welcome Future

On eve of the iCloud launch, I am reflecting on the past to predict the future.

Apple is currently the most valuable company in the world, the most valuable to have ever existed, with a cash balance larger than most industries, $0 debt, and an invincible combination of differentiation and low cost.

And yet, its market share is tiny.

The future has never been brighter for Apple. Go long, very long, Apple. 

And if Apple's future is bright. So is the world's.

For the past three decades, Apple has been focused on one goal: to make our lives better. 

In our terminology, Apple's mission is to help people get jobs done better. 

Jobs are the tasks and goals we need to accomplish to make our lives better. 

Learn a new skill, teach a child, cure a disease, build communities, collaborate, inspire...

Make our lives better. 

It is a simple goal with enormous complexity. And complexity creates opportunity to simplify.  

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Ending Free Money

How can we make our lives better?

First, let’s look at how we got here. Our economy is in trouble and your life is probably not better off than it was 10 years ago. It is probably not getting any better soon.

So why is this? Did you stop working hard? Probably not. Did our country stop innovating? No - just look at the innovation here in California: Apple, Google, Facebook, Twitter...

So what happened? What caused your life to be worse? In short, what has happened is very simple: a very bad idea has infected Washington and politicians. This bad idea has caused enormous damage to our economy and it even caused the total collapse of our economic system in September 2008. 

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Market Sizing: Numerical Narratives

Chris Dixon posted about market sizing using narratives as opposed to numbers, and Fred Wilson agreed - even demonstrating market sizing with a cartoon illustration. 

It is easy to see why Chris' and Fred's "narratives over numbers" market sizing might be appealing. After all, as Brad Feld writes, "Almost every market sizing presentation is incorrect - by a lot. Enough to make it irrelevant." Chris writes, "you should never rely on quantitative analysis to estimate market size. Venture-style startups are bets on broad, secular trends."

This seems to make sense: tell a story because your numbers are going to be wrong anyway. But let's analyze the traditional market definitions to see why traditional quantitative methods are incorrect. Non-quantitative analysis (a story) is not enough. Market sizing has to be quantitative because it is a tool to make an investment (i.e. a quantitative) decision.

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Fail Fast vs. Zero Burn

Mark Suster has a nice post about the "fail fast" method. He rails against fail fast, and rightly so. He writes:

I have met so many young entrepreneurs who tell me, “we don’t need business plans anymore, there a waste!  We’re going to put our product out there and fail fast!”... or they tell me, “we’ll launch a bunch of products and see what works.”  That is the old “throw spaghetti against the wall and see what sticks” approach.  It’s intellectually lazy and I doubt many great companies are born this way.

We definitely agree with Mark's view. In fact our plans are extensive and they take time and money to create for one reason: the goal is to never fail. Of course most of the venture community (and the broader innovation community) thinks this is impossible, but as we have shown with over two-decades of successful product launches, it is possible by using scientific methods to understand markets and customer needs. The problem is not with the idea of creating a business plan, it is with the inputs to the plan. The inputs (i.e. the definition of a market and a customer need) have to change, otherwise creating the plan will not result in a higher chance of success.

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Top 12 Mistakes (3,4, 5)

I wanted to continue my analysis of Marty Cagan's Top 12 Product Management Mistakes. I already analyzed the first two mistakes here, and I included an introduction to our ODI terms. I think it is helpful to look at the rest of the mistakes and offer ODI-based solutions. 

Mistake 3. Confusing Yourself With Your Customer

Marty identifies the third mistake as thinking "of yourself as more like the target customer than you are." This is a good mistake to avoid, but there are two dimensions to this mistake. The first is the functional job that the customers are trying to get done. Without a detailed understanding of the job, all the process steps in the job map, and all of the outcomes, it is almost impossible to make sure that your solution will meet the customer needs. The second is the consumption chain jobs (install, interface, learn-to-use, maintain, etc.). In this mistake, Marty is really talking about the consumption chain jobs (the "usability" in Marty's terms). 

Confusing yourself with your customer is only part of the reason usability testing fails to uncover flaws in the product. The real reason is because the product does not satisfy the functional job and it outcomes. Customers don't buy product to interface with them or to learn to use them. They buy products to get a functional job done. So it is no surprise that usability testing, no matter how much of it you do, fails to prevent a flawed product launch.  What is needed is testing of the features against the outcomes in order to validate that the feature satisfies the functional job's outcomes. And because outcomes are metrics, satisfaction levels can be measured accurately. 

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