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What Amazon Bears Don’t Understand About Big Data

|About: Amazon.com, Inc. (AMZN), WMT, Includes: FB, GOOG, JCP, NFLX, NFX, SHLDQ
Summary

The reason “experts” continue to pick traditional brick and mortar retailers like Walmart over Big Data companies like Amazon is because they base their evaluations on fundamental/historical analysis alone.

Thanks to Moore’s Law, we’ve passed a tipping point for computing power where Big Data analysis has become not only practical, but necessary to compete at the highest levels.

Amazon gets it. Walmart is about to be left in the dust.

Dig new moats or die!

It should come as no surprise that the world we live in is not the one that Warren Buffet or Michael Porter grew up in. So why is it that so many professionals and companies are operating in the old framework? The game is the same but the rules, the players, and the landscape all look drastically different than they did even just a few years ago. If this shift could be summed up in two words, it’s Big Data.

The following is an outline of the underlying philosophy of Brick & Mordor: how Big Data brought us to the point we’re at today, who the winners and losers will be, and - most importantly - what to do about it.

The Old School

Inarguably, the bible of the old school was written in 1934 and is known as Security Analysis, by professors Benjamin Graham and David Dodd of Columbia Business School. This sacred text outlines familiar concepts like Price-to-earnings ratios, bubbles, and market corrections to name a few fan favorites. These other “Buffet Metrics” comprise the fundamental toolkit that finance professionals have been using to make sense of the market since

… well 1934.

If the Buffet Metrics are the Old Testament for evaluating the performance of markets and companies, then the New Testament can be none other than the teachings of Professor Michael Porter, specifically Porter’s Five Forces Framework. This methodology, established in 1979, lays out the external forces faced by firms and is a key component in how Buffett-apostles evaluate the strength of a company’s position and core competencies.

They were invented in 1934 and 1979 respectively, and still you see professionals touting these ancient methodologies as the end all be all. By their logic, Amazon’s skyhigh P/E should have precipitated a dramatic downturn, instead of a historic rise to the top of multiple ‘impenetrable’ industries.

While the old thinking isn’t strictly wrong, it is no longer capable of explaining the full story, and that’s because it wasn’t built for the world we live in today. A world of Data Science and Artificial Intelligence. A world of cloud computing and systems of network intelligence. And a world that consumes, stores, and processes more data than Benjamin Graham and David Dodd could ever have imagined.

Moore’s Law, The Tipping Point, and The New Economy

Moore’s Law has massive implications on two of the most critical business principles, performance and cost. Increased computing power has the catch-22 effect of increasing performance while reducing cost, allowing existing businesses to scale dramatically and for new firms and even whole industries to spring up based around cheap and powerful computing. This is what has allowed heady upstarts with serious tech chops to compete with large incumbents faster and at a higher level than ever.

For the uninitiated, Moore’s Law is ‘the observation that the number of transistors able to fit in a dense integrated circuit doubles roughly every two years.’ In English, computing power doubles roughly every two years. Moore’s Law has taken us up to and past the tipping point where advanced computing is no longer a niche venture reserved for special projects, but a ubiquitous and cost efficient necessity. From a nice-to-have to an undeniable foundation upon which to build a scalable business.

Moore’s law has brought us all the way from the first computer to where we are today. We are at the point where its not only possible, but commonplace to capture unthinkably large data sets through APIs and FTPs, store them in databases powered by Amazon Web Services (AWS), Microsoft Azure, or one of the few other cloud storage providers, and then analyze them using Deep Statistics and eventually AI-driven tech, including: Machine Learning (ML), reinforced learning algorithms, and deep neural networks to produce invaluable business insights, incredibly accurate prediction models, and highly dynamic software that incorporates real-time data.

Buckle up, the New Economy has arrived.

Amazon(AMZN) Gets It. Walmart(WMT) Doesn’t

In the past five years, over the cries of overvaluation and impossibly sustainable P/E, five companies have proven our thesis by achieving eye popping growth and a combined market cap over $3 Trillion. They did this on the back of business models grounded in data science. Enter the age of FAANG.

Over the last five years, (A for) Amazon has watched its stock price and market capitalization soar to unprecedented levels in an unprecedented time frame. If you take a look at the graph below, you can actually see the aforementioned tipping point around 2014 where the returns from advanced cloud computing begin to take off. Shortly thereafter, Amazon (AMZN), a ‘simple’ ecommerce marketplace and cloud service provider, surpasses the market cap of the world’s largest retailer.

                        Please excuse the confusing reversal of colors

Four short years after toppling the retail superpower that is Walmart (WMT), in a turn of events that left traditional analysts baffled, Amazon’s stock price not only skyrocketed from around $300 in 2013 to over $1500 in 2018, but its market cap also surpassed the once impossible $1 Trillion mark. This meteoric rise is the unquestionable byproduct of Amazon’s heavy investment in data and tech, which simultaneously reduced costs and drove sales - sending profitability through the roof in recent years.

All the while, Amazon continues to defy conventional metrics. The analysts are looking for growth in the wrong places. Long-only stock pickers that primarily use "bottoms-up" fundamentals to judge a stock may find tough sledding moving forward. Stocks rise and fall regardless. It is very easy to mistake causation ("The P/E is too high...I told you!) with correlation. Volatility and credit cycles will continue. In other words, it won't look like much has changed initially but one only needs to look at the biggest companies listed on the exchanges 20 years ago v. 10 years ago v. today to see where we are heading.

What becomes apparent is that there is no measurable financial ratio that allows the value of a company’s technology to be factored into its stock price. And so, until the day that metric comes along, there will be those who can read the writing on the wall, and there will be those who are struggling to catch up.

The analysts have been warning to “sell your shares now” every week since 2014

What’s going on here is that Amazon has gone all-in on Big Data. Walmart hasn’t. Which might be the reason that Walmart and other big retailers took a surprising hit in the markets just a few days before Black Friday. Instead of building a business around traditional business fundamentals like Walmart and other legacy retailers, Amazon instead has opted to build their business around data and cloud computing.

The executives at Walmart and other legacy retailers are "incrementalists” because they came up in a time when this worked. Now is not that time. Who on Walmart's team is directing ecommerce strategy? How will these new acquisitions be integrated into their core business? What % of resources is directed to brick and mortar v. ecommerce in a finite resource world? Do they really think that ordering and picking up will keep them in the game v. Amazon? How will WMT compete if Amazon goes for a race to the bottom approach again and decides to lose money to increase sales once again (including groceries!)? The lack of immediately obvious answers means it’s very likely that there is nothing Walmart can do to stop Amazon.

Walmart Sells You Products. With Amazon, You are the Product

In tomorrow’s world, the success of a company will be determined by the strength of the insights it is able to extract from its own management systems. The surest way to do that is by implementing what Greylock Partners has dubbed Systems of Intelligence. SoI refers to systems that pull actionable analytics from massive enterprise management systems in real time. They are the bridge between the interface and the database, but instead of an added layer of complication, SoI provide outsized value in the form greater process control and automation, reduced cycle times, and advanced analytics with the potential for innovation in even the most overlooked aspects of a business. Instead of a hinderance, a company’s management systems can become a core strength and a key source of differentiation. The best part about SoI is that they can and should be used in conjunction with the systems of record and internal communication already in place (music to any CTO’s ears). This makes SoI the missing link in a successful and seamless Digital Transformation.

Examples of Systems of Intelligence that have cropped up over the last few years include things like “Customer Centric” Applications, various Employee Facing Workflow applications, Vertical Clouds, and other novel “intelligent applications” that improve workflows and create internal efficiencies. We will be writing more about the fascinating new field of SoI in the coming weeks / months.

Dig New Moats or Die

Economic moats are the most common things for FAANG and Amazon bears to point out when explaining why their advantages are unsustainable and their growth looks like a bubble.

This new class of companies has plenty of moats, just a new kind. Traditional moats include things like Brand Loyalty, High switching costs, patents and IP, and Walmart’s specialty, operational efficiency. Once impregnable, these moats can and have been circumvented by massive platform shifts - namely to cloud and mobile - and through Systems of Intelligence.

You might ask, why now? And what’s different about this time? The answer is that the technology only just became available. Moore’s Law had to propel cloud computing capabilities passed the aforementioned tipping point, and now that it has, all bets are off.

For the first time, it has become possible for companies like Amazon (also Facebook (FB), Netflix (NFLX), Google (GOOG), and a few others) to gain massive competitive advantages over big name legacy brands through the insights and efficiencies gained through the in sights achieved through the use of SoI. Not to mention the sheer force of will it takes to ignore all tradition and conventional financial wisdom and just put your head down and follow the data. Fortunately for Bezos, it seems to be paying off.

Walmart see it too and wants in on the action, but their first-follower mentality is leading them astray. Since 2016, Walmart has been in an acquisition frenzy to try to address the Amazon-shaped elephant in the room , but there is almost no hope of catching up. Amazon takes a highly analytical approach, relying on data to a religious degree to guide their decisions. Walmart, by comparison, is throwing spaghetti at the wall with their acquisitions of companies like Jet.com and Flipkart. Instead of investing in some kind of SoI to make use of the data they are already capturing, Walmart execs have chosen to acquire a handful of up-and-coming ecommerce companies with ready-made solutions to try to make up for lost time. The problem is there is no strategy - there’s no clear path to profitability for any of the new acquisitions, there’s no clear strategy for preventing cannibalization of Walmart’s own ecomm platform by Jet, and perhaps most importantly, there’s no one in the Walmart C-suite who understands the dire importance of the role Big Data will play Walmart’s survival, let alone the ins-and-outs of implementing one. (The same goes for almost every legacy brick & mortar retailer out there)

Amazon addresses the old problems, but in new, modern ways that take advantage of the capabilities of SoI to crunch massive data sets and seamlessly incorporate those insights into their operations. Instead of ‘low cost differentiation’, Amazon is going all in on digital differentiation (and winning).

On top of that, Amazon is in the process of digging some of the best antitrust entrenchments ever seen by cozying up to the US government. Between raising of wages to $15/hour, Bezos ownership of the Washington Post, and the recently secured $10B cloud computing contract with the Pentagon, how likely is it that Amazon is broken up by anti-monopoly laws? Not very.

Even President Trump has backed off.

As time moves on, cloud computing capabilities will only improve, and the possible applications will only become broader and more abstract. Companies like Walmart better start taking more cues from companies like Amazon, or end up on the trash heap alongside JCPenney (JCP) , Toys R Us, and Sears (OTCPK:SHLDQ). As a result of their first mover advantages, enormous investments in technology, and the massive infrastructure they’ve built - both online and off - Amazon is light years ahead of their counterparts in maximizing the potential of data, and as such is likely to keep blowing the minds of Buffett purists for years to come.

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What do you think will be the key indicators around tech and Big Data to watch for?

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Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

Additional disclosure: I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article *