Is the ‘Uber’ moment for the Telecom sector coming?

As I am preparing for my keynote speech for the Annual Dinner event of the Telecom Society Netherlands (TSOC) end of January 2020, I thought the best way was to write down some of my thoughts on the key question “Is the ‘Uber’ moment for the telecom sector coming?”. In the end it turned out to be a lot more than some of my thoughts … apologies for that. Though it might still be worth reading, as many of those considerations in this piece will be hitting a telcos near you soon (if it hasn’t already).

Knowing Uber Technologies Inc’s (Uber) business model well (and knowing at least the Danish taxi industry fairly well as my family has a 70+ years old Taxi company, Radio-Taxi Nykoebing Sjaelland Denmark, started by my granddad in 1949), it instinctively appear to be an odd question … and begs the question “why would the telecom sector want an Uber moment?” … Obviously, we would prefer not to be massively loss making (as is the Uber moment at this and past moments, e.g., several billions of US$ loss over the last couple of years) and also not the regulatory & political headaches (although we have our own). Not to mention some of the negative reputation issues around “their” customer experience (quiet different from telco topics and thank you for that). Also not forgetting that Uber has access to only a fraction of the value chain in the markets the operate … Althans of course Uber is also ‘infinitely’ lighter in terms of assets than a classical Telco … Its also a bit easier to replicate an Uber (or platform businesses in general) than an asset-heavy Telco (as it requires a “bit” less cash to get started;-). But but … of course the question is more related to the type of business model Uber represent rather than the taxi / ride hailing business model itself. Thinking of Uber makes such a question more practical and tangible …

And not to forget … The super cool technology aspects of being a platform business such as Uber … maybe Telco-land can and should learn from platform businesses? … Lets roll!

uber Uber

Uber main business (ca. 81%) is facilitating peer-2-peer ride sharing and ride hailing services via their mobile application and its websites. Uber tabs into the sharing economy. Making use of under-utilized private cars and their owners (producers) willingness to give up hours of their time to drive others (consumers) around in their private vehicle. Uber had 95 million active users (consumers) in 2018 and is expected to reach 110 million in 2019 (22% CAGR between 2016 & 2019). Uber has around 3+ million drivers (producers) spread out over 85+ countries and 900+ cities around the world (although 1/3 is in the USA). In the third quarter of 2019, Uber did 1.77 billion trips. That is roughly 200 trips per Uber driver per month of which the median income is 155 US$ per month (1.27 US$ per trip) before gasoline and insurances. In December 2017, the median monthly salary for Americans was $3,714.

In addition Uber also provides food delivery services (i.e., Uber Eats, ca. 11%), Uber Freight services (ca. 7%) and what they call Other Bets (ca. 1%). The first 9 month of 2019, Uber spend more than 40% of the turnover on R&D. Uber has an average revenue per trip (ARPT) of ca. 2 US$ (out of 9.5 US$ per trip based on gross bookings). Not a lot of ARPT growth the last 9 quarters. Although active users (+30% YoY), trips (+31% YoY), Gross Bookings (+32%) and Adjusted Net Revenue (+35%) all shows double digit growth.

Uber allegedly takes a 25% fee of each fare (note: if you compare gross bookings, the total revenue generated by their services, to net revenue which Uber receives the average is around 20%).

Uber’s market cap, roughly 10 years after being founded, after its IPO was 76 Bn US$ (@ May 10th, 2019) only exceeded by Facebook (104.2 Bn @ IPO) and Alibaba Group (167.6 Bn US$ @ IPO). 7 month after Uber’s market cap is ca. 51 Bn US$ (-33% down on IPO). The leading European telco Deutsche Telekom AG (25 years old, 1995) in comparison has a market capitalization around 70 Bn US$ and is very far from loss making. Deutsche Telekom is one of the world’s leading integrated telecommunications companies, with some 170+ million mobile customers, 28 million fixed-network lines, and 20 million broadband lines.

Peal the Onion

“Telcos are pipe businesses, Ubers are platform businesses”

In other words, Telco’s are adhering to a classical business model with fairly linear causal value chain (see Michael Porter’s classic from 1985). It’s the type of input/output businesses that has been around since the dawn of the industrial revolution. Such a business model can (and should) have a very high degree of end-2-end customer experience control.

Ubers (e.g., Uber, Airbnb, Booking.com, ebay, Tinder, Minecraft, …) are non-linear business models that benefit from direct and indirect network effects allowing for exponential growth dynamics. Such businesses are often piggybacking on under-utilized or un-used assets owned by individuals (e.g., homes & rooms, cars, people time, etc…). Moreover, these businesses facilitate networked connectivity between consumers and producers via a digital platform. As such, platform businesses rarely have complete end-2-end customer experience control but would focus on the quality and experience of networked connectivity. While platform business have little control over their customers (i.e., consumers and producers) experiences or overall customer journey they may have indirectly via near real-time customer satisfaction feedback (although this is after the fact).

Clearly the internet has enabled many new ways of doing business. In particular it allows for digital businesses (infrastructure lite) to create value by facilitating networked-scaled business models where demand (i.e., customers demand XYZ) and supply (i.e., businesses supplying XYZ).

Think of Airbnb‘s internet-based platform that connects (or networks) consumers (guests), who are looking for temporary accommodation (e.g., hotel room), with producers (hosts, private or corporate) of temporary accommodations to each other. Airbnb thus allow for value creation by tying into the sharing economy of private citizens. Under-utilized private property is being monetized, benefiting hosts (producers), guests (consumers) and the platform business (by charging a transactional fee). Airbnb charges hosts a 3% fee that mainly covers the payment processing cost. Moreover, Airbnb’s typical guest fee is under 13% of the booking cost. “Airbnb is a platform business built upon software and other peoples under-utilized homes & rooms”While Airbnb facilitated private (temporary) accommodations to consumers, today there are other online platform businesses (e.g., Booking.com, Experia.com, agoda.com, … ) that facilitates connections between hotels and consumers.

Think of Uber‘s online ride hailing platform connects travelers (consumer) with drivers (producers, private or corporate) as an alternative to normal cab / taxi services. Uber benefits from the under-utilization of most private cars, the private owners willingness to spend spare time and desire to monetize this under-utilization by becoming a private cab driver. Again the platform business exploring the sharing economy. Uber charges their drivers 25% of the faring fee. “Uber is a platform business built upon software and other peoples under-utilized cars and spare time”. The word platform was used 747 times in Uber’s IPO document. After Uber launched its digital online ride hailing platform, many national and regional taxi applications have likewise been launched. Facilitating an easier and more convenient way of hauling a taxi, piggybacking on the penetration of smartphones in any given market. In those models official taxi businesses and licensed taxi drivers collaborate around an classical industry digital platform facilitating and managing dispatches on consumer demand.

“A platform business relies on the sharing economy, monetizing networking (i.e., connecting) consumers and producers by taking a transaction fee on the value of involved transaction flow.”

E.g., consumer pays producer, or consumer get service for free and producer pays the platform business. It is a highly scaleble business model with exponential potential for growth assuming consumers and producers alike adapt your platform. The platform business model tends to be (physical) infrastructure and asset lite and software heavy. It typically (in start-up phase at least) relies on commercially available cloud offering (e.g., Lyft relies on AWS, Uber on AWS & Google) or if the platform business is massively scaled (e.g., Facebook), the choice may be to own data center infrastructure to have better platform control over operations. Typically you will see that successful Platform businesses at scale implements hybrid cloud model levering commercially available cloud solutions and own data centers. Platform businesses tend to be heavily automated (which is relative easy in a modern cloud environment) and rely very significantly on monetizing their data with underlying state-of-the-art real-time big data systems and of course intelligent algorithmic (i.e., machine learning based) business support systems.

Consider this

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A platform-business’s technology stack, residing in a cloud, will typically run on a virtual machine or within a so-called container engine. The stack really resides on the upper protocol layers and is transparent to lower level protocols (e..g, physical, link, network, transport, …). In general the platform stack can be understood to function on the 3 platform layers presented in the chart to the left; (top-platform-layer) Networked Marketplace that connects producers and consumers with each other. This layer describes how a platform business customers connect (e.g., mobile app on smartphone), (middle-platform-layer) Enabling Layer in which microservices, software tools, business logic, rules and so forth will reside, (bottom-platform-layer) the Big Data Layer or Data Layer with data-driven decision making are occurring often supported by advanced real-time machine learning applications. The remaining technology stuff (e.g., physical infrastructure, servers, storage, LAN/WAN, switching, fixed and mobile telco networking, etc..) is typically taken care of by cloud or data center providers and telco providers. Which is explains why platform businesses tends to be infrastructure or asset lite (and software heavy) compared to telco and data-center providers.

“Many classical linear businesses are increasingly copying the platform businesses digital strategies (achieving an improved operational excellence) without given up on their fundamental value-chain control. Thus allowing to continue to provide consumers a known and often improved customer experience compared to a pure platform business.”

So what about the Telco model?

Well, the Telco business model is adhering to a linear value chain and business logic. And unless you are thinking of a service telco provider or virtual telco operator, Telcos are incredible infrastructure and asset heavy with massive capital investments required to provide competitive services to their customers. Apart from the required capital intensive underlying telco technology infrastructure, the telco business model requires; (1) public licenses to operate (often auctioned, or purchased and rarely “free”), (2) requires (public) telephony numbers, (3) spectrum frequencies (i.e.,for mobile operation) and so forth …

Furthermore, overall customer experience and end-2-end customer journey is very important to Telcos (as it is to most linear businesses and most would and should subscribe to being very passionate about it). In comparison to Platform Businesses, it would not be an understatement (at this moment in time at least) to say that most Telco businesses are lagging on cloudification/softwarisation, intelligent automation (whether domain-based or End-2-End) and advanced algorithmic (i.e., machine learning enabled) decision making as it relates to overarching business decisions as well as customer-related micro-decisions. However, from an economical perspective we are not talking about more than 10% – 20% of a Telco’s asset base (or capital expenses).

Mobile telco operators tend to be fairly advanced in their approaches to customer experience management, although mainly reactive rather than pro-active (due to lower intelligent algorithmic maturity again in comparison to most platform businesses). In general, fixed telco businesses are relative immature in their approaches to customer experience management (compared to mobile operators) possibly due lack of historical competitive pressure (“why care when consumers have not other choice” mindset). Alas this too is changing as more competition in fixed telco-land emerges.

“Telcos have some technology catching up to do in comparison & where relevant with platform businesses. However, that catching up does not force them to change the fundamentals of their business model (unless it make sense of course).”

Characteristic of a Platform Business

  • Often relies on the sharing economy (i.e., monetizing under-utilized resources).
  • It’s (exponential) growth relies on successful networking of consumers & producers (i.e., piggybacking on network effects).
  • Software-centric: platform business is software and focus / relies on the digital domain & channels.
  • Mobile-centric: mobile apps for consumers & producers.
  • Cloud-centric: platform-solution built on Public or Hybrid cloud models.
  • Cloud-native maturity level (i.e., the highest cloud maturity level).
  • Heavily end-2-end automated across cloud-native platform, processes & decision making.
  • Highly sophisticated data-driven decision making.
  • Infrastructure / asset lite (at scale may involve own data center assets).
  • Business driven & optimized by state-of-art big data real-time solutions supported by a very high level of data science & engineering maturity.
  • Little or no end-2-end customer experience control (i.e., in the sense of complete customer journey).
  • Very strong focus on connection experience including payment process.
  • Revenue source may be in form of transactional fee imposed on the value involved in networking producers and consumers (e.g., payment transaction, cost-per-click, impressions, etc..).

In my opinion it is not a given that a platform business always have to disrupt an existing market (or classical business model). However, a successful platform business often will be transformative, resulting in classical business attempting to copy aspects of the platform business model (e..g, digitalization, automation, cloud transformation, etc..). It is too early in most platform businesses life-cycle to conclude whether, where they disrupt, it is a temporary disruption (until the disrupted have transformed) or a permanently destruction of an existing classical market model (i.e., leaving little or no time for transformation).

So with the above in mind (and I am sure for many other defining factors), it is hard to see a classical telco transforming itself into a carbon copy of a platform business and maybe more importantly why this would make a lot of sense to do in the first instance. But but … it is also clear that Telco-land should proudly copy what make sense (e.g., particular around tech and level of digitization).

Teaser thought Though if you think in terms of sharing economical principles, the freedom that an eSIM (or software-based SIM equivalents) provides with 5 or more network profiles may bring to a platform business going beyond traditional MVNOs or Service Providers … well well … you think! (hint: you may still need an agreement with the classical telco though … if you are not in the club already;-). Maybe a platform model could also tab into under-utilized consumer resources that the consumer has already paid for? or what about a transactional model on Facebook (or other social media) where the consumer actual monetizes (and controls) personal information directly with third party advertisers? (actually in this model the social media company could also share part of its existing spoil earned on their consumer product, i.e., the consumer) etc…

However, it does not mean that telcos cannot (and should not) learn from some of the most successful platform business around. There certainly is enough classical beliefs in the industry that may be ripe for a bit of disruption … so untelconizing (or as my T-Mobile US friends like to call it uncarrier) ourselves may not be such a bad idea.

Telco-land

“There is more to telco technologies than its core network and backend platforms.”

Having a great (=successful) e-commerce business platform with cloud-native maturity level including automation that most telcos can only dream of, and mouth watering real-time big data platforms with the smartest data scientist and data engineers in the world … does not make for an easy straightforward transformation to a national (or world for that matter) leading (or non-leading) telco business in the classical sense of owning the value chain end-to-end.

Japan’s Rakuten is one platform business that has the ambition and expressed intention to move from being traditional platform-based business (ala Amazon.com) to become a mobile operator leveraging all the benefits and know-how of their existing platform technologies. Extending those principles, such as softwarization, cloudification and cloud-native automation principles, all the way out to the edge of the mobile antenna.

Many of us in telco-land thought that starting out with a classical telco, with mobile and maybe fixed assets as well, would make for an easy inclusion of platform-like technologies (as describe above), have had to revise our thinking somewhat. Certainly time-lines have been revised a couple of times, as have the assumed pre-conditions or context for such a transformation. Even economical and operational benefits that seems compelling, at least from a Greenfield perspective, turns out to be a lot more muddy when considering the legacy spaghetti we have in telcos with years and years in bag. And for the ones who keep saying that 5G will change all that … no I really doubt that it will any time soon.

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While above platform-like telco topology looks so much simpler than the incumbent one … we should not forget it is what lays underneath the surface that matters. And what matters is software. Lots of software. The danger will always be present that we are ending up replacing hardware & legacy spaghetti complexity with software spaghetti complexity. Resulting unintended consequences in terms of longer-term operational stability (e.g,, when you go beyond being a greenfield business).

“Software have made a lot in the physical world redundant but it may also have leapfrogged the underlying operational complexity to an extend that may pose an existential threat down the line.”

While many platform businesses have perfected cloud-native e-commerce stacks reaching all the way out to the end-consumers mobile apps, residing on the smartphone’s OS, they do operate on the higher level of whatever relevant telco protocol stack. Platform businesses today relies on classical telcos to provide a robust connection data pipe to their end-users at high availability and stability.

What’s coming for us in Telco-land?

“Software will eat more and more of telco-land’s hardware as well as the world.”

(side note: for the ones who want to say that artificial intelligence (AI) will be eating the software, do remember that AI is software too and imo we talk then about autosarcophagy … no further comment;-).

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Telcos, of the kinds with a past, will increasingly implement software solutions replacing legacy hardware functionality. Such software will be residing in a cloud environment either in form of public and/or private cloud models. We will be replacing legacy hardware-centric telco components or boxes with a software copy, residing on a boring but highly standardized hardware platform (i.e., a common off the shelf server). Yes … I talk about software definable networks (SDN) and network functional virtualization (NFV) features and functionalities (though I suspect SDN/NFV will be renamed to something else as we have talked about this for too many years for it to keep being exciting;-). The ultimate dream (or nightmare pending on taste) is to have all telco functions defined in software and operating on a very low number of standardized servers (let’s call it the pizza-box model). This is very close to the innovative and quiet frankly disruptive ideas of for example Drivenets in Israel (definitely worth a study if you haven’t already peeked at some of their solutions). We are of course seeing quiet some progress in developing software equivalents to telco core (i.e., Telco Cloud in above picture) functionalities, e.g., evolved packet core (EPC) functions, policy and charging rules function (PCRF), …. These solutions are available from the usual supplier suspects (e.g., Cisco, Ericsson, Huawei, and Nokia) as well as from (relative) new bets, such as for example Affirmed Networks and Mavenir (side note: if you are not the usual supplier suspect and have developed cloud-based telco functionalities drop me a note … particular if such work in a public or hybrid cloud model with for example Azure or AWS).

We will have software eating its way out to the edge of our telco networks. That is assuming it proves to make economical and operational sense (and maybe even anyway;-). As computing requirements, driven by softwarization of telco-land, goes “through the roof” across all network layers, edge computing centers will be deployed (or classical 2G BSC or 3G RNC sites will be re-purposed for the “lucky” operators with a more dis-aggregated network typologies).

Telcos (should) have very strong desires for platform-like automation as we know it from platform businesses cloud-native implementations. For a telco though, the question is whether they can achieve cloud-native automation principles throughout all their network layers and thus possibly allow for end-2-end (E2E) automation principles as known in a cloud-native world (which scope wise is more limited than the full telco stack). This assumes that an E2E automation goal makes economical and operational sense compared to domain-oriented automation (with domains not per see matching one to one the traditional telco network layers). While it is tempting to get all enthusiastic & winded-up about the role of artificial intelligence (AI) in telco (or any other) automation framework, it always make sense to take an ice cold shower and read up on non-AI based automation schemes as we have them in a cloud-native cloud environment before jumping into the rabbit hole. I also think that we should be very careful architecturally to spread intelligent agents all over our telco architecture and telco stack. AI will have an important mission in pro-active customer experience solutions and anomaly detection. The devil may be in how we close the loop of an intelligent agent’s output and a input to our automation framework.

To summarize what’s coming for the Telco sector;

  • Increased softwarization (or virtualization) moving from traditional platform layers out towards the edge.
  • Increased leveraging of cloud models (e.g., private, public, hybrid) following the path of softwarization.
  • Strive towards cloud-native operations including the obvious benefits from (non-AI based) automation that the cloud-native framework brings.
  • We will see a lot of focus on developing automation principles across the telco stack to the extend such will be different from cloud-native principles (note: expect there will be some at least for non-Greenfield implementations but also in general as the telco stack is not idem ditto a traditional platform stack). This may be hampered by lack of architectural standardization alignment across our industry. There is a risk that we will push for AI-based automation without exploring fully what non-AI based schemes may bring.
  • Inevitable the industry will spend much more efforts on developing cognitive-based pro-active customer experience solutions as well as expanding anomaly detection across the full telco stack. This will help in dealing with design complexities although might also be hampered by mis-alignment on standardization. Not to mention that AI should never become an excuse to not simplify designs and architectures.
  • Plus anything clever that I have not thought about or forgot to mention ūüôā
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So yes … softwarization, cloudification and aggressive (non-AI based) automation, known from platform-centric businesses, will be coming (in fact has arrived to an extend) for Telcos … over time and earlier for the few new brave Telco Greenfields …

Artificial intelligence based solutions will have a mission in pro-active customer experience (e.g., cellwizeuhana, …), zero-touch predictive maintenance, self-restoration & healing, and for advanced anomaly detection solutions (e.g., see Anodot as a leading example here). All are critical requirements in the new (and obviously in the old as well) telco world is being eaten by software. Self-learning “conscious” (defined in a relative narrow technical sense) anomaly detection solutions across the telco stack is in my opinion a must to deal with today’s and the future’s highly complex software architectures and systems.

I am also speculating whether intelligent agents (e.g., microagents reacting to an events) may make the telco layers less reliant on top-down control and orchestration (… I am also getting goosebumps by that idea … so maybe this is not good … hmmm … or I am cold … but then again orchestration is for non-trusting control “freaks”). Such a reactive microagent (or microservice) could take away the typical challenges with stack orchestration (e.g., blocking, waiting, …), decentralize control across the telco stack.

And no¬†… we will not become Ubers … although there might be Ubers that will try to become us … The future will show …

Acknowledgement.

I also greatly acknowledge my wife Eva Varadi for her support, patience and understanding during the creative process of writing this Blog. Also many of my Deutsche Telekom AG, T-Mobile NL & Industry colleagues in general have in countless of ways contributed to my thinking and ideas leading to this little Blog. Thank you!

Further reading

Mike Isaac“Super Pumped – The Battle for Uber”, 2019, W.W. Norton & Company. A good read and what starts to look like a rule of a Silicon Valley startup behavior (the very worst and of course some of the best). Irrespective of the impression this book leaves with me, I am also deeply impressed (maybe even more after reading the book;-) what Uber’s engineers have been pulling off over the last couple of years.

Muchneeded.com“Uber by the Numbers: Users & Drivers Statistics, Demographics, and Fun Facts”, 2018. The age of the Uber statistics presented varies a lot. It’s a nice overall summary but for most recent stats please check against financial reports or directly from Uber’s own website.

Graham Rapier“Uber lost $5.2 billion in 3 months. Here’s where all that money went”, 2019, Business Insider. As often is the case with web articles, it is worth actually reading the article. Out of the $5.2 billion, $3.9 Billion was due to stock-based compensation. Still a loss of $1.3 billion is nevertheless impressive as well. In 2018 the loss was $1.8 billion and $4.5 billion in 2017.

Chris Anderson“Free – The Future of a Radical Price”, (2009), Hyperion eBook. This is one of the coolest books I have read on the topic of freemium, sharing economy and platform-based business models. A real revelations and indeed a confirmation that if you get something for free, you are likely not a customer but a product. A must read to understand the work around us. In this setting it is also worth reading “What is a Free Customer Worth?” by Sunil Gupta & Carl F. Mela (HBR, 2008).

Sangeet Paul Choudary“Platform Scale”, (2015), Platform Thinking Labs Pte. Ltd. A must read for anyone thinking of developing a platform based business. Contains very good detailed end-2-end platform design recommendations. If you are interested in knowing the most important aspects of Platform business models and don’t have time for more academic deep dive, this is most likely the best book to read.

Laure Claire Reillier & Benout Reillier“Platform Strategy”, (2017), Routledge Taylor & Francis Group. Very systematic treatment of platform economics and all strategic aspects of a platform business. It contains a fairly comprehensive overview of academic works related to platform business models and economics (that is if you want to go deeper than for example Choudary’s excellent “Platform Scale” above).

European Commission Report on “Study on passenger transport by taxi, hire car with driver and ridesharing in the EU”, (2016), European Commission.

Michal Gromek“Business Models 2.0 – Freemium & Platform based business models“, (2017), Slideshare.net.

Greg Satell“Don’t Believe Everything You Hear About Platform Businesses”, (2018), Inc.. A good critique of the hype around platform business models.

Jean-Charles Rochet & Jean Tirole“Platform Competition in Two-sided Markets” (2003), Journal of the European Economic Association, 1, 990. Rochet & Tirole formalizes the economics of two-sided markets. The math is fairly benign but requires a mathematical background. Beside the math their paper contains some good descriptions of platform economics.

Eitan Muller“Delimiting disruption: Why Uber is disruptive, but Airbnb is not”, (2019), International Journal of Research in Marketing. Great account (backed up with data) for the disruptive potential of platform business models going beyond (and rightly so) Clayton Christensen Disruptive Theory.

Todd W. Schneider“Taxi and Ridehailing Usage in New York City”, a cool site that provides historical and up-to-date taxi and ride hailing usage data for New York and Chicago. This gives very interesting insights into the competitive dynamics of Uber / Ride hailing platform businesses vs the classical taxi business. It also shows that while ride hailing businesses have disrupted the taxi business in totality, being a driver for a ride hailing platform is not that great either (and as Uber continues to operate at impressive losses maybe also not for Uber either at least in their current structure).

Uber Engineering is in general a great resource for platform / stack architecture, system design, machine learning, big data & forecasting solutions for a business model relying on real-time transactions. While I personally find the Uber architecture or system design too complex it is nevertheless an impressive solution that Uber has developed. There are many noteworthy blog posts to be found on the Uber Engineering site. Here is a couple of foundational ones (both from 2016 so please be aware that lots may have changed since then) “The Uber Engineering Tech Stack, Part I: The Foundation” (Lucie Lozinski, 2016) and “The Uber Engineering Tech Stack, Part II: The Edge and Beyond” (Lucie Lozinski, 2016) . I also found “Uber‚Äôs Big Data Platform: 100+ Petabytes with Minute Latency” post (by Reza Shiftehfar, 2018) very interesting in describing the historical development and considerations Uber went through in their big data platform as their business grew and scale became a challenge in their designs. This is really a learning resource.

Wireless One“Rakuten: Japan’s new #4 is going all cloud”, 2019. Having had the privilege to visit Rakuten in Japan and listen to their chief-visionary Tareq Amin (CTO) they clearly start from being a platform-centric business (i.e., Asia’s Amazon.com) with the ambition to become a new breed of telco levering their platform technologies (and platform business model thinking) all the way out to the edge of the mobile base station antenna. While I love that Tareq Amin actually has gone and taken his vision from powerpoint to reality, I also think that Rakuten benefits (particular many of the advertised economical benefits) from being more a Greenfield telco than an established telco with a long history and legacy. In this respect it is humbling that their biggest stumbling block or challenge for launching their services is site rollout (yes touchy-feel infrastructure & real estate is a b*tch!). See also “Rakuten taking limited orders for services on its delayed Japan mobile network” (October, 2019).

Justin Garrison & Chris Nova“Cloud Native Infrastructure”, 2018, O’Reilly and Kief Morris“Infrastructure as Code”, 2016, O’Reilly. I am usually using both these books as my reference books when it comes to cloud native topics and refreshing my knowledge (and hopefully a bit of understanding).

Marshall W. Van AlstyneGeoffrey G. Parker and Sangeet Paul Choudary“Pipelines, Platforms and the New Rules of Strategy”, 2016, Harvard Business Review (April Issue).

Murat Uenlue“The Complete Guide to the Revolutionary Platform Business Model”, 2017. Good read. Provides a great overview of platform business models and attempts systematically categorize platform businesses (e.g., Communications Platform, Social Platform, Search Platform, Open OS Platforms, Service Platforms, Asset Sharing Platforms, Payment Platforms, etc….).

Facebook Seasson 3 – Face/Off

1000 Days & a bit … As of January 2015 a Facebook share was around Double the price of their initial public offering (IPO) back in May 2012.

That increase in share price & value correspond to an investor belief (conscious or otherwise) that Facebook’s can grab around 40% of the online spend in the (near) Future versus a mediocre 20+% back in 2012.

If you had bought Facebook shares on September 4th 2012 and sold them again December 22nd 2014 (yes just before Christmas) you would have earned 5 times your original investment!

Back in 2012, some month after Facebook‚Äôs (FB) IPO, I wrote a Blog Facebook Values ‚Ķ Has the little boy spoken? on the FB value and how to get a feel whether the share price was Naked (‚ÄúThe Ugly‚ÄĚ), Half Dressed (‚ÄúThe Bad‚ÄĚ) or Nicely Dressed (‚ÄúThe Good‚ÄĚ).

I asked whether it was a good time to have confidence and invest in Facebook … My answer (at the time) was that the share price of about 20 US$ (August 2012 timeframe) appeared too low compared with the potential for capturing Online Advertisement Spending Market Share, that furthermore was poised to increase substantially going forward as funds were being redirected from traditional advertisement spend to digital / online media.

The primary source of revenue for Facebook (then & now) is from Online Advertisement Spend. Thus, I looked at what long-term share (chosen arbitrarily to be 5 years) of the Online Ad Market should Facebook have in order to justify its value and share price. Very simply I ramped up the revenue share from its current value to a target share that would correspond to Facebook’s Market Capitalization or Share Price.

In the following I will ignore all the goodies that Facebook have launched or acquired over their lifetime, such as

  • Instagram (Apr 2012).
  • Whatsapp (Feb 2013).
  • Oculus (Mar 2013).
  • Atlas Ad Server Platform (acquisition Feb 2013 & re-vamped Sep 2014).
  • Autoplay Video Ads (Mar 2014).
  • Regular Facebook Software Updates.

(note list is not intended to be exhaustive).

All of the above (and much more) serves to make sure that ‚ÄúPeople use Facebook to stay connected with friends and family, to discover what‚Äôs going on in the world, and to share and express what matters to them‚ÄĚ. (i.e., Facebook‚Äôs vision statement) ‚Ķ and (I assume) to make maximum profit out of the Facebook ‚Äúaddiction‚ÄĚ by providing a very efficient advertisement platform enabled by the gazillion of personal data/information & impressions we all continuously volunteer by using Facebook.

However, while the technologies (e.g., algorithms & communications software utilities) behind are very exiting it all serves one purpose … deliver the most efficient ad to the user and make as much money out of that customer touch point. I believe that the potential and value of Whatsapp is huge and in message volume already exceeds the number daily SMS transactions globally. This still largely remains un-explored by Facebook. The question will be whether FB will primarily use Whatsapp as another Ad delivery vehicle or also as a mean to generate communications revenues in both the messaging and the voice consumer segments.

The conclusion back in August 2012, was that the share price of Facebook, based on its equivalent long-term share of the the Online Ad Market Spend, appeared low and one should expect the price (and value) to increase.

FB share price value & share of online spend

  • Above figure: Analysis presented in my 2012 ‚ÄúFacebook – time to invest?‚ÄĚ. Note that the the share price dynamics are illustrated relative to the IPO price of 38 US$ or more accurately the stock price at closing on 18th of May 2012.

So what has happened in the almost 1000 days since the Facebook IPO?

Well after the share price dropped to 17.73 (at closing) on September 4th (2012), which roughly halved the Market Cap of Facebook, the FB Journey has been one of growth.

The cynic might of course point out that so has the rest of the market. However, while for example Nasdaq100 is ca. 68% higher (as of January 20th 2015) compared to the 18-May 2012, Facebook is almost double its IPO value (over the same period). If you take the lowest point (4 Sep 2012) and the highest point (22 Dec 2014) you have a 4.6 times ratio between high & low points.

So if you did the right thing and bought the lowest and sold at the highest … well I told you so (joking!) … Congratulation would be called for!

Here is the FB Journey ( = A Walk on the Wilder Side?) seen from an investors perspective

fb share dynamics

  • Above figure: illustrates Facebook stock price development since the IPO until end of January 2015 with commentary to the peaks and the dips.The Red Dot on September 4th 2012 represents the lowest historical share price (i.e., 17.71 @ closing) and the Green Dot the highest historical share price (i.e., 81.45 @ closing).

Taking the stock price dynamics as shown above, how would the previous analysis come out looking at what Online Ad Revenue Share could justify (approximately) the share price development over the period.

Well … it could look something like this based on Online Advertisement Market Share;

share price & online ad share

  • Above Figure: illustrates the share price dynamics relative to the IPO price, i.e., 100% level (at closing 18 May 2012). Further a relative simple valuation model based on Facebook‚Äôs long-term (i.e., 5+ years) online advertisement market share is used to derive the Online Ad Spend share that a given FB share price corresponds to. The methodology has been described in detail in ‚ÄúA walk on the Wild Side‚ÄĚ.

Current stock price range is fairly consistent with a 40+% long-term (i.e., 5 year linear ramp up from 2013 share and then keeping the share at the level going forward) share of the Online Advertisement Market. I would expect Facebook to hit at least 10% for 2014 (based on eMarketer data of the total online advertisement market).

Will Facebook be able to grow to 40+% share of the Online Ad Spending?

In my opinion that does not sound completely un-reasonable …

Though it would imply that (a) other social media players also relying on the Online Ad Market are going to lose their livelihood, some (b) business plans might look somewhat more sombre for others and (c)  Facebook needs to take Google Head-On.

It will be very exiting to follow Facebook’s Q4 2014 and Full Year 2014 Earning Call on 28th January 2015 at 2 PM Pacific Time (i.e., 11 PM CET & 1 AM AST 29 January).

I expect to see (28 January 2015); Below find the comparison between my predictions and the real thing (i.e., actual data) out of the Q4 Earnings details as presented at the Q4 & 2014 Full Year Earning Call (28th of January 2015), I also recommend to read the transcript of the earning call on SeekingAlpha Blog. (Strike out text is my predictions prior to Earning Call)

  • Facebook beating Q4 earnings expectations and came out at 3.851B US$ coming out at 3.84B US$ (Low) to 4.16B (US$) (high).
  • MAU 1,393 1,386 Million and Mobile MAU of 1,189 1,182 Million (both lower limit estimates).
  • Share price at closing was slightly higher than previous trading day ending at 76.24 US$ per share (+0.6%) will drop during the day of the earning call to around 71 ‚Äď 72 US$ per share.
  • Given the already high value of the stock, I do not expect much gain over the days after the earning call. Likely to recover to the level 5 ‚Äď 10 days before the Q4/Full 2014 Earning Call.

… and I might be completely mistaken (and will be crying all the way to the bank)… but at least we will know within the next hours & days to come!

… So I ended up being fairly close to MAU (0.5% lower), Mobile MAU (0.6% lower) and earnings expectations (0.3% from my lower bound). However, predicting the stock movement … yeah … not so good. Still next couple of days will be interesting to follow. Dave Wehner, Facebook Chief Financial Officer, was where careful in managing expectations for Facebook Topline in 2015. Concerns about exchange rate effects on the Topline could result in a 5% lower revenue than it would have been with 2014 exchange rates. Basically the revenue growth in US$ would reduce somewhat due to exchange rate effects. This is likely to have some negative impact on Facebook profitability and their margin as their fundamental cost base is in US$.

Methodology

See also my Social Media Valuation Blog ‚ÄúA walk on the Wild Side‚ÄĚ.

Following has been assumed in FB Valuation Assessment:

  1. WACC 9.11%
  2. 2013 FB capture 6% of total online ad spend.
  3. FB gains a sustainable share of online ad spend X%.
  4. 5 yr linear ramp-up from 2014 9.6% (assessed) to X%, and then maintained at that level.
  5. Other revenues 15% in 2014, linearly reduced to 10% after 5 yrs and then maintained.
  6. Assume FB can maintain a free cash flow yield of 25%.

It should be noted that the above analysis is in all likelihood oversimplifying. However it is not terrible difficult to add complexity. Though given the inherent uncertainties involved in predicting the future, the approach presented is good enough to get an idea about a given investments (or stock purchase) attractiveness.

For the financial history buffs, the Nasdaq100 is ca. 5% from the level of the dot.com foreshock (or pre-crash) of March-2000 and has surpassed the big crash of July-2000.

Acknowledgement

I greatly acknowledge my wife Eva Varadi for her support, patience and understanding during the creative process of creating this Blog.

Appendix

fb & nasdaq100

  • Figure above: shows the share price development from May 18 2012 (IPO date of FB) to 20 January 2015 of Facebook and Nasdaq100 composite. While Facebook largely under-performed in 2012 and well into 2013, its recovery from mid-2013 until January 2015 has been spectacular.

FB daily returns

 

FB vs Nasdaq100

  • Figure above: illustrates Laplace distribution representations of the daily returns of Facebook and Nasdaq100 over the period from 18 May 2012 to 20 January 2015. Note the slight right shift in centre point from the 0%. For a more detailed analysis of the Nasdaq100 and application of the Laplace distribution see the Business Forecasting Blog ‚ÄúThe Nasdaq100 Daily Returns and Laplace Distributed Errors‚ÄĚ.

online ad spending

  • Figure above: Online Advertisement Spending forecast from eMarketer (August 2013) representing the period 2013 to 2017. From 2018 and to 2022 Forecasts have been extrapolated based on 1st and 2nd derivative of the previous period growth. The resulting trend have been checked against other available projections.

facebook mau vs ad spend region etc

  • Figure above: illustrates for 2013 Facebook Monthly Active Users (MAU) in terms of share of population versus Region (source: Facebook Annual Report 2013), Region‚Äôs share of Ad Spend (source: eMarketer), Mobile Internet Penetration (i.e., CDMA2000, UMTS, HSPA, LTE, Mobile WiMax, source: Pyramid Research), and (fixed) internet penetration (i.e., the percentage of population having access to internet).

2017 facebook mau vs ad spend region etc

  • Figure above: illustrates for 2017 Facebook Monthly Active Users (MAU) in terms of share of population versus Region (Source: Authors Facebook Model), Region‚Äôs share of Ad Spend (Source: eMarketer), Mobile Internet Penetration (i.e., CDMA2000, UMTS, HSPA, LTE, Mobile WiMax, Source: Pyramid Research), and (fixed) internet penetration (i.e., the percentage of population having access to internet).

2013 mau vs reg lte wifi etc

  • Figure above: illustrates for 2013 Facebook Monthly Active Users (MAU) in terms of share of population versus Region (Source: Facebook Annual Report 2013), LTE penetration (Source: Pyramid Research), WiFi residential potential estimated from the broadband household penetration (Source: Pyramid Research), and  Mobile Internet Penetration (i.e., CDMA2000, UMTS, HSPA, LTE, Mobile WiMax, Source: Pyramid Research). For Facebook‚Äôs Autoplay Video feature it is important for the user to either have WiFi access or for a decent cellular performance LTE.

2017 mau vs reg lte wifi etc

  • Figure above: illustrates for 2017 Facebook Monthly Active Users (MAU) in terms of share of population versus Region (Source:Source: Authors Facebook Model), LTE penetration (Source: Pyramid Research), WiFi residential potential estimated from the broadband household penetration (Source: Pyramid Research), and  Mobile Internet Penetration (i.e., CDMA2000, UMTS, HSPA, LTE, Mobile WiMax, Source: Pyramid Research). For Facebook‚Äôs Autoplay Video feature it is important for the user to either have WiFi access or for a decent cellular performance LTE.

Facebook Values … Has the little boy spoken?

Facebook has lost ca. 450+ Million US$ per day since its IPO¬†… or about 40 Billion US$ …¬†in a little under 90 days¬†(i.e., reference date 17-08-2012).

This is like loosing an Economy such as the Seychelles every second day. Or a Bulgaria ¬†in less than 90 days. (Note: this is not to say that you could buy Bulgaria for $40B … well who knows? ūüėČ … the comparison just serves at making the loss of Facebook value more tangible. Further one should not take the suggestion of a relationship between market value of a corporation such as Facebook with GDP of country too serious as also pointed out by Dean Bubley @disruptivedean).

That’s a lot of value lost in a very short time. I am sure Bulgarians,”Seychellians” and FB investors can agree to that.

40 Billion US Dollar?¬† … Its a little less than 20 Mars Missions … or

40 Billion US Dollar could keep 35 thousand Americans in work for 50 years each!

So has the little boy spoken? Is the Emperor of Social Media Naked?

Illustration: THORARINN LEIFSSON http://www.totil.com

Let’s have a more detailed look at Facebook’s share price development since May 18th 2012.

The Chart below shows the Facebook’s share price journey, the associated book value, the corresponding sustainable share of Online Ad Spend (with an assumed 5yr linear ramp-up from today’s share) and the projected share of Online Ad Spend in 2012.

In the wisdom of looking backwards … ¬†is Facebook, the Super-Mario of Social Media, really such a bad investment? or is this just a bump in a long an prosperous road ahead?

I guess it all rise and fall with what ever belief an investor have of Facebook’s ability to capture sufficient Online Advertisement Spend. Online Ad spend obviously includes the Holy Grail of Mobile Ad Revenues as well.

FB’s revenue share of Online Ad Spend has raised steady from 1.3% in 2009 to ca. 5% in2011 and projected to be at least 6% in 2012.

Take a look at FB’s valuation (or book value) which at the time of the IPO (i.e., May 18th 2012) was ca. 80+ Billion US Dollars. Equivalent to a share price of $38.32 per share (at closing).

In terms of sustainable business such a valuation could be justifiable if FB could capture and sustain at least 23% of the Online Ad Spend in the longer run. Compare this with ca. 5% in 2011. Compare this with Googles 40+% om 2011. AOL, which is Top 5 of best companies at conquering Online Advertisement Spend, share of Online Ad Spend was a factor 15 less than Google. Furthermore, Top-5 accounts for more than 70% of the Online Ad Spend in 2011. The remaining 30% of Online Ad Spend arises mainly from Asia Pacific logo-graphic, politically complicated, and Cyrillic dominated countries of which Latin-based Social Media & Search in general perform poorly in (i.e., when it comes to capturing Online Ad Spend).

Don’t worry! Facebook is in the Top 5 list of companies getting a piece of the Online Advertisement pie.

It would appear likely that Facebook should be able to continue to increase its share of Online Ad Spend from today’s fairly low level. The above chart shows FB’s current share price level (closing 17-August-2012) corresponds to a book value of ca. $40 Billion and a sustainable share of the Online Ad Spend of a bit more than 10+%.

It would be sad if Facebook should not be able to ever get more than 10% of the Online Ad Spend.

From this perspective:

A Facebook share price below $20 does seem awfully cheap!

Is it time to invest in Facebook? … at the moment it looks like The New Black is bashing Social Media!

So the share price of Facebook might drop further … as current investors try too off-load their shares (at least the ones that did not buy at and immediately after the IPO).

Facebook has 900+ Million (and approaching a Billion) users. More than 500+ Million of those 900+ Million Facebook users are active daily and massively using their Smartphones to keep updated with Friends and Fiends. In 2011 there where more than 215 Billion FB events.

Facebook should be a power house for Earned and Owned Social Media Ads (sorry this is really still Online Advertisement despite the Social Media tag) … we consumers are much more¬†susceptible to friend’s endorsements or our favorite brands (for that matter) than the mass fabricated plain old online¬†¬†advertisement¬†that most of us are blind to anyway (or get annoyed by which from awareness is not¬†necessarily un-intended¬†).

All in all

Maybe the Little Boy will not speak up as the Emperor is far from naked!

METHODOLOGY

See my Social Media Valuation Blog “A walk on the Wild Side”.

Following has been assumed in FB Valuation Assessment:

  1. WACC 9.4%
  2. 2012 FB capture 6% of total online ad spend.
  3. FB gains a sustainable share of online ad spend X%.
  4. 5 yr linear ramp-up from 2012 6% to X%, and then maintained.
  5. Other revenues 15% in 2012, linearly reduced to 10% after 5 yrs and then maintained.
  6. Assume FB can maintain a free cash flow yield of 25%.

Social Media Valuation …. a walk on the wild side.

Lately I have wondered about Social Media Companies and their Financial Valuations. Is it hot air in a balloon that can blow up any day? Or are the hundred of millions and billions of US Dollars tied to Social Media Valuations reasonable and sustainable in the longer run? Last question is particular important as more than 70% of the value in Social Media are 5 or many more years out in the Future.  Social Media startup companies, without any turnover, are regularly being  bought for, or able to raise money at a value, in the hundreds of millions US dollar range. Lately, Instagram was bought by Facebook for 1 Billion US Dollar. Facebook itself valued at a $100B at its IPO. Now several month after their initial public offering, Facebook may have lost as much as 50% of the originally claimed IPO value.

The Value of Facebook, since its IPO,  has lost ca. 500 Million US Dollar per day (as off 30-July-2012).

What is the valuation make-up of Social Media? And more interestingly what are the conditions that need to be met to justify $100B or $50B for Facebook, $8B for Twitter, $3B (as of 30-July-2012, $5B prior to Q2 Financials) or $1B for Instagram, a 2 year old company with a cool mobile phone Photo App? Is the Social Media Business Models Real? or based on an almost religious belief that someday in the future it will Return On Investment. Justifying the amount of money pumped into it?

My curiosity and analytical “hackaton” got sparked by the following Tweet:

Indeed! what could possible justify paying 1 Billion US Dollar for Instagram, which agreeably has a very cool FREE Smartphone Photo App (far better than Facebook’s own), BUT without any income?

  • Instagram, initially an iOS App, claims 50 Million Mobile Users (ca. 5 Million unique visitors and 31 Million page-views as of July 2012). 5+M photos are uploaded daily with a total of 1+ Billion photos uploaded. No reported revenues to date. Prior to being bought by Facebook for $1 Billion, was supposed to have been prepared for a new founding round valued at 500 Million US$.
  • Facebook has 900M users, 526M (58%) active daily and 500M mobile users (May 2012). 250M photos are uploaded daily with a total of 150 Billion photos. Facebook generated ca. $5B in revenue in 2011 and current market cap is ca. $61B (24 July 2012). 85% of FB revenue in 2011 came from advertisement.

The transaction gives a whole new meaning to “A picture is worth a Billion words” ¬†… and Instagram is ALL about PICTURES & SOCIAL interactions!

Instagram is a (really cool & simple) mobile & smartphone optimized App. Something that would be difficult to say about FB’s mobile environment (in particular when it comes to photo experience).

One thing is of course clear. If FB is willing to lay down $1B for Instagram, their valuation should be a good deal higher than $1B (i.e., ca. $4+B?). It will be very interesting to see how FB plans to monetize Instagram. Though the acquisition might be seen as longer-outlook protective move to secure Facebook’s share of the Mobile Market, which for Social Media will become much more important than the traditional desktop access.

So how can we get a reality check on a given valuation?

Lets first look at the main Business Models of today (i.e., how the money will be or are made);

  1. Capture advertising spend – typically online advertisement spend (total of $94B in 2012 out of an expected total Media Ad spend of $530B). With uptake of tablets traditional “printed media” advertising spend might be up for grabs as well (i.e., getting a higher share of the total Media Ad spend).
  2. Virtual Goods & credits (e.g., Zynga’s games and FB’s revenue share model) – The Virtual Economy has been projected to be ca. $3B in 2012 (cumulative annual growth rate of 35% from 2010).
  3. Payed subscriptions (e.g., LinkedIn’s Premium Accounts: Business Plus, Job Seeker, etc or like Spotify Premium, etc..).
  4. B2B Services (e.g.,. LinkedIn’s Hiring Solutions).

The Online¬†Advertisement Spend is currently the single biggest source of revenue for the Social Media Business Model. For example Google (which is more internet search than Social Media) takes almost 50% of the total available online advertisement spend and it accounts for more than 95% of¬†Google’s¬†revenues. In contrast, Facebook in 2011 only captured ca. 4+% of Online Ad Spend which accounted for ca. 85% of FB’s total revenue. By 2015 eMarketeer.com (see http://www.emarketer.com/PressRelease.aspx?R=1008479) has projected the total online advertisement spend could be in the order of $132B (+65% increase compared to 2011). USA and Western Europe is expected to account for 67% of the $132B by 2015.

Virtual Goods are expected to turn-over ca. $3B in 2012. The revenue potential from¬†Social Networks and Mobile has been projected (see Lazard Capital’s Atul Bagga ppt on “Emerging Trends in Games-as-a-Service”) to be ca. $10B worldwide by 2015. If (and that is a very big if) the trend would continue the 2020 potential would be in the order of $60B (though I would expect this to be a maximum and very optimistic upside potential).

So how can a pedestrian get an idea about Social Media valuation? How can one get a reality check on these Billionaires being created en mass at the moment in the Social Media sphere?

“Just for fun” (and before I get really “serious”) I decided see whether there is any correlation between a given valuation and the number of Unique Visitors (per month) and Pageviews (per month) … my possible oversimplified logic would be that if the main part of the Social Media business model is to get a share of the Online Advertisement Spending there needs to be some sort of dependency on the those (i..e, obviously whats really important is the clickthrough (rate) but lets be forget this for a moment or two):

 The two charts (log-log scaled) shows Valuation (in Billion US$) versus Unique Visitors (in Millions) and Pageviews (in Billions). While the correlations are not perfect, they are really not that crazy either. I should stress that the correlations are power-law correlations NOT LINEAR, i.e., Valuation increases with power of unique and active users/visitors.

An interesting out-lier is Pinterest. Let’s just agree that this does per see mean that Pinterest’s valuation at $1.5B is too low! … it could also imply that the rest are somewhat on the high side! ūüėČ

Note: Unique Visitors and Pageview statistics can be taken from Google’s DoubleClick Ad Planner.¬†It is a wonderful source of domain attractiveness, usage and user information.

Companies considered in Charts: Google, Facebook, Yahoo, LinkedIN, Twitter, Groupon, Zynga, AOL, Pinterest, Instagram (@ $1B), Evernote, Tumblr, Foursquare, Baidu.

That’s all fine … but we can (and should) do better than that!

eMarketeer.com has given us a Online Advertisement Spend forecast (at least until 2015). In 2011, the Google’s share amounted to 95% of their revenue and for Facebook at least 85%. So we are pretty close to having an idea of the Topline (or revenue) potential going forward. In addition, we also need to understand how that Revenue translates into Free Cash Flow (FCF) which will be the basis for my simple valuation analysis. To get to a Free Cash Flow picture we could develop a detailed P&L model for the company of interests. Certainly an interesting exercise but would require “Millions” of educated guesses and assumptions for a business that we¬†don’t¬†really know.

Modelling a company’s P&L is not really a peaceful walk for our interested pedestrian to take.

A little research using Google Finance, Yahoo Finance or for example Ycharts.com (nope! I am not being sponsored;-) will in general reveal a typical cash yield (i.e., amount of FCF to Revenue) for a given type of company in a given business cycle.

Examples of FCF performance relative to Revenues: Google for example has had an average FCF yield of 30% over the last 4 years, Yahoo’s 4 year average was 12% (between 2003 and 2007 Google and Yahoo had farily similar yields ). ¬†Facebook has been increasing its yield steadily from 2009 (ca. 16%) to 2011 (ca. 25%), while Zynga had 45% in 2010 and then down to 13% in 2011.

So having an impression of the revenue potential (i.e., from eMarketeer) and an idea of best practice free cash flow yield, we can start getting an idea of the Value of a given company. It should of course be clear that we can also turn this Simple Analysis around and ask what should the Revenue & Yield be in order to justify a given valuation. This would give a reality check on a given valuation as the Revenue should be in reasonable relation to market and business expectations.

Lets start with Google (for the moment totally ignoring Motorola;-):

Nothing fancy! I am basically assuming Google can keep their share of Online Advertising Spend (as taken from eMarketeer) and that Google can keep their FCF Yield at a 30% level. The discount rate (or WACC) of 9% currently seems to be a fair benchmark (http://www.wikiwealth.com/wacc-analysis:goog). I am (trying) to be conservative and assumes a 0% future growth rate (i.e., changing will in general have a high impact on the Terminal Value). If all this comes true, Google’s value would be around 190 Billion US Dollars. Today (26 July 2012) Google Finance tells me that their Market Capitalization is $198B (see¬†http://www.google.com/finance?q=NASDAQ:GOOG) which is 3% higher than the very simple model above.

How does the valuation picture look for Facebook (pre-Zynga results as of yesterday 25 July 2012):

First thought is¬†HALLELUJAH¬†… Facebook is really worth 100 Billion US Dollars! … ca. $46.7 per share… JAIN (as they would say in Germany) … meaning YESNO!

  • Only if Facebook can grow from capturing ca. 6% of the Online Advertisement Spend today to 20% in the next 5 – 6 years.
  • Only if Facebook can improve their Free Cash Flow Yield from today’s ca. 25% to 30%.
  • Only if Facebooks other revenues (i.e., from Virtual Goods, Zynga, etc..) can grow to be 20% of their business.

What could possible go wrong?

  • Facebook fatigue … users leaving FB to something else (lets be honest! FB has become a very complex user interface and “sort of sucks” on the mobile platforms. I guess one reason for Instagram acquisition).
  • Disruptive competitors/trends (which FB cannot keep buying up before they get serious) … just matter of time. I expect this to happen first in the Mobile Segment and then spread to desktop/laptop.
  • Non-advertisement revenues (e.g., from Virtual Goods, Zynga, etc..) disappoints.
  • Need increasing investments in infrastructure to support customer and usage growth (i.e., negative impact on cash yields).
  • The Social Media business being much more volatile than current hype would allow us to assume.

So how would a possible more realistic case look like for Facebook?

Here I assume that Facebook will grow to take 15% (versus 20% above) of the Online Ad spend. Facebook can keep a 25% FCF Yield (versus growing to 30% in the above model). The contribution from Other Revenues has been brought down to a more realistic level of the Virtual Goods and Social Media Gaming expectations (see for example Atul Bagga, Lazard Capital Markets, analysis http://twvideo01.ubm-).

The more conservative assumptions (though with 32% annual revenue growth hardly a very dark outlook) results in a valuation of $56 Billion (i.e., a share price of ca. $26). A little bit more than half the previous (much) more¬†optimistic¬†outlook for Facebook. Not bad at all of course … but maybe not what you want to see if you paid a premium for the Facebook share? Facebook’s current market capitalization (26 July 2012, 18:43 CET) is ca. $60B (i..e, $28/share).

So what is Facebooks value? $100B (maybe not), $50+B? or around $60+B? Well it all depends on how shareholders believe¬†Facebook’s business to evolve¬†over the next 5 – 10 (and beyond) years. If you are in for the long run it would be better to be conservative and keep the lower valuation in mind rather than the $100B upside.

Very few of us actually sit down and do a little estimation ourselves (we follow others = in a certain sense we are financial lemmings). With a little bit of Google Search (yes there is a reason why they are so valuable;-) and a couple of lines of Excel (or pen and paper) it is possible to get an educated idea about a certain valuation range and see whether the price you paid was fair or not.

Lets just make a little detour!

Compare Facebook’s current market capitalization of ca. $60B (@¬†26 July 2012, 18:43 CET) at $3.7B Revenue (2011) and ca. $1B of free cash flow (2011). Clearly all value is in anticipation of future business!¬†Compare this with Deutsche Telecom AG with a market capitalization of ca. $50B at $59B (2011, down -6% YoY2010) and ca. $7.8B of free cash flow (2011). It is Fascinating¬†that a business with well defined business model, paying customers, healthy revenue (16xFB) and cash flow (8xFB) can be worth a lot less than a company that relies solely on anticipation of a great future. ¬†Facebook’s / Social Media Business Model future appear a lot more optimistic (the blissfull unknown) than the Traditional Telco Business model (the known” unknown). Social Media by 2015 is a game of maybe a couple of hundred Billions (mainly from advertisement, app sales and virtual economy) versus the Telecom Mobile (ignoring the fixed side) of a Trillion + (1,000 x Billion) business.

Getting back to Social Media and Instragram!

So coming back to Instagram … is it worth paying $1B for?

Let’s remind ourselves that Instagram is a Mobile Social Media Photo sharing platform (or Application) serving Apple iOS (originally exclusively so) and Android. Instagram has ca. 50+M registered users (by Q1’2012) with 5+M photos uploaded per day with a total of 1+B photos uploaded. The Instagram is a¬†through-rough¬†optimized smartphone application. There are currently more than 460+ photo ¬†apps with 60Photos being a second to Instagram in monthly usage (http://www.socialbakers.com/facebook-applications/category/70-photo).

Anyway, to get an idea about Instagram’s valuation potential, it would appear reasonable to assume that their Business Model would target the Mobile Advertisement Spend (which is a sub-set of Online Ad Spend). To get somewhere with our simple valuation framework I assume:

  1. that Instagram can capture up to 10% of the Mobile Adv Spend by 2015 – 2016 (possible Facebook boost effect, better payment deals. Keep ad revenue with Facebook).
  2. Instagram’s ¬†a revenue share dynamics similar to Facebooks initial revenue growth from Online Ad Spend (possible Facebook boost effect, better payment deals. Keep ad revenue with Facebook).
  3. Instagram could manage a FCF Yield to 15% over the period analysed (there could be substantial synergies with Facebook capital expenditures).

In principle the answer to that question above is YES paying $1B for Instagram would be worth it as we get almost $5B from our small and simple valuation exercise¬†… if one believes;

  1. Instagram can capture 10% of the Mobile Advertisement Spend (over the next 5 – 6 years).
  2. Instagram can manage a Free Cash Flow Yield of at least 15% by Year 6.

Interesting looking at the next 5 years would indicate a value in the order of $500M. This is close to the rumored funding round that was in preparation before Facebook laid down $1B. However and not surprising most of the value for Instagram comes from the beyond 5 years. The Terminal Value amounts to 90% of the Enterprise Value.

For Facebook to breakeven on their investment, Instagram would need to capture no more than 3% of the Mobile Ad Spend over the 5 year period (assuming that the FCF Yield remain at 10% and not improving due to scale).

Irrespective;

Most of the Value of Social Media is in the Expectations of the Future.

70+% of Social Media Valuation relies on the Business Model remaining valid beyond the first 5 years.

With this in mind and knowing that we the next 5 years will see a massive move from desktop dominated Social Media to Mobile dominated Social Media, should make us somewhat nervous about desktop originated Social Media Businesses and whether these can and will make the transformation.

The question we should ask is:

Tomorrow, will today’s dot-socials be yesterday’s busted dot-coms?

PS

For the pedestrian that want to get deeper into the mud of valuation methodologies I can really recommend “Valuation: Measuring & Managing the Value of Companies” by Tim Koller, Marc Goedhart & David Wessels (http://www.amazon.com/Valuation-Measuring-Managing-Companies-Edition/dp/0470424656). Further there are some really cool modelling exercises to be done on the advertisement spend projections and the drivers behind as well as a deeper understand (i.e., modeling) of the capital requirements and structure of Social Media Business Models.

In case of interest in the simple models used here and the various sources … don’t be a stranger … get in touch!

PSPS (as of 28-July-2012) – A note on Estimated Facebook Market Capitalization

In the above Facebook valuation commentary I have used the information from Google Finance (http://www.google.com/finance?q=facebook) and Yahoo Finance (http://finance.yahoo.com/q?s=FB) both basing their Market Capitalization estimation on 2.14B Shares. MarketWatch (http://www.marketwatch.com/investing/stock/fb) appear to use 2.75B shares (i.e., 29% high than Google & Yahoo). Obviously, MarketWatch market capitalization thus are higher than what Google & Yahoo would estimate.