Predicting Technology Adoption

Today we see many new ideas and product categories being introduced into the market. We see smart speakers, AI assistants, self-driving cars, wearables, VR headsets, smart homes and many more. Not all of these will be successful and become a part of our future lives. Surely some eventually will, but only after many years of mediocre sales mainly as an enthusiast’s toy. Others will become instant hits, and will be used by the majority of people within a decade or even shorter. Despite all of these sharing a common early enthusiasm, the eventual fates will be very different, and predicting which trajectory each product category will take is not an easy task. However there are some frameworks and theories which we can apply, so here, as an excercise to test my own understanding, I will try to do just that.

Smart Speakers

This is a very interesting product category to test and apply the Chasm theory of Geoffrey Moore and the Disruption theory of Clayton Christensen.

The Chasm theory applies to new category products that require customers to learn and change their behaviour. Essentially, the Chasm theory states that there is a very wide divide between the early adopters and the early majority, due to the lack of connection between these two different types of customer. The early adopters do not act as reliable references for the early majority, and hence technology diffusion cannot rely on word-of-mouth. Thus a deliberate and focused strategy is required to bridge this gap. On the other hand, Disruption occurs when the core appeal of a preexisting product that caters to advanced users is made available to a wider audience through technology or business model advancements. As a result the market share of the preexisting product is significantly reduced (hence the word Disruption), often not necessarily by stealing the preexisting product’s customers, but instead dramatically increasing the size of the pie. Often in Disruption, the benefits of the preexisting product will already have been defined and will be very apparent to the new users, and so there will not be a Chasm to cross. This can make adoption very rapid.

In the smart speaker market, and with the introduction of Apple’s HomePod, we will witness both of these theories simultaneously at work.

For the Amazon Echo and Google Home products, we will see the effect of the Chasm. Both of these products stress the AI assistant features which are new and without precedent in the market. Therefore the companies will struggle to define the must-have value proposition, and to educate consumers as to why they should own one. Geoffrey Moore advocates a whole product approach to overcome this, something that neither company is particularly known for. I therefore predict that both these products will seriously struggle to be widely adopted.

On the other hand, we see Apple’s HomePod taking a more Low-end Disruption approach. Instead of touting AI assistant capabilities, the HomePod takes aim at high-end audio and making that accessible to people who would appreciate high-quality sound, but who are unwilling to invest in the learning and the equipment. Therefore, this approach will not experience a Chasm. Potential customers already know what they are getting and do not need to be educated on why they would enjoy good sound. All they need to decide is when they are going to save up, and therefore we are likely to see a much faster adoption rate with this marketing focus.

As a result, my prediction is that the HomePod will be a hit akin to the AirPods, easily surpassing Amazon Echo sales in revenue and even units. As a result we will see both Amazon and Google changing direction and copying Apple’s approach by making speakers with at least acceptable sound. The smart speaker market will rapidly expand as a result, but only because the marketing approach is not about the AI assistant capabilities but the high-quality music.

Self-driving cars

Self-driving technology is also likely to follow a Chasm trajectory. Without a preexisting product with a similar value proposition, people will have to be educated on the benefits, especially if regulations require that the driver cannot fully delegate the role of driving to the AI, and must be available to intervene at any time. We will see a lot of early adopters, but for a long while, that is likely to be all. Even if full autonomy becomes a reality soon and regulations allow the computers to work without human supervision, I am not convinced that many people will immediately recognise the benefits since there is no preexisting market.

Wearables

This is product category that we know is in the Chasm. The benefits of the Apple Watch for example have been hard for even Apple to define, and consumers have yet to be educated of the benefits. Apple is certainly the most experienced company when it comes to crossing the Chasm (it was the company that succeeded in popularising the mouse and the GUI), but still it will take time.

The problem for wearables is that there is no preexisting product to disrupt. For example, except for a very limited number of people, tracking your heartbeat is hardly necessary regardless of how expensive or complicated the devices may be. Notifications on your wrist is also something that most people cannot immediately grasp the benefit of. On the other hand, it is also obvious that with only a minuscule screen size, a watch cannot replace the current day smartphone, no matter how powerful it may be or even if it is connected to an LTE network. Without a preexisting product, it’s very hard to understand what a wearable is good for. It is difficult to understand what benefit it can provide to a customer.

Remember that Apple initially positioned the Apple Watch as a fashion item and a high precision timepiece. The significance of this strategy was that they adopted the value proposition of a preexisting product, which enabled them to connect to customers who were not typical early adopters, thereby speeding up adoption and leaving Android Wear in the dust. Also note that while the regular smartphone manufacturers like LG have recently decided to wind down their smartwatch efforts, traditional watch vendors have started to do the opposite. Regardless of whatever tech is included in the product, at this early point in time where most consumers have no idea what tech can do for them, the value proposition of SmartWatches remain mostly the same as traditional ones and therefore the traditional vendors are the ones that have a story to sell.

Smart homes

Again, this is a product category with no predecessor. Even if you were rich enough to employ a maid or a butler, I suspect switching on the lights would not be typically something that you would do via voice commands. What has been much more critical and aligned better with what people typically hired maids for, was cleaning up and vacuuming the floors, something that Roombas do quite well without any need for a voice controlled “smart” UI. This is why we have seen pretty rapid adoption of these vacuum robots whereas Smart homes are still very much an enthusiast’s toy.

Smart homes will predictably hit a Chasm. The benefits are not clear and therefore only early adopters will buy these things. This will continue to be the case for at least several years. Early majority customers will not understand the benefits without a whole product strategy around a key use case, whatever that might be. Adoption will take a long time, if ever. On the other hand, we will continue to see innovations that use computer, sensor and software technologies to make household chores easier and quicker to do. It’s just that switching on lights is not one of those chores that is a recognised burden on our day-to-day lives.

Summary

The key framework that I’ve used above is to first identify if there is a precursor to a new product category and to see if that has already made consumers aware of the features and benefits. If so, and if the new product has the potential to dramatically increase the market, then I predict that we will see rapid adoption (whether its will be Disruptive or Sustaining depends on whether the incentives to pursue the new product aligns with the business models of the incumbents). Otherwise, we can expect the new product category to follow the technology adoption life cycle and to hit the Chasm. Since the Chasm can be overcome with a whole product strategy, whether or not the market players have experience in this is key to adoption speed.

With this framework, we can predict the rapid adoption of smart speakers by virtue of Apple’s high-quality music strategy, the relatively good adoption of smart watches due to Apple’s experience in whole product strategies and marketing, and the slow adoption of self-driving cars & smart homes due to the current lack of either.

It is also important to note that the key players during the early adopter phase are not necessarily the ones that will make it through to the early majority phase. The Commodores and Amigas of the early PC market did not thrive when PCs became mainstream. Likewise, it is a fallacy to assume that the companies that are currently “winning” in smart speakers and self-driving cars or even Artificial Intelligence in general will enjoy their early lead as the market goes mainstream. More likely than not, other companies that are better positioned for the early majority market and the specific use cases will take it from them.

Out of the markets that I have described here, the smart speaker market is the one that is most likely to see significant action in a year or two due to Apple’s fresh approach. I expect to revisit this post and review my predictions mid or at the very latest late-2018. Other ones will probably still be stuck in the early adopter market and it will be harder to say whether my predictions were right or not.

Do Targeted Digital Ads Work Better?

In a previous post, I predicted that Google's double digit growth will come to an end most likely before 2020. I argued that this was due to the fact that advertising spend has been pegged at about 1% of GDP for a century, and that this hard ceiling would make it challenging for Google to continue fast growth amidst increasing competition from Facebook and other social networks.

Recently it was reported that P&G slashed 140 million USD from its digital ad spending, but saw sales rise for 2017Q2. The article also mentions that

Over five years, P&G is aiming for $2 billion in marketing cuts, including media, with a heavy emphasis on cleaning up the digital supply chain.

Despite high double digit growth for the current quarter, it is clear that there are clouds in the horizon for Google.

The ceiling for ad spending

The Bloomberg article mentioned in my previous post presented the following chart showing just how constant ad spending has been as a percentage of GDP. The earliest data point in this chart goes back to 1926, which is very much the beginning of advertising as we know it today. This is when corporations started to take advantage of the government propaganda techniques that had been employed during World War I, in a massive effort to get young men to enlist in the military forces.

We can see that even as the advertising media shifted from street posters to radio to television and finally the mobile Internet, nothing has significantly grown the advertising market relative to GDP. The fact that ad spending has not significantly grown since the era when all we had were street posters is remarkable when you think about it. Ads used to only be on the streets but radio allowed private time with families to be targeted as well. Even then, ad spending remained constant. Importantly in the context of digital advertising, the advent of highly targeted digital ads which collect all sorts of private information about virtually person on the Internet have not detectably increased total ad spending.

The ceiling for ad spending is very robust indeed.

Sophisticated analytics in digital ads

A lot has been made about the highly sophisticated analytics that digital advertising makes possible (often at the expense of privacy, of course). By use of tracking across multiple websites, it is possible to see whether customers who saw banner ads actually came to an e-commence site to make the purchase. All sorts of techniques have been devised to even connect online behaviour to purchases at physical stores. All this should make it possible for the advertisers to see whether their online ads were useful or not. At the very least, there should be an improvement compared to the classical dilemma; "Half the money I spend on advertising is wasted; the trouble is I don't know which half."

The P&G example above suggests however that the improvement may have been illusional. Despite all the analytics that suggested otherwise, 140 million USD of their digital advertising budget apparently belonged to the wasted half. Maybe all the analytics that sacrifices user privacy does not provide any value after all.

The truth of targeting

Targeting means showing your ads to the people who are most likely to respond positively. Targeting is also purportedly beneficial to the end-user who will end up seeing more "useful" advertisements. Because of these benefits, argue the ad companies, collecting all your personal information is a reasonable compromise. However, despite their best efforts, P&G's CFO Jon Moeller did not have kind words to say.

Clearly we don't need to be spending money that is seen by a bot and not a person. Clearly we don't need to be spending money on ads that are placed in inappropriate places, and that's why you see a significant reduction.

The targeting capabilities that we have today apparently are not very good at distinguishing between a bot and a real human being with a profile that matches what P&G desired. From this, it is reasonable to assume that our current targeting algorithms are even worse at spotting the difference between two humans with different profiles.

Again, collecting all that personal information seems to have been in vain.

Future developments to watch

P&G is not the only company cutting back on digital advertising. Unilever is reportedly doing the same. As a result, in the next few quarters, we should get a better picture as to whether these companies will continue to see strong sales growth despite cutting back, or whether they will see negative impacts and eventually come re-invest in digital. We will also be able to discern whether or not there will be a ripple effect as other companies reconsider their ad portfolios.

If P&G and others do not observe a negative impact despite a continued cut-back on digital spending, then this will significantly blunt the growth of digital advertising. Although I expect this to slow down considerably within the next few years anyway, this may come earlier than I previously though. In the short term however, this will actually benefit Google because they are most likely to be able to maintain advertiser trust by implementing measures to counter the bot issues. In aggregate, I would expect a short term boost followed by an earlier slowdown for Google and Facebook , and an much more imminent downfall for other digital advertising companies.

One possible change that I would very much welcome, is a better understanding of how valuable our personal data really is. Television and magazine advertisements do not collect your personal information, but are nonetheless targeted to a certain degree based on the programme or genre that you are viewing. Targeting itself does not necessarily need personal information as long as the ad placement itself is intelligent, and targeting does not need to stalk your whole Internet browsing habits. Digital advertising might not necessarily need to stalk you. By understanding the true value of these privacy intrusions, our society should be in a much better position to discuss whether we have to make these concessions or not.

Can advertising grow beyond the 1% ceiling?

Given that a large number of Internet companies rely on advertising as their main revenue source, the presence of a hard ceiling should worry venture capitalists who are pouring ever increasing amounts of money into them. If tech is to continue to grow as a whole by high double digits, then tech needs to find a way to either break out of this, or to develop new business models with a more direct revenue.

However, as I have argued, I consider it unlikely that digital advertising is more revolutionary than radio or television advertising, and I strongly doubt that the 1% ceiling will be broken. As digital advertising saturates the ad market as a whole, this market will become a zero-sum game and will not contribute to the growth of overall tech.

Therefore, my belief is that tech needs to stop relying on advertising and that this is starting to be an urgent issue. As the tech advertising space saturates, the current incumbents will become stronger and stronger albeit with slower growth rates. On the flip side, it will be harder and harder for new entrants with an advertising business model to make it. Advertising will quickly cease to be a viable revenue strategy for start ups.

How Can Android Wear Succeed?

I know I’m very late to the party, but I recently noticed this post via a comment on “The Overspill” newsletter by Charles Arthur.

“Until we have an Apple Watch of our own, no one is going to take Android Wear seriously (opinion)” link

Essentially, this article calls on Google to create their own Android Wear watch instead of leaving this to their partners.

If Google is serious about Android Wear, it should be serious about building Android Wear watches – full stop. Only Google has the long-term motivation to keep the platform alive, and only Google can afford for its hardware business to be a zero-sum game in the name of building up an ecosystem. Without our own “Apple Watch” to act as a guidepost, as proof that a better smartwatch can be made, Android Wear seems doomed to continue on in stagnation and obscurity.

Of course, the problem with this argument is that it does not align with how Android nor Windows became popular. Google did not have to build its own phone for Android to gain steam. Similarly, Microsoft did not have to make its own PC to make Windows popular. In both cases, the respective companies followed a strict OEM partnership strategy. Essentially, this argument suggests a lack of understanding on why Android and Windows became popular in the first place.

  1. Both Windows and Android gained popularity on the back of the success of the Macintosh and iPhone respectively.
  2. Both Windows and Android were low-end alternatives to the Macintosh and iPhone. They did not necessarily bring something new, and in fact they started out being downright inferior. They were however cheaper.
  3. Due to the success of the Macintosh and the iPhone, customers were already aware that a GUI and a touch-based smartphone were very good ideas and that they would be useful. Apple had already educated customers to the benefits, and had primed the market. All that Google and Microsoft had to do was to make the same benefits accessible to the rest of the market.

So applying this to the state of smartwatches, we can foresee the following scenario that would take us to the success of Android Wear.

  1. Apple will continue to work hard to educate customers on the benefits of a smartwatch. Apple will explore what features resonate, and what a smartwatch would actually be useful for (something that is still quite ambiguous).
  2. Once the Apple Watch starts selling something like 20-30 million units per year, then a) customers will be fully aware of the benefits of a smartwatch and b) Google will know what to make.
  3. Then all that Google needs to do next is to collaborate with their partners to develop such a smartwatch that is half the price of an Apple Watch, and to bring the benefits to Android users. Importantly, it is OK for this smart watch to be downright inferior. Since Android users are currently >80% of the smartphone market, there is a potential for Android Wear watches to exceed Apple Watch sales someday.

My point is, Google does not need to make its own smartwatch. Doing so would not move the needle one bit. Instead, what Google needs to do is to keep their OEMs cosy until Apple Watch goes mainstream, and make sure that their team can pounce then. The risk here is that Samsung is going their own way with Tizen OS, and will not be with Google when the moment arrives. Google has to make sure that Sony, LG and others will not follow suite, and this is indeed the only meaningful thing they can do.

The funny thing is even among the huge tech giants, it is only Apple that can predictably make a new category product go mainstream. All the rest can do is follow.

Predictions For 2017: Autonomous Driving Reality Check

I am planning a series of posts where I make predictions for 2017. I will put each prediction out one by one, and I will only pick those that have a strong implication for how we think about tech and innovation in general. I will also try to pick those that are likely to actually happen in 2017, rather than something that will happen eventually. That is to say, I will make it possible to check if the prediction was correct at the end of 2017.

Serious autonomous driving fatalities

In 2016, we saw a Tesla owner killing himself in a self-driving car. We also saw Uber self-driving cars running red lights in San Francisco.

Tesla managed to wiggle out of the problem by putting the blame on the driver, who may have been watching a Harry Potter movie instead of being ready to resume control of the vehicle. Uber managed to put the blame on the driver, by saying that the driver was actually in control of the vehicle at that time (which frankly sounds rather unconvincing).

In 2017, more companies will put their self-driving cars into public roads. Fierce competition and investor pressure will mean that some companies will even do this prematurely, before the technology is truly ready. In effect, it is likely that we see something like the Titanic crashing into an iceberg. That is, we will see companies hastily putting autonomous cars onto roads before they are ready, possibly with more fatal consequences. For the sake of prediction, I would say that we will see at least two fatalities by June.

What will subsequently happen is very politic and depends on the huge lobbying power of the large tech companies. There will no doubt be a move towards regulation, but on the opposing end, we will also see an eagerness from governments to embrace the promise of innovation. It is difficult to predict which way the scales will tip.

The Last Straw Of Creepiness

Eric Schmidt has previously mentioned that  Google’s company policy was “to get right up to the creepy line and not cross it”. And despite occasions where it has got itself real trouble by sniffing in on data from personal WiFi routers as Google Maps cars roamed the streets, the general public has not made a huge fuss over privacy.

However, it is not as if the general public is totally oblivious to the privacy issues. There have been reports, for example, that young adults (being more tech savvy) take more security/privacy measures than their elders. Interestingly, the young adults are more concerned with hiding information from their parents than from Google and Facebook, which is obvious when you think about it. A Pew Research survey also show “Some 86% of internet users have taken steps online to remove or mask their digital footprints, but many say they would like to do more or are unaware of tools they could use.” I have also seen similar surveys in Japan.

If this is the case, then it seems like there is a delicate balance in place which reflects Eric Schmidt’s quote, where online privacy is a serious issue for many, but not quite enough for a public backlash. The Internet trackers are a whole have been successful in coming close to the creepy line, but also in not having crossed it.

The next question is then, how will the Internet trackers including Google, Facebook, and a slew of other online ad brokers, cross the line? When will they do something that is so creepy that the public will revolt?

The key to understanding this is, I think, by recalling why the US does not appreciate Edward Snowden. Snowden uncovered rampant privacy intrusions on a massive scale by the NSA. However, the US citizens do not seem to care so much. They seem happy to let the NSA collect data, as long as the information spied upon is not used against themselves, but against terrorists. Of course, I’m sure that US citizens who come from the middle east are not so reassured, but for the majority of Americans, they simply don’t consider themselves as the victims.

Looking at it this way, the creepy line will be crossed when and only when the massive data collected is used against the majority of citizens, and not against terrorists, in a way that is easily noticeable and potentially harmful. For example, re-targeting ads are getting very close to the line because they demonstrate in an unambiguous way, that Google is carefully watching which 3rd party websites you visit. This is completely unlike the previous generation of search or display ads. Re-targeting ads have reminded the public that Google is watching your every move. The only thing that has to happen now is for something to demonstrate that this information can be used to harm you, and then the creepy line will most likely be crossed.

Thus we should next focus on when the public will consider the information gathered by Google and Facebook to be dangerous and harmful. If the information that they have is used in crime in a way that the majority of citizens can identify with, then I would most certainly expect a backlash. This will be when the creepy line will be crossed. However, Google and Facebook themselves have no intention of harming their users, so it won’t be them that cross the line. It will be someone else.

There is no doubt that the information in Google’s servers is potentially damaging. Google probably has the most harmful data if revealed. Unlike Facebook or Apple where you typically send the information yourself, and are unlikely to send stuff that will harm you down the road, Google collects everything. They collect all your searches, all the places that you’ve been to, and all your emails. You do not select which information to share with Google, so the good and the bad get sent there.

I think we a just one major security breach or one major malware attack away from a crisis of confidence. Google itself will not cross the line, but malware can make this happen. Current malware does not collect the privacy/location information from Android devices or Google accounts, but this is because the business model is not there yet. If somebody decides that this is indeed something that they can make money from, then this will happen, and I expect it will bring down Google’s data collection practices down along with it.

Security breaches are becoming more sophisticated and more targeted. Large leaks of accounts are reported quite frequently, although not all of them can be entirely trusted. Indeed, one could imagine hackers announcing the leak of a large number of bogus accounts, just to scare the public into responding to phishing emails. As long as this trend continues, I believe that the largest threat to Google’s data collection practices will be a security breach and not a sudden awakening to privacy by the public.

Points Of Convergence

I’ve been studying the Android operating system and ecosystem recently, out of boredom, and one thing struck me as very odd. That is, Google’s AI applies (or is supposed to apply) to Google’s services, but that is not necessarily the case for third parties.

For example, the Calendar app has an option to scan Gmail and extract event information (presumably using clever AI), which is then automatically added into your calendar. However, although the Android Gmail app can now comfortably connect with Microsoft Exchange servers, Android cannot touch email coming out from these.

This is not the case with iOS. Mail.app analyses all email, regardless of where it came from, applies the same algorithms to extract date information, and suggests events to add to the calendar (it will automatically add events if there is an attachment with the “.dat” extension). Mail.app can do this legitimately because everything is done on the device, without sending the emails to Apple servers. (Note that Google is still facing litigation regarding scanning of email for advertising purposes, which questions their scanning non-Gmail originating email.)

From a technical point of view, features like Google Now-on-Tap may allow Google to analyse data that resides in third party services. However, these third parties may be reluctant due to competitive concerns. Furthermore, privacy policies at least in Japan are very sensitive about sending data to other entities. I expect the same policies or at least expectations exist in many other countries as well, and the above Gmail litigation suggests that this is indeed the case.

This means that iOS will be able to analyse and learn (locally) from emails stored in third party servers like Microsoft Exchange, whereas Gmail will not. In other words, the iOS Mail.app can stand at the crossroads where information from multiple sources come together, and learn from each of them. The iOS Mail.app will be able to benefit from being at the point of convergence. On the other hand, Gmail will have to be separated and isolated.

Gartner has reported that only 4.7% of public companies use Gmail for work. This is based on email routing records, and is likely to be quite reliable. Therefore, in terms of the treasure trove of corporate email data, Gmail is mostly insignificant. For Google to really access this information, it most likely needs to move away from cloud computing and towards AI on the device, because the device is where the data converges.

The interesting to note here is that the point of convergence from a purely technical point of view, will not necessarily be where it will be in real life. Whereas technically it makes sense to accumulate all data in the cloud, privacy concerns alone could force convergence to occur solely on the device.

Peak Google Revisited

Almost a year ago, I noted that while a few prominent tech pundits had pronounced “Peak Google” at the beginning of 2015, Google was actually as strong as ever 12 months later.

In my post, I said that since no company keeps succeeding forever, anybody that predicts the demise of a company without giving a specific timeframe will always eventually be right. That is to say, any prediction without a timeframe is utterly valueless. I also noted that giving a timeline is extremely difficult.

However, I think we now have enough information to give a rough timeline on when we can expect “Peak Google” in financial terms.

Data points

I will lean on the following data points.

  1. The historically constant size of advertising spending
    In 2014, Eric Chemi writing for Bloomberg noted that the US advertising industry has always been about 1 percent of US GDP since the 1920s. This is significant because the US is much wealthier than it was 100 years ago, and it has gone though many ups and downs, even one world war in this time.
  2. The share of internet advertising within the whole advertising market
    According to eMarketer, total digital ad spending in 2017 will be 38.4% (77.37 billion USD) of total media ad spending. It will surpass TV ad spending which will be 35.8% of total.
  3. Google’s US advertising revenue is 31.00 billion USD in 2015, calculated from 67.39 billion global revenue of which 46% comes from the US. This is close to half of total digital ad spending (77.37 billion USD as noted above).
  4. Facebook’s 2015 advertising revenue was 17.08 billion USD. This is roughly a quarter of Google’s.
  5. As noted by Horace Dediu, economic growth in developing nations is not accelerating Google’s revenue growth. Despite rapid economic growth, developing nations are not becoming a larger part of Google’s revenue.

Assumptions

I will also assume the following;

  1. Google will not find a new revenue source that will be large enough to significantly add to its top line.
  2. Google’s revenue growth will continue to be dependent on and on par with growth in the US.

Logic

  1. Since the size of total media ad spending is constant as a percentage of GDP, this is the hard ceiling of advertising growth in the US.
  2. Digital ad spending is rapidly approaching this ceiling. With already close to 40% of total ad spending, there is less and less room left for digital to grow.
  3. Google has close to half of total digital ad spending. Of the remainder, it is likely that Facebook is taking half of this. Google has little space to grow by increasing its share within the total digital ad market. In fact, it is more likely that Facebook will eat into Google’s ad market share. Note that one estimate suggests that Google & Facebook own 85% of the US the digital ad market.
  4. Since Google’s ad revenue growth has largely been independent of developing countries, it is reasonable to assume that this will continue for the mid-term.

In simple terms, there is no longer room in the advertising industry for both Google and Facebook. Since Facebook has more momentum, it is likely that we will see Google being increasingly squeezed. Although the total digital ad spending will likely still see mid double digit growth, Facebook will take the majority of this growth and Google will probably drop to single digit growth before 2020.

What to expect in the future

We are already seeing signs of more disciplined spending at Google/Alphabet, most likely in anticipation of a slow-down in growth. Given the highly talented people at Google, it is no surprise that they understand that the end of double digit ad revenue growth is near.

However, disciplined spending can significantly alter what projects companies chase. Unlike the current Google which constantly throws spaghetti on the wall, a fiscally disciplined Google would probably be more cautious. Within the next few years, I expect that we will see a very different Google from what we are seeing now.

Update

One important thing to note is that “Peak Google” will be a result not of any strategic mistake made by the company, but rather a result of the saturation of the digital advertising market. This has the following implications;

  1. The whole digital advertising industry will suffer along with Google. In fact, smaller and less established players are more susceptible to adverse environments. This is already happening

  2. The saturation of the digital advertising industry also means the saturation of the ad-driven Internet. Startups without a monetisation model will find it harder to bolt-on an ad-driven one later.

  3. Being the most established brand in digital advertising, it is likely that Google will maintain a very strong position in the market for years to come. Like Apple, the issue will be the lack of rapid growth.

Who Will Win The Next Big Thing?

Many people seem to think that the next big thing in tech will be artificial intelligence, and that Google is much better positioned to win than Apple. Other people think that VR/AR is the next big thing, and again, at least one of the companies that is currently announcing hot new VR/AR gadgets is going to win (and not Apple).

However, history has clearly shown that this discussion is without merit. In fact, when a next big thing does come along, the most unexpected company or a company that simply did not exist before, is the one that actually wins. Very rarely if ever, does the company that invests tons of money on the early stage research emerge as the victor.

Google did not exist yet when Yahoo, Lycos, Altavista and many others were first battling to become the telephone directory of the web. Apple was just a failed PC company that was finding success in music when Blackberry, Palm, Microsoft and Nokia were battling to bring smartphones to the masses. Again Apple was a company that was fighting a losing war against IBM when Steve Jobs visited Xerox PARC which had invested heavily in next generation computing research. Compaq did not exist when IBM introduced the IBM Personal Computer. Microsoft was not even in the OS market when IBM knocked on the door looking for an OS for the x86 CPU.

Time and time again, history has shown that when something really new comes along, the companies that seem to have the strongest position from both market and technical standpoints, are rarely the ones that win in the end. The companies that do win are those that we would not even think about, or the ones that didn’t exist. This is what Clayton Christensen’s Disruption Theory is all about.

Therefore from a historical standpoint, if AI or VR/AR succeeds in disrupting tech, it is actually very unlikely that Google, Microsoft of Facebook would win in the end. These companies are in the exact same positions regarding AI and VR/AR as were Blackberry and Palm prior to iPhone, or as were Yahoo, Lycos and others were prior to Google Search. They have invested heavily into research and also into developing the early market. However, they have not yet discovered the formula that would propel them into the mass market.

No matter how unlikely it may seem today, history is actually quite unequivocal on this. The large and established companies that pioneer an early market, do not reap the rewards when disruption happens and the market goes mainstream. The odds are against Google for winning in AI, and the odds are against Microsoft and Facebook for winning in AR/VR (assuming though that AI and AR/VR do end up being disruptive technologies and not simply sustaining).

Although it is almost impossible to predict what will happen, I will just end this post highlighting a couple scenarios under which the Google might find itself vulnerable for illustrative purposes only.

  1. What if privacy became a block for AI penetrating the mainstream? What if consumers started to feel uneasy with the suggestions that Google’s AI made. What if a data breach at a major internet advertising company made it clear to mainstream customers that far more information was being collected about them than they had ever imagined? What if the technology emerged that made machine learning possible without compromising privacy? Would Google invest in this technology, or would it try to improve the AI results with its current privacy compromising methods? It is likely that Google will invest in the latter, which might be a bet on the wrong horse.
  2. AI could actually become the biggest threat to Google’s business model. What would happen if somebody came along with a good enough AI service which made web search obsolete, and which was combined with a monetisation scheme that was far less profitable than Google’s search advertising? Would Google copy that scheme, or would it wait until it found something that was at least as lucrative as the search business that it was cannibalising? What if this service took off, while Google was still looking for ways to maintain profits?

Thoughts On Andromeda

It is widely expected that Google will announce their new Andromeda operating system next week on Oct. 4th. There is a lot of speculation on what the Andromeda OS might look like, and the original sources (1, 2) suggest some key points.

  1. Ambitious initiative that is being pursued via merging Chrome features into Android, not vice versa.
  2. Google plans to launch its forthcoming Andromeda Android/Chrome OS hybrid OS on two devices: a Huawei Nexus tablet and a “convertible laptop”.

All this suggests that Andromeda is mainly focused on tablets and convertible laptops, at least for the short-term. Without going into the details of what Andromeda is actually capable of, I believe that this is the core of the argument and what will dictate whether Andromeda will succeed or not.

Andromeda is aimed at Google’s weakness

Google has two separate operating systems for the PC and tablet markets. One is Chrome OS which has seen significant adoption in the institutional US education market, but has mostly failed to make any significant contribution to the general consumer or business markets. The other is Android which holds a significant share of the tablet market, but only for what is often labeled “media consumption” consisting largely of video viewing.

Unlike Microsoft which still commands the vast majority of the business personal computing market via PCs, Android tablets do not appeal to people who want to work on business documents. This is also true for the mass iPad market, and is the challenge for tablets as a whole.

It has also been often mentioned that there are very few Android apps that have been designed to take advantage of the tablet form factor. Ars Technica’s Ron Amadeo examined 200 apps from Google Play’s “Top Apps” list and found the situation to be quite dire. (To be fair, the design of this analysis experiment is not very scientific. The choice of the “top free apps” list is arbitrary, and a control experiment with a similar list for iPad is necessary.)

Of the top 200 apps:

  • Nineteen were not compatible with the Pixel C
  • Sixty-nine did not support landscape at all
  • Eighty-four were stretched-out phone apps
  • Twenty-eight were, by my judgment, actual “tablet” apps

From the above, I think that it is safe to say that the markets that Andromeda is targeting (the PC and tablet markets), are the markets where Google is weakest.

Similarities to Microsoft’s attempt at the smartphone market

The above situation is similar to the predicament where Microsoft finds itself in with respect to entering the smartphone market. Android is very strong in the smartphone market, and Andromeda is an attempt to use that strength to push Google into the productivity tablet (a market that has yet proved illusive for the iPad as well) and PC market. Microsoft on the other hand has tried to use their dominance of the PC market to gain an entry into the smartphone market.

We know that Microsoft’s attempt has largely failed up till now. The smartphone market has matured and is split between iPhone and Android. Although newcomers have tried to break into the market, all have failed to date. Microsoft’s chance was during the early days when Android’s dominance was not yet secured, but they failed to deliver a compelling solution in time.

We can apply the same analysis to the PC market. The PC market has matured and is dominated by Windows. Although the Mac has tried to regain market share on the halo effect of the iPhone and has gained some market share, this has been a very slow process. The majority market is still dominated by Windows. Similarly, Andromeda will find it extremely challenging to break into a market which is highly mature, and where the major battles have already been fought decades ago.

The consumerisation of IT as a tailwind

The consumerisation of IT is a relatively new phenomenon, and favours players that are strong in the consumer IT arena over those in corporate IT. That is, if the consumerisation of IT is a strong tailwind and if Apple and Google ride this well, there is a possibility that they could challenge Microsoft’s dominance in PCs. Given the maturation and stability of Microsoft’s dominance, without some kind of strong tailwinds, Apple and Google cannot win. In other words, the consumerisation of IT is a new force that could change the balance of power in the PC market, and could create an opening for Apple and Google that they could not have pried open alone.

However if the reverse happens, that is if IT stops flowing from the consumer to corporate and instead starts flowing in the other direction, the direct opposite situation can happen. Jan Dawson has argued that this is indeed starting to happen. Therefore, instead of Andromeda gaining traction in the PC market, we might actually see the the reverse which is Windows gaining traction in smartphones.

The OS is not what matters most

When looking at a new OS like Andromeda, we must be careful to remember that the OS is not necessarily the most important piece of the puzzle. In fact, its importance may indeed be minor. More important is the market position that Google is currently in, their ability to execute a coherent strategy, the commitment of 3rd party developers to create software that makes use of the new OSes features, and the broad market trends that sweep across the industry.

As I have argued above, regardless of the features that Andromeda may have, other factors are not in Google’s favour. Furthermore, what I consider to be most significant and indeed pivotal is whether the consumerisation of IT continues, or whether this will be reversed. The fate of Andromeda hinges on this.

Conclusion

  1. Whatever features may be announced for Andromeda will not be the most important.
  2. Andromeda and Windows 10 are tackling the same problem from opposite ends and with inverse strengths & weaknesses.
  3. What will determine Andromeda’s fate is whether the consumerisation of IT will continue. Recent trends suggest that this is questionable.

Google’s Justification

At Google I/O 2016, CEO Sundar Pichai showed a future filled with their artificial intelligence (AI).   It is all very interesting, but I do have some questions.

How much data does Google’s AI need?

Google’s AI is backed by enormous amounts of data about us. Data that is collected from photos that are publicly posted onto the Internet, and from photos that we upload onto the Google Cloud services from our mobile phones. Data from our messages on Gmail or events on Google Calendar. Data from the GPSs on our Android phones which tell Google where we are every hour of the day. Data from our browsers which tell Google (often without us knowing it), which website we have been visiting. No other company has access to similar amounts of private information.

However, what has not been answered is how much data Google’s AI actually needs.

Can effective AI be created without too much data?

A recent article by Steve Kovach on Apple’s next generation AI system is very interesting.

Siri brings in 1 billion queries per week from users to help it get better. But VocalIQ was able to learn with just a few thousand queries and still beat Siri.

This suggests that it is possible to construct a advanced AI system with magnitudes smaller data sets; data sets that do not have to be aggregates of private user information, but can simply be collated from a relatively small number of people who were paid for the work.

Of course we need to see the results to be sure. At the same time, I find it interesting that IBM Watson was able to win Jeopardy without tapping into huge data sets like those that Google uses.

Does an intelligent assistant mean you have to give up your privacy?

Apple tries hard not to see your private data. Apple believes that your private data belongs to you only, and that you should be the only one who holds the keys. Many people have questioned this approach, based on the assumption that widespread access to private information from millions of people on the server level is the only way to create a sufficiently good AI system.

Apple’s approach does not preclude the storage and analysis of personal data, as long as it happens in a way that Apple itself cannot see. One way to do this is to handle analysis on the smartphone. This is what the NSDataDetector class in the Mac/iOS API does. It’s actually pretty neat, and Apple has a patent on it. Similar but more advanced approaches could easily be implemented in iOS, given the performance of today’s CPUs.

The question is, is this approach sufficient? Will analysing your private data on your device always be much less powerful than analysing it on the server? Furthermore, will there be a significant benefit in collating the private data from strangers to analyse your own? If so, then Google’s approach (which sacrifices your privacy) will remain significantly superior. If not, then Apple’s approach will suffice. That is, you will not necessarily have to give up your privacy to benefit from intelligent assistants.

Does Google need the data for other purposes?

Let us assume that there existed a technology that allowed you to create an effective intelligent assistant, but that did not require that you give up your personal data. Would Google still collect your personal data?

The answer to this question is quite obviously YES. Google ultimately needs your private information for ad targeting purposes.

Could Google be using the big data/AI argument to justify the collection of huge amounts of private data for ad targeting purposes? I think, very possibly YES.