Apple and the Cloud: A Cautionary Tale

4/6/12

The consumer’s electronic world as we know it today is shared between Apple, Google, Facebook, Twitter, and a handful of other popular brands. Most offerings must ride on these platforms and play by their rules. Yet I believe our current interest in—and use of—this ecosystem will peak in 3-6 years, and what awaits each of these companies on the other side must be a completely different business.

In this article, I will focus on Apple’s transformation. I want to lay out some areas where Apple is weak and some trends that threaten the business model, and show that strategy and vision are as important as execution. Just as Apple is wondering what to do with its mountain of cash, the company may want to dedicate a paltry $1 billion to building a company that eventually will replace the Apple we know today.

Digital is Done

We have spent the last twenty years making everything digital, and now that transformation is 99 percent complete. Twenty years ago, Sony was a much larger company than Apple was, because Sony made high-tech analog products. As Steve Jobs pointed out, Sony didn’t make the transition to digital, and Apple surged as Sony slumped. Now that everything is digital, there are two more waves ahead:

1. Analog
2. Digital
3. Meaningful
4. Adaptable

This isn’t about devices, it’s about data. To make our digital data meaningful we need to add descriptive information (called metadata) that will help machines make sense of the digital world (that’s what my book, Pull, is about). To make our environment adaptable, we’ll need to build an entirely new information infrastructure, best shown by a few examples.

Let’s look at maps. For the past thousand years or so, maps were printed pieces of paper. If you had the paper, you could look at the map. Now take the same map and scan it in and make it digital, so you can see it on your iPhone or iPad. Is that what people want? No. As Google Maps shows, we can make the underlying map meaningful by layering on roads, cities, elevations, gas stations, restaurants, hotels, etc. And we can add more meaning by tagging locations with relevant information—populations, weather, road conditions, photos, etc.

Think about documents. Today, most of our documents are digital. They come as PDF/Word/Excel attachments into our email in-boxes. Yet the information value is still trapped inside a document meant for humans to read. When we can extract and use the information without having to read, re-enter, and translate it, we’ll get rid of documents. Instead we’ll have meaningful data we can use and re-use easily.

Think about video. Today, networks broadcast baseball games in digital high definition. They add live statistics along the top in a data bar. Even though it’s digital, it’s still just a single video signal. To make it meaningful, we’ll separate the various video and data feeds and let viewers combine them however they like. For example, you may want all the statistics and player profiles running on your tablet as you watch two side-by-side video feeds of your choice on the big screen. You may want to choose from different commentators, participate in a few chats, ask a question, or keep track of your fantasy league team at the same time.

Not only does this make the experience more personal, it makes the video contents much more findable later—one could easily search for all the at-bats by a particular player, all the home runs, fast balls, strike outs, walks, etc. As we make data more interoperable, it will be woven into products we use every day, making them much more capable than today’s “smart” phones.

Once our data is meaningful and interoperable, we can start to make more aspects of our lives programmable, using the entire web as a resource. An example I give in my book is that individual buildings can plug weather data right into their control systems, so a building responds not just to the conditions outside but can prepare for what’s coming. Highways can redirect traffic automatically after an accident occurs. Hospitals with critical patients can find the nearest resources necessary in seconds, not hours. Airplanes can adapt to route conditions. Our home can start heating when our car is 20 minutes away.

As more of our digital data becomes programmable, the true “web” of interconnected services starts to give us much more power than we get from our computers, apps, and closed systems today. Contracts transform from documents to software that can execute commands according to various conditions. Our televisions find shows we want to watch. The Web itself will match our “haves” and “wants” with those of everyone else on a planetary scale, avoiding today’s “silo” sites that try to aggregate buyers and sellers (think eBay). We will collaborate with thousands of suppliers, vendors, and contributors to build large-scale projects we can’t even dream of today.

Most of us don’t want to program our televisions, cameras, or thermostats. We can adjust settings and preferences, but only after products and services are programmable can they then become adaptable, which is where the magic happens.

Let’s look at bicycles. Like the airplanes and cars of yesteryear, our bicycles use cables to transmit information to brakes and derailleurs. A new system by Shimano, called DI2, uses wires and small battery-driven motors to do the shifting. As usual, we’re using new technology to imitate the old ways of doing things. Shimano’s shifting system gives the rider four buttons: rear derailleur up/down and front derailleur up/down. That’s familiar, but all we really need are two buttons: one to make pedaling easier and one to make pedaling harder. We should be able to program the progression from easiest to hardest and then shift up or down without having to think about which derailleur does what. The logic can be programmed into an app, the app runs on the phone sitting on our handlebars, and the phone becomes our interface to the transmission. That would be a big step, but we can do better.

The Shimano shifting system. The first thing that comes to mind: Imitate old functionality with new technology.

After we have the shifting logic in place, we can get rid of the buttons and shift by voice command. Eventually, we’ll add more data and let our bikes adapt to changing road conditions on their own. Using sensor data from cranks, pedals, wheels, road, and other bikes nearby, the phone can do the shifting and we can give it feedback, so it gets better and better at anticipating our needs. We can still give the occasional voice command before jumping out of the saddle and sprinting. As a bonus, we can keep in touch with teammates while riding or answer an important call.

Adaptability is event driven. It’s very different from the demand-driven systems we have today. If something happens in front of you, whether you’re on a bike path, driving down the freeway, or flying at 30,000 feet, the system (all participants and their equipment) adjusts. When you take a pill, don’t take a pill, hit a golf ball, reschedule an appointment, get in your car, or walk near a store that has something on your shopping list, the event triggers a response and keeps other people up to date automatically. In an event-driven world, we don’t know which apps we need, and it won’t matter. A piece of code sitting in the cloud that is perhaps almost never used is nevertheless ready to respond to something unusual, and we may only learn about this software service after we needed it. An event-driven world is designed to change as the data changes. This is an important concept, one that isn’t integrated into Apple’s developer universe.

From Smart to Dumb

Today, apps rule. App stores have more than half a million apps, and they all do more or less what our computers did 15 years ago—carry out instructions in a stand-alone environment. Many of them share data and sync to the cloud, but apps have their limitations. And our needs have changed.

Let’s look at how a pilot controls an airplane. Today, pilots still go on board carrying a briefcase full of papers that help them fly the plane. While most everything is run by computer, the paperwork is still connected to that particular flight. But now imagine this: a pilot walks up to a huge jetliner, sits down in the cockpit, takes out her iPad, and plugs the iPad into a “well” in the dashboard designed specifically for the iPad. Now the cockpit environment comes to life, showing the pilot exactly what she wants to see the way she wants to see it, with screens that can adapt and show data in context, so that if something is wrong it can get bigger and more detailed while other indicators go off to the side. Her route is already programmed in and connected to weather data, her iPad knows how rested she is, and as she flies the plane, she sees all the other planes on the route and their telemetry data. Pilot and equipment are one, able to adapt together to whatever comes at them. And the cool thing is that the iPad has all the data from every flight that pilot has ever flown, plus data for the next upcoming month’s worth of flights.

Now think about it—how necessary is the iPad in this scenario? Not very. The pilot needs a big touch-sensitive display that shows all the various data sources, programs, and other elements of the system. Add a connection to the Internet with the ability to run independently if the connection goes away, and we have the cockpit of the future. Seen from this perspective, the iPad is just an expensive screen, and the price of screens is coming down fast.

To help us navigate and interact in the coming dataverse, the devices in our lives will become simple, connected, cheap, and ubiquitous. There are data ecosystems emerging everywhere—government, education, business, manufacturing, transportation, science, etc. Imagine going to the Olympics—you wouldn’t use a single app to manage your entire experience for two weeks, would you? Or even a few apps? To navigate the Olympics, you’ll need a web of data and services that keep you up to the second on tickets, meals, transportation, events, athletes, media, people, groups, crowds, and more. To build a fully programmable and adaptable set of tools, we will need to harness the power of cloud computing in a way that doesn’t imitate the old model of apps holding the data.

Most Apps are Websites

This isn’t something Apple talks about, but the truth is that almost all the apps in the app store are really just websites. Here’s how it breaks down:

The vast majority of apps are 98 percent content and 2 percent programming. They are like lightly programmed Flash or JavaScript pages that present content and navigation. Examples include education, recipes, kid games, quizzes, shopping, reviews, sports, cartoons, magazines, stories, ebooks, video, travel, maps, reference books, weather, search, video, social networking, stores, etc. These apps aren’t very interactive. They are based on their web versions. And they are a hassle to maintain. Our app economy penalizes small publishers with quality data by making them build and maintain a growing number of apps on various platforms.

Some apps are 80 percent content and 20 percent programming. This covers most games, which provide high speed interaction with environments that change. Apps that control things in the real world—the camera on your phone, your bicycle, a baby monitor—tend to fall into this category. While some of these are true apps, most have web-based versions that work just fine in a browser. And we can improve technology to let our devices store immediate data and instructions for high performance (or, for example, if you are away from Internet access) but still reside in the cloud.

Many big desktop/enterprise apps are 50 percent content and 50 percent programming. Think of the big programs we own or use—Photoshop, Lightroom, CAD, Word processors, spreadsheets, ERP systems, etc. They are designed to move data in, process it, and ship it out. These general-purpose apps aren’t found on the lightweight app platforms we have today. In the connected, interoperable, collaborative, programmable, adaptive future they won’t play much of a role in our daily lives.

A few apps are 20 percent content and 80 percent programming. Think of an iPad drawing or note-taking app. The app and its features are more complex than what we make with it. Few apps fall into this category.

A handful of apps are 98 percent programming and 2 percent content. Examples are a chess game, translation, or voice recognition, where a small input requires a large amount of computation. This category also includes interfaces to hardware, like opening a garage door or turning on the lights in our homes. The best of these tend to run on servers, where they have access to many resources and can learn constantly, using the device only for input and output.

As you can see, very few apps really need to be apps. Most of our computing needs can be handled by Web servers, rather than having to run locally (and trap data) on stand-alone machines. We don’t really need to improve the storage capacity or CPU capability of our devices. We just need to use the cloud more effectively.

Should these be apps, bookmarks, or both?

It’s the Data, Stupid

One possible solution is to replace our smart phones with a netbook or Web-based tablet, where all the apps are replaced by websites using HTML5 and other connective tissue being built today. Many people think this would be much better and more scalable than the stand-alone apps we have today. In this scenario, all the little squares on the phone aren’t apps but simply bookmarks and automated logins.

And yet even that vision comes up short when you start to think about the scale of future data ecosystems. Here, watch these two vision videos from Microsoft—yes, Microsoft!—Labs to get the idea. [Story continues below videos.]

As you walk down the street, you sport a pair of fashionable glasses that interact with the dataverse all around you. Where is the app store in this scenario? It should be obvious that a single app, or something like today’s web browser, isn’t going to be enough to help you do what you want. You’ll need to broadcast your identity on a need-to-know basis, receive permissions, provide access to your preferences, make transactions, get information, find people, make decisions, update plans, collaborate, negotiate, and much more. Now that the transparent AMOLED screen is available in test quantities, we can start to see the day when the screens are brutally cheap and ubiquitous, and the data is the valuable thing. A web of data integrates with a web of events and services that constantly adapt, learn, and grow to meet ever-changing demands.

In this rich environment, we won’t think nearly as much about apps as we do today. We don’t need an app-centric computing environment; we need a model with the data at the center. And that’s where the personal data locker comes in.

The Personal Data Locker

As much as both Apple and Facebook would like everyone to do everything on their platforms, we are a long way from building webscale data/service ecosystems. Just 10 years from now, we will have 7 billion people and some 50 billion sensors all using the Internet to do an almost infinite variety of things. As I show in my book, the way forward is to turn the current computing paradigm on its head: Keep the data in one place and turn apps into services that come and go as needed.

Think of it this way—did you ever lose some important data? You probably have. On the other hand, did you ever lose an app? Probably not. And, if you did, you probably found it again pretty easily.

Wouldn’t it be cool if, instead of apps, our phones had icons for all our personal and professional data? There would be buttons labeled:

identity
family
finance
health
education
career
home
travel
my stuff
etc.

It would be a start, but the last place we want to store all that information is on a single device. We want it online, so we can access it from any device. We don’t need hundreds of different websites to store our data; we need a secure online data-management system. On the personal side, I call it the personal data locker. Some people call it the personal data store. There is much more information on personal data in my book and in the blog posts below.

Android is not the Problem. Android is the Symptom.

Steve Jobs swore he would “go to war” against Android and its various intellectual property infringements. Today, companies are spending billions to lock up and defend patents pertaining to apps, app stores, and all the features companies are pouring into their smart phone platforms these days.

Android, which also has the app model, is an important step toward the ultimate goal of the personal data locker, because it will bring the price of battery-powered touchscreens down dramatically. The next step is to put all the data into a cloud-based personal data store, and access it using a dumb phone. Software development costs will come down significantly, and the data ecosystems will continue to emerge.

Forget about Android. Concentrate on Chrome. Chrome OS is an open-source web browsing platform. Within a few years, Android and Chrome will merge, giving developers using HTML5 the chance to run Web-native apps on phones, tablets, and other cheap devices. Then we’ll use a $50 “Chrome phone” that has no contract and loads everything from the cloud. We’ll make phone calls using Skype, use websites to do everything apps do today, and more. (Come to think of it, which company recently bought Skype?) This Web-powered phone will be the world’s first true dumb phone. There will be billions more to come. It’s hard to imagine right now, because Chrome is just for browsing the sites we have today, WiMax is just getting started, and the information infrastructure hasn’t been built yet. But as Android and Chrome merge, and the price of hardware plummets, we inch closer to the ubiquitous dumb phone every day.

People say we are in the post-computing era, but our devices are still tiny computers running tiny little apps. As civilization progresses, more and more of our information will go online. Rather than using the cloud to imitate our old ways of working, we’ll use it in a way that is naturally connected and collaborative. When the data never moves, we’ll use information at Web scale, and everyone will have access to the best of everything worldwide. The World Economic Forum says personal data is the new oil. We are just beginning to see a new way of working and playing.

The Road Ahead

Sony’s stock price peaked in February of 2000. That was the beginning of the end for analog devices, and for Sony. Here in 2012, it’s clear that Apple’s current business model is good for many more years. Apple will likely become a Dow component before the company feels the sting I have described. But Apple might want to think about making a small investment in the datacentric future.

Remember distributed computing? We’ve taken that as far as it can go. Now we’re shifting to distributed data. This shift will happen; it’s just a matter of when. Before building an Apple store in Kathmandu, I recommend that Apple take a billion dollars out of the money market account and start building the cloud-based infrastructure that will one day save the company. A few suggestions for Apple’s management to consider:

Make some vision videos. Are Microsoft and Corning really going to show people what the future will be like? John Sculley’s 1988 Knowledge Navigator video is worth revisiting, if only for inspiration. I’ve made a personal data locker video I think all Apple influencers should see. It’s time Apple’s creative team showed us what 2020 will look like. How open will Apple be in ten years? We, the people of the Web, would love to know.

Fix identity. Soon, anyone with a smart phone will be able to take your photo and learn more about you than you may want him/her to know. Digital identities are a massive train wreck that gets worse every day. In the long run, Facebook, Apple, Google, and others have more to gain from cooperating on identity than competing. They should come together and fix the identity problem. The standards exist, but the momentum is going the wrong way.

Get started on the Internet of Things. Now that LogMeIn has acquired Pachube, Apple should think about acquiring LogMeIn and iDigi and getting ahead of the game on the Internet of Things. Here—IBM will show us how.

Get started on distributed data. Read my book—there are dozens of companies and groups already building meaningful data infrastructures. Sooner rather than later, Apple must understand that the cloud is not just for storage. If Apple is going to learn about it, Apple should start trying some experiments.

Build the architecture and developer tool kits for distributed data and services. This is what we call the programmable web. We need to reinvent everything from collaboration to printing to transactions and much more. Look at companies like Kynetx, Mashery, Programmableweb, FacetApp, and others. Read The Live Web, by Phil Windley.

Make Safari into the data-centric browser of the future. Get a jump on Google by overhauling the server/client/data/service/scripting/presentation stack that keeps browsers in the stone age. The W3C people will be glad to take time out of their busy schedules to help.

Join the movement. The online world of data and services is nothing like the closed world of Apple hardware. Apple should join a bucketful of standards organizations and foster industry acceleration of distributed data and services. A good example would be fonts and printers—when you can work online from any device, how do you print to any printer? And how do you make sure the fonts work properly on all devices? Google is working on this now. Is Apple?

Build the personal data locker. Join PersonalDataEcosystem.org and help build the standards that will allow everyone to have a personal data locker. Then move the Apple experience to the cloud and create the best personal data locker experience in the world. It’s hard to see, but this may one day replace all the hardware and all the apps and all the stores. Ten years from now, the data locker could be where the Apple experience lives and thrives.

Start imagining the browser-based data-driven user experience. Apple may not excel at data, but Apple excels at user interfaces. To build the best personal data locker, Apple will need to learn how to present information natively in the cloud, viewable by anyone from any device. When the device doesn’t matter, the user experience still does. Gmail is currently the most impressive effort in this category—Apple has a long way to go to catch up.

Jumpstart vertical ecosystems. Set aside a measly $500 million and start the hundreds of companies that will be needed to build out data ecosystems and services in the top ten industries. I’m happy to head this up.

Help WiMax emerge. So far, Apple has left connectivity to the big telcos and cable companies, but their business models are also peaking. They charge for voice, text, and data, but all we really need is data. Apple could hedge this bet by partnering with those building the new data transmission grid around the globe.

Help protect basic Internet rights. Join AccessNow, a group of people working on keeping the Internet open and free to all.

Summary

Very little changes in a single year, but it’s surprising how much changes in 10 years. Companies like LG and Samsung may see the data-centered web as a chance to do to Apple what Apple did to Sony. IBM shows every day that they get it. Microsoft may look asleep now, but if they focus on data rather than apps, and if they can get Steve Ballmer to focus on his golf game, that could be the start of something big. Google is years ahead in this race already. I’m sure Apple’s TV offering will be slick, and selling gorgeous aluminum-skinned hardware is extremely profitable, and I love the glass staircases, but it can’t last forever. Apple may be worth half a trillion dollars, Facebook may get a billion users, but the Web itself is bigger than both combined. And HTML5 could level the playing field in a few short years.

While Apple has thousands of patents and many more fun surprises in the works, someday the entire Apple experience will be online. Eventually, most Apple products must become Apple cloud services, and this is exactly where the company is weakest. For companies sitting at the top of the heap today—Apple, Facebook, Google, Twitter, etc.—the message should be clear: get more meaningful or get out of the way.

Next step: be sure to see my Personal Data Locker video, below.

After that, come to ThePowerOfPull.com for more links and resources.

Personal Data Locker Vision from dsiegel on Vimeo.

David Siegel is an author, consultant, and investor focusing on the future of technology, the Internet, and business. He has written three bestselling books about the Internet and started one of the first web design and strategy agencies, Studio Verso, which he sold to KPMG in 1999. He is an active angel investor and advisor to startups and the author of Pull: The Power of the Semantic Web to Transform Your Business. Follow @

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