Map the Future

Please visit the new version of this weblog

2006-04-10T21:24:00.000-07:00

This weblog has moved! Nothing new is being posted here. Please visit the new, renamed and re-structured site: Stop Flying Blind.

"Why haven't you posted any more?"

2005-11-20T18:02:00.000-08:00

Map the Future is on a brief hiatus. After a lot of frustration, I've discovered that I can't get Blogger to do all the formatting and other functions I need in order to make this online book experiment work. So I am going to re-host the blog using a different tool. Look for a re-launch in January 2006. In the meantime, look through the material I already posted, and feel free to make comments. They'll be preserved then the blog gets re-launched.

Thanks,

Mike

Introduction: We’re very, very, very bad at predicting the future

2005-10-16T21:31:00.000-07:00

In 1994, a best-selling business book declared that the world was “standing on the edge” of a series of technology changes that would revolutionize our lives. It’s interesting to check in on those predictions to see how they have turned out. Here are seven predictions made in the book:

Live machine translation of speech, so people in different countries could talk to each other on the phone. Nope. The closest thing we have today is automatic translation of websites, which occasionally lets you dig out a useful fact from a Chinese or Korean website but is mostly good for a laugh.

For example, I used a prominent automatic translation service to convert the paragraph above into Chinese and then back into English. Here’s what happened to it:

Speech, therefore person's live machine translation can converse with the different country mutually makes the telephone. Nope. We have the closest matter is the website machine translation, occasionally lets you dig but today is main good is smiles outside a useful fact from Chinese or the South Korean website.

Not only is it pretty much incoherent, but Korean was changed into South Korean, a subtle error that could cause big problems in certain political situations. If that’s the best we can do with text, how do you think we’d do with live speech, which can be pronounced in a huge variety of ways?

Urban underground distribution systems that let companies deliver goods without tying up traffic. Right. Anyone have an update on the construction of that delivery tunnel system under, say, Paris? Or New York?

Microrobotic machines that could unclog arteries. We call it nanotech today, but we’re nowhere near having autonomous surgical robots you could inject into the body.

Virtual meeting rooms so people can have meetings without travel. We’ve made great progress on this with Web-based conferencing systems, but they aren’t nearly as ubiquitous as the book predicted.

Satellite-based communicators that would let anyone make a call from anywhere on the earth. You can actually buy these today, but satellite phones are incredibly unattractive compared to a cellphone. Here are typical specs:

	Satellite	Cellphone
Monthly charge	$30	$40
Per minute	$1.50	First 500 free, then 45¢
Phone weight	13 oz	4 oz
Standby time	24 hours	200 hours
Cost of phone	$1,500	Free with contract

Not surprisingly, satellite phones are being used today mostly for specialized purposes like ship to shore communication. So does this prediction count as a hit or a miss? Since the context was helping businesses plan for the future, I think you have to call it a miss. A company that bet big on satellite communication in 1994 would have lost its shirt. In the case of Motorola’s investment in the Iridium satellite phone system (which Wired magazine kindly called “Edsels in the Sky”) the shirt cost about $2.6 billion.

Machines capable of feeling emotions. We’re not completely sure how emotions work in human beings, so putting them in machines may be a bit of a stretch for now.

Digital highways that bring torrents of information into the home. Right on! This one was correct.

The book’s batting average was .214: one correct, one partly correct, and five wrong. In baseball that would buy you a ticket to the minor leagues -- but business isn’t baseball. In business, a single wrong prediction can cost you billions.

It’s tempting to say the authors screwed up, but actually future business predictions are almost always wrong. Check any 10-year-old business strategy book and chances are you’ll find celebrations of companies that subsequently collapsed, and technology predictions that turned out to be fantasies. And it’s not just a book problem. Companies make the same mistakes internally, as Motorola discovered with Iridium.

The problems with the future are so common that I don’t think we can blame them on dumb authors or dumb managers. There’s something systematic going on. I think the trouble is that we’re looking at the future the wrong way.

Our bipolar view of the future

I’ve been in the technology industry for almost two decades, which in Silicon Valley makes you a grizzled veteran. I’ve worked with a lot of different companies, spending much of my time on strategy and trying to figure out how the marketplace will develop. One of the most striking things I’ve noticed is that most of the companies I work with have trouble thinking about the future.

Silicon Valley likes to present itself as the place where the future comes to life, but in practice the companies are bipolar about it. They either try to beat the future into submission, or they surrender to it as an immutable force of nature. These two groups, which I call visionary and reactive companies, both mishandle the future in important ways.

Visionary companies represent the triumph of individual brilliance over mundane thinking. They’re usually still led by founders who started the company with a strong idea of a new market or product that could change the world. Despite doubters (and there are always doubters in the backstory of these companies), the founders had a correct vision of what would happen, and they drove the company to success.

Visionary companies are usually focused and decisive. They are very good at tuning out distractions and staying on course, because they believe that with good execution they can force the future to evolve the way they want it to. These companies are often indifferent to market research and outside information from people who don’t “get it.” Based on their own history, they usually feel they can do a better job of intuiting opportunities than any research can. Research would just get in the way of their freedom to create.

In my experience, the visionaries are completely right about this up to the point where they start being badly wrong. Even the most brilliant individuals have limits. Eventually inspiration runs out, and the company’s differentiators are copied by competitors. Or the vision hardens into dogma, and the company starts missing new opportunities. Visionary companies are the most likely to march into utter disaster as they cling to a vision that’s no longer valid. They’re flying blind because when you’re inside a vision, you can’t see what its limits are.

Reactive companies are on the other extreme. They view the future not as something they can control (they’d call that arrogance), but as something they can predict, like the weather. Once they have predicted the future, they then make logical plans that react to that prediction. These companies are often superb at responding to changes in the market. They’re very open to outside information, and are willing to learn from anyone.

But this same openness makes reactive companies vulnerable to industry groupthink. In the process of scanning the world for ideas and trends, those that have the most currency among analysts and press will naturally rise to the top of the pile. It’s almost like a voting process -- if enough consultants and other credible people are saying satellite phones will take off, it must be correct.

This makes it very difficult for a reactive company to form a differentiated strategy. Instead, it tends to pursue whatever everyone else is pursuing. You could see the process at work during the Internet bubble, when the tech industry consensus said the most valuable thing to own was an online service. Many of the established companies in high tech threw themselves into the creation of online services, or paid enormous sums to acquire online service companies, even if those services didn’t actually have much to do with their core businesses.

In response to thrashes like this, reactive companies sometimes evolve into fast followers. They become convinced that you can’t really predict the future at all, so they focus instead on quickly co-opting new opportunities and products that other companies produce.

Although American business culture tends to admire renegade visionary leaders, there’s nothing shameful about being a reactive company. It’s the strategy followed by many of the world’s largest consumer electronics firms, most of them headquartered in places where renegade behavior is discouraged. But whatever your cultural attitude, reactive companies are flying blind when it comes to the future. If the consensus prediction of the future turns out to be wrong, or if they don’t spot a major change early, they won’t be able to react in time to survive.

The middle road: Anticipate, don’t react

I think there’s a third approach to the future, one that’s more powerful than either the visionary or reactive path. In this approach, you have to take a different view of how the future works. It’s not something you can control completely through sheer will, and it’s not a single force of nature you can predict perfectly through logic and research. The future is a series of possibilities that might or might not come true. Although you can’t predict what will happen, you actually can predict pretty accurately what might happen, and how you can change it.

Once you’ve made a list of these potential futures, it works like a road map for a family vacation. It shows you cool destinations, routes to get there, and potential hazards along the way. It also shows places that you can’t possibly reach, no matter how badly you want to drive there. Unlike a vacation map, a futures map also shows you the competitors traveling those same roads -- where they are, and where they’re likely to go.

Once you know what the routes are and where they lead, you can pick ones that take you to the best destinations.

To a visionary company, this means the right kind of futures analysis can help you extend your vision, to give you new ideas on possibilities and to anticipate the cliffs before you march off them.

To a reactive company, this means you can free yourself from responding to either rigid predictions or marketplace events. Instead you can identify the best possibilities and the risks along the way to them, and guide the future toward the outcome you want.

Specifically, mapping the future lets you:

--Anticipate the development of new markets, allowing you to seize the best position in them before your competitors even know they exist.

--Predict how competitors will react to actions your company takes, so you’re ready to counter their responses before they even happen.

--Identify major technological turning points that will change your industry (and learn to disregard the changes that won’t really matter).

Most of the companies I work with are not organized to map the future. The people who know critical parts of the map -- competitive analysts, market researchers, and advanced technologists -- are usually scattered in different parts of the company, where they perform mostly support tasks for the business. These functions often don’t communicate with each other, and don’t even respect one-another’s work. To map the future successfully, they need to be organized differently, taught how to work together, and in some cases staffed with a different type of people.

In other words, they need to be treated like a single strategic asset, rather than three separate service groups.

In this blog I'll give my ideas about how to map the future -- how to manage the groups that build the map, how to tie them together, and what sort of benefits you should expect from them.

Think of this as a how-to manual. It’s based on almost two decades of competing and partnering in fast-changing markets with large, aggressive companies like Microsoft, Intel, IBM, and Nokia, often with very little budget or headcount.

Sometimes I've been successful, sometimes not. But I've learned a lot, and one of the things I've learned is that most companies don't think about the future the way they should. I'd like to fix that.

Disclaimer: "What works for me"

Gardening is supposedly the most popular hobby in America, and there are an incredible number of books and websites telling you how to do it. Somebody smart once pointed out that every one of them ought to carry the disclaimer, "this is what works for me." Conditions vary incredibly from yard to yard and from state to state. The exact same treatment that grows a pine tree at my place might kill it in yours. The best I can do is say what works for me, and hope you can adapt it to your needs.

I think the same is true of business advice. Companies, industries, and national cultures differ so much that what's brilliant in one firm may be disastrous in another. In my case, I've worked in high tech, in Silicon Valley, in the United States, for most of my career. Our company cultures here are very informal; information flows up and down the org chart readily. For example, it's commonplace for a CEO to exchange e-mails with an individual contributor -- and woe on the middle manager who gets in the way.

Darwinian competition dominates our economy; firms grow up fast and die even faster. Almost no one builds a long-term career at a single company. In fact, you're viewed with suspicion if you stay in one place for too long -- it must be a sign that you couldn't get work elsewhere.

The lessons and techniques I've learned are adapted to conditions here. If you're in a hierarchical company, in a conservative industry dominated by 30-year veterans, some of my advice may be irrelevant, if not downright dangerous to your career.

On the other hand, if there's one dominant trend in the world's economy, it's that the pace of change is accelerating. Companies are becoming more flexible, information needs to flow more freely, and the days of lifelong employment in a single company seem to be coming to an end.

In other words, like it or not, the world is becoming a little more like Silicon Valley. Maybe some of my experiences will help you, and your company, compete better in that future.

Are we there yet? Knowing when you've crossed the Chasm

2005-10-15T14:59:00.000-07:00

If your company's launching a product or building a new market, one of the most important questions you'll be asked is "where are we on the adoption curve?"

The adoption curve is a graph that shows how groups of people tend to adopt innovations. It was drawn by Everett Rogers in the book Diffusion of Innovation, and re-popularized by Geoffrey Moore in his book Crossing the Chasm.

Rogers based his work on cases like the adoption of improved seed among farmers, and the diffusion of sanitation practices among rural villagers. He found that an innovation moves through a predictable pattern of adoption in a group of people. First, it's tried by a small percent of the population, which he called the Innovators, who are willing to try almost anything new just to be different from everyone else. It's easy to get them to adopt an innovation, but because they like being different from others, the Innovators are not the greatest champions to get others to adopt it. In fact, sometimes other people will avoid things the Innovators like because they don't want to be seen as weird.

(If you're having trouble picturing this type of person, think back to high school and substitute the word "geek" for "Innovator." Got it?)

If you want others to adopt an innovation, the Early Adopters are the ones to focus on. They're a little more numerous than the Innovators, and they're social leaders, the people that the rest of the population looks to for guidance. Unlike the Innovators, Early Adopters crave social status, and they get it by being the first to popularize new innovations. Think of that guy on your block who was the first to buy a flat-screen TV. Everyone else comes over to his house to look at the TV, ask questions, and so on. He gets social status, and the rest of the neighborhood gets to see what the TV's like before they buy one.

Rogers' work was very important because, for example, it told social workers that that rather than trying to teach new sanitation practices to everyone in the village at once, they should focus on the early adopter leaders in a village. Once they're on board, everything else would follow more or less automatically. Rogers also cautioned that it's not very useful to get the Innovators to adopt something new, because they're viewed as weirdos by the rest of the village and if they adopt something, it'll actually be less appealing to the rest of the population.

This advice has been adopted aggressively by marketeers trying to sell new products. The idea's simple -- focus first on the early adopters, and use them to help sell an innovation to the rest of the population. In theory, marketing of an innovation should work like the flow of water through a multi-tier garden fountain: First you fill the small bowl at top, then water spills down to fill the second bowl, then water spills down to the third, etc.

What Geoffrey Moore added to the mix was the idea that in high tech, it's pretty hard to get the water to flow from the early adopters to the mainstream. You have to budget extra time and investment, and make sure your product has very practical benefits, in order to get across the "chasm" to mainstream adoption.

That means for tech companies selling to consumers, knowing where you are on the adoption curve is obsessively important. If you're still selling to early adopters, you need to keep investing patiently and refining the product. If you're across the chasm, you can scale back your investment and focus more on harvesting profit and defending market share.

I've tried very hard to use this methodology to manage and track adoption of my companies' products. Unfortunately, after spending a lot of time and research money on it, I've found that it's much easier to use the adoption curve to explain things after the fact than to use it as a guide when you're trying to make decisions. In practice there are several different adoption curves, and it can be very hard to determine which one you're on. It's disturbingly easy to convince yourself that you're selling to mainstream users when in fact you aren't, or that your market is close to saturated when in fact it's about to take off. Misread the adoption curve and you can easily kill off a product long before it's destined to decline, or pour money into something that's doomed to fail. I've seen three main sources of problems: Determining the shape of the adoption curve, determining who's really an early adopter, and determining which of several adoption curves you're on.

What shape is the adoption curve?

The first and most important question you need to ask yourself is whether you're selling a consumer or enterprise product. I'm using the words "consumer" and "enterprise" a little differently from the way most people use them, so here's a quick definition:

By "consumer," I mean any product that's selected by the person who'll use it. That includes just about anything in your house (unless it was a gift, a situation I'll discuss below). By my definition, consumer products also include a lot of business-related items -- your suit, your cellphone, your briefcase. If your company lets you choose which car you rent on a business trip, or which airline you fly on, I'd call those consumer purchases as well.

An "enterprise" product isn't selected by the user. It's selected by an employer and assigned to a user, who has little or no say in the product choice. If there's a computer on your desk at work, chances are it was an enterprise purchase. So was the phone, and the desk for that matter. Most other things at work are enterprise purchases, including the corporate servers in a closet somewhere, the building your work in, and the corporate health care plan.

The main difference between these two worlds is who's doing the buying. In consumer products, the person who'll use the product picks it out. In enterprise products, the product is chosen by a corporate buyer, on behalf of the whole organization. For high tech products, that buyer is a member of the Information Technology (IT) staff.

Because of this difference in buyers, the adoption curves for consumer and enterprise products are vastly different, which means you need to design and sell the products completely differently. I can't over-emphasize how different these worlds are. A corporation's culture, language, brand image, and business practices all have to be tuned to one or the other. They're so different that it's very rare to find a high tech company competent to sell both consumer and enterprise products. For example, IBM and Sun are both enterprise companies. The old IBM PC was an exception, but as you can see IBM couldn't sustain the business. Apple is consumer. It tried for more than a decade to make itself into a corporate supplier, before Steve Jobs came back and told them to face reality (and focus on their strengths). Nokia too is a consumer company, although it's trying mightily to build up an enterprise business.

The only high tech companies I can think of that manage to be both consumer and enterprise have set up separate divisions to do it. HP is an example, as is Microsoft. But they're exceptions rather than the rule.

	Consumer	Enterprise
Buyer is...	The user	Corporate purchasing manager
What's desired in a product	Productivity Status Pleasure	Lowest cost Minimize support expense Not getting yourself fired
Example products	Cars, consumer electronics, clothing, food, homes	Buildings, business PCs and servers, employee benefit plans

If you're selling a consumer product, even a high tech one, I've found that Rogers' classic adoption curve applies pretty well. Early adopters try out the products, share their findings with others, and if a product is good, adoption will move fairly smoothly to mainstream users. The challenge in consumer products seems to be more about understanding exactly why your product’s being purchased, and therefore which market segments you’re really operating in. More on that below.

For enterprise products, the smooth continuous adoption curve simply doesn’t exist. This is primarily what Crossing the Chasm was about, and if anything I think it understates the differences between consumer and enterprise sales.

First, let's look at the motivations of the buyer. Someone buying a consumer product is usually motivated for the benefits it brings to himself -- usually a mix of increased productivity ("If I bought that circular saw, I could finish paneling the den a lot faster"), increased status ("I can't wait to se the look on Dad's face when he sees the new den"), and increased pleasure ("Man, what a cool saw.")

A corporate buyer cares about none of those things. In fact, they are trained to ignore them. Employees in the company are constantly lobbying for nicer corporate goodies -- plusher cubicles, better computers, nicer office chairs. The buyer's job is to defend the company against all those demands, and instead do something that's sensible. That doesn't mean user desires are completely ignored, but it's more important to stay within budget, and to avoid new support costs.

Support costs are a big issue for high tech products -- if a product is cheap to buy, but is so complex or flawed that it generates a lot of user questions, the cost of answering those questions can easily be greater than what you saved on the product. The tech consulting firm Gartner Group has for years argued that for PCs, the cost of training and support is higher than the total purchase cost of the hardware.

But the most important priority for a corporate buyer, exceeding all other requirements, is avoiding a mistake that could get you, the buyer, fired.

This means that corporate buyers as a group are extremely conservative, much more so than the average consumer. They'll tend to buy only from companies they know, and they'll be very leery of new products. Even a proven increase in productivity may not be enough to motivate them to buy. After all, most IT departments are not rewarded for increasing the productivity of the company. They're service groups, rewarded for controlling costs and not allowing any major technical disasters.

When I was at Palm, we surveyed corporations to determine their attitudes toward purchasing new technology, especially handhelds and smartphones. Instead of the usual bell-shaped curve, we found a two-humped curve:

Left: How corporate technology buyers describe their companies’ adoption of new technologies.

About 30% of the companies surveyed said they were aggressive technology buyers -- they viewed the use of advanced technology as part of their competitive advantage. As a deliberate corporate policy, they tried to stay on the leading edge of new products and services. These companies tended to decentralize technology purchasing, allowing individual departments to buy rather than forcing them to work through a central purchasing group.

The other 70% of companies were more conservative about technology. They didn't try to be at the leading edge, and in fact were fairly reluctant to integrate new technology. They were more likely to have centralized control over technology purchases.

When we looked specifically at corporate-funded purchases of handhelds and other mobile devices, we found that the early adopter companies were moving ahead aggressively to broad deployments across the company, while the other 70% of corporations were still doing small trial deployments, if anything at all. The early adopter companies accounted for 68% of all corporate handheld purchases, even though they were only 30% of companies. If you’re interested in methodology, this was a survey of 440 randomly-selected technology buyers/approvers in US companies having 100 or more employees. The survey was conducted in 2003.

(Incidentally, this split adoption pattern explains why you sometimes see schizophrenic press coverage of the market for mobile devices. One article will say the market is taking off fast, another will say it's dead in the water. Both are true; it just depends on which companies you're looking at.)

We also found some interesting differences in technology adoption by industry. Some industries were biased toward early tech adoption, while others tended to be more conservative. For example, engineering and research firms, communication, and wholesale all tended to be aggressive tech adopters. Meanwhile, companies in education, government, and health care were much more likely to be laggards. (In health care, remember that we were looking at adoption of new computing technology, not new medical technology.)

Corporate handheld purchases tended to mirror these adoption preferences, with one exception. Health care has a large installed base of handhelds even though it's slow to adopt new information technology. Apparently doctors find handhelds so useful for tracking drug and other information that they're forcing the devices into medical corporations whether IT wants them or not. This is an interesting case of a consumer (user-led) adoption cycle driving corporate adoption. Something similar happened when the first PCs entered corporations in the late 1970s.

In most companies, we found that the actual purchasing decision was controlled by two parties -- the departmental manager (who's paying for the product) and the corporate IT manager (who enforces corporate standards, supports products, and often negotiates the actual purchase). The relative strength of these two groups varies from company to company, but in most cases both of them have some level of veto power.

Because of all this, you can't sell an enterprise technology product the way you do a consumer one. In an enterprise sale, you usually need to generate two different types of demand in two different places. First, you need demand from the managers of the department that will use your product. Usually they need to be convinced that they'll improve productivity or make their employees happier. Then you also need IT management to at least acquiesce to the purchase. They don't have to love it, but they must at least be willing to put up with the product, or they'll find a way to stop the sale.

I have vivid memories of watching a focus group with IT managers while I was at Apple. One of them said adamantly, "I have devoted my career to keeping Macintosh computers out of my company." No matter how many cool and creative ads Apple came up with, no matter how much the employees wanted Apple's computers, they were not going to be bought by that company.

As Geoffrey Moore has pointed out, this means companies need to use a two-step selling process for enterprise technology products. It's relatively straightforward to sell to the corporate early adopters, because they make it their business to try everything that's new. But to sell to the other 75% of corporations, you have to look closely at the adopter profile of the particular vertical you're selling to. You have to prove not just that your product is useful in that industry, but you also have to demonstrate that it's not going to cause trouble for the IT staff (a much higher hurdle, and one that takes time).

This means the deck is stacked against small startups selling new technology products to corporations. If a similar or even somewhat inferior product is offered by a large company that IT already knows, the IT buyers will try to steer purchases toward their trusted supplier. For years IBM used this effect to lock out competitors, by pre-announcing copies of a competitor's innovation, so customers would hold off buying from the upstart. Microsoft uses similar tactics today.

Some markets mix consumer and enterprise. Not all markets can be cleanly sorted into either the corporate or consumer bucket. A very good example is mobile phones. Most mobile phones are bought by the people who will use them, and so I’d classify that as a consumer market. But if you’re a mobile phone manufacturer, you don’t sell directly to most of those users. Instead, you sell phones to a mobile phone carrier like Verizon or T-Mobile, who in turn sells the phones to users. From my perspective, that starts to look more like an enterprise market.

If you’re running a mobile phone company, do you focus on phone users, or on the buyers at mobile phone companies?

The answer is that you agonize about it a lot, and different companies come to very different conclusions. Some companies market focus mostly on users, counting on demand from them to force the carrier to offer their phones. Nokia is notorious for doing this in Europe. Other examples are Motorola’s Razr slimline phone and Palm’s Treo smartphone. But some other major mobile phone companies don’t worry as much about appealing to users, instead trying to produce whatever the carrier want, and counting on the carrier to push that to users. The Korean company LG, one of the fastest-growing mobile phone companies in the world, uses this approach.

What about gifts? These are a special case because they're not bought by the user or a corporate buyer, but instead by someone trying to express love or make an impression. Gifts don't follow the normal adoption curve. Instead, they're driven by fashion and herd thinking. The fashion cycle moves very quickly -- a hot gift one year is likely to be a doorstop a couple of years from now. For example, PDAs were a raging gift item in the late 1990s; gift giving accounted for about a quarter of Palm's sales. A few years later, the rage had moved on to digital cameras.

Gift sales grow explosively and decline just as fast. If you're selling a consumer product, it's important to track what percent of your sales are gifts. Restrain your expectations (and the expectations of your investors) if you see a lot of gift-giving. Think of the revenue as a one-time upside event rather than sustained demand. The hot gift period won't last.

Are your early adopters actually mainstream buyers?

In a stable rural town or village, it's pretty clear who the high-status people are, and if you're a leader in one aspect of village life, you'll tend to be a leader in most aspects. But in the modern world, most of us belong to a series of different villages -- a neighborhood, a job, interest groups around town or on the Internet. You might also be a member of a social club or school alumni association. It's pretty common to be an early adopter in one area but a laggard in another (for example I'm a geeked-out innovator when it comes to computers, but a late adopter in cars). Consultant Peter de Jager does a nice job of explaining this in an essay on his website.

This makes it much harder for a marketer to proactively identify who the early adopters are for a new product. There are some people who just have that early adopter personality type and tend to lead in everything they do, so you can try to focus on them. In high tech, we try to find technology early adopters, assuming that someone who's quick to buy a flat screen TV will also be quick to buy a new mobile phone. But in that case it's easy to end up accidentally marketing only to the technophile Innovators, and they're a dead end in terms of driving sales to others.

When you're not sure who the early adopters are, it's also hard to track your position on the adoption curve. For example, say you have sold a product to 10% of the population. That might mean that you're just now finishing with the early adopters in a market that will eventually include 90% of the population (curve B in the chart at left). Your sales are about to explode. Or it might mean that you've just saturated a market that's destined to top out at 12% of the population (curve A). Your sales are about to plummet.

It is surprisingly hard to tell the difference between these two cases when you're in the middle of them. Generally if a product has reached 10% of the population, a lot of other people will be thinking about buying it, just because it generates some buzz. It's very difficult to sort out the difference between this buzz and actual demand until after the fact, when you look back at what happened to real sales.

The better you know your market(s), the better your chance of avoiding this problem. This is why you have to be very serious in asking the question, what problem are you solving for your customers? Why are they buying from you? Often a company will have a lot of noble and interesting reasons why customers are supposed to buy its products, but when you look intensely at the customers, that's not why they're buying. Once you know the real reason why people are buying, the next question is, how many people have this problem? Or more to the point, how many people have this problem and care about it so deeply that they're willing to spend money to solve it?

Even if you determine that you really are solving world hunger or some other universal problem, you then need to use market research to map out your demand funnel -- how many people are aware of your products, what percent of those people think about buying, and what percent actually do buy. Where are you losing the most people? These two products both sell to 15% of the market, but they very different problems:

Most people have heard of product A, but they generally think it’s not for them. Doing a lot more marketing for this product is not likely to produce a rise in sales, unless the product has some incredibly compelling secret feature that no one currently knows about. Even then, you’ll be fighting against the current impressions people have about your product, which can be very hard to change.

More marketing might help Product B; the biggest barrier to its sales is that people just haven’t heard of it. When a company sees a chart like Product B’s, it’s pretty common to assume that if you increase awareness, consideration and purchase will also rise as well. That might happen, but you can’t take it for granted. Probably the people who have already heard of your product are the most enthusiastic customers for it, and you can’t count on everyone else reacting to it the same way.

The overall point here is that additional marketing won't necessarily create more demand, until you know why people aren’t buying today.

Which demand curve are you on?

Many high tech products are flexible, and can be used for multiple purposes. The Internet's a great example -- its first mainstream use was for transferring e-mail. Then it was used for browsing information. As the new medium grew, companies created additional uses for it -- online auctions, sharing music, e-commerce, and so on. If you're a company selling Internet access or Internet hardware it's almost impossible to plot Internet demand on a single curve. Instead, your demand is a composite of a lot of different curves -- one for e-mail, one for music, one for auctions, etc. Some of those curves are probably close to saturation (e-mail, at least in the US). Others are still in the early adopter stage.

In the case of PCs, demand has gone through several curves as different uses for the PC emerged. PCs started mostly as appliances for word processing and spreadsheets. Desktop publishing came along in the late 1980s and created a new surge in demand. Games and the Intenet drove much higher penetration of PCs into homes in the 1990s. Other applications have created their own smaller surges in demand along the way.

Looking back at the development of the market, it's easy to see how these overlapping demand curves worked, but at the time it was very hard to predict them. For example, in the mid-1980s it was very easy to predict that PC sales would soon plateau, as usage of spreadsheets and word processing saturated. In reality, a new wave of growth was about to start.

Today we face some of the same questions. Although PCs have high penetration in the US, they are not as ubiquitous in Europe, and are downright rare in developing countries like China and India. As those countries' economies grow, will PC ownership approach US levels? Or will other products, like advanced mobile phones, take over some functions of the PC in other countries?

No one knows.

Although multiple usages are commonplace in high tech products, they’re not unheard of elsewhere. For example, as low-carb diets took off, beef became a diet food.

Overlapping adoption curves of a hypothetical product with multiple usages. The first usage gets the product launched, and it also becomes a popular gift item in the fourth year. The second, more popular, usage doesn’t get started until year seven.

Here’s what those three adoption curves could do to the sales of our hypothetical product. At any point on the curve, it’s extremely difficult to predict what will happen next. In this case, I have imagined a happy outcome for the company and its investors – they are patient enough to get to the second wave of growth. In reality, most companies today make savage resource cuts at the point I’ve labeled “management team fired,” and wouldn’t have enough money to fund the second wave of growth. You must understand your market segments, and where you stand in them, or this sort of demand hiccup is likely to cripple your company.

This chart shows the real penetration of various products into American households over time (I assume the line for “airplane” indicates percent of families who have ridden on airplanes, not the percent of homes that have been penetrated by them). To me, the most striking thing about the chart is how many glitches and reversals there are in the curves. All the lines eventually go up and to the right, if you’re willing to wait 100 years. But if you were actually living at a particular point on one of those curves, you couldn’t reliably predict the size and timing of future growth. For example, imagine yourself as a telephone executive, 60 years after the invention of the phone (dark blue line). Telephone penetration has been dropping for the last five years, and is now back down to where it was twenty years ago. Would you predict that it was about to start going up again? What would shareholders do to an executive making a prediction like that today?

[Chart: Federal Reserve Bank of Dallas Annual Report 1996. ]

In the handheld market, we had a terrible time figuring out where we were on the demand curve. When we researched our customers, we found a situation that diffusion theory says shouldn't exist. Our penetration into technology early adopters was okay but not very high. A lot of early adopters were still thinking about buying our products. This should have meant we were still in the early stages of growth.

On the other hand, a lot of people in our installed base looked like mainstream and late adopters. You're supposed to get those people after you saturate the early adopters. So what were they doing buying our products while most of the early adopters hadn't bought yet?

Looking back, I think two things were going on. The first is that there were two demand curves for handhelds. One demand curve was for the use of a handheld to track your calendar and address book. In that market, handhelds were well past the early adopter stage, and in fact were approaching saturation. There are only so many people in the world who are so obsessive about their calendars that they want an electronic tool to track them, and most of them have already bought, at least in the US. That's why there were so many technology late adopters in the installed base.

But the second use of handhelds is as a more generalized information management device. Add software, and a handheld can become a medical database for doctors, or a flight computer for a pilot. There are software programs for almost any vertical market or hobby. The growth in awareness of these programs is much slower than the growth in calendar and address book, because the add-in software is hard to find and isn't bundled with devices. So that demand curve is still in the early adopter stage. I think that's why there was still a lot of consideration among early adopters.

The second factor complicating the demand curve was that during the bubble years, handhelds became a popular gift item. They were the "in" thing to give Dad for father's day or Christmas, even if he didn't really need or want one. These gift sales made the market look bigger than it really was.

Looking back, after the fact, it's possible to tease apart all of these threads and see how they fit together. At the time, it was almost impossible to see. The analysts were exuberantly predicting sales would rise from 10 million units a year to more than 60, and it was very hard not to get caught up in that -- especially when some of the research seemed to support it.

Unfortunately, in the real world handheld demand plateaued at about 20 million units a year.

Lessons

What can you learn from all of this? I think the message isn’t to abandon the demand curve, but you have to be very careful in how you use it.

Know if you're an enterprise or consumer product. Even if your product is designed for use in businesses, if he buyer is the user, you're going to see a consumer buying pattern, and you need to set up your sales, marketing, and product design for that. On the other hand, if the buyer is an IT manager or other corporate official, you need to organize to sell to both the departmental manager and the corporate buyer. That takes longer than winning over a consumer, because you're asking the corporate buyer to put his or her job on the line when buying from you. On the other hand, once you win over corporate buyers, their conservatism can make them very loyal customers.

Make sure your investors and management team understand the dynamics of the markets you’re after, very early in the game. The better you set their expectations, the better the chance that you’ll be given the time and money you need to develop the markets. Few things are more unpleasant, and more likely to destroy your credibility, than spending two years on product development, and then going back to the board of directors to ask for a huge marketing fund because you’ve switched target markets.

Know your segments. The better you understand the actual usages of your product, the better you can apply the demand curve. Understand who's buying your products, and what their motivations are. If there are multiple motivations, investigate whether those point to distinct segments, each of which will have its own demand curve.

It's easy to get tremendously confused when you lump multiple segments together. For example, the research that has been done on advanced phones implies strongly that there will be at least three different segments for such devices -- one for communicators, one for entertainment phones, and one for information phones. The market for communicators could easily saturate before the market for entertainment phones even takes off. I think it's very likely that these out of phase adoption curves will lead to big swings in enthusiasm for the advanced phone market in the next few years, with some people predicting it's about to explode and others predicting it's about to die. The reality is, there isn't a single market to forecast.

Avoid the self-fulfilling prophecy. You need to accept that you can't completely plot the demand curve until after the market has saturated. Your position on the curve depends a lot on how attractive your products are and how well you market them. Do a better job, and the market will grow. You can change the curve.

Many of the biggest mistakes I've seen companies make were mis-judging where they were on the adoption curve.

For example, in the early 1990s many analysts concluded that the Apple Macintosh was a dead end, with a saturated market destined to die. They encouraged Apple to pour hundreds of millions of dollars into other new businesses -- servers, new devices, applications, new operating systems. Most of them didn't pay off. Meanwhile, investment in the Mac was constrained. When Steve Jobs returned to the company, he put the focus back on the Macintosh, and revived demand for it. You can still make a good argument that the Mac will eventually be a dead end, but it's impossible to say if “eventually” will be in five years or twenty. A lot depends on what Apple does. It's up to them.

There were other problems at Apple, of course; I'm oversimplifying the situation. But one of the company's biggest burdens was a belief that the adoption curve was a prophecy rather than a problem to be fixed.

Welcome!

2005-10-15T13:47:00.000-07:00

Welcome to Map the Future, a blog on business strategy and how to do it right. I’ve been working in roles related to high tech strategy for most of my career, including long stints at Apple and Palm. I think most of the companies in our industry do a poor job of using external information (competitive analysis, market research, and advanced technology planning) in their strategic thinking. In this blog I’ll lay out my ideas on how to do it right.

I call the blog “Map the Future” because that’s what I think most companies fail to do.

I’ll post a new essay about once a week. I’m very interested in your feedback and suggestions.

Thanks,

Mike

Note: This is one of two blogs I’m running. The other, Mobile Opportunity, is a look at the mobile and wireless marketplace.