Map the Future ranges from broad concepts to very detailed how-to instructions. Here are two samples that give you an idea of how that works. The first one tells you how to collect information on competitors, and the second talks about the problems in using the demand curve to forecast product sales.
From Chapter 1. Competitive Analysis: Peeking Inside Your Competitor's Brain
This chapter gives you detailed instructions on how to gather and interpret competitive information, one of the pillars of a future roadmap. In this excerpt, I talk about some of the best sources of competitive information...
1.6 How to collect competitive information
Most books on competitive intelligence-gathering fall into one of two camps: structural analysis and espionage. Structural analysis looks at the forces affecting a company: its financial status, the structure of the market, the supply chain, etc. This is the perspective usually taught in business schools. This information is very valuable, although it tends to assume that all companies behave rationally in response to external pressures, something that I question. I’m not going to spend much time on structural analysis here because it has been so well discussed elsewhere.
The espionage approach is all about collecting information that’s not publicly available. The techniques range from well-accepted practices like sending a “secret shopper” to hear the sales pitch of your competitor, to CIA-style stunts like aerial surveillance, to distasteful (and potentially illegal) activities like going through your competitor’s trash. If you want to see the full list, I encourage you to get a competitive intelligence book from the library.
What I want to focus on here is a different set of techniques that help you understand a competitor’s thinking. If you’re trying to project the future, getting inside the heads of your competitors is mandatory – not so much to understand what they’re planning now, but to anticipate how they will react in the future. But I haven’t seen much literature on how to do it. I’ve found that a few basic, straightforward techniques give me what I need, without the risk of embarrassing the company if word gets out about them.
Hands-on product testing. This is the single most effective competitive analysis tool. Unfortunately, most companies I’ve worked with are shockingly bad at competitive testing – the employees rarely even touch a competitor’s product, let alone use it intensely. They are so wrapped up in their day to day jobs that they simply have no time for looking at other companies’ stuff.
The amount of hands-on testing you can do varies by industry, of course. I once worked with a software company that makes enterprise products – programs that are used by large companies to manage things like payroll and customer databases. The competitive analysts there told me they can’t do hands-on testing because the competitive products cost millions of dollars. I think that’s short-sighted. You should get creative: find one of their customers who’s willing to give you some hands-on time with the product, or send one of your analysts to a training class in the product.
Of course, there are cases in which you really can’t test a competitor’s product. For example, I’m not sure how someone in a pharmaceuticals company would fully test the competition’s products. Taking a few pills home to try out over the weekend doesn’t seem like a good idea.
In those cases, you should talk directly to people who do use the products. Never accept the consensus in the industry or the “buzz” online – the web is too often just an echo chamber of people repeating the ill-informed comments of a few noisy cranks. Get first-hand, real-world experience with the competition whenever you can.
You learn a lot from hands-on product work. First, you’ll spot the competition’s advantages and disadvantages. The disadvantages you tell to marketing, the advantages you show to engineering. Embarrass the engineers a little with the nice points of a competitive product, and challenge them to do better (if they’re good engineers it won’t take much to get them cranked up).
You may also find some opportunity areas where your products could be much better than the competition’s, if only you made one or two simple changes. It’s very important to communicate this sort of low-hanging fruit to the product people aggressively. Don’t assume the opportunities will be self-evident; the product managers don’t have the same background as you and so they may not get the same insights.
Testing is important not just because you learn how you stack up competitively, but because it helps you understand the thinking of your competitor. Like people, most companies have distinct personalities that make them act in predictable ways. A small company usually carries the personality of its founder. A larger company will usually carry some residue of the founder’s personality, plus others that have been grafted into it. If the company has been built through mergers, it may have several competing personalities inside – in other words, it may be schizophrenic.
A company’s product decisions reflect its thinking. As you work with the product, ask yourself some questions:
—What sort of user are they targeting? Is the user well defined? Are they designing for themselves, or for a particular person?
—How well integrated is the product? Is it easy to set up and learn? Do its features work well together? For example, in the mobile phone market, it’s a common sin to stuff a phone with apps that don’t work well together, or with hardware features that don’t really work with the installed software. What does that tell you about the company’s internal planning and organization?
—Look at the packaging and marketing. Do they target a particular person and problem, or do they just talk about the product?
—How does their pricing fit with the product and marketing? Are they trying for a premium price? If so, what do they do (if anything) that justifies that price?
—What assumptions are they making about the customer’s background and skills? Can a new customer figure out how to use it? That may not matter for a piece of heavy equipment sold with training, but in that case you want to ask how the training fits with the product. Is it an afterthought? A core benefit? A profit center for the manufacturer?
If you do the right sort of testing, you’ll get a window into how your competitor thinks and what motivates them.
For example, Microsoft’s products give an endless essay on its thinking and motivations. From the 1990s until 2012, it designed most of its core software products for power users of Microsoft Windows. The software’s look, and the way the user interface worked, all reflected the assumption that the user was already comfortable with Windows.
Generally this was a good assumption, since Windows has such dominant share in personal computers. But it became a handicap when Microsoft started dealing with other categories of product. Many of the design elements of Windows (created for a large screen and a mouse) did not work well on a cellphone (small screen and no mouse). Microsoft struggled with this issue for more than a decade, repeatedly shipping products that forced smartphones to work like Windows. To a competitive analyst, those products were a billboard saying “Microsoft’s internal thinking is dominated by the PC mindset.”
After a decade of failure, in 2012 the company finally gave up and redesigned Windows to work more like a smartphone. That product, Windows 8, has not been a raging commercial success as I write this, but it was very significant because it meant Microsoft’s mindset had finally changed, and therefore that we could expect different behavior from Microsoft in the future.
Nokia’s struggles in smartphones were another great example. For years, Nokia created the world’s most elegant mobile phones. They were usually both more beautiful and more durable than competitors, a difficult combination. Nokia once invited me to a publicity event in which it wined and dined bloggers and passed its latest phones around the table. I remember spending five minutes opening and closing the keyboard on a new Nokia smartphone so I could feel the incredibly nice way the hinge worked. The keyboard didn’t just unfold, it snapped out with a subtle click. But despite the complexity of the hinge, it never felt loose or unsteady. If you know hardware, that’s a remarkable accomplishment.
Yet as soon as I started trying to use the software on the phone, I wanted to throw it out the window. The device was very awkward to use, but what’s worse, there were bugs and missing features.
Nokia was a hardware company in a phone market that had been dominated by hardware features. The selling points for a next-generation mobile phone were almost always hardware: does it have a camera built in, does it have a color screen, etc. Software was just the glue that made the hardware work. Nokia succeeded for many years because it played the hardware game better than anyone else: it turned out lots of phones with great durability, on time, and very competitive pricing. And its designs were, as I mentioned, often very elegant.
But when companies like Apple and BlackBerry shifted the value in phones toward software, Nokia’s advantages became handicaps. The rigid development process needed to produce dozens of phone models a year was an impediment to software developers, who tend to be more fluid and exploratory. Nokia’s strict development deadlines, essential when you’re shipping millions of phones that go obsolete within months, forced the company to sometimes ship phones with unfinished or buggy software.
That pattern of thoughtful hardware and thoughtless software led directly to Nokia’s struggles in the smartphone market, and opened the door to Apple’s success.
It’s hard to believe that you could learn all of that from a few minutes of product testing, but it was blindingly clear in Nokia’s products if you knew what to look for.
Sometimes what you learn from hands-on testing isn’t easy to describe, it’s just a feeling for how the company thinks and operates. But that impression will be immensely helpful as you try to predict the competitor’s actions in the future.
Watch your competitors talk. It’s surprising how much you can learn about a company’s thinking by watching its executives talk. Try to attend executive speeches – live when you can, or on video when necessary. Pay attention to not just their messages but also the way they’re delivered: everything from body language to choice of words to clothing. When Mark Zuckerberg, CEO of Facebook, wore a hoodie to his meetings with Wall Street financial firms, the analysts said it was a sign of immaturity. I disagree; I think it was honesty. Zuckerberg’s hoodie said more about his attitude toward quarterly earnings than a stack of financial filings two inches thick.
Interviews will be more useful to you than canned speeches, because they’re unscripted. Google is a great example. Google CEO Larry Page is notoriously reclusive for a CEO, rarely speaking in public, and allowing Chairman Eric Schmidt to be the company’s main spokesman. This has led to a lot of confusion in the tech industry about Page’s long-term plans, and about the relationship between Schmidt and Page. Although Page was Google’s founding CEO, investors convinced him to allow the far more experienced (and older) Schmidt to run the company from 2001 to 2011, after which Page took over again as CEO and Schmidt was chairman. There were occasional reports of tension and disagreements between Page and Schmidt, but because Google is so secretive, it was hard to determine what was really happening.
Video interviews shed some interesting light on the relationship. In 2002, a year after Schmidt came into Google, he and Page took questions from a live audience as part of an entrepreneurship program at Stanford University. In the video of that talk, Schmidt repeatedly interrupts Page, framing his comments and correcting things Page has said. I think Page looks very frustrated at times.
Fast forward to 2011, when Page took over again as CEO. He immediately reorganized Google, and purchased mobile phone maker Motorola Mobility for about $13 billion. The purchase shocked many observers, but it was in character given Page’s history. In 2000, a year before Schmidt came in as CEO, Page was interviewed on video by the Academy of Achievement, which asked him about the handicaps of being a CEO at age 27. Page replied:
“If you manage people for 20 years, or something like that, you pick up things. So I certainly lack experience there, and that's an issue. But I sort of make up for that, I think, in terms of understanding where things are going to go, having a vision about the future, and really understanding the industry I am in.”
Connect the dots: Page calls himself a visionary at age 27, and then spends the next 10 years in a sometimes frustrating apprenticeship. When he finally takes over, should we be at all surprised that he makes bold moves? I think we should expect more of the same in the future.
Read their books. If a competitor’s employees write books or blogs, those can also be a useful source of insight. Blogs by typical employees can be very helpful for learning a company’s culture and decision-making, and sometimes you can piece together insights on what a company is working on by comparing the things written in various employee blogs.
Executive blogs are a little harder to interpret. They’re often ghost-written by a PR person, and so may be full of marketing fluff. But over time, most companies end up believing the stories that they tell about themselves. Besides, even if something is ghost-written, the executive usually is involved in the choice of topics and language, so you’ll still get a window into the company’s thinking.
Once in a while you’ll pick up a real gem. In 1986, retired IBM VP of Marketing F. G. “Buck” Rodgers wrote a book called The IBM Way. It’s a tribute to the IBM selling process, and even today you can pick up some interesting techniques from it. But far more important is what it said about IBM’s culture at the time. In the introduction, Rogers promised to “expose the heart and soul of IBM.” That raised the question of whether the book would aid IBM’s competitors. Rogers wrote:
“If because of this book other companies increase their level of productivity and profit, we all will benefit. And if competitors improve their operation and make an effort to close the gap, IBM will feel the heat and enjoy the challenge.”
Nothing could better communicate the self-assured sense of invulnerability that permeated IBM in the mid-1980s. Read that quote and you’ll start to understand why Microsoft and Intel were able to steal the PC market from IBM...
The section goes on to discuss other techniques, including going on sales calls, gathering information at conferences, and filtering online information.
From Chapter 7: “Are We There Yet?” Knowing When You’ve Crossed the Chasm
In this chapter, part of the advanced techniques section of Map the Future, I discuss the difficulties in using the “demand curve” to project your company’s sales...
7.4 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 – sharing music, shopping, video, 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 videoconferencing, etc. Some of those curves are probably saturated (e-mail). Others are still in the early adopter stage.
In the case of PCs, demand went 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, multimedia, and the Internet 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 it looks like PC sales have saturated, and tablets are the new growth area. But will they take over the PC market, or just pieces of it? And how big will the tablet market grow?
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 and eggs became diet food for some people.
Let me show you what those overlapping demand curves look like when you chart your sales:
The chart above shows the overlapping adoption curves of a hypothetical product with multiple usages. The first usage gets the product launched. After a few years, it becomes a popular gift item, producing a huge but short-lived surge in sales. The third, most popular, usage doesn’t emerge until years later.
Here’s what those three adoption curves would 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 third wave of growth. In reality, most companies today make savage resource cuts at the point I’ve labeled “panic,” and wouldn’t have enough money to fund the next wave of growth. You must understand your market segments, and where you stand in each one of them, or this sort of demand hiccup can easily cripple your company.
You might think those charts are just theoretical and don’t happen in the real world. But check out this classic chart, which was created by the US Federal Reserve in the late 1990s to show the adoption rates of some of the most important consumer technologies in the US:
This chart shows the real adoption curve for various products into American households over time. Although most people look at this chart and take away the lesson that eventually everything goes up, you have to keep in mind that this chart shows only the winners. It doesn’t show the adoption curves for, say, digital watches or 8-track tape players. But even if you do focus only on the winners, I think the most striking thing about the chart is how many glitches and reversals there are in the curves. All the lines do eventually go up, 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 about 55 years after the invention of the phone. 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?
When I was working at Palm, we had a terrible time figuring out where we were on the adoption curve for PDAs. When we researched our customers, we found a situation that diffusion theory says shouldn’t exist. Our penetration into early adopters of technology products 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.
But many of the people who were already using our products looked like mainstream and late adopters of technology. You’re supposed to get those people after you saturate the early adopters. So how could they possibly be using our products while most of the early adopters hadn’t bought yet?
I think two things were going on. The first is that there were two demand curves for PDAs. One demand curve was for the use of a mobile device to track your calendar and address book. In that market, we 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 those folks had already bought. That’s why there were so many technology late adopters in the installed base.
But the second use of a mobile device is more generalized information management. Add software, and a mobile can become a medical database for doctors, or a flight computer for a pilot. In the early 2000s, Palm had tens of thousands of such apps, covering almost any vertical market or hobby. But the add-in software was hard to find and no app store was bundled with the devices. The growth in awareness of these programs was much slower than the growth in calendar and address book, so the second demand curve was still in the early adopter stage.
The applications market became a driver of iPhone sales many years later. Palm was tantalizingly close to unlocking that much larger market, but didn’t recognize the opportunity.
The second factor complicating the demand curve was that during the bubble years around 2000, handhelds became a popular gift item. 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. Explosive growth in gift purchases of Palm handhelds made the market look much bigger and more mature 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. Palm was widely hailed by market experts as a case study of a company that had successfully “crossed the chasm” and was selling to a mass market. The analysts were exuberantly predicting sales would rise from 10 million units a year to more than 60. It was very hard not to get caught up in that exuberance – especially when some of our research seemed to support it.
Unfortunately, in the real world PDA demand plateaued at about 20 million units a year and then collapsed. Palm missed its sales forecasts, cut back on its investments, and eventually lost the smartphone market...
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