3: Thinking Like a Designer
The opening narrative is an observation of the headquarters of a technology company that was at one time heralded for being highly innovative. In particular, the author notes that the offices were sparse and austere, nothing like the technology start-ups whose offices are filled with avant-garde furniture, improbable things like foosball tables, and executives dressed like they are doing yard work or taking a vacation at the beach.
His implication is that there is a difference between a firm that wants to be perceived as innovative and a firm that actually is innovative - the latter doesn't need pretenses.
(EN: The same can be said of individuals, particularly in the design field: pretenders dress and behave in an affected manner to pose as being "creative" person, but are often quite inept. Those with real talent are often very plain and humble people, and their skill shows in their work instead of their superficial appearance and attitude.)
Leading Design
Martin rattles on a while about the founder and CEO of RIM (EN: which is entirely ironic, as the company is a one-hit wonder whose blackberry phones were popular with businesses because they were cheap and standardized, and RIM plummeted as quickly as it rose when it failed to innovate and fell behind in the smart phone industry.)
His take on the founder is a man whose primary interest is in the product, and who was "fascinated with technology" and particularly designing gadgets. (EN: which is another irony, as true design thinking begins with people and sees gadgets as merely a means to serve their needs. It is likely this myopic fascination that caused the company to keep trying to make a better berry and ignoring the market's movement to devices that were better at serving their needs.)
The last bit is an extended quote, which comes down to this: "That's what's going to get you ... [your competitor is] going to start from a different premise and they're going to come to a different conclusion that makes you irrelevant. Motorola lost because it didn't embrace the future. It was too damn good at what it was doing." (EN: which is exactly what happened to RIM, as a matter of fact.)
Abductive Reasoning
The phrase "design thinking" has become something of a buzzword in corporate circles, which conveys a hazy notion of something different to conventional procedures. A popular definition is that "design thinking means thinking like a designer" - which is a meaningless tautology. Other definitions are presented that are so vague and effuse as to convey nothing.
Martin reckons that design thinking is about using intuition to "match people's needs with what is technologically feasible" and determining whether this is financially feasible. He then waxes poetic about it being a "fruitful balance ... between art and science." (EN: which is so much pretense about so simple a thing: it's merely imagining possibilities by extrapolating from observable phenomena.)
The scientific method is grounded in two basic forms of reasoning:
- Inductive Reasoning - Looks to specific things to draw general conclusions. (If every crow I see is black, then all crows must be black.)
- Deductive Reasoning - Draws on general conclusions to make observations about specific things. (If all crows are black, then the red bird I see cannot be a crow.)
The obvious flaw in these forms of reasoning is generalization, and as such science has attempted to make the theories more specific - defining a checklist of properties that define a thing. If you happen across a crow that is red, and insist on calling it a crow, the list of "rules" for being a crow must be extended to indicate that crows might be black or red. Or you must come up with a different name for a bird that is like a crow, but happens to be red.
But a more insidious flaw in these forms of logic is the very processes by which they work: they are based on observation (which is limited to the scope of perception) and focus on generalization (which pointedly ignores anything that is not consistent).
When applied to human behavior, these forms of logic fail completely: we speculate that people act in a consistent manner (which is often but not always true) and we assume that we are fully aware of all the external conditions and internal motivations (which is never true).
And when the time is shifted from examining what "is" as opposed to what "will be" their failure is complete. They can only succeed if conditions are identical to those that have been observed in the past, and as soon as a new element is added to the equation, it completely undermines them.
Innovation is all about introducing new elements to the equation - doing things differently, in a way they have never done before. Traditional logic fails because it cannot account for anything different and ignores anything that is inconsistent.
It is for this reason that traditional approaches to logic cannot be applied to design, and a more speculative approach must be employed to make an educated guess about how the new element is going to change things in a way that undermines inductive and deductive reasoning.
(EN: It is also for this reason that many firms that fail to innovate are quite good at imitation - because once a new element has been brought into existence by an innovator, those who depend on traditional logic now have seen something that they can apply their skill at induction and deduction to understand. But someone else has to show them the way.)
Charles Sanders Peirce
Martin considers Charles Sanders Peirce, an early twentieth-century American philosopher, who recognized that the development of new ideas was entirely incompatible with traditional forms of logic. His argument was that deductive and inductive reasoning were utterly incapable of producing new ideas - so innovation must require a different fundamental mode of thinking.
Pierce struggled to define this mode of thinking, calling it at various times "logical leaps of the mind," "inferences to the best explanation," or even "guessing." He chose for his theory the unfortunate name of "abductive" logic.
This form of logic extrapolates upon what is known to form ideas about what is unknown. Because there can be no data to examine about a phenomenon that does not yet exist, abductive logic is based on theory, which can be horribly wrong, but which seeks to be at least plausible.
Consider the predictions about the Internet: there was no data available about how popular it would be. Some speculated it would be a fad among a small number of computer enthusiasts, others speculated it would be in every home, and still others speculated it would replace all existing modes of communication (books, magazines, newspapers, radio, television, telephones, postal mail, etc.).
Each of these three theories has some basis in fact, and is plausible - but none of them could be proven. And as it turned out, the first was true for a time, but the Internet grew beyond that. The second is spot-on. The third is not yet true, but there are still those who argue it will be in a few more decades.
In terms of the business world, ideas need not only to be plausible, but financially feasible. Many product ideas, and quite good ones, fail because the cost of production far exceeds the price a customer will pay for the benefit of ownership. Other ides fail to achieve success because people are not interested in changing their behavior, in spite of the benefits of an innovation. Nothing was intrinsically wrong with the ideas - but they were simply not financially feasible (though presumably, the companies that manufactured them found arguments to be plausible).
Abducitive logic is not purely imaginative. The "logic" component consists of extrapolating from things that are known to be true. Before the smart phone was conceived, it was possible to witness the popularity of email among business executives, to witness that they are unable to access their email when they are not at their desk, and to witness that executives are often in motion. All of these observable facts lead to the speculation that executives would value a method of accessing email when they are not at their desks.
But this conclusion alone is the beginning of the process: we must investigate technology to determine how email access can be made portable, investigate manufacturing to determine the cost of such a service, investigate the market to determine how many people might like that service and how much they would pay. And putting all of that together, we have a viable idea for a new product.
All of these investigations are assessments of possibilities rather than a review of facts and proof, because until the blackberry existed there was no way to determine if the guesses that are made are true. They merely seem plausible.
Many leaders are frankly afraid of taking such risks, which is the reason they remain mired in the past - doing what is already being done because there is hard evidence of its (past) success.
Solving the Paradox
Martin suggests that what stands in the way of discovery is a paradox, and the discovery will be made once the paradox is solved.
He returns to the Blackberry device, which represents the solution to the paradox that executives want constant access to email, but cannot constantly be in a fixed location to receive it. The moment of inspiration occurred when it was realized that this paradox could be solved by a device that is portable and can send/receive data without a wired connection. From that idea, it was simply a matter of identifying or inventing the solution.
There were other paradoxes along the way, such as the paradox of miniaturization: people want things to be smaller, but things that are small are difficult to use. The small screen size and tiny keyboard of a mobile decide represent imperfect solutions to those paradoxes.
He also mentions the importance of questioning assumptions. The keyboard problem existed because it was assumed that people use both hands and all their fingers to type. That assumption made designers unable to conceive of a keyboard that would fit in the palm of a person's hand and would be operated with one thumb. Unless that assumption had been questioned and dismissed, there would have been no mobile computing.
He also speaks of the problem of pigeon-holing - which is the limited perception that something is only one thing, and can do no more than what it was originally intended to do. The perception that a telephone is only good for making telephone calls is the reason that mobile phones provided nothing else for two decades before someone perceived that, if fitted with a larger screen and a keyboard, that a phone could be capable of doing more.
(EN: Considering mobile development back in 1998, it's not so much of a leap as the author suggests. Developers notices that there was an LED display that showed numbers, and figured it could be reconfigured to show letters, then found that sixteen letters wasn't enough and enlarged the screen. Then they wanted it to display more than letters - like pictures - following the same path that transformed desktop computing from a small grid that displayed text in amber light to a large screen. My point is that not all inspiration is a leap of logic that comes out of the blue, and it is often in small evolutionary steps that require little more than observation and consideration.)
It can be observed that most innovation takes place in narrowly-defined areas, but this is largely because of the structure of business. A company that manufactures cell phones is interested only in innovation related to cell phones. If a bright employee stumbles across an idea that is too dissimilar to what the firm already does - say that he has an inspiration that will revolutionize doorbells - the company either refuses to pursue it at all, or finds a way to mash this incongruous idea into their product (creating a doorbell that buzzes your cell phone).
Few companies embrace broad-scale innovation, and few individuals have the courage to leave their firm and start their own business to pursue an innovative idea that their employer rejected. There are likely many wondrous things that have been conceived, but never prototyped, out of this sense of fear - which also reflects the pigeon-holing assumption (that a firm of a certain type can only do certain things, that a person who is an employee can only be an employee).
Dragging it back to topic, Martin indicates that the firms that are truly innovative make a conscious and overt effort to avoid accepting paradoxes, question the assumption that things can only be what they presently are, and otherwise depart from the practices common to those who rely on the past rather than speculating about the future. Such an attitude is not an experiment done half-heartedly, but part of the fundamental philosophy that is done with full conviction.
Navigating the Knowledge Funnel
The first step in solving a mystery is to accept and admit that you don't know what you're doing. If you did, it wouldn't be a mystery in the first place. The quest for discovery involves seeking to learn something you didn't know in the first place.
The next step in solving a mystery is exploring. And at its best, exploring means looking at everything you can find to gather information. The danger in forming a hypothesis too soon is that it blinds you to critical information you assumed was unimportant because you are fixated on the things that relate to your hypothesis. Granted, looking at everything takes a lot of time and effort, and is considered by some to be a waste of time and resources - but it is a greater waste, in the end, if you ignore something critical.
The next step, or perhaps the second part of exploring, is heuristics: asking questions such as "how does this relate?" and "why should this be so?" in an open fashion, sometimes observing things that do not seem to have an immediate connection to the mystery. Again, this is purposefully broad in order to avoid jumping to conclusions and prejudicing your inquiry.
Finally, when the exploration and heuristics are done, you are ready to form a hypothesis. You now have a broad knowledge of the subject, and can begin to assess which causal connections may be relevant to the problem itself: you know the elements that are achieving the present outcome, and have a good idea of how they can be changed to achieve a different one.
The hypothesis is formed and tested to determine its validity, and if it is valid, the process is not over: you must formulate an algorithm that can be applied. An algorithm can be understood as a mathematical equation to suggests the probability of outcomes based on the adjustment of variables in the equation - but often, the variables are not quantifiable, so the algorithm takes the form of a logical syllogism - if this and this and this, then the result will be this.
Unfortunately, commercial organizations are interested in one thing: money. So it is not sufficient to express that undertaking a course of action will create "more" customer satisfaction in a general way. You have to translate that into the dollars and cents of revenue, cost, and profit in order to get anyone to take interest in your proposal.
(EN: And unfortunately, this involves some fuzzy math. Top suggest that a 5% increase in customer satisfaction will generate 12% more revenue, you have to do a lot of guesswork based on observation. In a perfect world the work would have already been done - a business that extols the value of customer satisfaction should already have an equation that suggests that every 1% increase in satisfaction causes X% increase in revenue, but things are not always this: a senior executive may be very enthusiastic about customer satisfaction, unable to tell you the reason why, and expect you to prove the dollar-value of increasing satisfaction.)
Roadblocks to Innovation
There are many roadblocks to innovation, even in companies that claim to wish to be innovative - perhaps too many to describe, but Martin provides a brief list of some of the more common ones:
- Executives satisfice. If they are profitable, they see not need to deviate from what is already working - even if there is something that would work much better - and it takes a crisis to motivate them to even consider new ideas.
- Executives are often arrogant about what they know, and are reluctant to admit that there might be something about their business, industry, or market that they don't already know.
- Executives are egotistical. The business operations of today are the result of their good thinking, and to question the status quo is to suggest they may have been wrong, which threatens their egos.
- Executives are autocratic. Their general attitude is that "it's so because I say it is so" and defend the most gorgeously stupid declarations they have made. An executive who declares something to be "impossible" is hostile toward any suggestion it is possible.
- Executives fear failure. Anything that is new and unproven represents a significant risk, and it's safer to stay to the well-worn path than blaze a trail. They are often financially rewarded for doing so, and punished for doing otherwise. (EN: many firms punish a bad decision but fail to reward a good decision - which eliminates the reward for taking risks)
- Executives fear conflict. As with workers, executives want to fit in with their peers and avoid making waves. This means failing to address issues others may find uncomfortable or unpleasant, even if those issues are impediments to success.
- Executives delegate thinking. It used to be that executives made decisions and handed off the tasks to execute on those decisions - but more and more they hire a consultant or delegate to a lesser employee to do the decision-making work for them, this avoiding being to blame for failure.
- Executives are foolhardy. To give the impression that they are men of action, executives want to act - prematurely if necessary. They do not invest time in discovery and exploration, but start with a hypothesis and gather superficial proof (if any at all) and then start doing things.
- Executives like numbers and dislike qualitative measures. This has been discussed elsewhere, but to recap: some things don't lend themselves to quantification - and sometimes, the non-quantifiable elements are the most critical.
- Executives focus on the process instead of the outcome. The purpose of an operation is to achieve an outcome, but the outcome can be ignored in the name of "fine tuning" the existing process.