Monthly Archive for March, 2010

It seems counter-intuitive, but it seems to be human nature to jump directly from an intuited need straight to an answer, without ever bothering to clarify the need and posing it as a question or a defined problem. This means that much of the time it is difficult to agree on the suitability of an answer, because there’s no standard against which the answer can be measured.

It might seem logical to resolve this situation with a self-disciplined refraining from answering questions before the questions have been asked, but maybe it would make even more sense to work with the grain of human nature, and to take a Jeopardy approach: start with answers as clues to what the question may be, then working backwards to clearly formulate the question and define the problem.

These days the word “wisdom” is disreputable. For most people, it has no precise, definite meaning which makes it a magnet for charlatans and romantics. Its has connotations ranging from the embarrassing to the offensive: it’s quaint, ludicrous, vague, presumptuous, pompous, flaky. But it also has a certain protected status that makes it slightly taboo to attack it directly (however much the attacks are deserved), and that makes it exponentially annoying. Using the word “wisdom” in a business setting is credibility suicide.

So here we go.

When I say wisdom I actually do have a very specific meaning, and it is a meaning that deserves respect, and not only respect. It deserves enthusiastic adoption and action.

Understanding what wisdom is, how to acquire it and how to share it in a business setting is a huge competitive opportunity.

Here is my definition of wisdom: Wisdom is subjective knowledge, standing between tacit experience and explicit fact, and mediating between them. It is knowing how to navigate one’s own experiences and to gain explicit knowledge about these experiences from having been in them — without reducing the experiences to this explicit knowledge, and without accepting the tacit nature of the experience at face value. What wisdom produces are insights, expressions of truth that help people orient themselves to an experiential point of view and to see from the perspective of that view. Wisdom deals with symbols, relations and relevance. Or to put it in the language of anthropology (which is the science of wisdom), it means tacking back and forth between emic and etic modes of understanding — and then synthesizing these modes into effective practical responses, which is politics (the technology of wisdom), or in application to business, management. Politics and management bring together all the modes of intelligence (scientific, technical, theoretical, and every discipline of business) — each with its own characteristic kind of understanding — to address the situation at hand, and form it into something that achieves the desired experiential outcome.

To date, the business world has mirrored the larger culture in exalting the scientific mode of explicit knowledge, and has become very good at observing and measuring things and behaviors. This is important but it is no longer enough to manage people and knowledge. Organizations also need to learn how to manage its wisdom, to continually improve the lives of customers and employees and of our culture.

Years ago I read a passage from Thomas Kuhn’s Structure of Scientific Revolutions which caused me to understand the importance of examples in illustrating concepts in a deeply different way. (This book is infamous for unleashing  the expression “paradigm shift” on the world.)

What Kuhn helped me grasp was that examples do not only illuminate or prove a theoretical statement — they give the theoretical statement its sense.

Why am I talking about this here? The ends experience strategists try to accomplish, the means we use to accomplish them, and the language and concepts we use to talk about our means and ends are very abstract. Our clients are often flying blind. They know (sometimes vaguely) what they hope to accomplish by way of “improving the customer experience”, but much of what leads up to this improvement is either confused, force-fitted into more familiar (mis)conceptions, or fragmentary, wispy or left a frank mystery. When we supply a client examples we are not only reassuring them that we are capable of solving their problems for them — we are also helping them understand how to see their problems in clearer and more productive terms.

If you’re interested, here’s a large chunk of the quote (bolds added):

Philosophers of science have not ordinarily discussed the problems encountered by a student in laboratories or in science texts, for these are thought to supply only practice in the application of what the student already knows. He cannot, it is said, solve problems at all unless he has first learned the theory and some rules for applying it. Scientific knowledge is embedded in theory and rules; problems are supplied to gain facility in their application. I have tried to argue, however, that this localization of the cognitive content of science is wrong. After the student has done many problems, he may gain only added facility by solving more. But at the start and for some time after, doing problems is learning consequential things about nature. In the absence of such exemplars, the laws and theories he has previously learned would have little empirical content.

To indicate what I have in mind I revert briefly to symbolic generalizations. One widely shared example is Newton’s Second Law of Motion, generally written as f = ma. The sociologist, say, or the linguist who discovers that the corresponding expression is unproblematically uttered and received by the members of a given community will not, without much additional investigation, have learned a great deal about what either the expression or the terms in it mean, about how the scientists of the community attach the expression to nature. Indeed, the fact that they accept it without question and use it as a point at which to introduce logical and mathematical manipulation does not of itself imply that they agree at all about such matters as meaning and application. Of course they do agree to a considerable extent, or the fact would rapidly emerge from their subsequent conversation. But one may well ask at what point and by what means they have come to do so. How have they learned, faced with a given experimental situation, to pick out the relevant forces, masses, and accelerations?

. . .

A phenomenon familiar to both students of science and historians of science provides a clue. The former regularly report that they have read through a chapter of their text, understood it perfectly, but nonetheless had difficulty solving a number of the problems at the chapter’s end. Ordinarily, also, those difficulties dissolve in the same way. The student discovers, with or without the assistance of his instructor, a way to see his problem as like a problem he has already encountered. Having seen the resemblance, grasped the analogy between two or more distinct problems, he can interrelate symbols and attach them to nature in the ways that have proved effective before. The law-sketch, say f = nw, has functioned as a tool, informing the student what similarities to look for, signaling the gestalt in which the situation is to be seen. The resultant ability to see a variety of situations as like each other, as subjects for f = nw or some other symbolic generalization, is, I think, the main thing a student acquires by doing exemplary problems, whether with a pencil and paper or in a well-designed laboratory. After he has completed a certain number, which may vary widely from one individual to the next, he views the situations that confront him as a scientist in the same gestalt as other members of his specialists’ group. For him they are no longer the same situations he had encountered when his training began. He has meanwhile assimilated a time-tested and group-licensed way of seeing.

The role of acquired similarity relations also shows clearly in the history of science. Scientists solve puzzles by modeling them on previous puzzle-solutions, often with only minimal recourse to symbolic generalizations. Galileo found that a ball rolling down an incline acquires just enough velocity to return it to the same vertical height on a second incline of any slope, and he learned to see that experimental situation as like the pendulum with a point-mass for a bob.

. . .

That example should begin to make clear what I mean by learning from problems to see situations as like each other, as subjects for the application of the same scientific law or law-sketch. Simultaneously it should show why I refer to the consequential knowledge of nature acquired while learning the similarity relationship and thereafter embodied in a way of viewing physical situations rather than in rules or laws. . . .  the verbal statement of the law, taken by itself, is virtually impotent. Present it to a contemporary student of physics, who knows the words and can do all these problems but now employs different means. Then imagine what the words, though all well known, can have said to a man who did not know even the problems. For him the generalization could begin to function only when he learned to recognize “actual descents” and “potential ascents” as ingredients of nature, and that is to learn something, prior to the law, about the situations that nature does and does not present. That sort of learning is not acquired by exclusively verbal means. Rather it comes as one is given words together with concrete examples of how they function in use; nature and words are learned together. To borrow once more Michael Polanyi’s useful phrase, what results from this process is “tacit knowledge” which is learned by doing science rather than by acquiring rules for doing it.

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In my opinion, getting a better grasp of what tacit knowledge is, what it effects, how to research it and how to employ it in design is the most interesting and explosively promising area of exploration in experience strategy and design.

In pursuit of this goal, I’ve been reading Suzanne Langer’s Philosophy in a New Key, whose central idea is that human beings use two different kinds of symbolic meaning to order our existences, and James Spradley’s  The Ethnographic Interview which teaches methods for learning about and analyzing (at least some of) these symbolic meanings. Very exciting stuff.

James Spradley’s fantastic book The Ethnographic Interview identifies four different roles a research participant can play, and each implies a different kind of relationship between researcher and participant, and a different conception of what the participant is:

• Informant – In ethnography, a participant is related to as an informant. Informants are native speakers, “engaged by the ethnographer to speak in their own language or dialect”, providing “a model for the ethnographer to imitate” so that “the ethnographer can learn to use the native language in the way informants do.” The ethnographer learns as much about the informant’s world as possible, in the terms — linguistic terms — of the informant. The informant is related to as a teacher.
• Subject – Subjects are participants in social science research, used to test hypotheses. “Investigators are not primarily interested in discovering the cultural knowledge of the subjects; they seek to confirm or disconfirm a specific hypothesis by studying the subject’s responses. Work with subjects begins with preconceived ideas; work with informants begins with a naive ignorance. Subjects do not define what it is important for the investigator to find out; informants do.”
• Respondent – A respondent is any person who responds to a survey questionnaire or to queries presented by an investigator. “Survey research with respondents almost always employs the language of the social scientist. The questions arise out of the social scientist’s culture. Ethnographic research, on the other hand, depends more fully on the language of the informant. The questions arise out of the informant’s culture.”
• Actor – “An actor is someone who becomes the object of observation in a natural setting.” In ethnographic research, participants are also often observed but the participant is still related to primarily as an informant, indicating through language, in his own terms, the significance of his actions, to give (to use Clifford Geertz’s term) “thickness” to the description of what is actually going on. As with subjects and respondents, when participants are related to as actors, the terms of the description are those of the researcher, not of the participant.

My takeaway from this is that while customers (or any other kind of experience participant) might eventually being regarded as subjects, actors or respondents later in the design process or after it, if the goal is to really understand and to form an authentic relationship, at the beginning customers must be related to as informants. This is why early interviews are semi-structured or unstructured conversations rather than structured in-person questionnaires. Once customers are understood as informants, the hypotheses a researcher tests on them (as subjects of, for instance, a split/multivariant test) will be more relevant, the answers they provide to formatted, statistically-analyzable questions (as respondents to surveys) will have more context, and their observable  behaviors (as actors observed in site analytics) will be more meaningful. The insights on hidden “subjective” motivations can complement the objective data to help the organization avoid superficial misinterpretations of the kind people make of strangers with whom one has never spoken, and instead to gain a much more complete and human understanding of the people with whom the organization is seeking to cultivate relationships.

It’s not a matter of qualitative vs quantitative; it’s a matter of recognizing the relationship between insight and data.