Don Norman has a provocative article on his site about ethnography and design research. See “Technology First, Needs Last“. He gets right to the point, summarizing his basic premise in the first sentence:

I’ve come to a disconcerting conclusion: design research is great when it comes to improving existing product categories but essentially useless when it comes to new, innovative breakthroughs.

He goes on:

Myth: Use ethnographic observational studies to discover hidden, unmet needs. To achieve major conceptual breakthroughs, we should do ethnographic field study to understand the hidden unmet needs of our potential customers. Right or wrong? It all sounds logical: study people. Discover hidden, unmet needs. Fulfill those needs, and leap ahead of the competition, producing yet another wondrous advance.


But the real question is how much all this [design research] helps products? Very little. In fact, let me try to be even more provocative: although the deep and rich study of people’s lives is useful for incremental innovation, history shows that this is not how the brilliant, earth-shattering, revolutionary innovations come about.

He claims to have done some kind of investigation to arrive at this opinion:

I reached this conclusion through examination of a range of product innovations, most especially looking at those major conceptual breakthroughs that have had huge impact upon society as well as the more common, mundane small, continual improvements. Call one conceptual breakthrough, the other incremental. Although we would prefer to believe that conceptual breakthroughs occur because of a detailed consideration of human needs, especially fundamental but unspoken hidden needs so beloved by the design research community, the fact is that it simply doesn’t happen. New conceptual breakthroughs are invariably driven by the development of new technologies

Interestingly enough, I had just finished reading an article in the Harvard Business Review called “The Innovator’s DNA” (Dec 2009) by Jeff Dyer, Hal Gregersen, and Clayton Christensen. After extensive research of top executives, the authors identify five key qualities that separate innovative leaders from the non-so-innovative leaders: associating, questioning, experimenting, and networking, and observing. Regarding the latter—observing—Scott Cook, founder of Intuit, has this to say:

Often the surprises that lead to new business ideas come from watching other people work and live their lives.

A.G. Lafley, former CEO of Proctor and Gamble, is generally seen as a leading innovator amongst executives. He writes about how direct observation of customer behavior has lead to greater innovation at P&G in his book The Game Changer:

P&G spends more time living with people in their homes, shopping with them in stores, and being part of their lives. This total immersion leads to richer consumer insights, which helps identify innovation opportunities that are often missed by traditional research.

You’ve probably heard short sound bites like this before. For sure, such snippets alone don’t disprove Norman’s thesis. But if you look around a little more, you’ll find other contradictory evidence.

For instance, Indi Young, author of Mental Models, also has a recent posting that is somewhat related to this topic. See “Support Intentions, Not Existing Workflows”. Indi concludes:

When you spend time with people who might become someone you produce a service or a product for, concentrate on finding these underlying intentions. Deliberately jump past the details of how they execute something currently and spend time instead asking them what’s behind this step. What are they trying to accomplish besides the step itself? Frequently, people haven’t really thought past the steps, and your conversation turns into more of a psychotherapy session, helping the person work through the underlying issues and describe them for you. When this happens, you know you’re on the right track. With the results of several conversations like this, you can guide your organization into areas you hadn’t previously considered or been consciously aware of. This direction leads to services and products that support what a person really intends to do and makes their life smoother. And that is a very attractive proposition to most of us.

More formally, consider the results of the study “Ideation for product innovation: What are the best methods?” by Robert Cooper and Scott Edgett (2008, Stage-Gate). Ethnography emerged as the #1 method to foster innovation and creativity in organizations. The authors write:

Ethnography is ranked #1 of all methods among users, with a strong effectiveness score of 6.8 out of 10. (For comparison, the average effectiveness score for all 18 methods is 5.6, with a standard deviation of 0.73; so a score of 6.8 is, relatively speaking, “strong.”) The method provides perhaps the greatest insights and depth of knowledge into users’ unmet and unarticulated needs, applications, and problems of all the ideation approaches we studied, according to users.

Finally, the work of Sarah Miller Caldicott really flies in the face of what Norman is trying to say. She is the author of the book  Innovate Like Edison: The Five-Step System for Breakthrough Business Success, co-authored with Michael J. Gelb (Dutton Penguin, 2007), as well as the great-grandniece of Thomas Edison. She did a first-ever analysis of hundreds of thousands of documents in Edison’s collection in Menlo Park, NJ over the course of an intense three-year study.

Caldicott’s recent white paper for Strategyn is directly relevant to the debate of the effectiveness of needs versus technology: “Ideas first or needs-first: What would Edison say?”. In it she writes:

Edison learned a valuable lesson with this failure. He realized that his approach to innovation was somehow faulty. He began reshaping his efforts by redefining what success would need to look like for one of his inventions, and he decided that success was now going to be a function of utility; that is, a function of the ability to satisfy a customer need or a marketplace need. He said, “Anything that won’t sell, I don’t want to invent. Its sale is proof of utility, and utility is success.


He recognized that simply bringing hundreds of ideas to market would result in many failures. Being a man who was focused on efficiency and success, failure was an unattractive proposition. Edison realized that by understanding customer needs first, he could invent useful products more efficiently than he could otherwise.

It would also appear that Edison did a type of ethnographic observation in inventing the light bulb:

Edison’s trained teams visited people in their homes and watched how they used their current lighting products— kerosene, whale oil, and gas. The goal was to figure out what consumption chain jobs to consider and how to address them. This process enabled Edison to gain insight into all these critical jobs. From there, Edison worked with numerous employee teams to develop products that would address the consumption chain jobs. Products like the electric circuit, the on-off wall switch, the fuse box, electric meters, and dynamos that could power the entire lighting system were all invented. Edison received over 40 patents for these inventions. Yes, Edison invented the lightbulb, but within three years he also invented the entire system of electrical power distribution, along with the world’s first central power station. That’s fast, even by modern standards.

Here again, Edison’s needs-first approach enabled him to identify a large market and guided his research and development efforts. He was able to come up with a revolutionary lighting solution and address all the consumption chain jobs required to bring this solution to market. Because he kept his focus on exactly what customers needed, he could hone his product development timetable and production timetable very efficiently.

Caldicott concludes:

If your company wants to take a page out of Edison’s innovation playbook, it should start by discarding ideas-first thinking and adopt an effective needs-first approach to innovation. This crucial lesson enabled Edison to pioneer the creation of six industries and lead the United States to a century of prosperity—a feat that has not been duplicated since.

Compare this to Norman’s contention about how Edison worked:

Edison launched his first phonograph company within months of his invention: he never questioned the need.

Overall, it seems other examinations of innovation have proven the exact opposite of what Norman claims in his article. There is indeed a wealth of evidence that people’s needs can and should precede technology. And frankly, Norman’s “examination” seems more of the back-of-the-napkin type with several errors.

But does Norman have a point? Well, I guess it’s always good for us design researchers to step back and question our own practices. But I think there are two key arguments that speak against Norman’s main point:

  • First, there much more evidence from much more rigorous studies to suggest that ethnographic techniques and understanding people’s needs has preceded technical invention in the past.
  • Second, Norman seems to forget that there are different types of innovation, not just product innovation. There’s also process innovation, organizational innovation, business model innovation, and strategy innovation. The equation isn’t as simple as: research needs, then develop technologies (or vice-versa), as Norman suggests.

I’d actually argue that it’s better to understand customer needs before creating the strategy that allows technologists to start working on a given technology or not. That is: needs > strategy > technology. So needs do precede technology.

Everett Rogers, author of Diffusions of Innovations—the “bible” in innovation diffusion literature—also indicates that needs identification precedes the entire innovation process. In Chapter 4, “The Generation of Innovation,” he outlines six phases, the first of which is “recognizing a problem or need.” He writes:

The innovation-development process often begins with recognition of a problem or need, which stimulates research and development activities designed to create an innovation to solve the problem or need. (p. 137)

And later, in the discussion on “compatibility” as a factor of adoption rates, he writes:

One indication of the compatibility of an innovation is the degree to which it meets a felt need. Change agents seek to determine the needs of their clients and then to recommend innovations that fulfill these needs. Determining felt needs is not a simple matter, however. Change agents must have a high degree of empathy and rapport with their clients in order to assess their needs accurately. Informal probing in interpersonal contacts with individual clients, client advisory committees to change agencies, and surveys of clients are sometimes used to determine needs for innovations. (p. 146)

So innovations that are conceived around user needs from the very beginning (i.e., BEFORE technology) have a higher chance of adoption and therefore a higher chance of success. Norman alludes to Roger’s work saying:

The path of diffusion of innovation has been well studied, well documented. Most radical innovations fail. Those that succeed can take decades before they are successful.

But that’s the point: innovators generally want to increase their chances of succeeding from the beginning, even if only marginally. Needs identification up front helps with that, at least according to Rogers (among others).

Perhaps a quote from Scott Berkun, author of The Myths of Innovation, can shed some light onto this whole debate. He says:

Successful innovators spend as much time understanding the people they are designing for, their beliefs, feelings, values, and needs, as they do the technologies they’re using to build innovations, and the book offers the fundamentals on how to do this. So, the superiority of your mousetrap is sure nice in an ivory-tower setting, but if people—customers—can’t see why it’s superior, then the superiority is just your opinion. And sadly, I don’t know anyone who has made millions solely on the superiority of their own opinion.

Ultimately, I believe it’s not an either-or question, nor is it a first-last question. It’s a question of balance. This is what the HBR article “The Innovators DNA” suggests as well as detailed studies like those of Sarah Miller Caldicott. But since technology already gets so much attention, Norman’s basic claim “technology first, needs last” is in the end a more harmful perspective than helpful.

via Steve Baty, I came across a post by Will Evans called Design Ethnography & Mood Maps. He touches on two of my favorite topics at the moment: ethnography and emotions in design. In particular, Will introduces the concepts of Mood Maps to record user emotions. In a nutshell, mood maps are about mapping the emotional states people have to phases of a process.

This is similar to what I recommend in what I call the Information Search Experience (ISX), which I presented at the IA Summit in Austin TX in 2004. See my presentation: Information Search Experience: Emotions in Information Seeking. Of course, I was focused on information seeking in my model, but the principle is the similar: uncover the different states of emotions people have and map them back to phases of a given process. Here are two publications where I also present this idea:

  • I’m Feeling Lucky: The Role of Emotions in Seeking Information on the Web,” Journal of the American Society for Information Science and Technology, 57(6), 813-818 (April 2006).
  • Feeling Lucky? Emotions and Information Seeking,” interactions, v. XI.5 (September-October 2004).

I also present this very briefly in Designing Web Navigation. Here’s the excerpt from the end of Chapter 2:

Emotions in Information Seeking
Information seeking on the web, in particular, is an emotional experience. Unfortunately, confusion and uncertainty tend to dominate feelings of enthusiasm and optimism. For many web surfers, the joy of discovery and pride of learning can be rare feelings against a backdrop of frustration and a sense of being overwhelmed.
When discussing the emotions users have while finding information on the web, it is critical to look at common situations and states users are in. Here is where patterns in basic human information-seeking behaviors give rise to a framework for both evaluating and designing web-based search and navigation systems.

Information Search Process
A holistic approach to explaining the user’s experience in information seeking, the Information Search Process (ISP) is a model of searching for information with a difference: it takes emotions into account. Developed by Carol Kuhlthau, a professor at Rutgers University, the ISP has six stages:

  • Initiation – The user becomes conscious of a gap in knowledge. Feelings of uncertainty and apprehension are common, and the main task is to recognize a need for information.
  • Selection – Uncertainty often gives way to feelings of optimism and a readiness to begin searching. The task is to identify and select the topic to be investigated. Thoughts are forward-looking and attempt to predict an outcome.
  • Exploration – Feelings of uncertainty, confusion, and doubt return. A general inability to precisely express an information need commonly results in an awkward interaction with the search system.
  • Formulation – Rising confidence and decreasing uncertainty mark a turning point in the process. Forming a focus becomes the chief task as thoughts become clearer.
  • Collection – Interaction with the information system is most effective and efficient. Decisions about the scope and focus of the topic have been made and a sense of direction sets in. Confidence continues to increase.
  • Presentation – The goal now is to complete the search and fulfill the information need. A sense of relief is common, as well as satisfaction or dissatisfaction (in the case of a negative outcome). Thoughts center on synthesizing and internalizing what was learned.

Kuhlthau also observed a “dip” in confidence often seen after a seeker began looking for information and started to encounter overwhelming, perhaps conflicting information. This contradicts the previous assumption that confidence steadily increases as more information is found. A seeker “in the dip” can experience uncertainty, confusion, and even anxiety until a focus is formed or a search is broken off.

The existence of that dip suggests a gap between users’ natural information use and information system design. Acquiring more information in initial stages (particularly in Exploration) increases rather than decreases uncertainty. In terms of emotions, searching for information is a discontinuous endeavor with highs and low of confidence and certainty.

Tailoring the ISP
In an attempt to avoid the dip, you can use Kuhlthau’s theoretical model as the framework for navigation design, tailoring an ISP to reflect the actions, thoughts, and feelings for your site visitors. The steps are:

  1. Segment users and create profiles. An ISP only applies to a particular target group.
  2. Identify the information seeking stages and user goals for each. The established phases will serve as a starting point, but must be adapted.
  3. Record the typical feelings, thoughts, and actions at each stage.
  4. Map stakeholder goals to each stage. What is your organization trying to achieve and how does it fit in with the natural navigation process of users?
  5. Derive features and requirements for the site that map to each phase in the seeking process

This is best summarized in a large table. The columns are labeled Actions, Thoughts, Feelings, Features, and Business Goals. The rows are the stages in your tailored ISP.

Tricia Ryan, an instructional designer at Laureate Higher Education Group, Inc. where she develops courses for Walden University, picked up my Commercial Ethnography presentation from the Euro IA Summit in Amsterdam and used it for a class. Here’s the online synched slideshow of my presentation.

Those of you who know me will recognize that that’s not my voice. Someone at Walden U. wrote and spoke the text in the video above. Kinda weird to see my slides and have someone else talk to them. But, whatever–I’m just happy someone else is interested in the subject.

Growth Leaders and Personas

8 September 2008

I came across an article in the Sloan Management Review from July 2008 entitled “In Search of Growth Leaders” by Sean D. Carr, Jeanne M. Liedtka, Robert Rosen, and Robert E. Wiltbank. The authors discuss key qualitities of growth leaders, or managers that produce above-average organic growth figures.

There are several factors that signal a so-called growth leader, such as the type of experience they have and how they manage risk. The thing that caught my eye was that growth leaders also tend to see customers as people rather than as data. The authors explain–

Success was based more often on thoughtful exploration of customers’ needs than on dry market data. The managers in our study personally sought detailed knowledge about individual customers, instead of just seeing them as data in market-research reports.

One manager told us he was not “customer-centric,” he was “Cynthia-centric.” Cynthia, he explained, was a single mother who had ordered his company’s personalized candies to be delivered for her son’s birthday party. Sadly, the product arrived a day late, and afterward, Cynthia, who had barely been able to afford the gift, called him in tears to express her disappointment. She became his constant reminder of what it means to be a day late in his business.

Direct knowledge about customers also helped the managers see what was most important to the customers in terms of products and services. One manager with a home-electronics retailer went directly to the sales floor to find ways to serve small-business customers better. He talked to the customers himself, asking them about their businesses. When he met real-estate agents, for example, he learned how much time they spent in their cars. So, even though they had come to the store to buy, say, a personal computer, he steered them toward other products that could improve their efficiency on the road, such as a GPS navigational device or a cellphone-speaker system.

This frequent in-store dialogue taught him and other salespeople to see previously unidentified sales opportunities. Their experience, in turn, led to a companywide initiative to teach employees to acquire customer insights through interactions in stores.

That sounds very similar to field studies, personas, and the like to me.

Overall, it seems that the rhetoric in the business community is starting to mirror what folks in the user experience community have been saying for a long time. Building empathy for customers, for instance, is something that Adapative Path talks at length about in Subject To Change. (See my review of that book in a previous post).

And of course being reminded of Cynthia’s needs in the above quoted passage is the job of personas. I just wish people in the business community would start using the same terms and say things like ‘personas’ if that’s what they mean. I also wish they’d start calling on UX people more directly to help solve their business problems.


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