Editor’s Note:

Improving healthcare is a wicked problem [1]. Healthcare’s many stakeholders can’t agree on a solution, because they don’t agree on the problem. They come to the discussion from different points of view, with different frames. Wicked problems can be “solved” only by reframing, by providing a new way of understanding the problem that stakeholders can share [1]. This article describes a growing trend: framing health in terms of well-being and broadening healthcare to include self-management. Self-management reframes patients as designers, an example of a shift also occurring in design practice—reframing users as designers. The article concludes with thoughts on what these changes may mean when designing for health.

—Hugh Dubberly

What is health?
From the point of view of today’s healthcare system, health is largely about minimizing illness. The healthcare system has evolved primarily for treating acute conditions. Despite flaws (including high cost and limited access), the system does a good job of curing infections, repairing injuries, and responding to emergencies. The healthcare system does less well in treating chronic conditions. It provides resources for managing aspects of systemic problems, such as statins for cholesterol, ARBs and ACE inhibitors for high blood pressure, and insulins for diabetes; but in most cases that means merely slowing the rate of decline. Yet health is “not merely the absence of disease or infirmity.” In contrast, the World Health Organization defines health as “a state of complete physical, mental and social well-being” [2].

Health as well-being depends not just on healthcare but also on employer practices [3], social policies [4], and self-management, the main subject of this article. Of course, health is “not the objective of living”; health is a resource contributing to the quality of our everyday living [5].

Traditional healthcare focuses on treating acute problems.

Traditional health management applies the tools of acute care to stabilizing chronic conditions.

Health is more than eliminating or managing disease; and its requirements extend beyond traditional healthcare.

Health is a means to higher goals — “a resource for everyday life, not the objective of living” — World Health Organization (WHO)

Identifying the Frame of Healthcare

The way we usually think about health today is bound up in the language of our healthcare system. We call individuals “patients.” We call physicians healthcare “professionals” (HCPs). Professionals “care for” patients—by observing symptoms, diagnosing diseases, and proposing therapies. Their proposals are not just suggestions; they are prescriptions or literally “physician orders.” Patients who don’t take their medicine are not “in compliance.”

In the relationship between HCPs and patients, HCPs dominate. HCPs do whatever is necessary, with patients playing a relatively passive role [6]. In some ways, the system reduces patients to the status of children—simply receiving treatment. The power imbalance may grow out of illness. When we feel ill, we may seek comfort or aid from others. When we feel afraid, we may hand responsibility to a confident expert. In a medical emergency, letting a physician take charge is probably the surest way to stabilize things and return to normal.

A heart attack requires quick action; it’s not the best time for discussion. The time for discussion is before a heart attack occurs—and after—finding ways to avoid the heart attack in the first place or at least avoid another one.

Yet the language of acute conditions (the frame of healthcare) is ill suited to managing chronic conditions or preventing disease (often framed as behavior change). The American Heart Association reports, “The No.1 problem in treating illness today is patients’ failure to take prescription medications” [7]. Patient behavior does not change on a physician’s orders. To expect behavior change on command is to misunderstand human nature. To blame patients (who respond to the very present pressures of busy lives rather than less tangible long-term risks) is unhelpful, unkind, and perhaps unethical. (Blaming patients—or clients—suggests that one doesn’t understand or respect their context and constraints and doesn’t share responsibility for outcomes.) According to social epidemiologist Leonard Syme, “We need to pay attention to the things that people care about, and stop being such experts about our risk factors” [8].

The language of acute conditions (the frame of healthcare) limits what we imagine. Discussions about improving healthcare focus mainly on improving assessment of patient conditions, improving HCP education, and improving therapies—since surviving a crisis depends mainly on the patient’s condition, the HCP’s skill, and the medical technology at hand.

We debate how to have more of the same rather than something new. We debate how to be more efficient and reduce cost rather than radically increase effectiveness and eliminate causes. Our goals remain modest. We seek little more than increased patient compliance and more knowledgeable consumers. We can do better.

The language of acute conditions (the frame of healthcare) is ill suited to achieving well-being (the frame of self-management). By its very definition, healthcare almost assumes both a present problem and an expert who intervenes. In that sense, well-being lies outside the scope of our current healthcare system. Wellness is more than absence of illness: It’s is a way of living. Well-being requires its own language, its own frame.

Self-management does not replace healthcare; rather it acknowledges the limits of what healthcare can accomplish and seeks structures that go beyond those limits.

Imagining the Frame of Self-management

Foucault attributes “the birth of the clinic” to the Enlightenment, when early versions of the current healthcare paradigm displaced a medieval paradigm [9]. The language of health had a beginning; it was invented. And like other languages, it can evolve; we can reinvent it [10].

Imagine reframing health so that it includes self-management.

Self-management suggests a fundamental shift of responsibility. Patients reclaim their role as adults responsible for their own well-being. The relationship between HCP and patient becomes more symmetric (at least outside of medical emergencies). Issuing orders gives way to discussing and collaborating. HCPs become coaches and assistants, shifting their stance from dispensing knowledge to learning from patients. As Melanie Swan reports, “a collaborative co-care model is starting to evolve for healthcare delivery…the patient’s role may become one of active participant, information sharer, peer leader and self-tracker, while the physician’s role may become one of care consultant, co-creator and health collaborator” [11].

In the parlance of “design for service,” HCPs begin to think of themselves as “co-producing” health and well-being with their patients. Imagining healthcare as a designed service is another way to reframe it. Kaiser and the Mayo Clinic employ design innovation teams; UPMC has teamed with CMU design students to reimagine patient experiences [12].

Self-management also suggests setting goals and measuring progress—the basis for managing and improving quality. Individuals decide what’s important to them, what well-being means, what they want to work on. Individuals record their actions; for example, meals eaten, exercise completed, medications taken, hours slept, time spent working or playing or commuting, and perhaps even interactions with others and media consumed (e.g., music played). Individuals also measure results; for example, hard values such as their weight, pulse, blood pressure, cholesterol, and blood glucose; and softer values such as energy, stress, pain, happiness, or mood.

Then they repeat the cycle. If they’ve made progress toward their goals, they may continue the same course of action or even speed up. If they’re diverging from their goals, they may change course. Individuals find and maintain a “healthy balance,” one that’s comfortable for them. They take an active role in their body’s process of homeostasis—including physical, emotional, and social dimensions.

This process is directed trial and error—experimenting, something like the Shewhart-Deming PDCA cycle, a simple application of the scientific method, a version of the design process.

Imagine patients as designers—conducting billions of tiny self-experiments, prototyping their own well-being. That’s the essence of a self-management approach to health [13].

Far-fetched? An impossible change?

Emerging Trends Support Self-management

Self-management has always existed. Americans spend billions of dollars each year on health foods and diet programs. A doctor reported, “20% to 30% or my patients are into some type of supplements or ‘nutraceuticals’” [14]. Deloitte reported that 20 percent of consumers used alternative therapies [15]. Kaiser reported that 33 percent of consumers had “relied on home remedies or over-the-counter drugs instead of seeing a doctor” in the past 12 months because of cost concerns [16].

Several factors have begun the process of reframing health as self-management. The U.S. healthcare system is out of control; managing costs requires a focus on what the medical profession calls outcomes. The public has a growing awareness that well-being is more than healthcare. The fitness and exercise movement, elements of the DIY (Do-It-Yourself) movement like the Quantified Self group, behavior-change programs like Weight Watchers, and more progressive programs for managing chronic conditions like the Stanford Cardiac Rehabilitation Program [17], all point the way to self-management.

The shift to self-management is also supported by changes in the Internet and related technologies. Melanie Swan reported, “Individuals are becoming more engaged in a variety of self-testing and self-management of conditions, symptoms, genomics and blood biomarkers, behaviors and personal environmental factors. Individuals could dramatically expand their use of web-based tools, devices and health-based social networking platforms as their awareness increases, costs drop, financial incentives arise and automated tools proliferate” [11]. The Internet and related technologies are also making it easier for people to have conversations that support self-management.

Imagine online social-network applications creating communities of support around diseases, chronic conditions, and fitness. Of course, health-based social networks have already begun; what’s surprising is just how many there are [18]. Other social network applications serve broader audiences while also offering health-related components [19].

Social networks are dynamic; they can generate collective action. In addition to individuals experimenting on themselves, groups of people with similar conditions—people joined together through online social networks—may sponsor or conduct research. Already, online social networks have begun to affect clinical trials, helping researchers find participants and helping participants compare outcomes.

Imagine several sensors monitoring each person. Already nearly continuous monitors are available for pulse, steps walked, and blood glucose, at relatively low cost. More types are on the way. Many of these sensors send data to the Internet, either directly or through mobile devices or desktop computers, which forward the data. Withings sells a Wifi Body Scale that sends your weight to Twitter each time you weigh yourself [20].

The sensor revolution will change the way we view data and ourselves. Children born in the next decade may look back across a lifetime of data. We won’t be able to ignore how we’re doing; we’ll always know. Continuous feedback may provide micro-motivation—the ongoing awareness we need to live healthier lives.

Imagine personal-health dashboards, applications for tracking your sensor data based on the Web or mobile phones. (Your mobile phone may become a server at the hub of your body-area network.) Health dashboards will provide trend graphs, comparisons with goals and norms, and alerts when things change suddenly or move toward unsafe levels. Health dashboards will be just one of several dashboards in our lives, including those for finance like mint.com, home networks like Pie Digital, and home energy management like the demo Intel showed at CES 2010. In a way, social-network sites, like Facebook, are also dashboards—for friends and message management. Health-based social networks and personal health dashboards seem likely to combine and reinforce one another.

Imagine big data-mining software learning from all the data stored in health dashboards. (Big data is computer-industry jargon for huge databases of information generated on the Web; data mining is jargon for the process of correlating data to generate value. Google’s page-rank algorithm, which bases relevance on counting links to a Web page, is a classic example of big data mining.)

Data that individuals collect will establish a baseline for comparing future measurements. Identifying personal norms is important, especially when we’re not average. For some, 98.6 may indicate a fever, especially as normal body temperature decreases with age. Collecting data will also enable individuals to compare themselves to others—to the entire population or to those sharing similar characteristics, such as age, sex, height, weight, conditions, genes, environment, and even behavior.

Ian Shadforth points out that once health data collecting begins in earnest, we can quickly generate population-wide norms and norms for many sub-groups. By collecting data on a range of age groups simultaneously, we may need just a few years to generate a picture of what’s “normal” across a lifetime [21].

The growth of online health-based social networks, bio-medical sensors, personal health dashboards, and health-focused big data mining applications will not of themselves or even in combination force a shift to self-management. They simply make measurement and tracking a lot easier. They lower the bio-cost of self-management. And they make visible—perhaps even cool—the practice of measurement and tracking. In this way, technology may set off a process of bootstrapping, which can lead to the broader changes we describe.

Parallels with Changes in Design Practice

Reframing health as self-management parallels similar trends in education, where we increasingly recognize that students manage (or design) their own learning, and design practice, where we increasingly recognize that users manage (or design) their own experiences. Perhaps these changes are part of larger trends, the democratizing of professionalism and the shift from a mechanical-object ethos to an organic-systems ethos [22].

Good teachers do more than pass on facts; they help students learn how to learn, so that teaching becomes what Paulo Freire calls the “practice of freedom,” a means to deal critically with one’s living and discover how to transform the world [23].

Freire also insisted on symmetry in the relation between teacher and student—or at least “deep reciprocity.” (Good teachers learn from their students.) Freire’s position echoes Horst Rittel’s assertion that the participants in a design project (all the stakeholders including professional designers) share a “symmetry of ignorance” (or knowledge) regarding the problem. Rittel’s point is that design problems are always “owned” by someone [1]. Design problems have no objective definition; their definition reflects the owner’s point of view. Here, Rittel challenged the orthodoxy of professional problem solving and opened the door to the design process, inviting users and other stakeholders to step inside.

The 1990s saw the flowering of user-centered design. Ethnography and other forms of research about users became standard practice in software design.

Some professional designers began to see their work as engaging stakeholders in a discussion. Liz Sanders and others have begun to advocate for participative design and co-creation—not just designing for users, but designing with them. Co-production has become a watchword in the emerging field of service design (or design for service), as designers recognize the integral role of “consumers” in producing services.

Shelley Evenson and others talk about creating conditions in which users become designers—creating spaces in which people can learn and grow. That means professional designers become meta-designers, designing open-ended systems, languages, platforms, APIs, construction kits, or kits of parts, which others configure or re-configure to their own ends. Wooden blocks, Legos, and train sets are classic examples, kits of parts with which we may play—and design. Herman-Miller’s Action Office is a kit of parts designed for others to design offices. (Sadly, it gives little design control to the office’s occupants.) Programming languages and code libraries like Java and Flash are kits of parts for others to design software. (How much design control can the resulting applications give end-users?) Even simple services like restaurants offer a menu of choices from which patrons may design a dish or a meal. Starbucks and Mini-Cooper offer a dizzying array of choices from which customers can design.

As with health (and education), reframing design will not be easy. For designers who have spent years perfecting their craft and who delight in making beautiful form, the notion of user as designer and designer as facilitator can seem frighteningly foreign. Yet this transition offers the opportunity to make the world richer—to create more options for everyone, including professional designers (and HCPs and teachers).

As the era of mass production ends, design practice must adapt to the new era of information. In order to create value, designers will increasingly have to frame their work in new ways.

Design for Health

As healthcare becomes a larger part of the economy and as healthcare practice and research biology both converge with computing, opportunities to design software and services for health abound. We should keep in mind that health is a means to a goal—one of the things that supports the quality of our everyday living.

Designers should ask their clients: How should we frame health in this engagement? Are we bound to the frame of traditional healthcare? Or can we apply a broader frame, such as self-management?

Designers should also ask themselves and their colleagues: How should we frame design in this engagement? Are we designing artifacts or services? Where might we create opportunities for users to design?

If the user is both designer and implementer (combining first- and second-order agency), what is possible? How can we help users act? Track results? Set goals? How do we “scaffold” tiny self-experiments, learning, and sharing?

Designers should also help users discover and understand both the short-term relationship between action and result (incremental changes that the individual can actually make) and the long-term consequences (big outcomes that matter over time).

Creating opportunities for users to design requires not only giving them responsibility for means and goals but also enabling conversations for:

• overcoming the barriers (bio-cost) of making incremental change through…
• making results, trends, and projections visible and…
• providing emotional support (such as family and community engagement) to maintain…
• higher-level strategic views of the entire process, to maintain goals and momentum, that in turn…
• create learning across time and circumstances that can be shared…
• improving the system for others

We’re on the brink of something new—the intersection of health and computing, design and service. What will we invent as these processes converge? What happens when health self-management meets meta-design?

About the Authors

Hugh Dubberly manages a consultancy focused on making services and software easier to use through interaction design and information design. As vice president, he was responsible for design and production of Netscape’s Web services. For 10 years he was at Apple, where he managed graphic design and corporate identity and co-created the Knowledge Navigator series of videos. Dubberly also founded an interactive media department at Art Center and has taught at CMU, IIT/ID, San Jose State, and Stanford.

Rajiv Mehta consults on exploring and commercializing radical innovation, driving ideas from concept to market. His work has ranged from photography to lasers, computer vision to wireless, and health, at companies from Adobe and Apple to Symbol Technologies and Zume Life. He studied at Columbia, Stanford and Princeton.

Shelley Evenson recently joined Microsoft’s FUSE (Future Social Experience) Labs as a principal in user experience design. Before FUSE, Shelley was an Associate Professor teaching interaction design at Carnegie Mellon University. Shelley taught courses in designing conceptual models, interaction, and service design, and collaborated in projects with colleagues from the Tepper School of Business and the Human Computer Interaction Institute. Shelley jumpstarted the study of service design in the U.S. designing courses, energizing students, and hosting the first international conference on service design-Emergence. Before joining the faculty at Carnegie Mellon University, Shelley worked for more than 25 years in multidisciplinary consulting practices, working with on a wide variety of design and development projects.

Paul Pangaro is the CTO at CyberneticLifestyles.com in New York City, most recently working for clients in consumer internet and mobile computing. He has designed a search engine for poetry, interactive information strategies for medical services, and a framework of ontogenetic sharing for social networking. Paul has lectured at London’s Bartlett School of Architecture, São Paulo’s Instituto Itaú Cultural, École Nationale Supérieure des Mines de Paris, and MIT’s Media Lab and Sloan School of Management on design process, conversation theory applied to interaction design, and the cybernetics of innovation. He was CTO of several startups, including Idealab’s Snap.com, and was senior director and distinguished market strategist at Sun Microsystems. Paul has taught at Stanford University and teaches in the MFA program on interaction design at the School of Visual Arts, New York City.

Continuous Cycle of Health Self-management.

Self-arrangement augmented by conversation with others, sensors, and services.

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We are surrounded by things that have been designed—from the utensils we eat with, to the vehicles that transport us, to the machines we interact with. We use and experience designed artifacts everyday. Yet most people think of designers as only having applied the surface treatment to a thing conceived by someone else. Eli Blevis created an illustration to emphasize the gulf between the general public’s notion of design and designer’s views of design (Blevis et al., 2006) (see Figure 19.1).

Figure 19.1 – A caricature of the popular conception of design vs. all other concepts.

Ultimately, everything that has not come from nature has been designed—it just may not have been consciously designed. As early as 1938, Moholy-Nagy described design as more than just facade making. He suggested that design was “a complex and intricate task … and the integration of technological, social and economic requirements, biological necessities, and the psychophysical effects of materials, shape, color, volume, and space’’ (Moholy-Nagy, 1938). Most design definitions also include planning as a critical element. Janet Murray, author of Hamlet on the Holodeck, describes the designer’s role as making ‘‘something new that fits in with what already exists or changes it in a positive way.’’ This description of design is consistent with Herbert Simon’s seminal work in which he says, ‘‘Everyone designs who devises courses of action aimed at changing existing situations into preferred ones’’ (Simon, 1996). Marty Neumeier simplifies further by suggesting that ‘‘design is change’’ (Neumeier, 2009). Of course, change (or the process of change) can be changed. That is, change can be designed; thus, design can be designed.

Service

There are many definitions of service in the literature. On one hand, services are viewed as performances: choreographed interactions manufactured at the point of delivery that form a process and coproduce value, utility, satisfaction, and delight in response to human needs (Zeithaml and Bitner, 1996; Evenson, 2005; Engine, 2006). On the other hand, activities or events in a service process are described as forming a perceivable set or ‘‘product’’ through interaction with designed elements or resources from representatives of the service organization, the customer, and any mediating technology.

For purposes of this discussion, we put forth the definition described by Jean Gadrey and based on Peter Hill’s 1977 work (Gadrey, 2002): ‘‘a service may be defined as a change in the conditions of a person or a good belonging to some economic unit, which is brought about as the result of the activity of some other economic unit with the prior agreement of the former person or economic unit.’’ Gadrey goes on to explain that a service should first be considered a process, and illustrates service as a triangle that includes three primary elements: service provider, customer/client/user, and transformation of a reality (Figure 19.2).

Figure 19.2 – The service triangle as illustrated and defined by Jean Gadrey. (2002)

Are services in support of ‘‘changes in the conditions of a person’’ similar to changing existing situations into preferred ones? Are services change? Are people participating in the service designing as they cocreate the service? The concepts Gadrey presents with respect to service relations, interactions, operation, and activity are well suited for defining service as design.

We view designing for service as a meta activity: conceiving and iteratively planning and constructing a service system or architecture to deliver resources that choreograph an experience that others design. When a company provides the optimal mix it will have produced a resonating service system and delivers an experience advantage (Evenson, 2005).

Designing for service is a process that brings together skills, methods, and tools for intentionally creating and integrating (not accidentally discovering and falling into) systems for interaction with customers to create value for the customer, and, by differentiating providers, to create long-term relationships between providers and customers.

Figure 19.3 – A service as design triangle. After Gadrey. (1996A)

Experiences Matter

Our lives are shaped by—and emerge from—the experiences we have. How we are greeted when we enter a store shapes the experience that we will have while in the store. When Apple introduced the iPhone, they consciously designed the journey that their new phone customers would have—from learning about the features they would use on the phone in advance of sale of the phone, to making the activation (once a torturous event with most cell providers) a self- service affair that could be done at home with ease. Smart companies work hard to provide the appropriate resources for customers to have experiences that they value.

Pine and Gilmore (1999) suggest that we seek out experiences that fulfill our needs and satisfy our wants. Today (having satisfied many basic needs), people are looking for more (and more meaningful) experiences. Many people are willing to pay more for their coffee or their hotel stays if the brand reinforces their image of themselves. Consider the shift in just one generation’s experience. Many baby boomers grew up in small town America, purchasing through the Sears, Roebuck catalog. In that shopping experience, the catalog arrived and the customer poured over the pages to select just the right thing. The customer either called or mailed an order form back to Sears. Weeks later the purchase arrived and the customer was either pleased or not. If the customer was not pleased, there was a lot of work to be done to return the item and receive credit. Fast-forward to today: Nike offers customers the opportunity to design their own shoes (items that are notoriously hard to fit) online. Zappos also sells shoes online. From the get-go they understood the need for an experience that would exceed customer expectations (Taylor, 2008). They began by offering overnight delivery, which in part was made possible by the technical infrastructure they have in place. Customers report ordering shoes at 8 p.m. and having them arrive at 8 a.m. the following morning. Both examples contrast with the customer experience with Sears decades earlier. Customer expectations have changed dramatically, and if they want to be successful, organizations need to provide the resources for exceptional customer experience. Zappos and Nike are raising the standards for their competitors and for all online retailers.

But not only have expectations changed for online retail, expectations are changing in health care. In a recent McKinsey survey of more than 2000 patients with commercial insurance, ‘‘75% would consider switching hospitals to become better informed about treatments or if appointments were kept on time. If forced to choose between information and timeliness, 3 times as many patients said they valued information more’’ (Grote et al., 2007). Because there is so much more information available generally, people’s expectations have been raised to want better information, tailored for them personally.

People today also want experiences that support their values, whether it is their concern for the environment or their belief in natural foods. Perhaps this fulfillment behavior has gone too far (or at least lacks substance) when people with means can purchase ‘‘carbon offsets’’ to ease their guilt over behaviors that conflict with their personal value of not contributing to pollution. People are seeking meaningful experiences as part of a community as evidenced by the doubling in recent years of people who planned to volunteer on their vacations (Dalton, 2008).

Great experiences are leading to a demand for even better experiences. As expectations for service experiences rise—are the people participating or cocreating those experiences becoming more skilled at leveraging the resources for their experience and designing their service? If so, then what are the implications for designing-for-service experiences?

In designing-for-service experiences we must provide the opportunity for customers to have meaningful, compelling, and fulfilling experiences that address their needs and satisfy wants. We need to provide the resources for people to design, so that they can create their own experiences (Tempkin, 2008).

Given the current cultural, social, and economic contexts, the resources need to meet or exceed people’s expectations, and encourage participation so that customers become advocates for the brand. (In a sense, they invest in the brand, taking ownership and cocreating the brand itself.) The technology is now in place as a key differentiator in service delivery. What happens at Zappos today simply was not possible just a few years ago. They have raised the table stakes for all other companies.

Creating an Experience Advantage by Providing the Resources for Cocreation

Ganz and Meiren (2002) suggest a need for knowledge about social interaction activities. This is due to an intense awareness that service work is ‘‘people work,’’ and too little is known about the human aspect of both the provider and the client in service definition. The consideration of this human aspect is a key differentiator in the design of a service system. People-centered research can drive innovation.

Designing for service, from our perspective, assumes the participants are the starting point or lens for this exploration. This is essential because the service designer is providing the ‘‘clay’’ (or perhaps the potter’s wheel and kiln) for participants to design for themselves. Through the use of creative, human-centered and participatory methods, we model how the service could be performed or provided.

At the same time, service design identifies and integrates the means to provide a service with the desired qualities within the economic and strategic intent of an organization. Collaborators ‘‘visualize, express and choreograph what other people can’t see, envisage solutions that do not yet exist, observe and interpret needs and behaviors and transform them into possible service futures, and express and evaluate, in the language of experiences, the quality of design’’ (Service Design Network, 2005). As a discipline, service design should not be viewed in isolation, but as complement to service development, management, operations, and marketing (Service Design Network, 2005; Mager, 2002; Edvardsson et al., 2000).

In our approach to designing for service innovation, we integrate these activities across a service development process that includes exploratory, generative, and evaluative research that spans the entire development process—from discovery to release The process differs from conventional approaches, such as those defined by Booz and Hamilton (1982), Bowers (1985), Khurana and Rosenthal (1997), and Zeithaml et al. (2006), where strategy is defined prior to investigation, creating an outline of the service that has to then be filled in. We argue that the right strategy cannot be known a priori. Instead of trying to define a service from the top down, we start with exploratory or immersive research to lead to opportunities for innovation in strategy. This, in turn, provides context (or the fill) from which the service can be created.

People-centered Research Drives Innovation

The approach we have taken to service design is based on our experience in interaction design and approaches developed and published primarily in Europe (Erlhoff et al., 1997). At Carnegie Mellon University we have organized our approach within a conventional design process framework, leveraging exploratory, generative, and evaluative research methods along the way.

Exploratory Research—Uncovering and Understanding Latent and Masked Needs.
In exploratory research, techniques are used to define ‘‘what is’’ in the current situation or context. Methods used in exploratory research are typically drawn from ethnography and include shadowing, participant observation, and contextual inquiry. The goal of this type of research is to immerse the researcher–designer in the context of the inquiry and to provide a deep under- standing of not only the category of people under observation, but also their goals and needs.

In a recent project at Carnegie Mellon, students were asked to improve service flow at the Transportation Security checkpoint at the local airport. Students first documented stories of their experiences at the Pittsburgh airport and other airport checkpoints. This directed storytelling exercise immersed them in the context of the experience even before going onsite. After just a few hours of observation, the students uncovered a latent need and documented it. They found that passengers and their friends and loved ones had no place to say goodbye. The service as designed for the critical security-checking goal provided resources for security officials and a few for passengers to participate in the process, but the physical space, in particular the area leading up to the security checkpoint, the communication products such as the signs and cue markers, and the service providers offered little support for another fundamental activity in the traveling process—people simply saying goodbye.

Generative Research—Determining What Is Meaningful.
In generative research, the goal is to verify the framing of the ‘‘what is’’ and assumptions about how to respond to the needs identified with representatives of the service participants. Early on in generative research the activities are more projective and include exercises that help people express ideas, emotions, and desires around the service experience, The exercises are designed to help people express or explore what is usually hard for them to communicate—how they feel about the given service experience on an emotional level. Later activities are more constructive and are designed to validate specific reactions to service concepts, flows, and evidence. Figure 19.4 illustrates the projective and constructive faces of generative research (Hanington, 2007).

Figure 19.4 – Model of generative reserach (Hanington, 2007)

The later activities are usually design collaborations between designers and participants in sessions that may include people, process, and artifacts that encourage creativity and conversations (Sanders, 2000). In these sessions designers and participants engage in the meta-design of the experience resources when they coproduce prototypes and enactments of the service experience. In a recent project with UPMC (the University of Pittsburgh Medical Center) students teams engaged in two very different activities to elicit patients’ emotional needs with regard to their health-care experiences. In the first case, students provided patients with a set of stimulus cards that had images of different environments in which the ambiance ranged from a baby sleeping in a room to a pianist playing in a concert hall. The participants were asked to select images that best represented the experience they would like and to explain why. Another team took a slightly different approach. They provided respondents with sets of four images of the same thing, such as four orange juicers or four magazine covers, and asked respondents to compare the images to what they wanted from the service setting and explain why one of the images was most appropriate and another was least.

The resulting conversations from both of these participatory exercises helped the design team suggest appropriate resources (places, products, and people’s behavior) for the ultimate service users to design a health-care experience that would be right for them.

Evaluative—From Concepts to Recommendations.
Evaluative research helps validate whether the needs and expectations people bring to the service experience are actually met by the resources as designed. Ultimately, the goal is to determine if the resources provided for the experience are useful, usable, and desirable for the intended service users and providers (Sanders, 1992). Methods may be tightly controlled as in a lab experiment or loosely defined as an extension of generative activities (Hannington, 2007). The purpose is to evaluate the resources while they are still easy to change and before major investment is made in producing the service process, service products or evidence, or the setting for service delivery.

An Integrated Service Design Process

An integrated service design and implementation process is key to the success of any service experience. We have found a multidisciplinary effort with a modeling-centric approach to be most effective for service design. The process is illustrated in Figure 19.5 in the context of the previously described people-centered research model. Though the process as shown is illustrated in a linear fashion in practice, it is fluid and iterative.

Figure 19.5 – Integrated design process and people-centered research.

The Five Major Stages in Designing for Service.
There are many models of the design process, and many service design organizations opt for their own variations, while others prefer not to be confined to a single process. We have refined our process through practice, but admit that it is fluid and should change according to the design challenge (Evenson, 2005). The activities in the stages of our current process are described briefly in Table 19.1.

Table 19.1 – Process Overview

Service designers must account for the complexity of service resources that must be accessible to the appropriate participants to design the service experience for themselves. Methods that service designers use to address this complexity in particular are service ecologies, experience prototyping, and service blueprinting. Service ecologies are maps of the participants and entities affected by a service and the relationships between them. Ecologies or mappings of the research findings reveal new opportunities and inspire ideas, and they help to establish the overall service concept (livejwork, 2004). Experience prototyping brings the service experience to life. First designers, and then stakeholders in the experience, act out the service experience with specific roles and rough props. This is similar to Brenda Laurel’s design improvisation (Laurel, 2003). The goal is theater that enables the designers to better understand the contextual level of the design experience. This understanding is crucial because experience emerges from the activity of persons acting in a setting and is embedded in context and ongoing social practices.

G. Lynn Shostack developed service blueprinting. She states, ‘‘a service blueprint allows a company to explore all the issues inherent in creating or managing a service.’’ She goes on to explain that there are four aspects to the blueprint. They are process identification, isolation of fail points, establishing the time frame, and analyzing profitability (Shostack, 1984). We have extended this approach to include opportunities for service innovations that are derived from immersive research.

Service Design Languages

Just as spoken languages are the basis for our conversations with people, so design languages are the basis for conversations with services—they are building blocks of the service experience. People use spoken language to express themselves; services designers use service design languages to express the service, what it does, how it is to be used, and what experiences or journeys are made possible through it. Service design languages are used to visualize, express, and choreograph the resources that mediate the service experience. A design language consists of a system of elements (with associated meanings) through which designers signal purpose and users ‘‘read’’ intent (interacting with expectations), for example, ‘‘grip here’’ or ‘‘this is a button that can be pressed.’’ A design language also includes a set of organizing principles (the rules and conventions) for combining elements.

Spoken languages consist of words and rules of grammar. Design languages consist of design elements that are combined into constructs, such as a touch point, and the principles for their combination. Spoken language supports the production of meaningful expressions by allowing people to combine well-known sets of words and rules of grammar to create previously unknown but usually comprehensible expressions. In addition, spoken language is generative and inherently open. Research into creating a service language, so it is similarly open, will be invaluable.

With a service design language it is possible to visualize, express, and choreograph the resources for interaction. Design languages are general to a servicescape, such as a coffee shop with a condiment station for tailoring the coffee that has a flat place large enough to hold several drinks, trash receptacles, sugars, creamers, and so on, and specific to a particular brand (e.g., in the way Starbucks expresses a condiment station) (Bitner, 1992). Essentially, design languages are the means by which

• Designers build meaning and create coherence in the service interface
• Service interfaces express themselves and their meanings to people
• People learn to understand and use the service and engage in experiences associated with the service journey
• Companies establish new industry standards for quality, market presence, and customer satisfaction

When an effective service design language is deployed consistently, people who use or access services become fluent in their interactions with the service. Designers and developers are also articulate and skilled at the production of the resources for service delivery. Research into design languages is likely to influence service design in multiple ways. An exploration of service design languages will augment or change existing business process description or blueprinting methods that are used for describing the current state of service experiences. This work is a natural compliment to research into specification, choreography, improvisation, and, most importantly, implementation.

Cocreating and Experience Advantage – Designing Design

Approaching service as designing will lead to new ways of thinking about service innovation. Service as designing means service itself is fundamentally a creative process. As service designers we are engaged in meta-design—designing design—and are producing resources for people to creatively engage with a service. The position explains why the metaphor of choreography that is so often used with service experience may not be a metaphor at all. The choreographer creates a plan for the dance, but the dancer also creates the dance as he brings his own point of view to performing it.

What will the impact of a ‘‘service as designing’’ mindset be on the design of services such as a healthcare experience? In recent projects with the University of Pittsburgh Medical Center and the Mayo Clinic, Carnegie Mellon students have shown that a design approach and design mindset can lead to innovative solutions to serious service challenges. At a small scale it can mean simply better understanding the relationships that are created through interaction around the service. This is illustrated through the suggestion that catheterization lab team members wear ‘‘gear’’ that unifies them as a group and allows the patient and family to see them as their team. On a broader scale, the service as design mindset leads to service innovation concepts that put the patient more in control of their experience—both in proactive and in chronic primary care situations. In this case, the patients would then be provided with the resources to change their existing situations into preferred ones. We hope that more efforts to frame service as design can lead to even more innovative solutions for these and other important challenges.

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In this article, we contrast the “sales cycle” and related models with the “experience cycle” model. The sales cycle model is a traditional tool in business. The sales cycle frames the producer-customer relationship from the producer’s point of view and aims to funnel potential customers to a transaction. The experience cycle is a new tool, synthesizing and giving form to a broader, more holistic approach being taken by growing numbers of designers, brand experts, and marketers. The experience cycle frames the producer-customer relationship from the customer’s point of view and aims to move well beyond a single transaction to establish a relationship between producer and customer and foster an on-going conversation.

We acknowledge the sales cycle model has value. And designers need to be familiar with it. But when the sales cycle comes up as a topic of discussion in a client engagement, designers should also think of the experience cycle as an alternative frame—and should introduce it into the discussion. We believe the experience cycle is a more useful model not only for designers but also for marketing and sales people, because it is more likely to lead to an experience of lasting value for customers, and thus greater long-term value for producers.

Sales Cycle

The “sales cycle” is a model commonly used in business. It often frames the basic structure of marketing and sales activities, providing a practical template for planning.

The sales cycle describes the series of steps leading to a sale (or purchase), including awareness, consideration, and selection. The goal is to push customers to buy—advertising to increase familiarity, informing to build knowledge, offering incentives to close a deal.

The sales cycle also refers to the time required to complete the sales process. The length of the sales cycle varies depending on the cost, complexity, and context of use of the product being sold. For example, a hospital information system might have a three-year sales cycle; a new game console might have a sales cycle lasting a few days or weeks.

The sales cycle does not have a single, canonical form. Many variations appear in the literature, and in practice people often tailor the model adding or subtracting steps to fit their own situations. A common characteristic of sales cycle models is the funnel shape, a visual analogy to a process that begins with a large pool of candidates, narrows to a group of interested prospects, and narrows again to those who purchase. The funnel model is useful in managing a “sales pipeline.” Defining a series of steps in the sales process creates opportunities for setting goals, tracking performance, and analyzing effectiveness, which makes forecasting more reliable and enables improvement of the process.

Sales Cycle – Expanded

This model updates the sales cycle, framing stages in the process as goals the seller has for customer thinking and adding actions the seller may take to achieve those goals and measures of their effectiveness. This model also adds a stage for customer feedback, important for product improvement and innovation.

Related to the sales cycle model are models of decision-making and technology-adoption. Rogers 6. articulates a five-step innovation-decision process:

• Knowledge
• Persuasion
• Decision
• Implementation
• Confirmation

Kotler and Armstrong 4. articulate another variation on the decision process:

• Problem recognition: Perceiving a need
• Information search: Seeking value
• Alternative evaluation: Assessing value
• Purchase decision: Buying value
• Post-purchase behavior: Value in consumption or use

Defining the first step as problem recognition may imply the “problem” has an objective existence, independent of the customer—and the producer. Framing the decision process as problem-solving suggests the customer is a “rational actor.” The danger is that people often act more on emotion than by rationally calculating self-interest. And their definitions of problems depend on their point of view and are often formed in conversations with others—including producers. Indeed part of the innovation process is reframing an existing situation to create consensus around a new definition of a problem.

>Models of decision-making as problem-solving echo models of the design process as problem-solving which were common in discussions of first-generation design methods. In proposing a second generation of design methods, Horst Rittel 5. articulated the limitations of design as problem-solving and offered as an alternative a view of design as conversation.

Bitner 1. articulates a six-step self-service technology adoption process:

• Awareness
• Investigation
• Evaluation
• Trial
• Repeated use
• Commitment

Bitner suggests “trial” is the most important stage because it is influenced by customer readiness or the expectations that they bring to the interaction—can they do “it” (ability), do they know what to do (clarity), and do they see benefit in doing it (motivation). These ideas are consistent with the concept of transparency in interaction design. Of course, producers (and designers) have goals for their customers’ experience. But all they can do is provide artifacts and services that create opportunities for experience. We should be cautious about proposing to “design experience.” Ultimately, construction of experience remains with the customer. You own your experience. No one else can construct your experience for you. In John Dewey’s words, “a beholder must create his own experience.” 3.

So: What is the customers’ view of their experience?

Customers interact with producers through “touch- points,” clusters of elements combined into artifacts that foster product or service experiences. These touch-point experiences form a larger arc or path: the customer journey. The series of customer experiences aggregate to form an impression of the product or service in its context—developing an idea of what it does, what it means, and what its worth—what the customer thinks of the brand. Indeed, the impression (the sum of the experiences) is the brand. 7.

Ideally, the experiences build a strong relationship between customer and producer. John Rheinfrank, Shelley Evenson, and others developed a model of the ideal “experience cycle” as they worked on a usability design strategy for Xerox in the 1980s. They were searching for a way to describe a copier in its broader context—in its ecology—so that they could design the product to fit its context. The initial model had seven steps, but over the years the team refined it to five.

Experience Cycle

The experience cycle model describes the steps people go through in building a relationship with a product or service:

• connecting (first impression)
• becoming oriented (understanding what’s possible)
• interacting with the product (direct experience)
• extending perception or skill and use (mastery)
• telling others (teaching or spreading activation)

Explicit in the experience cycle is the process by which customers become advocates and introduce others to the product, beginning the cycle anew. This frame suggests a shift in focus from “the sale” as a point event or “trial” as a single interaction to nurturing a series of relationships in a continuous cycle that yields increasing returns.

The experience cycle model suggests attributes for an ideal experience—criteria for evaluating experience or even key performance indicators (KPI)—which designers can address. A good product or service experience is:

• compelling (it captures the user’s imagination)
• orienting (it helps users navigate the product and the world)
• embedded (it becomes a part of users’ lives)
• generative (it unfolds, growing as users’ skills increase)
• reverberating (it delights so much that users tell other people about it)

In Csikszentmihalyi’s concept of “flow,” people are completely involved in an activity for its own sake. In peak flow experiences, people are engaged in discovery, transported to a new reality. 2. Though in most experiences we cannot expect people to “become so involved that nothing else matters,” addressing the facets of experience can make flow easier to achieve.

The experience cycle also helps designers reflect upon another important design consideration—what expectations people bring to the experience. At each stage, resources for experience must account for or consciously disregard a customer’s expectations for the stage and design accordingly. The experience cycle plays out at multiple scales. It plays out “in-the-large,” across the life of the relationship between a customer and a product. It also plays out “in-the-small,” across the experience a customer has with each touch point. For example, a good magazine ad connects immediately with readers, presents a clear structure, draws readers in, extends their knowledge, and delights them so much that they show it to other people. A good product package, a good interface, a good support service, and other well-executed touch points enable a similar cycle of experience. These interactions build on one another and further cement the producer-customer relationship.

The experience cycle model suggests experience has a fractal quality—that experience has a self- similar structure at different scales. The model suggests recursion—each stage stands for itself but can also “call” the whole model. The recursion process can continue down to a fi ne scale as designers work out the ways an experience ramifies. (Design also has a self-similar structure at different scales; employs recursion; and ramifies.) Thus the experience cycle model is useful to designers both in early stages of a project when working out the broad outlines of a product or service and also throughout the process as successive iterations add increasingly finer levels of detail.

See an Apple Case Study of the experience cycle.

Experience cycle “in the large” and “in the small” Integrated experience across multiple scales: Apple as a case study
The fractal nature of the experience cycle

In the large
Multiple touch-points across the life of a product

In the middle
Multiple touch-points in the store experience

In the small
Multiple touch-points within the in-store purchase process

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The simplest way to describe the design process is to divide it into two phases: analysis and synthesis. Or preparation and inspiration. But those descriptions miss a crucial element—the connection between the two, the active move from one state to another, the transition or transformation that is at the heart of designing. How do designers move from analysis to synthesis? From problem to solution? From current situation to preferred future? From research to concept? From constituent needs to proposed response? From context to form?

How do designers bridge the gap?

The bridge model illustrates one way of thinking about the path from analysis to synthesis—the way in which the use of models to frame research results acts as a basis for framing possible futures. It says something more than “then the other thing happens.” It shows how designers and researchers move up through a level of analysis in order to move forward through time to the next desired state. And models act as the vehicle for that move.

The bridge model here is organized as a two-by-two matrix. The left column represents analysis (the problem, current situation, research, constituent needs, context). The right column represents synthesis (the solution, preferred future, concept, proposed response, form). The bottom row represents the concrete world we inhabit or could inhabit. The top row represents abstractions, models of what is or what could be, which we imagine and share with others.

Analysis-Synthesis Bridge Model

Ideally, the design process begins in the lower-left quadrant with observation and investigation—an inventory (or description) of the current situation. As the process moves forward, it moves to the upper-left quadrant. We make sense of research by analysis, filtering data we collect to highlight points we decide are important or using tools we’re comfortable with to sort, prioritize, and order. We frame the current situation, but move out of the strictly concrete. We define the problem. We interpret. Analysis begins as thoughtful reflection on the present and continues as conversation with the possible. Crucial for progress is documenting and visualizing our analysis, making it possible for us to come back to it, making it possible to imagine alternatives, making it possible ultimately to discuss and agree with others on our framing and definition. We might write down a list of findings or a statement defining the problem. Better still is writing a story. A story describes actors and actions; it suggests relationships, which we may represent in visual form. A story of what happens suggests a model of what is—an interpretation of our research. The process of coming to a shared representation externalizes individual thinking and helps build trust across disciplines and stakeholders.

Having agreed on a model of what is (framed the current situation, defined the problem) then the other side of the coin (the preferred future, the solution) is implied. An interpretation provides “a description of the everyday in such a way as to see how it might be different, better, or new [1].” We can devise stories about what could happen. We can model alternatives in relation to our first model. In doing so, we’ve moved to the upper-right quadrant, to the use and development of models of what could be. It is in the realm of abstraction—by thinking with models—that we bridge the gap between analysis and synthesis. These models are hypotheses, speculations, imagined alternatives to the concrete we started with, but they are still abstract themselves. It is easy to “play” with models at this point, to test and explore. But design requires that the work return to the concrete, that we make things real, realize our models as prototypes or even finished form. This is the lower-right quadrant. Of course, results improve with iteration. Submitting the new prototype to testing, further observation and investigation, continuing around the quadrants, we learn and refine our work. The bridge model has several antecedents and variations.

Robinson Model

The bridge model grew out of personal discussions over the past few years. Rick Robinson has written about “the space in between” research and concept. He has described anthropologist Clifford Geertz’s essay, “Deep Play: Notes on the Balinese Cockfight,” as an example of abstracting a model from research, and one that parallels strongly the moves that other forms of research and design make in moving from description through interpretation to application. “[The construct of] Deep Play becomes a lens through which Geertz can show what’s important about the Balinese cockfight, and his colleagues can understand important underlying factors in something like fan riots at soccer matches [1].”

Beer Model

Writing about the relationship of science to management, Stafford Beer presented a more elaborate model of the move from cases to consensus, from particular to general. He points out that several levels of models are involved [2].

Alexander Model

At the beginning of his career, Christopher Alexander described a six-part model. It differs from the bridge model in two important respects. First, Alexander explicitly separates the mental picture (model) from a formal picture of the mental picture (a representation of the model). Second, his notion of a model (at that time at least) was highly mathematical [3].

Kumar Model

Vijay Kumar has proposed a model of the innovation process.[4] He frames it as a two-by- two matrix, moving from research, to “Framing Insights,” “Exploring Concepts,” and “Making Plans.” He notes, “’Framing Insights’ are primarily about descriptive modeling, creating abstract mental pictures about the patterns that we recognize about reality. ‘Exploring Concepts’ and ‘Making Plans’ are about prescriptive modeling.” Where the bridge model forefronts the role of models, Kumar’s model forefronts steps that make use of modeling. He recently published a wonderful poster that maps the steps in the “innovation process” to a series of methods.

Kaiser-IDEO Model

During the process of writing this article, interactions co-editor Richard Anderson pointed out this model of the innovation process. Christi Zuber reports that Kaiser Permanente’s Innovation Center (working with IDEO) developed this model in 2004 as part of an innovation toolkit created for use inside Kaiser. This model is similar to Kumar’s model, but the Kaiser model emphasizes storytelling and brainstorming as key methods.

Suri-IDEO Model

Responding to questions about the origin of the Kaiser/IDEO model, Jane Fulton Suri supplied this recent model of the process of moving from synthesis to strategy. It shares the same basic structure as the Robinson model; though synthesis (depicted as the right column in other models) is here depicted as the left column. The framing of models as a link between patterns and principles is a useful addition [5].

While practitioners and educators increasingly make use of models, few forefront the role of modeling in public summaries of their work processes. Glossing over modeling can limit design to the world of form-making and misses an opportunity to push toward interaction and experience. We see modeling becoming an integral part of practice, especially in designing software, services, and other complex systems.

The bridge model makes explicit the role of modeling in the design process. Explicit modeling is useful in at least two ways. First, it accelerates the design process by encouraging team members to understand and agree on the elements of a system and how those elements interact with each other and their environment. Second, by making the elements and their interactions visible, it reduces the likelihood of overlooking differences in point of view, which might otherwise eventually derail a project.

Explicit modeling also helps scale the design process. It enables designers to develop larger and more complex systems and makes the process of working with larger and more complex organizations easier. Discussing the role of modeling in design also invites comparison and interaction with other disciplines that use models. Ideally, practitioners that use models may, over time, be able to see patterns across their models that will advance the practice of design.

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Joanne Mendel and Jan Yeager build on the bridge model in their article Knowledge Visualization in Design Practice.