Design Thinking for the Greater Good

by Jeanne Liedtka

  Identifying potentially promising but flawed solutions and developing the ability to design and execute cheap, fast experiments is critical to reducing innovation risk. Even expert scientists at the FDA can be ineffective testers when their emotions and personal beliefs interfere with their neutrality, as Suzanne Schwartz, their director of emergency preparedness, pointed out. Marliza’s experiments at Whiteriver reduced risk by helping her to pivot from kiosk to paper to fast track as she learned quickly and cheaply what didn’t work or wasn’t legally permissible. At the Kingwood Trust, Katie Gaudion created prototypes—and expected some of them to be destroyed. Even beyond testing the quality of the ideas, Dr. Don Campbell discovered at Monash that learning launches of the long-stay app were not just testing ideas; they were building trust and ownership among the staff, reducing risk even further by increasing the likelihood of successful implementation.

  Managing Change

  How has design thinking helped innovators improve their abilities to manage the changes involved in carrying new concepts into successful action? Don’s observations about the unanticipated benefits of learning launches for staff ownership of ideas suggest one direction. Ultimately, innovation requires that a particular set of human beings behave in new ways. Without encouraging different choices as part of implementation, our investment in creative idea generation and rigorous testing is useless. Since change theorists argue that behavioral change is intensely personal and subjective, this dovetails with design thinking’s human-centered focus. It is not just users that we strive to understand; it is the entire set of stakeholders who are part of transforming new concepts into reality.

  One popular theory of how change occurs illustrates vividly how design thinking’s approach supports critical elements of change. It argues that behavioral alterations are a function of four factors: the dissatisfaction with the status quo, the clarity and resonance of the new future, and the existence of a pathway to get there, all balanced against any perceived loss associated with the change.

  Design thinking methodologies encourage change and increase the likelihood of successful implementation by influencing each factor in that formula. Exploration of the problem during What is builds engagement that leads to alignment around the nature of the problems needing to be addressed, and that naturally deepens dissatisfaction with the status quo. Ethnography that identifies pain points and unmet needs helps develop empathy and builds change agents’ resolve to make life better for those they serve.

  Christine Miller at Monash reminded us of this when she recounted the impact Tom’s journey map had on the staff at Monash: “It was shocking …We needed to feel the blockages and struggles.” In Dallas, at Children’s Health, Eli MacLaren worked to shift the mindset of clinical staff from one of evaluation (patients weren’t using the system correctly) to one of empathy, or from a “place of judgment to a place of possibilities,” as she described it.

  But design thinking doesn’t stop there. It works on the second factor: building greater clarity around what the new future looks like, as well. Based on that deeper empathy and understanding, design thinking helps everyone involved envision new possibilities for addressing challenges with clear and compelling concepts during What if. In Dallas, the Business Innovation Factory insisted on formulating a specific “from-to” construct for each of the opportunity spaces at Children’s Health, to provide the detail that successful change requires. And by moving beyond complaining about current reality, design thinking confers an additional benefit: it gives people who are stuck in the problem space the motivation and hope that there can be a new and better future. Remember former high school principal Michael Donnelly’s comment on the way the Kerry charrette process helped them think in a new way: “We’d been analyzing and defining the problem for years. This conversation was about solving the problem. It meant that there could be a solution. Maybe our problems weren’t just an inevitable part of society evolving that we had to accept.”

  During What wows, prototyping and co-creation require that we flesh out salient details of any new future in even greater detail, adding further clarity. And in What works, experiments involving actual stakeholders further enhance the tangibility and vividness of the new future. MasAgro’s practice of encouraging the physical planting of rows of old and new crops side by side provided the ultimate prototype in making the promise of modern farming techniques tangible to skeptical farmers.

  Design thinking’s emphasis on the particular also addresses the third factor: providing pathways to the future. It insists that we address the means as well as the ends—what resources will be needed? What training? What measures should we be paying attention to? What are the way stations along the path? Recall that the Institute without Boundaries left the Kerry community not just with potential solutions; it also included detailed timelines of the different specific activities needed along the way. BIF worked with Children’s Health not only to create a new business model but also to design new metrics to measure wellness. And the local networks facilitated by the design processes at the FDA, CTAA, and Children’s Health actually increased the resources available to achieve the new future by pooling the capabilities of the different players in the ecosystem.

  THE FAMILY 100 PROJECT

  New Zealand’s Family 100 Project provides an example of the power of narrative to build empathy and, along with it, the kind of dissatisfaction with the status quo that motivates change. The project followed poverty-level families for a year to understand the issues behind being poor in New Zealand. ThinkPlace, a design consultancy, worked with the Auckland City Mission to distill the massive amount of data into the compelling story of a single mother, Charlotte, trying to hold a job, care for her children, and find food, medicine, and housing while utilizing Auckland’s transit system. Few could fail to be moved by Charlotte’s struggle in seeking the basics for her family, and a set of Auckland politicians were even motivated into personal action. “I didn’t realize how time consuming and expensive it is to be poor,” one deputy prime minister acknowledged, as he sought greater involvement from his staff, through volunteering in soup kitchens and shelters, to better empathize with their clients.

  Finally, the sense of loss that so often accompanies behavioral change—the loss of control when new solutions ask partners to assume more responsibility, or the lost sense of competence arising from the demand for new skills, or even, perhaps, just nostalgia for the comfort of the “good old days”—are outweighed by achieving greater clarity on the gains associated with change. At Monash, learning launches built trust and ownership that combated loss. Seeing the crops planted side by side reduced farmers’ fears of accepting MasAgro’s advice. No one said it better than Eli, regarding her work aiding the shift from medical-centered treatment of illness to community-centered encouragement of wellness at Children’s Health:

  People feel threatened by work they think is going to disrupt their job. You have to help them to see themselves in the future …use their stories, their insight, and their expertise so that they hear their voices reflected in the future state. You co-create so that they feel like they helped build this new model. There’s an old adage that change is painful when done to you but powerful when done by you. If you can just tap into that, you’re golden.

  Dealing with Complex Social Systems

  In the background of our discussions, there is a shift even more fundamental than the one from Innovation I to Innovation II—one that we believe is driving the changing paradigm of how innovation happens. It is the shift from a mechanistic view of organizations and the larger systems they operate in to one that sees them as complex social systems. Traditionally, we have treated organizations and their ecosystem as though they were machines, inert things that could be controlled and managed and that made decisions based on logic and evaluation of consequences—the “rational actor” model. Now, we increasingly see them, instead, as collections of human beings who are motivated by differing logics and perspectives, who
se reactions are sometimes based on emotions and politics and bureaucracy rather than careful, comprehensive decision making that “optimizes” the choice, as the rational actor allegedly does. Recent research illustrates clearly that the complex reality of social systems is not consistent with the convenient “rational actor” assumptions. These complex human social systems are inherently unmanageable and often chaotic. We can shape and influence their operations, but that requires different tools than customary approaches to strategy and policy traditionally offered.

  How does design thinking help innovators deal with the complexity in modern social systems? It challenges the underlying premise of a rational actor approach by focusing on innovation as a social process, intimately tied to human emotions and reliant on inexact methodologies in which humans collaborate and solutions emerge over time. In doing so, it better reflects the actual reality of organizational life in the social sector. In this way, it gives us, as we argued in chapter 1, a social technology better matched to the reality of achieving innovation and change in the social sector. Let’s look at how it does this, in more detail:

  • In design thinking, the traditional notion of a single “optimal” solution, selected from among a set of alternatives identified in advance, is rejected. That premise is replaced in design thinking by a search for multiple possible solutions, with the most promising ideas emerging during the process, shaped by conversation among the players involved. In complex social systems, it is almost impossible to “optimize” in the usual sense—we lack both the alignment around objectives and the data to assess cause and effect. In the design conversations during the Kerry charrette, for instance, there was no “right” answer. Four areas of opportunity, identified by the community, sparked the conversation and continuously morphed throughout subsequent discussions as thinking diverged and converged during brainstorming by students, staff, experts, and community leaders. In fact, the emergence of solutions throughout the process, with their diversity and their continuous evolution and change, forms one of the characteristic themes in our research. We see it in nearly every story.

  • Network effects play a much more critical role in complex social systems. Access to their powerful network is a key reason why the Ignite Accelerator program at the US Department of Health and Human Services accelerates innovation. Marliza was able to pivot quickly away from her second paper-based concept without doing any actual experimentation, after learning—through the IDEA Lab staff connections with HHS legal experts—that the Emergency Medical Treatment and Labor Act prohibits screening of patients on entrance to the emergency room. CTAA’s ambitions are as much to construct local networks in the areas served as they are to solve the currently presenting problems. The same is true in Dallas, as Children’s Health works to construct the kind of ecosystem that makes community-based wellness, rather than medical-centered treatment, even possible. Perhaps Ken Skodacek said it most clearly when he talked about the FDA’s need to work across organizations: “When the FDA controls all aspects of the process, then maybe you don’t have to bring in other stakeholders. But in many cases, a government agency is at the crossroads of an issue—we don’t have complete control over it.” This is true not just for government agencies. We see it in health care, in education, in charitable foundations. Increasingly, it is the network that matters. And design thinking has a unique ability to bring members of an ecosystem into productive conversation with each other.

  • Efficiency, the dominant criteria in stable, simple systems, must be balanced against the need for resilience and adaptability in complex, unstable systems. Design thinking’s patience with seeming inefficiency can thus be a positive rather than a negative. At Kingwood, when Katie used a mirroring technique to better understand what the world looks like from Pete’s perspective, taking the time to experience ripping pieces off the sofa and leaning her ear against the wall with him, she uncovered insights that “efficient” methodologies like focus groups would probably not reveal. In our stories, the conversations meander. The inclusion of disparate voices takes time and patience. It is often chaotic. But out of that chaos we see better solutions emerge. From a short-term perspective, it may have looked initially more “efficient” for the FDA to mandate what issues would be addressed at the respiratory device meeting, but they would have missed perhaps the most essential learning of all: that training, not regulation, was the driving factor in preparedness.

  One key feature in many of our stories is the avoidance of top-down standardization (always a favorite when efficiency is the goal) in favor of locally determined, customized solutions and processes. Standardization, again, may seem efficient in the short run, but in a complex world, adaptability favors solutions grounded in local conditions. Innovation is often driven by attending to the needs of a smaller subset, and then adapting that to a larger group. It also favors an emphasis on identifying design criteria—the qualities of desired solutions in general—rather than on the specific solutions themselves. Design criteria have more inherent resilience; that is, they are useful in telling you how to pivot when an initial solution fails. TSA’s investment in their research into traveler experiences did not become obsolete when an unanticipated agency mandate shut down the creation of the Sapient-designed website. The information they learned was equally useful in the switch to the development of a mobile phone app.

  Diversity plays an increasingly critical role here, too. Simple, stable systems favor homogeneity and usually see diversity of input as a nuisance. In complex social systems, heterogeneity is more valuable because it increases the range of both current information and the breadth of solutions generated. The introduction of new voices helps an organization see more opportunities—ones not necessarily path-dependent on previous choices. That understanding also produces the possibility for more intelligent and adaptable coordination. However, diversity must be of the right kind—it must be “requisite” diversity, in the language of systems theory.

  Empowering Local Capability Building

  Local, rather than global, decision making is likely to be most successful in complex social systems. This is because local intelligence is necessary and local action truly matters. Though the larger system is itself complex and difficult to predict, its subunits are less so, system theorists argue. These subunits tend to operate on what researchers call “replicator dynamics.” As in a fractal pattern (in which each subunit is a smaller-scale picture of the whole), simple central guidelines—established globally but applied locally—are often the most promising method for bringing order and accomplishing change. These rules generally specify processes or the larger purpose, leaving decisions about the specific content of problems and their solutions to frontline staff. Considering design thinking as a set of “simple rules” allows us to coordinate and encourage innovation in complex social systems. Think of IwB’s simple rules for charrettes, such as that no one can say no on day one.

  Throughout our discussions—on producing better solutions, on minimizing risk and managing change within complex social systems—the power of the local has been a strong theme. This has taken the form not only of local intelligence on any particular issue but also of the creation of local networks capable of coordination and joint action. How has design thinking helped innovators build these networks of capabilities that allow for ongoing innovation? The answer is that it has democratized design in a way that brings new voices into the conversation to identify and solve their own problems, while fostering sharing across units.

  In doing this, it addresses one of the key challenges in governance: the tension between centralization and decentralization. Centralization offers economies of scale as well as the ability to share best practices across units, but it often comes accompanied by the emphasis on standardization that we talked about earlier. Decentralization, on the other hand, offers responsiveness to local conditions and builds engagement to catalyze change but can make coordination and learning across units difficult to achieve. Design thinking,
we have argued, can help us get at the best of both worlds.

  CTAA uses design thinking as their mechanism for standardization and centralized control, but they focus on controlling the quality of the process, not the prescription of local outcomes. By combining the use of design thinking with the formation of diverse community teams who share their learnings with others, they seek the best of both worlds. MasAgro goes even a step further toward a powerful resolution of the central/local tension, building on the concept of repertoire at an institutional level. Think back to the stories we recounted in which an individual’s unique repertoire—Dr. Melissa Casey’s combination of experience as a tax specialist and psychiatrist at Monash, or Peter Roberts’s work in both health care delivery and insurance at Children’s Health—made a difference. At MasAgro, we see the benefits of an organization’s repertoire. Because of its global operations, MasAgro is able to reach across its enormous cache of worldwide farming knowledge to create a broad menu of choices, and then work with community thought leaders to select the ones most appropriate to whatever locale they are currently working in. Farmers in Oaxaca, Mexico, have access to a global knowledge base while retaining the power to select the specific information that works best for them. Their successes, failures, and modifications, in turn, feed learning back into the larger system.