Human-Centered Design

What is HCD?

Human-Centered Design (HCD) is a problem-solving, design-based discipline that quickly moves ideas for products, services, and systems from concept to prototype so that it can be tested with participants to see if it meets their needs. These prototypes are developed with the people who will ultimately use the product or service, and reflect their values and needs. It requires rigorous qualitative research, directing that research towards the goal of deeply understanding the needs, insights, and emotions of customers. By using Human-Centered Design, we can focus our time, resources, and energy on solutions and innovations that make service delivery effective, easy, and in tune with the emotions of our participants.

HCD involves four phases of sequential work: discovery, design, delivery, and measurement. HCD is also cyclical. Once a design solution is launched, we measure its effectiveness against initial and intended aims, and then we continually tweak it, thus improving the solution over time. HCD recognizes that people and their needs are dynamic and changing and so our solutions must be dynamic and changing.

A prototype is the first version of a product, service, or system; it can and should be low-fidelity and rapidly generated so that it can be tested. The prototype won't be the final version of the product, service, or system, nor will it be the version that gets made with expertise and scaled across an organization. It will be the expression of the design idea that the team creates from their research, and it will be questioned and changed by the participants during testing, so that the design team can refine it towards a final, scalable product, service, or system solution.

HCD allows us to understand the types of experiences participants want from a system, product or service. We refer to their experience as the “front stage” of the design effort. HCD also helps us craft the interactions of the people, processes, and technology that create those desired experiences. We refer to this behind-the-scenes work as “the back stage” of the design effort. By tending to the front stage and the back stage, HCD allows us to put the customer at the center of our design development.

The HCD approach has already created immense value in advancing public sector missions. For example, redesigning USAJOBS, the hub for federal hiring where nearly 1 billion job searches are done annually by over 180 million people, has resulted in a 30% reduction in help desk tickets after the first round of improvements. Not only does this reflect an easier experience for those involved in the hiring process, this change also creates savings in support costs.

HCD Phases: A Breakdown

Discovery

This Design Guide series began with the Discovery phase. Both Concept (why) and Operations (how) guides are available for this research-focused phase. To review, in the Discovery phase, teams participate in research to gather participants' and stakeholders' perspectives and experiences in that frame, synthesize the results of that gathering, and define possible parameters for the Design phase.

Design

With your insights gathered and opportunities defined, teams enter the Design phase. This phase is characterized by working through design ideas and building models, also called prototypes, of design solutions. Instead of trying to make the first version of a design perfect, the team will prioritize iteration, testing, and making incremental refinements. Build, test and repeat. As the team and stakeholders converge around a best product or service solution, refinements can be made to start moving towards a product, system, or service that will be the team's final deliverable.

Deliver

After prototyping and testing, public sector design teams typically work with implementation teams and other stakeholders to create a small pilot and test the logistical needs around the launch of the product, system, or service the team has designed. The teams should build into the delivery process mechanisms to gather feedback on the product, service, or system once it has been in the hands of participants for stipulated amounts of time. Creating these mechanisms will feed into the success of the next phase, Measure.

Measure

In the Measure phase, the design team should be part of gathering quantitative and qualitative data to learn if the goals and expectations of your work are being met. When applied, this data will help improve your design.

Divergent & Convergent Thinking

As we've seen, the Human-Centered Design process is cyclical both within and without each phase. In addition, each phase requires movement between convergent and divergent thinking. In Discovery, a team diverges through desk research, then converges on a problem frame, and diverges again when listening to the points of view of the participants.

In the Design phase, idea generation, also called ideation, requires divergent thinking, then convergence around a few viable options to prototype and test. This prototyping and testing also requires that the team start considering the potential measurement points for the designed product or solution. These measurement points include a spectrum of measurements built on both quantitative and qualitative data points. This will allow the design team and stakeholders to gain a robust evaluation the product or service, once it has been deployed.

Delivery includes divergence around modes of delivery and collaboration with implementation teams, then convergence around an workable model. The creation of measurement points also exist in this phase. Since the delivery of and access to a product or service is an integral part of that product's or service's success, the team should build qualitative and quantitative measurement points into this phase as well.

Finally, the Measurement requires that the team and stakeholders not only converge around the collection the data from the measurement points built in the previous sections, but also think divergently in their parsing of that data. Divergent thinking in this phase is also known as interpreting the data, or creating understanding or meaning from the data. The data itself will not give the team and stakeholders insights and direction on where to go next; the interpretation of data provides those.

At each stage, the team is aware that a return to a previous stage might be necessary. The HCD process is not strictly linear, progressing from one stage to another; it is subject to informed and intentional revision at all points, which gives it its cyclical nature. The balance between when to move forward and when to revise is sometimes a tough one to strike, but through practice and mentorship through this process, practitioners can refine their instincts for when this balance point is struck, and when it feels like a project might need to re-cycle through a phase again.

HCD and LEAN

HCD and LEAN Six Sigma are both methods by which improvements to organizations can occur. Although often framed as mutually exclusive, they actually complement each other: they both build solutions based on a mixture of qualitative and quantitative data and include the voice of the customer as a key portion of their methodology. HCD, however, places more emphasis and importance on qualitative data and centers itself on the human experience of a product, service, or system, while Lean Six Sigma emphasizes quantitative data and focuses on improving the inert product, service, or system instead of responding most intensely to human need.

Both methods rely on the ideas and actions of Ease and Effectiveness, two components of exceptional service delivery. Easily quantifiable, LEAN highlights those exceptional service delivery attributes. Emotion, the third attribute, requires more qualitative data collection to understand. Although LEAN integrates some emotional components of the participants' experience, it does not center on them or allow for the large-scale questioning of the entire system itself. HCD, on the other hand, centers on the participants' emotional experience and allows for broad questioning of the system itself and its component parts. For this reason, HCD's qualitative data-based approach to solution-finding complements LEAN's quantitative data-based approach.

Human-Centered Design and other qualitative research methodologies investigate and help sort out the root causes of conflicts like the one above by Dr. Margaret Mead. LEAN and other quantitative methodologies allow for the understanding of current system states and the rational elimination of mechanical and nonhuman inefficiencies in systems.

An additional nuance: quantitative data is, by definition, historical and evaluative: in order to be collected, the actions and events quantified in this data has to have already occurred. The data is a record of what has happened in the system that exists. For this reason, LEAN-generated solutions reflect the systems that already exist. Qualitative data, by contrast, is not bound by historical events. By including participants' and stakeholders' hopes, impressions, and, yes, emotions, as data, solutions generated by qualitative data-based research approaches can imagine wholly new systems from that which already exist. These solutions can support incremental or radical change, depending on the needs and desires of the participants and stakeholders.

For a more detailed understanding and case studies regarding how HCD and LEAN might work together, please reference The Lab's talks on HCD + Lean and Qualitative + Quantitative research and Arup and the Rockefeller Foundation's City Resilience Index.

Additional Research Methods
Additional social science research methods abound; all drive towards finding the truth of situations or the core causes of problems. You can find more on social science research methods from GSA's Office of Evaluation Sciences and Stanford's Institute for Research in the Social Sciences.