Eleven Reasons You Should Have A Landscape Architect on Your Development Team

 

via Eleven Reasons You Should Have A Landscape Architect on Your Development Team | LinkedIn

By Timothy Brown  Principal at Traverse Landscape Architects

As a landscape architect, my experience has often been that we are brought in late on a project to “shrub it up”. The most unfortunate part about this is that owners and developers are being deprived of the chance to have a much richer and more significant project.

Below I offer eleven reasons why landscape design should be considered and landscape architects should be included throughout the project development process.

1. The landscape is the warp and weft which can weave a disparate collection of buildings into a cohesive city, community or campus.

2. Whether they are biking, walking or driving, people most often experience a place from ground level, and landscape provides the interest and impetus which inspires people to return in order to spend time in a place.

3. Vibrant native plantings, flexible plaza spaces, legible and convenient pathways and wayfinding provide a framework within which critical placemaking events can happen, contributing to the overall success of a place

Johnson and Wales University John J. Bowen Center for Science and Innovation

4. Landscape architects are often the keepers of a holistic vision and balance on a project, reconciling the sometimes conflicting design aspirations of architects, engineers, owners and developers.

5. Landscape touches every component of a development project and is a major factor inspiring people to live in a place or return as a visitor.

6. As this article from Time Magazine asserts, access to high-quality green spaces and nature makes people happier, improves physical and mental health and improves our overall sense of well-being. (Also See: WHO)

7. Well-designed landscapes, especially in neighborhoods and on campuses, contribute to an overall sense of well-being by providing places for people to meet up for a walk, for collaboration or to just chat. People places are successful places.

American Locomotive Works

8. Well-designed landscapes provide a myriad of ecosystem services, not the least of which include groundwater recharge, habitat creation, and mitigation of urban heat island impacts.

9. Using vernacular materials in innovative ways, referencing natural landscapes with native plantings and providing places for people to gather, recreate and relax are just a few ways that well-designed landscapes contribute to a culturally impactful and potent sense of place.

10. Landscape architects are trained to look closely at all the existing conditions of a site. The inclusion of landscape architects from the beginning of the process can avoid costly mistakes down the road and ensure the preservation of historically important vegetation and site artifacts.

11. Well-designed landscapes bring people closer to the places where they live work and play, giving them a place to dwell, promoting stewardship and inspiring advocacy.

These are just a few of the many reasons landscape architects should be an integral member of the development team starting from project conception.

UX Process: What It Is, What It Looks Like and Why It’s Important

via UX Process: What It Is, What It Looks Like and Why It’s Important | Adobe Blog

Nick Babich

As a UX designer, I am sure you have been asked many times “What is your UX design process? What and how many steps does it have?” There is a simple reason why this question so popular among designers: UX process is a cornerstone of UX design, it’s a make-it-or-break-it aspect of UX design. Without a solid UX design process, a designer could be completely moving in the dark. A clear and concise UX process, on the other hand, makes it possible to craft amazing experiences for users.

In this article, we’ll define a general UX design process, as well as the order in which specific UX phases should be taken. We will also see what methods can be used by UX designers during each phase.

What Does a UX Process Look Like?

The answer to this question is: it depends. A UX design process is something that everyone has in the UX industry, but something that everyone does differently. This happens because UX process depends heavily on the project. Different projects require different approaches: the approach to a corporate website differs from the way we design a dating app. And while there are some practices UX designers should follow for each project (such as conduct product research before moving on to prototyping), there are principles in every part of the process that have to be custom designed for the specific project.

UX Process Overview

At its core, every UX process should consist of the following 5 key phases:

1. Product Definition

One of the most important phases in UX design is actually done before the UX design process even starts. Before you can build a product, you need to understand its context for existence. Product definition phase sets the stage for the success of a product. During this phase, UX designers brainstorm the product at the highest level (basically, the concept of the product) with stakeholders.

This phase usually includes:

  • Stakeholders interviews: Interviewing key stakeholders in a project to gather insights about their goals. Defining the goals and values of the product that you would like to build is a key driver for a results-driven process.
  • Create value proposition: Value proposition maps out the key aspects of the product: what it is, who it’s for and when/where it will be used. Value proposition helps the team and stakeholders create consensus around what the product will be.
  • Concept sketching: Creating an early mockup of what the team is looking to build.
  • Project kickoff meeting: The kickoff meeting brings all the key players together to set proper expectations both for the team and stakeholders. It covers the high-level outline of the product purpose, who is involved in designing and developing the product, how they will work together, and what stakeholders expectations are (such as KPI and how how the success of the product should be measured).

2. Product Research

Once the product idea is defined, product research (which naturally includes user and market research) provides the other half of the foundation for great design. Good research informs your product and the fact that it comes early in design process save a lot of resources (time and money) further down the road (as fewer adjustments will need to be made).

The product research phase is probably the most variable between projects – the phase varies based on the complexity of the product, timing, available resources and many other factors. This phase can include:

  • Individual in-depth interviews (or IDI): A great product experience starts with a good understanding of the users. Not only do UX designers want to know who their users are, but designers want to dive deeper into their needs, fears, motivations, and behavior.
  • Competitive research: A comprehensive analysis of competitor products maps out their existing features in a comparable way. Research helps UX designers understand industry standards and identify opportunities for the product in a given area.

3. Analysis

The aim of the Analysis phase is to draw insights from data collected during the Product Research phase. Capturing, organizing and making inferences from the “what” users want/think/need can help UX designers begin to understand the “why” they want/think/need that. During this phase, designers confirm that the most important assumptions being made are valid.

This phase usually includes:

  • Create hypothetical personas: Personas are fictional characters created to represent the different user types that might use a product in a similar way. The purpose of personas is to create reliable and realistic representations of the key audience segments for reference.
  • Create experience maps: An experience map is an important design tool to understand the product/service interactions from users’ point of view. An experience map is basically a visual representation that illustrates user flow within a product/service. A basic experience map just follows one path (one user, one goal, one scenario) even when the product/service allows multiple path variations.

4. Design

When user expectations from the product are established (it’s clear what their goals are and how they like to operate with it), UX designers move to the design phase. An effective design phase is both highly collaborative (it requires input from all team players involved in product development) and iterative (meaning that it cycles back upon itself to validate ideas and assumptions).

The design phase usually includes:

  • Sketching: Sketching is the easiest way of visualizing our ideas. Drawing by hand is also the fastest way to visualize a concept – it allows the designer to visualize a broad range of design solutions before deciding which one to stick with.
  • Create wireframes: A wireframe is a visual guide that represents the page structure (hierarchy and key elements). Wireframing acts as the backbone of the product – designers often use them as the skeletons for mockups.
  • Create prototypes: If wireframes are mostly about structure and visual hierarchy (look), then prototypes are about interaction experience from it (both look and feel). A prototype is a simulation of the product, commonly using clickable wireframes.
  • Create a design specification: Design specifications usually consist of user flow and task flow diagrams which outline the functionality and style requirements of the product. Design specifications describe the processes and graphical assets needed to make a working product.

5. Validation (Testing)

Usually, the validation phase starts when the high-fidelity design is fleshed out. A product is validated with stakeholders and end-users through the series of user testing sessions.

Similar to the product research phase, this phase is also variable between projects. Validation phase can include:

  • “Eat your own dogfood:” Once the design team has iterated the product to the point where it’s usable, testing it with the product team is a great low-cost validation technique.
  • User testing sessions: User testing sessions serve as a validation of design, based on tests with real users.User testing sessions have a lot of forms, some of the most popular are usability testing, focus groups, beta testing, A/B testing, and surveys.
  • Create user diaries: User diaries are great at capturing an information from real-world users. Using Google Docs, UX designers can create a simple template and then include open-ended questions such as:
    • Where were you when using the product?
    • What tasks did you hope to achieve?
    • Do you have something that frustrated you?
  • Metrics analysis: Numbers provided by an analytics tool about how a user interacts with your product: clicks, navigation time, search queries etc. Metrics can also “uncover the unexpected”, surfacing behaviors that are not explicit in user tests.
  • Working with feedback from users: Feedback data such as support tickets, bug reports, and other analytics are able to drive product refinement.

How To Improve UX Design Process

Now you’ve seen how each phase is connected to each other, let’s consider some helpful tips for improving the UX design process:

Consider Overlap Between Phases and Iterations

It’s important to understand that UX design isn’t a linear process. The phases of the UX process often have considerable overlap and usually there’s a lot of back-and-forth. As the UX designer learns more about the problem being solved, the users and details about the project (especially, constraints), it may be necessary to revisit some of the research undertaken or try out new design ideas.

The Importance of Communication

Communication is a key UX design skill. While doing great design is one thing, communicating great design is equally as important, as even the best concepts will fail if they don’t accept by the team and stakeholders. That’s why the best UX designers are great communicators.

Processes Morph To Fit Projects

UX designers should be flexible with every project – the process employed should be tailored to fit specific project needs, both business and functional. A process tailored to the capabilities of the business and the clients proved to be generally effective.

Conclusion

When it comes to UX design process, there’s no one fits all solution. But whether your UX process lightweight or it’s full of a lot of activities, the goal of each UX design process is the same – create great a product for your users. Thus, use what works the best for your project, get rid of the rest, and evolve your UX process as your product ev

introducing mixed reality

via designboom’s TECH predictions for 2018: mixed reality

THE future ..its already arrived but it definitely not evenly distributed yet ….

four decades ago, virtual and augmented reality were the future. fast forward to the present day and they combine to create a 21st century passport into an alternate universe in mixed reality. merging the digital and the physical, tech giants everywhere are recognising the value in bringing together the immersive capabilities of a head-mounted VR set and the ability of AR to place data into the real world environment. mixed reality reinvents the storytelling process. it merges narratives with reality and presents viewers with a wholesome experience that’s perpetually indistinguishable from real life. this cultivates a fertile ground for increased contact between all participating entities, ergo fostering the creation of shared experiences.

 

google invested in ‘magic leap’, an allusive mixed reality company. now, apple are getting their teeth into MR which means only one thing – world domination. but back in 2015, microsoft launched hololens, one of the first devices both popularising and merging AR and VR. and the evolution of this device provides an interesting framework with which to navigate the future of MR.

 

‘computers used to be flat?’

2018 tech predictions mixed reality
microsoft hololens enables you to interact with content and information in the most natural ways possible.
image courtesy of microsoft

 

 

microsoft’s creator of the hololens, alex kipman, thinks headsets could be the successors to computers everywhere. its no surprise when MR extends current limits of presenting data, making physical screens a thing of the past. simple 2D analytics tools seem old school when you can project renders as large as the environment allows. employees of the future could even don company-issued mixed reality glasses as their PCs, releasing employees from the chains of their desks as well as their desktops – read more.

 

hello holoportation

2018 tech predictions mixed reality
holoportation looks set to transform the way we communicate with each other from afar
image courtesy of microsoft

 

 

heard of holoportation? well as MR evolves the advent of holographic images talking to us becomes ever more real.microsoft’s hololens uses a new type of 3D capture technology allowing 3D models of people to be transmitted anywhere in the world in real time. that means talking to your friend who lives miles away from you in a hologram – read more.

 

 

shop till you never ever drop

2018 tech predictions mixed reality
tenants will eventually have the option to view their potential accomodation in VR
image courtesy of airnbnb

 

 

mixed reality could transform the way we shop, creating a productless experience where consumers get to try items and services in real-time without breaking a sweat. furniture giant IKEA already saves couples all over the world by letting them skip flatpack fury, placing furniture in-situ via their PLACE app. and airbnb just recently announced it’s in the early stages of adding VR and AR to its services, predicting their own use of 360 photos and 3D scans to let tenants explore homes and cities before they arrive.

 

 

entire ecosystems made of sound

2018 tech predictions mixed reality
a shot of what magic leap and sigur rós’ tónandi looks like in action
image courtesy of magic leap

 

 

the secretive mixed reality company, magic leap, made waves back in 2015 with a huge investment from google which many people doubted would ever come to anything. well apparently it has it’s an alternate sonic universe… the company has been working with icelandic rock band sigur rós on an audiovisual project called tónandi which projects waveforms of the music into the physical space. this immersive way of releasing music could either be the future of music as some are predicting – a flop similar to the google glass – read more.

 

and there’s more…

2018 tech predictions mixed reality

magic leap one’s lightwear which comes with a lightpack and control

 

 

if the internet is a virtual, infinite universe, then the ‘magic leap one creator edition’ (the company’s main focus) may be the first step in exponentially multiplying the size of that universe by colliding it with the physical world. it’s an AR headset for developers (‘built for creators’) that according to an interview with rolling stone will ship in 2018. the technology is supposed to accept multiple input modes including voice, gesture, head pose and eye tracking whilst mapping persistent objects onto the environment.

Co-living 2030: Are you ready for the sharing economy?

Interesting alternatives living and working typologies for co-living examined with background on a possible history

via Co-living 2030: Are you ready for the sharing economy? | Features | Archinect

Illustration Evgenia Barinova

Illustration Evgenia Barinova

Last month I attended a SPACE10 forum led by New York-based design duo Anton and Irene on the resurgence of co-living. They suggest the financial squeeze of modern life combined with an upsurge in digital nomads is bringing the ‘sharing economy’ into the home. As 40% of the urban areas required by 2030 are not yet built—which means a city the size of New York needs to be constructed globally every month—it is crucial architects stay up-to-date with contemporary living patterns to respond appropriately to shifts in housing requirements. My last Archinect feature of the year will provide a short overview of the history and challenges that co-living has previously faced, discuss trends emerging from the ‘ONE SHARED HOUSE 2030‘ survey and speak to Dorte Mandrup, architect of the Lang Eng Co-housing Community, on how to approach the challenge of designing successful spaces for co-living.

‘Co-living’, an umbrella term for different types of ‘co-housing’ setups, can loosely be defined as a home where two or more people live together who are not related. While ‘co-housing’ is an intentional community created and run by residents, ‘co-living’ may also encompass shared accommodation initiated by an external agent, such as a developer or entrepreneur.

Aside from the investor rush to fuel co-living startups, concrete figures on the international co-living boom are not yet available. However, early indicators such as the UN now offering support to co-living initiatives within their sustainable development goals and last year’s prestigious Harvard Wheelwright architecture prize being awarded to a project innovating in co-living, suggest it is gaining traction. While it is indisputable that young people strapped for cash have always had roommates—think Bret and Jemaine from Flight of the Conchords—co-living is now simultaneously becoming part of everyday urban life and billion-dollar business.

I expect most people reading this who have lived in cities during their 20’s have experienced a houseshare, myself included. I rented a terrace with friends in Sheffield, moved into a Danish kollegium when I started my masters in Copenhagen and had a stint in a family attic while working in London. But rather than remaining a student necessity, increasing numbers of families and professionals are now opting to co-share. This also reflects a surge in the rental market, which in the US has jumped from 52% of total adults in 2005 to 60% in 2013. This is perhaps unsurprising with soaring urban property prices and take-home wages barely rising across the country, a pattern which is echoed in cities worldwide.

Last year Anton and Irene initiated ONE SHARED HOUSE as they became fascinated in how co-living seemed to be experiencing a cultural resurgence. The documentary maps Irene’s childhood experience of growing up in a communal house in Amsterdam. In the early 1980’s Amsterdam was facing an acute housing shortage so the government enacted a law ruling that 1% of all apartments had to be communal. In 1984 Irene’s mom responded to a newspaper ad for a co-share and moved their family into Kollontai, a communal house with 8 other women and their 3 children designed by the new brutalist architect Sier van Rhijn. In the film, Irene explains “they were feminists and non-conformists […] and many were rebelling against the traditional 1950’s families they had grown up in.”

Amsterdam co-housing showing Kollontai. Image: Anton and Irene

“Whenever I would tell people I grew up in a communal house”, Irene explains to me, “it inevitably turns into a 30-minute conversation about the pros and cons of communal living.” To delve deeper into the subject, she contacted architect Sier van Rhijn about his experience of designing Dutch co-living spaces during that period. “It was fun,” he explained, “even though [the occupants] had no experience designing living spaces, they were very engaged and very idealistic. As an architect, it was sometimes hard to deal with their ever-changing demands, and sometimes it drove us a little crazy.”

It was fun. Even though [the occupants] had no experience designing living spaces, they were very engaged and very idealistic. As an architect, it was sometimes hard to deal with their ever-changing demands, and sometimes it drove us a little crazy.” Sier van Rhijn, architect

Modern co-living can be traced back to thoughts emerging from Denmark in the 1960s, which crystallized in Bodil Graae’s 1967 newspaper article ‘Children Should Have One Hundred Parents’. There was a consensus at the time that modern housing was unable to provide adequate wellbeing for occupants over their lifetimes, and that ‘bofællesskab’ (living community) should instead be the aim for future housing projects. In 1972, a group of families were inspired to create the Sættedammen co-share, realized by architects Palle Dyreborg and Theo Bjerg. The project is generally accepted to be one of the first contemporary co-shares, favoring both autonomy from powerful landlords and the Danish government. The living community approach was introduced to the States in 1989 by Kathryn McCamant and Charles Durrett in their book ‘Cohousing: A Contemporary Approach to Housing Ourselves’.

Continue reading

Kevin Lynch Memorial Lecture

Space Syntax plug – but good read if you are not familiar with Space Syntax and its open source analysis tools and the theory behind them for urban spatial analysis and design

The power of the network

Slide 1      

Good evening. It’s a great honour to have been asked to give this evening’s Kevin Lynch Memorial Lecture, and a special honour to be doing so on behalf of Bill Hillier, who is unable to join us. Bill sends his best wishes to the Urban Design Group.

Slide 2      

First, I can’t do justice in the time available to the breadth and depth of Bill’s genius. And I use the word genius carefully. I believe, as do many others, that he is a genius.

I may only this evening touch on concepts that each deserve a more lengthy explanation and discussion. And, likewise, on the hundreds of urban planning and building design projects that Bill and Space Syntax have helped create over the past four decades.

But what I hope I will do is paint a picture of Bill’s achievement – albeit a personal one.

I…

View original post 6,600 more words

Spotting the Patterns: 2017 Trends in Design Thinking

via Spotting the Patterns: 2017 Trends in Design Thinking | Stanford Social Innovation Review

More insights in alternative design methodologies

Creative leaders and innovators are thinking about design thinking in more mature ways. Moving away from a sole emphasis on language and learning, they are increasingly focusing on questions of application, ownership, and impact.

(Illustration by John Kutlu)

Design thinking: It started as an academic theory in the 60’s, a notion of starting to look at broader types of challenges with the intention and creativity that designers use to tackle their work. It gained widespread traction as a product design process, has been integrated into culture change initiatives of some of the world’s most important organizations and governments, and has been taught in schools kindergarten to grad school. It’s been celebrated, criticized, merged with other methodologies, and modified for nearly every conceivable niche.

Regardless of what side of those perspectives you fall on, it’s undeniable that design thinking is continuing to grow and evolve. Looking across the social innovation landscape today, we see a few patterns that, taken together, suggest that social innovators continue to see great promise in design thinking. They are working to find ways to make it yield real performance gains for their organizations and clients.

From design thinking to design doing

Creative leaders have moved beyond increasing people’s awareness of design thinking to actively seeking concrete opportunities for using it. One of the principal drivers of this shift has been the need to demonstrate value and return on investment from design-thinking initiatives—something people have talked about for years. (Ever heard the question, “Is design thinking just the next fad?”) Social sector organizations, in particular, stand to benefit from the shift from design thinking to design doing. Timelines for getting things built in the social sector are often slow, due to legitimate constraints of responsibly doing impact work, as well as to legacy practices and politics. As long as organizations use design thinking responsibly and acknowledge the broader systems in which new ideas live, some of the emerging models can help them move projects along more quickly and gain greater stakeholder participation.

At The Design Gym, we have seen this eagerness for results show up in the form of Design Sprints—fast, iterative, user-focused project cycles that tackle a problem over the course of several days or weeks. Design Sprints emphasize seeing problems in smaller chunks, and encourage users and stakeholders to play a central role in problem solving, moving projects forward faster and cheaper than “business as usual,” and leading to more concrete and tested outcomes.

This year, our team led the FSG Impact Hiring Innovation Lab’s cohort of companies through design thinking sprints to gain insights from stakeholder groups, generate unique ideas, and prototype solutions. Such projects allow organizations to put design thinking to work on high-priority, strategic challenges. They often produce outcomes impressive enough to influence larger organizational and team design strategies, project scoping, and internal culture shifts—approaching problems with design thinking sometimes becomes the norm. We expect the next question for leaders who have seen the benefits of “design doing” will be how to continue designing their teams and cultures to show not tell—showing stories of real outcomes, not telling of their new training toolkit, and making design thinking more than a side-of-desk project.

Building cultures around design thinking

As design thinking has proliferated, many organizational leaders have moved from replicating the design thinking programs of academic institutions like the Stanford d.School or foundational agencies like IDEO to adapting the methodology to their own goals, external environments, and organizational cultures.

One organization that has particularly inspired us is Beespace, a New York City-based social-impact foundation. Beespace has designed a two-year program that helps new organizations not only get off the ground, but also create the conditions for breakthrough innovation. To create this program, which combines deep thinking, impact assessment, and rapid prototyping, Beespace’s leadership asked itself what tools it would need, and came up with a mix that included not just design thinking, but also disciplines of behavioral science and systems thinking, and tools stemming from emotional intelligence and theory of change.

This shift from replicating approaches to fashioning ones that serve a particular organization’s unique needs represents movement to a more mature, sustainable way of employing the methodology. It is a shift away from copying and pasting toward something more introspective, customized, and hopefully impactful. Leaders should not get too caught up in stories of success, but instead push their organization to dictate what success means and how it should show up. Given that these practices overlap so deeply with mission, people, organizational structure, and definition of impact, no two programs should look the same.

Empowering the few to shift the many

We have seen a lot of interest this year in “train the trainer” programs, particularly from organizations realizing the value of developing their internal capabilities to reduce reliance on outside consultants. Such development often entails focusing on the few people in the organization who are highly capable of instigating major change, as opposed to spreading awareness among the many. It takes time and resources, but the payoff is well worth it from both cultural and operational perspectives.

The Rockefeller Foundation’s 100 Resilient Cities initiative (100RC) takes such an approach to its mission of working with cities around the world to help them become more resilient. 100RC has focused on training a relatively small group of change agents, called Chief Resilience Officers (CROs), in the cities in which it works. CROs are senior-level city employees tasked with developing strategies and initiatives—with significant support and guidance from 100RC—to bring about long-term transformation.

Although the concept of developing internal advocates is surely not new, as an approach to adopting design thinking, it is generating a conversation we believe will continue to get smarter. We expect to see different models for building internal expertise, as the work of introducing design thinking into an organization can be done by lots of different people: expert facilitators, workshop trainers, creative leaders, designers and design strategists, or even just that brave soul who suggests approaching a 30-minute brainstorm slightly differently. We’re excited to see how different organizations explore the possibilities and find which ones work best for them.

Looking at the creative community holistically to tackle larger societal issues

No beating around the bush here—it’s quite a political climate here in the United States. But, out of this has come an absolute groundswell of creative activism and some really unexpected collaborations. Among the creative community, the boundaries around problems that fit within our scope of work have expanded. Individuals, nonprofits, government agencies, start-ups, and huge corporations alike are asking what it means for them, where they can (and should) put a stake in the ground, and who else out there can help make it happen.

Over the past few years, there’s been greater cross-pollination between different industries and types of organizations—collaboration that’s creating wild innovation bigger than either political party could achieve on its own. As Paola Mendoza, artistic director for the Women’s March on Washington, recently said, “We, artists, inspire people to love when it is easier to hate.” Now is the time to begin looking beyond our traditional boundaries of for-profit vs. nonprofit, public sector vs. private sector, and one mission vs. another. The time is ripe to call for collaborators rather than competitors to tackle some of the larger creative challenges facing society today.

FSG Impact Hiring Innovation Lab, for instance, is bringing together nonprofits such as The Aspen Institute, Fortune 500 companies such as McDonald’s and T-Mobile, and creative agencies like ours to develop innovative strategies in hiring, retention, and advancement of opportunity youth and other populations facing barriers to employment.

We anticipate that collaboration between governments, nonprofits, individuals, corporations, and startups will continue to increase. And, there are few greater motivators than a sense of passion and purpose—something individuals and organizations alike can amplify to energize their cultures. We have yet to see what true beauty can blossom from these dynamic and often trying times. What we do know is that complex problems require new ways of thinking, new ways of working, new types of partnerships and conversations, and radical forms of diverse collaboration. And the creative catalysts inside all of us are best positioned to address them.

Shifting the storyline

Social innovators have begun thinking about design thinking in more mature ways. As some of the concept’s novelty wears off, the social sector is increasingly focusing on questions of application, ownership, and impact. The theme of the story is shifting from “What is design thinking?” to “Look at what we did using design thinking.” For practitioners and creative leaders, it is a good time to ask what these trends mean for your ability to tell your own future success stories.

The New Science of Designing for Humans

via The New Science of Designing for Humans | Stanford Social Innovation Review

Beyond Human Centred Design methodologies using behavioural science is proposed as more rigorous way to extend solution based design

The days of privileging creativity over science in design thinking are over. The rise of behavioral science and impact evaluation has created a new way for engineering programs and human interactions—a methodology called behavioral design.

(Illustration by Mike Austin)

Today the design of things that involve human interaction, such as programs, product delivery, and services, is more art than science. Here is how it typically works: We use our creativity to brainstorm a few big ideas, experts decide which one they like, and then investors bet on the winner, often with billions of dollars at stake.

This way of design thinking should be replaced by a superior method that can enable us to innovate with more success and less risk. Specifically, we can use scientific insights to generate new ideas and then systematically test and iterate on them to arrive at one that works.

Advances in two academic fields afford this opportunity. The first is behavioral science, which gives us empirical insights into how people interact with their environment and each other under different conditions. Behavioral science encompasses decades of research from various fields, including psychology, marketing, neuroscience, and, most recently, behavioral economics. For example, studies reveal that shorter deadlines lead to greater responsiveness than longer ones,1 that too much choice leads people to choose nothing,2 and many more observations, often counterintuitive, about how people react to specific elements of their context.

The second academic field is impact evaluation. Economists have used randomized controlled trials (RCTs) and other experimental methods to measure the impact of programs and policies. Such impact evaluations are becoming more and more common in the social sectorand in government. These methods allow us to test whether an innovation actually achieves the outcomes that the designer sought.

Taking a scientific approach also solves another common problem: Sometimes we do not even realize that there is something in need of rigorous, thoughtful design. When we look carefully, the success of most of what we design for people depends as much, if not more, on the human interaction as on the physical product. For example, the first iPhone offered essentially the same functions (phone, calendar, address book, etc.) as a BlackBerry, but it totally changed the experience of using those functions.

In the social and public sectors, programs and services are made up largely of human interactions. And yet anything involving human interaction can be designed more scientifically, and more successfully, when behavioral science and impact evaluation are applied. For instance, a vaccine is a technological product, but how and when parents get their children vaccinated, and how they are reminded to do so, is as much a part of the innovation as the vaccine itself. Poorly designed interactions make products less successful and can also underlie serious social problems.3

By putting behavioral science and impact evaluation together—a methodology we call behavioral design—we can design more like engineers than like artists. We can use behavioral science to develop ideas that are much more likely to work than those relying entirely on intuition. And we can rigorously test those ideas to determine which ones truly work. Following the model of engineering and scientific progress, we can build on prior success to make enormous advances that, under previous approaches, would not be possible.

A Better Methodology

At ideas42, the behavioral science innovation lab I co-lead, we encounter many different approaches to innovation among our partners. I have also spent considerable time comparing notes with experts in design thinking, attending design workshops, and reading about design methodologies. The typical approaches for innovation range from quickly brainstorming some ideas in a boardroom to using some version of human-centered design (HCD). Fundamentally, all of these approaches aim to generate “big ideas” that appeal to the intuition of a few decision makers considered experts in the area where the idea is to be implemented.

HCD appears to be the methodology of choice for a significant, and growing, number of organizations. The most advanced version begins with defining the problem or design mandate, and then conducts qualitative research with potential users and proceeds through a series of structured exercises to promote creative thinking. The design team may also test some crude prototypes to get feedback along the way. This approach is called “human-centered” because it focuses on users’ and other stakeholders’ needs and preferences.

In the qualitative research phase, designers use ethnographic techniques such as qualitative interviewing and observation. They not only interview potential users but also may talk to others, such as program administrators and front-line staff involved in delivering a program or product. In the design phase, HCD employs several techniques to enhance creativity (which remain useful in the next-generation behavioral design methodology as well). Finally, HCD ends with trying a few prototypes with a handful of potential users. Some ethnographic research methods are incorporated into HCD, but on the whole the approach is still much closer to an art than a science.

It is time to build on HCD with a better method. Let us begin our investigation by comparing how engineers invent new technology. Two features stand out. First, engineers rely on a rich set of insights from science to develop new ideas. Every invention builds on countless previous attempts. For example, the Wright brothers are credited with inventing the airplane, but the key parts of their design leaned on previous inventions. The wing was based on science that went back to 1738, when Daniel Bernoulli discovered his principle about the relationship between pressure and the speed with which a fluid is moving. The engine design was borrowed from automotive engines invented more than 25 years earlier. They were able to test model wings in a wind tunnel thanks to Frank H. Wenham, who had invented that critical apparatus 30 years before that, in 1871.4

Second, contrary to popular belief, inventions do not come simply from a single flash of insight, but rather from painstaking refinement in small steps. Sir James Dyson, the famous vacuum cleaner tycoon, went through 5,126 failed iterations of his new wind tunnel design to separate dirt from air before he landed on the right one.5 Inventors sometimes iterate only on particular components before working on the complete invention. For example, the Wright brothers tested some 200 wing designs in a wind tunnel before settling on the right one.

Why do engineers work so differently from those of us who are designing for human interactions? Until recently, we did not have a sufficiently large body of scientific insights that describes how humans interact with their environment, and each other, under different conditions. True, the field of user-experience design offers some insights, but it is very new and is still restricted to certain elements of digital interactions such as Web-page layout and font size. Direct marketers within for-profit businesses have experimented with letters and phone scripts for years, but those findings also cover a very narrow set of interactions and are often not public.

The second engineering feature—experimenting and iterating—is also hard to replicate, because measuring whether something “works” in this case is more complex than simply turning on a piece of technology and playing with it. We must first clearly define what outcomes we want from the design, devise a way to measure them, and finally run a test that reliably tells us whether our design is achieving them

More Rigorous Testing of Ideas

The problem with HCD and similar approaches to innovation is that they depend too much on intuition. Research has repeatedly shown that our intuitions about human beings are often wrong. Take the commonsensical idea that penalties always help prevent people from engaging in bad behaviors; this notion may have intuitive appeal, but it has proven false. For example, in a study of Israeli day-care centers that sanctioned parents for being late to pick up their children, researchers found that penalties made parents even more likely to be late.6 This is because they viewed the penalty as a cheap price for the option to be late, versus feeling bound by a social obligation to be timely.

Not only do the social and behavioral sciences give us better starting points, but it also enables us to prototype and test ideas more readily, because we can measure if they are working using impact evaluation methods as well as lab testing procedures from experimental psychology. We can then iterate and improve on the idea until we have a solution ready for implementation.

The behavioral design methodology incorporates HCD’s fundamental approach of being human centered and thoughtful, but adds scientific insights and iterative testing to advance HCD in three significant ways. First, it applies observations about people from experimental academic research. HCD’s reliance solely on self-reported and intuitive insights presents a risk, since so much human behavior is unconscious and not transparent. Also, psychology research shows that people’s self-perception is biased in several ways.7 When we do supplement academic insights with qualitative research, we can use behavioral science to make the latter less vulnerable to bias. For example, we can get more unvarnished answers by asking subjects what their peers typically do rather than what they themselves do. When asked about themselves, subjects may be embarrassed to admit to certain behaviors or may feel compelled to give what they assume the interviewer thinks is the “right” answer.

Second, behavioral design can enhance HCD in the design phase. The behavioral science literature can contribute ideas for solutions based on previously tested interventions. As behavioral design becomes more widely used, more and more data will become available on what designs work and under what conditions. In filtering ideas, we can use behavioral science to anticipate which solutions are likely to suffer from behavioral problems such as low adoption by participants or misperception of choices.

Third, this new approach improves upon HCD by adding more rigorous testing. Many HCD practitioners do test their ideas in prototype with users. While helpful, and part of behavioral design as well, quick user testing cannot tell us whether a solution works. Behavioral design leverages experimental methods to go much further without necessarily adding considerable cost or delay.

Using this approach, we test whether something works—whether it triggers a desired behavioral result—rather than whether the subject thinks something works. We can also test a single component of more complex designs, such as whether a particular piece of information included on a Web page makes a difference, in a lab setting with subjects from our target audience. This is analogous to aeronautical engineers testing wing designs in wind tunnels. By testing and iterating in the field, we do not need to bet on an untested big idea but instead can systematically develop one that we know works. Testing is also what makes it possible, in the design phase, to build on previous successful ideas.

ideas42’s work includes many examples of using behavioral design to invent solutions to tough social problems. For example, we recently worked with Arizona State University (ASU) to encourage more eligible students to apply for a special federal work-study program called SEED. In fall 2014, before we started working with ASU, only 11 percent of eligible students were applying for SEED jobs, leaving nearly $700,000 in financial aid funds unused. ASU wanted our help to increase this proportion.

Diagnosing the problem through a behavioral lens, and interviewing students and staff, we learned that students mistakenly believed that SEED jobs were menial and low-wage. Some thought that a work-study job would interfere with their education rather than complement it. Others intended to apply but missed the deadline or failed even to open the e-mail announcing the program. We designed a series of 12 e-mails to attempt to mitigate all of these barriers. The e-mails dispelled the misperceptions about workstudy jobs by stating the correct facts. They made the deadline more salient by reminding students how many dollars of aid they stood to lose. Behavioral research shows that losses loom larger than gains, so the loss framing promised to be more impactful than telling students how much they stood to gain. The e-mails asked students to make a specific plan for when they would complete the work-study job application to reduce the chance that they would forget or procrastinate past the deadline. These behaviorally informed e-mails were compared against a control group of 12 e-mails that contained only basic information about how to apply to the SEED program.

With the redesigned e-mails, which ASU has now adopted, 28 percent more students applied for jobs, and the number of total applications increased by 56 percent. As we were sending 12 e-mails, we used the opportunity to test 12 different subject lines to try to maximize the number of students who opened the e-mail. In five out of the 12 cases, the rate of opening increased by 50 percent or more, relative to a typical subject line. A subject line that increased the open rate from 37 percent to 64 percent made students feel special: “You have something other freshmen don’t.” The control in this case was commonly used language to remind the recipient of impending deadlines: “Apply now! SEED jobs close Thursday.”

The Behavioral Design Methodology

Efforts like this one may sound like nothing more than trial and error, but a systematic and scientific process underlies them that tracks the success of engineering or medicine more closely than HCD. It begins with defining a clear problem, diagnosing it, designing solutions, testing and refining the effectiveness of those ideas, and then scaling the solutions.8 It also starts from a body of knowledge from behavioral science, rather than intuition and guesswork, so that the solutions tried are more likely to succeed.

Let us take a closer look at these steps:

1. Define. The first step is to define the problem carefully to ensure that no assumptions for causes or solutions are implied and that the desired outcome is clear. For example, organizations we serve commonly ask: “How do we help our clients understand the value of our program?” In this formulation, the ultimate outcome is not explicitly defined, and there is an assumption that the best way to secure the outcome is the program (or product) in question. Say the relevant program is a financial education workshop. In this case, we do not know what behaviors the workshop is trying to encourage and whether classroom education is the best solution. We must define the problem only in terms of what behaviors we are trying to encourage (or discourage), such as getting people to save more.

2. Diagnose. This intensive phase generates hypotheses for behavioral reasons why the problem may be occurring. To identify potential behavioral hurdles, this approach draws insights from the behavioral science literature and what we know about the particular situation. For example, in the ASU work-study project, we hypothesized that many students intended to apply but failed to follow through because they procrastinated past the deadline or simply forgot it. Both are common behavioral underpinnings for such an intention-action gap.

After generating some initial hypotheses, the next step is to conduct qualitative research and data analysis to probe which behavioral barriers may be most prevalent and what features of the context may be triggering them. Here, “context” refers to any element of the physical environment, and any and all experiences that the consumer or program’s beneficiary is undergoing, even her physical or mental state in the moment.

Qualitative research usually includes observation, mystery shopping (purchasing a product or experiencing a program incognito to study it firsthand), and in-depth interviews. Unlike typical qualitative research that asks many “why” questions, the behavioral approach focuses on “how” questions, since people’s post-hoc perceptions of why they did something are likely to be inaccurate.

3. Design. Having filtered down and prioritized the list of possible behavioral barriers via the diagnosis phase, we can generate ideas for solutions. Here many of the structured creativity techniques of HCD prove useful. When possible, it is best to test a few ideas rather than to guess which solution seems best. Solutions also change during their journey from the whiteboard to the field, as numerous operational, financial, legal, and other constraints invariably crop up. Such adaptations are critical to making them scalable.

4. Test. We can then test our ideas using RCTs, in which we compare outcomes for a randomly selected treatment group vis-à-vis those for a control group that receives no treatment or the usual treatment. Although RCTs in academic research are often ambitious, multiyear undertakings, we can run much shorter trials to secure results. An RCT run for academic purposes may need to measure several long-term and indirect outcomes from a treatment. Such measurement typically requires extensive surveys that add time and cost. For iterating on a design, by contrast, we may only measure proximate indicators for the outcomes we are seeking. These are usually available from administrative data (such as response to an e-mail campaign), so we can measure them within days or weeks rather than years. We measure long-term outcomes as a final check only after we have settled on a final solution.

When RCTs are impossible to run even for early indicators, solutions can be tested that approximate experimental designs. A more detailed description of these other methods is outside the scope of this article but is available through the academic literature on program evaluation and experimental design.

If the solution is complex, we first test a crude prototype with a small sample of users to refine the design.9 We can also test components of the design in a lab first, in the way that engineers test wing designs in a wind tunnel. For example, if we are designing a new product and want to refine how we communicate features to potential users, we can test different versions in a lab to measure which one is easiest to understand.

5. Scale. Strictly speaking, innovation could end at testing. However, scaling is often not straightforward, so it is included in the methodology. This step also has parallels with engineering physical products, in that designing how affordably to manufacture a working prototype is, in itself, an invention challenge. Sometimes engineers must design entirely new machines just for large-scale manufacturing.

Scaling could first involve lowering the cost of delivering the solution without compromising its quality. On the surface, this step would be a matter of process optimization and technology, but as behavioral solutions are highly dependent on the details of delivery, we must design such optimization with a knowledge of behavioral principles. For example, some solutions rely on building a trusted relationship between frontline staff and customers, so we would not be able to achieve a cost reduction by digitizing that interface. The second part of scaling is encouraging adoption of an idea among providers and individuals, which itself could benefit from a scientific, experimental process of innovation.

A Closer Look at the Methodology

To be fair, it is sometimes impossible to go through the full, in-depth behavioral design process. But even in these cases, an abridged version drawing on scientific insights rather than creativity alone is always feasible. Notice that the define, diagnose, and design stages of the behavioral design process apply the scientific method in two ways: They draw on insights from the scientific literature to develop hypotheses, and they collect data to refine those hypotheses as much as possible. The first of these steps can be accomplished even in a few hours by a behavioral designer with sufficient expertise. The second component of data collection and analysis takes more time but can be shortened while still preserving a scientific foundation for the diagnosis and design. Field testing with a large sample can be the most time-consuming, but lab tests can be completed within days if time is constrained.

Two sorts of hurdles typically confront the full behavioral design process: lack of time and difficulty measuring outcomes. In our experience, time constraints are rarely generated by the problem being addressed. More often, they have to do with the challenges of complex organizations, such as budget cycles, limited windows to make changes to programs or policies, or impatience among the leadership. If organizations begin to allocate budgets for innovation, these artificial time constraints will disappear.

To better understand working under a time constraint, consider ideas42’s work with South Africa’s Western Cape to reduce road deaths during the region’s alcohol-fueled annual holiday period. The provincial government had a small budget left in the current year for a marketing campaign and only a few weeks until the holiday season began. The ideas42 team had to design a simple solution fast; there was no time to set up an RCT with a region-wide marketing campaign. The team instead used an abridged version of the first three stages to design a solution grounded in behavioral science. Quick diagnosis revealed that people were not thinking about safe driving any more than usual during the holidays, despite the higher risk from drunk driving. To make safe driving more salient, ideas42 designed a lottery in which car owners were automatically registered to win but would lose their chance if they were caught for any traffic violations. That design used two behavioral principles coming out of Prospect Theory,10 which tells us that people tend to overestimate small probabilities when they have something to gain, and that losses feel about twice as bad as the equivalent gain feels good.

Applying the first principle, we used a lottery, a small chance of winning big, rather than a small incentive given to everyone. Using the second, we gave people a lottery ticket and then threatened to take it away. Since an RCT was not feasible, we measured results by comparing road fatalities in the treatment period with road fatalities in the same month of the previous year; this showed a 40 percent reduction in road fatalities. There were no known changes in enforcement or any other policies. While ideas42 was not able to continue to collect data in subsequent years, because its contract ended, the program saw success in subsequent years as well, according to our contacts in government.

Adopting Behavioral Design

If you were convinced of behavioral design’s value and wanted to take the leap, how would you do it? There are resources available, and many more are still in the works. Behavioral insights are not yet readily available in one place for practitioners to access, but are instead spread out over a vast literature spanning many academic disciplines, including psychology, economics, neuroscience, marketing, political science, and law. Results from applications of behavioral science are even more distributed because many are self-published by institutions such as think tanks, impact evaluation firms, and innovation consultancies.

To mitigate this problem, ideas42, in partnership with major universities and institutions that practice behavioral design in some form, is building an easily searchable Web-based resource as well as a blog that will make it possible to find ready-to-use behavioral insights in one place. In the meantime, some of these organizations, including ideas42, also offer classes that teach elements of behavioral design as well as some key insights from behavioral science that practitioners would need in order to do behavioral design. As the practice of behavioral design is adopted more widely, and its use generates more insights, it will become more powerful. Like technology, it will be able to continue to build on previous discoveries.

Organizations and funders would also do well to adopt the behavioral design approach in their thinking more generally. Whenever someone proposes a new approach for innovation, people scour the methodology for the secret sauce that will transform them into creative geniuses. In this case, the methodology applications of behavioral science, in themselves, do have a lot to offer. But even more potential lies in changing organizational cultures and funding models to support a scientific, evidence-based approach to designing interventions. Here are three suggestions about how organizations can adopt behavior design:

Fund a process (and people good at it), not ideas. | Today’s model for funding innovation typically begins with a solution, not a problem. Funders look to finance the testing or scaling up of a new big idea, which by definition means there is no room for scientifically analyzing the problem and then, after testing, developing a solution. Funders should reject this approach and instead begin with the problem and finance a process, and people they deem competent, to crack that problem scientifically. To follow this path, funders must also become comfortable with larger investments in innovation. The behavioral design approach costs a lot more than whiteboards, sticky notes, and flip charts—the typical HCD tools—but the investment is worth it.

Embrace failure. | In a world where ideas are judged on expert opinion and outcomes are not carefully measured, solutions have no way of failing once they leave the sticky-note phase and get implemented. In a new world where ideas must demonstrably work to be successful, failure is built into the process, and the lessons learned from these failures are critical to that process. In fact, the failure rate can serve as a measure of the innovation team’s competence and their bonafide progress. To be really innovative, a certain amount of risk and courting failure is necessary. Adopting a process that includes failures can be hard to accept for many organizations, and for the managers within those organizations who do not want their careers to stall; but as in engineering and science, this is the only way to advance.

Rethink competitions. | The first XPRIZE for building a reusable spacecraft rekindled the excitement for competitions, which have now become common even outside the technology industry. However, competitions to invent new technology are fundamentally different: With a spacecraft, it is relatively easy to pick the winner by test-flying each entry. In the social sector, by contrast, competitions have judging panels that decide which idea wins. This represents a big-idea approach that fails to motivate people to generate and test ideas until they find one that demonstrably works well, rather than one that impresses judges. Staged competitions could work much better by following a behavioral-design approach. The first round could focus on identifying, or even putting together, the teams with the best mix of experience and knowledge in behavioral design and in the domain of the competition. Subsequent rounds could fund a few teams to develop their ideas iteratively. The teams whose solutions achieved some threshold of impact in a field test would win. Innovation charity Nesta’s Challenge Prize Centre has been using a similar approach successfully, as has the Robin Hood Foundation, with the help of ideas42.

Revolutionizing how we innovate presents a huge opportunity for improving existing programs, products, and policies. There is already sufficient scientific research and techniques to begin making the change, and we are learning more about how to better devise things for human interactions every day. The more we use a scientific approach to innovate, and construct platforms to capture findings, the more science we will have to build on. This immense promise of progress depends on changing organizational cultures and funding models. Funders can and must start to bet not on the right “big ideas” but on the right process for solving challenges and on the people who are experts in that process. They must also not just expect failures, but embrace them as the tried and true means for achieving innovation.

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