Your organization invents something no one else does (as well, yet). The rest of the process goes like this: I have this tail. I put it on the donkey. I spend money testing and fixing the tail to get it closer to what the donkey wants it to do. I also spend money on marketing and sales people to convince the donkey I have what it needs.

Why do we waste money like this? It’s very easy to get caught up in the excitement of innovation. Most of us hear about something that can be done and adore taking it one step farther. Example: technology is able to discern between voices speaking? Why not make a mobile app that can measure the give-and-take in a conversation? Never mind the fact that the app would be an awkward contribution to any conversation, even if used covertly. The initial perception to seeing the results probably be “Hey, cool gadget!” or “Do you think I talk too much!?!?” Ironically, it would be a great application to use for ourselves as we practice running these deep conversations with possible customers using as few words as possible. But who were the designers empathizing with when they designed the talk-o-meter?

Often we receive a command from someone like, “figure out a cool way to mash up these two huge databases about London that’s visually interesting.” I encourage you to push back on the command a little and perfect it into something involving your empathy for people. “Figure out a visually interesting way for people who are moving to London to explore which neighborhood to live in.” This empathic perspective might require more than just the original mega-databases specified in the original request. In addition to housing prices and commute times, you will want to allow folks to choose crime history, traffic flow, noise and air pollution sources, special tax zones, income levels, school scores, restaurant reviews and ages, tree counts, architectural types, or frequency of art galleries or non-franchise cafés— whatever is important to them. All this information does exist as data. Now each person can identify their own unique considerations when exploring neighborhoods in a city. Now you are designing with a person as your primary concern, rather than letting data or technology limit your thinking.

Leaders want to see how well an idea works before investing time and money developing it. Leaders don’t want to waste resources. They want to feel confident. They want their investors to feel confident, and their employees to feel confident. They want to know the organization has done everything possible to ensure success and done everything possible to discover concealed opportunities.

Notice the focus on the organization, almost forgetting about the people the organization serves.

Leaders are all about making the organization successful. Organizations, in turn, are all about making their customers successful. Or that’s how it’s supposed to be. Frequently leaders seed the organization with organization-focused goals, and the people you are trying to help become secondary.

Notice, too, that fear of failure and desire for confidence are emotions. The leaders I know would be unlikely to say, “I guide this organization based on emotion.” Instead, most leaders focus on knowledge that will create a feeling of confidence, and frequently this gets defined as statistics, numbers, graphs, and projections.

Don’t fight this. Empathize and turn your insights into valuable material for him or her.

We’ve all heard the word “fluffy” associated with qualitative knowledge. If quantitative research is seen as producing reliable, incontrovertible facts, then qualitative research is seen as the opposite—the soft, made-up, inapplicable knowledge. You’ve probably observed this tacit “definition” a few times. How do we convince people it isn’t true?

The dictionary says quantitative is “measurement describing quantity, as in cost, members, or ages.” Qualitative is “distinctions based on relative characteristics.” Qualitative research involves descriptions, rather than numbers, because the data can be observed, but not measured. For example, in many projects I have observed participants talking about how they distrust sales people and marketing materials because it’s all predicated on “getting money out of me. Of course they’re going to say it’s wonderful and will make my life better. They don’t really know whether it will work for my particular circumstances. What they promise may not be true for me.” There is no way to put a number on that description. Yet it is an observable trend, a philosophy of doubt that many people follow in their evaluation and purchasing process. This trend should not be ignored simply because it cannot be represented by a measurement.

Stories are data with soul

Here’s another way to see the value of qualitative data. Dr. Brené Brown is the author of The Gifts of Imperfection and in a 2010 TED Talk, she has an interesting definition which you can use to persuade people away from strictly quantitative research. She says, “Stories are just data with soul.” I like that phrase. It references both the descriptive, rather than numeric, aspect of qualitative knowledge. And it references empathy. When you can walk in the shoes of other person, make decision like they make decisions, react like they react, then you have gotten in touch with the soul of their being.

Getting outside our routine surroundings takes a little effort. You have to ask for names of people to talk to and find out if they’re willing to talk to you. Much of this can be done by recruiters or social media these days, but I swear you have to get out and talk to people. Don’t let a glass pane materialize between you and the participant (read: camera lens, laptop screen, touch screen). Technology puts us at a remove from the people we want to empathize with. Conversation puts us in their head. When someone suggests, “Set up two video cameras, one at regular speed and one on time lapse to try to find patterns in behavior, and then do some casual shadowing observations without the cameras,” it smacks of being too caught up in the researcher/analyst role. You can only guess at what is going on inside people’s minds and hearts. You must ask them and listen to their stories to find out for sure.

How do we do this comfortably? Harness your natural curiosity about the way other people think. You like making things better—but for whom? Question yourself. Usually you can make things better based on your own perspective, but to understand someone else’s perspective you need to do more than observe and interpret.

Paying full attention to someone makes them feel good. In my experience, people from all sorts of countries and professions will respond to me with more and more detail when they realize I am only thinking about them. They are willing to unfold their thought processes to me; some people even express revelations in the process of explaining themselves. Nearly everyone ends the session thanking me for such a good discussion.

I love doing this. I have developed a practice of getting people to tell me stories at gatherings that have nothing to do with work, like at a food court in a mall. I’ll be standing next to someone in line, for instance, and make some comment about the circumstances or about what they are wearing or carrying. I’ll listen and ask for more detail. I’ll find out why they reacted some way or why they made some decision. Within a few minutes a complete stranger will feel comfortable enough to explain a story to me. We are, of course, in the relative safety of a gathering, which helps. But the fact that I am concentrating on their answers, rather than trying to make a point of my own or trying to count out money for my lunch bill, makes that person feel a little cherished. I practice this in unofficial settings so that I’ll be skillful when interviewing people for generative research.

Other divisions at your organization may have to be introduced to the preceding idea of generative research. The definition of generative is “capable of creating.” Compare the definition of evaluative, “judging the quality or value,” and you can see the clear difference between the type of knowledge gained from either type of research. Generative research is a collection of knowledge about people who might potentially use your services or products, but might not. It is neutral to any products or services. Instead, generative research focuses on internal reasoning while a person does something of particular interest to your organization. This knowledge helps your team produce better ideas, more on track with people’s real life situations. The knowledge gives you empathy.

Generative research works hand-in-hand with evaluative research as a part of a cycle that keeps risk, concealed opportunities, and wasted investment at bay. To start the cycle, begin building empathy with a particular subset of the people your organization is interested in. Paper the walls (or the virtual walls) with the knowledge you gather. Feather your nest. I particularly like that phrase because your nest is where you create, prepare, correct, groom your offspring—the products and services you offer. You do your best work in your nest, nourished by the empathy you have of the people you are supporting. (Some teams bring those people in to their nest, or go out to them, and ask them to assist in the creation process. That’s participatory design.)

Once you have an idea you believe is viable, take it out into the world. Evaluate whether your idea does a good job of supporting the people you have identified, making them successful. This second part of the cycle gives you knowledge about where the idea needs adjusting, so back into the nest you go, again drawing on your empathy to improve the design. After the design is improved and seems likely to be successful for everyone, develop it. Invest the money and get it out there.

Then extend your empathy to include another subset of people that your organization is interested in. Add more knowledge to the walls of your nest. Create more ideas. Go out and judge how well those ideas work, adjust them, and then develop them with less risk. And so on.

How many times have you wished that you could really make a difference at your organization? If only you had the time to perform all that analysis or the budget to actually do some field research or the recognition and trust to lead multi-department participatory design sessions? In real life, the amazing stories you see presented at conferences don’t seem to get off the ground back home. Well, here’s a story of a user experience practitioner who saw a way to quickly pull together different materials into a cohesive, convincing whole. Within a few months of being “the new guy” just hired in, he managed to wake up his company. His name is Boris Chong. He works at the headquarters of one of the big-box stores in the US.

It was November 2009 when Boris joined the headquarters dot-com team in the newly minted role of User Experience Strategist. He had previously worked as a director at an online company overseeing information architects, creatives, and usability folks. At this point, Boris had been obsessed with getting science and data to further percolate through the product design process. He had been trying to bring more research into the process in recent years, and when he was faced with the opportunity that the big-box company was offering, he jumped at it.

“I was lucky,” he says, “Here I literally walked into a treasure trove of data. Not just raw data—analyzed data. I went through probably 10-15 PowerPoint decks of conclusions from merchandising research that had already been completed.” The decks were created by the corporate research group (and a few outsourced vendors) who does ongoing marketing support research. There was also one ethnographic research project done by a vendor just before Boris joined the team. Boris’ dream was to marry the quantitative, demographics type of marketing data to the qualitative, contextual inquiry data and make it more usable in design sessions. As many folks working for large merchants have observed, “We have so much data sitting out there not really getting used in the design process.”

A Strategic Roadmap

He also wanted to execute on the UX strategy handed to him, making the data more strategic to the company, to plot a path forward enabling the business to offer support more closely knit with actual customer needs.  Some good thinking had already been done and handed to Boris when he came on board, but there had been a couple of failed attempts at executing because the crucial DNA  behind the strategy had not been properly infused into the design and the team. “The good data was there, but not the story. A mental model was the right way to tell the story,” Boris concluded.

The group wanted to start building something, and they wanted release plans. So Boris did some heavy lifting. He took over an empty Vice President’s office and filled the walls with 3×5 cards and sticky notes, breaking down the conclusions from the many quantitative studies into discrete concepts. He admits that part was really hard work. Luckily, the folks who did the contextual inquiry had created a sequencing model and an affinity model which made the qualitative data feed into the mental model cleanly. “I didn’t do the work collaboratively because the analysis was already done. What I had to do was see how I could pull it together as the top part of a mental model. It was kind of a one-person job,” he explains. Everyone was interested in the process. They kept stopping by the office, gaping at all the notes on the walls, and asking what he was up to. Boris would explain his method. As more and more people stopped by, they developed a nickname for him: Nash … as in John Nash the mathematician from the movie A Beautiful Mind. He could look at all the data points on the wall and pull them together.

People were thrilled when three mental models rolled out of that office—each one ten to twelve feet long. “I put the data into spreadsheets and used the mental model script to generate the initial versions. It worked great!” In six months, Boris pulled together three mental models from existing, analyzed data that the company already possessed.

“After I finished the top parts of the mental models, that’s when I got collaborative.” He had slotted only a few existing features under the behavior towers in the model. Boris would roll up the scroll of paper and take it with him to meetings. All the disciplines would gather in the room together—the user interface guys, designers, and business team and they would start to add services and features and content below the line, aligned with the behavioral towers in the model that they supported. The group would include new ideas and things to ask the vendor for. Then Boris would organize all these items into layers according to whether they were interactive widgets, reading material, merchandising connections, or had to do with in-store or mobile situations instead of strictly online.

Finally the organization had a picture of what they were doing. In the one mental model, here were all the bright, shiny ideas folks had and how they came into play for the customer—or not. The team even added some dull, boring ideas that no one had bothered to imagine but that the customer really needed. Boris was able to line up all the touch points with the customer—from conception purchase—with activity online, in the store, and with mobile applications. The team could suggest places where an online account could be available in-store or triangulate how a customer might look for things in different ways.

Now we can start building the right things first.

In addition, Boris helped the team prioritize the ideas and updates into three phases. “I really like what Jeff Patton has to say about iterative releases and card-storming to get at what we need to deliver first,” says Boris. So he color coded each item below the line in the mental model for Phase One, Phase Two, and Phase Three. It was much easier with the model to get people to understand why a particular item was in Phase Two and not Phase One because they could see the most important user needs and the gaps that needed filling first.

Walk the Wall

The design process is underway. As the team creates wireframes to represent certain online experiences, they take the wireframe and “walk the wall along the mental model.” They make sure they have met the need of each item listed using the model as a guidepost and driver. As features are vetted by IT and the rest of the organization the model helps to inform tradeoffs, keeping the user’s needs at the forefront of decision making process.

A Thin Layer

Tactically, Boris also wanted to fix the way the online site was structured and written. “They’ve not yet fully taken advantage of leveraging libraries, components, and templates,” Boris observes. So he added a thin layer just below the line in the mental model to mark out what types of online templates could be used in support of the towers. This addition to the mental model reminds designers of other opportunities for serving customers. There is an opportunity to support a customer in the initial stage of a purchase. Perhaps she’s shopping for a refrigerator. Maybe she needs a bigger refrigerator because her family has grown or because she has started shopping for locally grown produce at farmers markets. Or perhaps she is worried that her current 17-year-old refrigerator might break down soon. “We can create some context for this. We can have an article about why you should replace an appliance before it breaks.” Boris also says that in addition to merchandising and marketing opportunities that can pop up in templates, the team can explore things like teaching customers about warranties earlier in the process. Listing the templates in the mental model helps designers remember other prospects and perspectives.

Opening Eyes Outside of the Dot-Com Division

Boris was eager to show the mental models to the store operations guys. “The first time we got these mental models in front of people outside of dot-com, I saw them have that ah-ha moment!” The guys said this was the first time they had seen it all in one place, made actionable, and aligned with offerings already in place. And they could see that, yeah, there were gaps. The store operations guys said the data agreed with what they had found—it was the same stuff, but presented differently. Right away they could see how to align merchandising opportunities and future content they were thinking of. They could see how what they were experimenting with for mobile would weave in to the model.

Senior management outside of dot-com had a similar reaction. Boris relates their words as, “Wow, this is really actionable now.”

Boris says in summary, “It’s interesting, from that aspect, that regardless of the data and the business, the mental model is successful in opening eyes.”

Where Next?

The dot-com management came to Boris recently asking to create a site supporting a new audience segment. Boris knew he needed another mental model to understand this audience segment, but there were no existing studies—and management said he has to release the new site in a few short months. So he looked at emerging work being done outside of the company and pulled a team together who had experience with the behavior of these particular people. Looking at each mental space in the mental models they already had, they asked themselves, “How would this re-apply to the new audience segment?” Boris grins, “Maybe this is cheating, but you do what you can with what you got.” What they got was a good sketch of behaviors to use as a new mental model.

They rounded up a collection of products that support the needs of the new audience segment. They slotted items below the line that would focus on enabling the audience segment to achieve what they wanted to do. They marked the ideas into three phases. “IT told us they couldn’t build half of the ideas, but we at least have a good road map now,” Boris chuckles.

Another project Boris is trying to get closer to is a research project another team is doing on store associates—the people who play the role opposite the customer helping them make decisions in the store. Boris wants to be able to juxtapose the store associate behaviors with the customer behaviors and see if everything aligns.

“You can’t do it all at once,” he muses. “Going forward we would like to do more formative research. I just don’t have the bodies to do that now, though.” Boris is building the user experience discipline and getting more user interface designers on the team. He is outsourcing more usability testing and moving to online remote usability. At some point, he envisions reaching across channels at the company and teaching everyone how to pull together mental models. “I want to teach them how to fish, so they don’t have to rely on me.”