Stop Visualizing Data!

You work in a small company that has a program to help consumers manage their health. Your basic product involves a mobile app for tracking daily events and a personalized dashboard. For a monthly subscription users can also get access to coaching and other resources.

There’s a meeting with a potential investor on the calendar and you want to use data to support your story that things are going well. So, you open up Excel and start digging through the data you have.

Finding the Story

You got some nice local news coverage back in March and you signed your first partnership in June, both of which resulted in a spike of app downloads. So, you look at that.

1-downloads

Well, that’s something, but it doesn’t really communicate the excitement of the last few months. You remember that a lot of those downloads in the spring never turned into even free accounts. So, you decide to look at new accounts instead of downloads.

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That looks more like what you were expecting. Whereas the app downloads spiked in March, the new accounts hit a peak in July. Comparing the two graphs, you become curious as to how many new accounts were linked to the news coverage and the partnership, so you draw another graph.

3-new-accounts-source

This view makes it clear that by the time the July peak hit, the effect of the news story had died. The big spike in July was just the partnership. You kind of knew this, but it’s the first time you’ve seen a picture of it, which is pretty cool.

You remember that your company has a 20% download-to-account conversion target, and you want to see how many of these months hit that. This seems like a good situation for a scatter plot:

4-scatter

Wow. Comparing against the diagonal line that represents the 20% target, you can see July and August blew it away, while March and April didn’t even come close.

You note another promising detail on the spreadsheet. Not only are accounts up, but the percentage of accounts that are paid subscriptions is rising as well. This is good for revenue, which investors obviously care about.

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You wonder how many of the paid accounts come from the new partnership, so you look at that.

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Clearly, the partnership has been a great thing for your company. Armed with these insights you put together a nice summary in dashboard form for your investor. You add a few other interesting tidbits (you know from your market researcher that about two-thirds of your paid account holders are women) to make it visually interesting.

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When you walk a few of your colleagues through it you get some nice comments—this is the first time some of them have seen all this information together like this—but when you present it the following day, your potential investor squints at the wall and tries to figure out what’s going on

Visualize Situations, Not Data

When you start by looking at the data you have and concentrate on how to draw a picture of it, it’s easy to lose track of the message. Overwhelming your audience with data is an easy trap to fall into. The person crafting a dashboard (or an article, or a presentation, or a web page) knows the content backwards and forwards and can unconsciously assume that the audience is on the same page.

A graph is a picture of a situation. The trick to creating a good one is to start by identifying a situation that your audience cares about. In some cases, you may know. Your investors probably care more about revenue (and projected growth) than they do about specific conversion rates.

8-revenue

This graph describes a situation that investors will understand: Revenue is going up due to a partnership, and more partnerships and more revenue are on the way.

Often you won’t know what situations your audience cares about, even when you think you do. A clinician who is monitoring a heart failure population may not need to know about her patient’s every movement but does care if he has become less active over the past few days. A credit card customer looks at a breakdown of his purchases out of idle curiosity, but what he really wants to know is how he can maximize the frequent flyer miles he earns by using his card. A patient doesn’t understand what her deductible is, but she does want to know which insurance plan is going to cost her less over the coming year.

It’s not fair to throw data at people and expect them to decode it. Just as with any design, effective data visualization requires you to understand the situations that are significant to your audience. By starting there, you can use data to describe something they will care about.

Practicing Divergent and Convergent Thinking: Destination Imagination

For the past five years I’ve been coaching my kids and several of their classmates as they compete in the Destination Imagination (DI) challenge program. The program offers seven different open-ended challenges that allow kids to learn about creativity and innovation by experiencing the design process firsthand. This year’s program culminated last week at the global tournament in Nashville.

One of the key tasks facing any DI coach each year is helping the team understand what type of thinking is called for at different parts during the challenge season. At the beginning of the season, the team needs to brainstorm as many different potential solutions as possible. Then, once they have a rough outline of what they want to accomplish, participants need to focus on executing their solution efficiently and creatively. By following the design process through divergent and convergent thinking they arrive at the tournament prepared to win.

Work with our clients at Evantage also allows us to practice divergent and convergent thinking on a regular basis. Our clients often approach us with a need to design products, processes, or services that meet certain user needs or solve challenges facing a particular type of customer.

Traditionally, design thinking relies on two separate rounds of divergent and convergent thinking. The first round begins by thinking about all the possible drivers of a problem and ends by defining a discrete problem on which to focus. The second round begins with ideating as many potential solutions as possible and ends with focusing on finding the best solution through testing and iteration. (Unlike most work with our clients, however—where the first round often takes a great deal of time to research and complete—the DI challenge program gives us the problem, defined in great detail, so we skip to ideation.)

Design Thinking Cycle

 

Encouraging Divergent Thinking

Divergent thinking—where we try to understand all possible drivers of the problem and imagine all possible solutions— is the place where creative types thrive. Yet many of us are deeply uncomfortable with this type of thinking. In school we are taught to come up with “correct” answers and may have few opportunities to exercise our innovation muscles. But anyone can be a good divergent thinker with practice and the right setting. Here are some techniques that encourage divergent thinking:

1) Warm up properly. To get folks comfortable with shouting out any idea that pops in their head, I often start with an “alphabet brainstorm.” In this exercise I hand a common household item—like a lightbulb, a pillowcase, or a birthday candle—to small teams of two or three people. I then give them three minutes to come up with 26 uses for the item, one for each letter of the alphabet. Once one person has shouted out something as silly as, “You could yodel into it!”, they’ll be ready to stop censoring all of their ideas before they make it out into the open.

2) Keep things moving. When facilitating an idea generation session, make sure each idea is brief. When one brainstormer starts elaborating and explaining her idea, it’s common for others in the room to converge around that solution and abandon their own divergent thinking efforts. For example, at a DI team meeting this fall, each member’s “pitch” for a mystery play the team would write and perform could only contain a two-word description of the time period, the names and professions of the three main characters, and a concise description of the crime that was committed. (It was like our own version of Professor Plum in the Library with the Lead Pipe!).

3) Level the playing field. Similarly, if one idea seems more “baked” than others, team members may focus on that idea at the exclusion of others too early in the process. Using design studio techniques or having team members sketch storyboards works well to force people to communicate their ideas at the same level of fidelity.

4) Quality is still king. Often, too much focus is placed on the sheer number of ideas generated during a brainstorm. Instead, look for a small number of truly novel ideas, or ways that traditional ideas could be combined in new and interesting ways. To encourage this, I lead the team in “pile on” brainstorming in which someone begins an idea and each person thereafter stretches it just a little bit further. For example, one person might say, “What if our vehicle had a rudder to steer?”; the next person might add, “Yes, and the rudder could be connected to a pair of handlebars”; and a third person might add, “We could mount a walkie talkie to the handlebars so the driver can easily talk to the navigator.” And so on.

Effectively Practicing Convergent Thinking

As the project progresses, convergent thinking takes over and the team focuses on efficiently executing their chosen ideas. Unlike the lateral jumps and unexpected connections of divergent thinking, convergent thinking is relatively linear (e.g., first we sand the rudder and then we attach it to the vehicle) and often there is one best answer. Here are some tips for narrowing in on the best solution:

1) Try it out. In many cases, hands-on experimentation and iteration are required to find the best solution (e.g., the walkie talkie won’t stay attached and if we just tape it on, we can no longer change the batteries, but we could build a holster from duct tape and cradle the walkie talkie in it). Have extra materials on hand so you can prototype ideas to see if they work, rather than just talking about them. Each time a production method doesn’t work, teammates must come together to think up new solutions to move forward (some of the same methods listed above may help).

2) Fail fast. Failing fast means doing the least amount of work you can do to find out if an idea is feasible or not. Don’t build an entire product when testing a prototype will tell you if meets the users’ needs, and don’t ever spend more than a week of working without testing something out.

3) Avoid backsliding. At this stage, having teammates who continue to practice divergent thinking can be troublesome. With the tournament (or, in real life, perhaps a code freeze) a few weeks away, it becomes disruptive to say, “Wait, maybe we should build a hovercraft instead!”

4) Embrace project management. The basic tools for managing convergent thinking are well-known to most of us. Create a timeline with milestones, call out dependencies, and plan what materials and tools you will need along the way. This will ensure smooth progress from idea to solution.

 

Celebrating Your Solution

On launch day, or tournament day, it’s time to put it all out on the table and execute flawlessly. A team that has spent dedicated time in the first divergent and convergent thinking cycle can feel confident that they are solving a well-understood problem. If they’ve also practiced convergent and divergent thinking in the second cycle they will arrive with the absolute best solution possible. It’s time to celebrate by raising a cupcake or a pint of beer, as appropriate to your team’s age!

Design for the Caring Professions: New White Paper and Slideshare

Yesterday I had the opportunity to present to 45 UX professionals at TC UX Meetup. I chose to speak on a topic that has become close to my heart over the past few years:  what it’s like to work on the front lines of healthcare and social services as a caring professional. We explored methods for doing in-depth user research and guidelines for designing effective solutions once you understand the user needs.

This topic is also covered in a white paper I recently wrote. Analyzing data from nearly 200 individual interviews, the paper explores how the unique needs of caring professionals are shaped by how they think about their work, the environments in which they perform it, and their interactions with other people. In addition, it provides concrete guidelines to help those who are designing for this specialized user group to maximize the effectiveness of their solutions.

Download the paper for a deep dive into:

  • The mindset of those who have chosen to work caring for people,
  • Constraints imposed by the environment in which they work, and
  • Expectations placed on them by others.

 Design_for_Caring_Professions_Icons

Gaining a deep understanding of how care professionals approach their work, spend their days, and adapt to their organization’s expectations enables the creation of systems and procedures that work for this unique user group.

The same techniques used for this research and analysis could be applied to most other user groups with similar success. With meaningful and directed curiosity, a user experience partner can uncover the authentic needs of your users and create designs that exceed their expectations.

Download Whitepaper  View SlideShare Presentation

 

How Might We… make a better world in just one weekend?

“It’s amazing what can happen in just three Earth rotations…”

This past weekend I was lucky enough to participate in the Twin Cities gathering of the Global Service Jam 2016, both as a coach and observer. A “service jam” brings together small, local groups to use design thinking techniques to brainstorm, research, and prototype completely new services inspired by a shared theme.

Friday kicked off with revealing the secret theme for this year’s Global Service Jam. “Jammers” were surprised to hear an audio clip of what sounded like someone (or something!) splashing into a pool of water. They then took out their Post-It notes and pens and started brainstorming things that the splash reminded them of; first individually and then as groups. Ideas were sorted into related themes and groups of two to four “Jammers” used the themes to create their preliminary “How Might We” questions.

Haven’t heard of a How Might We question? The term is used frequently in design thinking activities to describe a question that acts as a foundation for research and design inquiries. It describes the problem you are trying to solve, and is stated optimistically to reinforce the feeling that a good solution is possible. A How Might We (HMW) question is usually brief, allows for a variety of answers, and inspires ideation and creative thinking.

Here are three ways you can form great How Might We Questions:

  1. Refine the scope. It’s important to have a statement that sets helpful boundaries. Avoid questions that are so narrow that they shut down creativity (“How Might We build more community spaces for relaxation?”) or too broad (“How Might We redefine how people spend their free time?”). A right-size question leaves room to be surprised by your research findings and iterate solutions, but doesn’t feel overwhelming or unfocused. One team eventually settled on “How Might We remove barriers that keep people from finding peace and relaxation?” and after interviewing several users, decided to focus on one persona that seems to have the most barriers to relaxation: Millennials.
  2. Remove embedded biases and assumptions. By Saturday morning, another team had coalesced around the question, “How Might We raise awareness of individual water consumption so that people reduce their global footprint?” By writing down as many assumptions as they could think of, the team realized that they had started wading in to “solutioning” before even beginning their research. In order to identify the most effective ways to get people to reduce their global footprint, the team needed to be open to any number of solutions, not just the solution of “raising awareness.”  Another way to avoid type of assumption is to focus on the ultimate benefit or change you want to bring about. While it is natural to imagine the best way to get there, those perspectives should come later and be based on user research.
  3. Let the facts speak for themselves. On the other hand, do rely on available facts to inform the background of your user research. This same team also wondered if they had gone too far by assuming that individual water consumption has a negative environmental impact. They questioned whether they should do user research to determine causality. While asking users if they think their individual water consumption has an impact on the environment could be an interesting area to research, it’s not necessary to support this particular How Might We—this information has been proven through scientific research and is easily found online. The team decided to move forward, and their final prototype of the weekend outlined a campaign that began with awareness of consumption and then grew into a competition engaging communities, large corporations, and even governments.

I could not have been more impressed by Sunday’s team presentations. In just 48 hours the “Jammers” had become very comfortable with terms like “insights,” “personas,” and “failing fast.” Their prototypes were solidly based in research and they were able to articulate the needs they had uncovered and how they had iterated their solutions as they got more and more feedback. Not a bad way to spend a weekend. You can view all of the projects from the Twin Cities Service Jam and others around the world here.

Prototype from Global Service Jam

Prototype of a community to address the question “How Might We help millennials find more opportunities to relax?”

GSJ2016_1

Prototype of a five-part campaign to address the question “How Might We increase community members’ capacity to positively affect water consumption?”

 

Visualize Nothingness

By Jeff Harrison

It’s an exciting time to be me! If this email I got from LinkedIn is any guide, my career is about to really take off.

linkedin

Also, this email from my bank shows my rewards balance on this credit card remains at an all-time high. (I don’t know what “Earn More Mall Earnings” means but as someone who lives within a hypothetical short drive of the Mall of America I’m pretty stoked.)

rewards

To top it off, according to this visualization in ClassDojo, my kid is rocking Spanish class. The chart helps me see that all of the feedback from his teacher is positive.

class dojo

All these displays have one thing in common: underwhelming data. I do not actively promote my profile on LinkedIn [edited to add link to LinkedIn profile], and my son’s Spanish teacher never got into the habit of using ClassDojo to communicate with parents. I never signed up for the rewards program for which I receive the monthly grid of zeroes above; they just started showing up in my email a year or two ago. (The program is attached to an overdraft protection feature that Wells Fargo couldn’t figure out how to implement without issuing me a second debit card, which I routinely cut in half each time I get a new one.)

It’s easy to imagine the design reviews for these interfaces. Colorful charts! Insights! Engagement! When there’s a match between the data in these displays and what customers care about optimizing, magic happens: think of all the Fitbit users who consult their apps to monitor their steps and optimize their day for physical activity. The data contributes to a feedback loop, and more people take the stairs. However, when there’s a mismatch the displays aren’t motivating. They just feel kind of lame.

Do your user research. Get it right. And stop sending me notifications that suggest my life is somehow disappointing. Because LinkedIn and my mom would both tell you different:

allstar

You Still Have to Do the Work

By Jeff Harrison

Here’s a common exchange when I’m talking to a prospective client (let’s call him “Steve”) about an Axure workshop:

Me: Tell me a little bit about how you see your team using Axure.

Steve: We’re using all kinds of tools today. Some people are using Visio, some are using PowerPoint. The designers are using Photoshop and OmniGraffle. It’s all over the map. Everybody’s stuff looks different. We have decided to standardize on Axure, so the purpose of this training is to get people up to speed.

Me: Okay, that makes sense. Is there anything you know you want to focus on?

Steve: I’m extremely interested in the custom libraries that Axure has, so we can all be working with the same components. We spend too much time reinventing the wheel today. I definitely hope that these libraries are part of the training.

Me: Sure, I can cover that. What are you doing today to try to standardize components?

Steve: As I said, it’s all over the map. We have no standards.

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