Take the Strata Vizathlon Challenge & Visualize Yourself in the Big Apple.

We're teaming up with O'Reilly Media to challenge you to participate in a data visualization contest leading up to O'Reilly's Strata New York Summit September 19 - 23. Data has become nearly as essential as food in both our personal and professional lives. So, why not use food as the basis for a data visualization contest?

Play With Your Food.

Join in the competition and visualize information about all the delicious fare our society enjoys. (First, you'll want to put down that chicken wing, lest you get sauce on your keypad.) Being the foodie you are, you'll appreciate that we've found some pretty cool data sets from for you to play with, making this subject matter you can really, uh, sink your teeth into.

A Trip to NYC, Strata Conference Passes and More.

The grand prize winner will win a trip to the Big Apple to present their winning visualization at the O'Reilly Strata NY Summit in New York, NY September 20 - 21, 2011.  Other prizes include Strata NY Conference passes, ebooks from and more. Sweet.

On-the-Map Judges.

Who would pass up an opportunity to get the attention of these judges, let alone have their work reviewed by Flowing Data's Nathan Yau, The New York Time's Amanda Cox and Juice's own Chris Gemignani?  Serious bragging rights.

All That.

More information about the challenge categories, the rules, the prizes, the judges, judging criteria and all you could possibly want or need know about the contest is here.

So, get started on your data visualization now, while your appetite is whet for competition. Entries are due by August 28, 2011.

Juice Fans Get 30% Off Strata NY.

Register now to attend the O'Reilly Strata NY Conference, and get 30% off your registration fee with the special Juice fan discount.  Just enter "JUICE" on the conference registration page.  Learn more.

Chart Makeovers

Earlier, Zach wrote a blog post on the ins and outs of chart selection. It reminded us how important it is to balance the right chart with the right visual presentation as dimensions and complexity change.

But your data presentation decisions don’t end there! Once you have a good handle on the right structure for organizing the presentation, you have to make it look good - making it function good and accomplish original goals. As promised in the previous post, here are the chosen chart structures at each stage of complexity redesigned for presentation. We’ll keep this simple with before and after shots, key design principles highlighted, and a freeform reflection on some practical design decisions. The explanations aren’t meant to be exhaustive but rather are a glimpse into design thinking.

Phase 1 | Sales + Calls, Aggregate Performance

Phase 1,  Phase 1 | Before and After

Before & After

Design Principles

  • Visualisation is not always the best solution
  • Emphasise the interesting

Design Reflection

  • For fonts, often the best choice is sans-serif, tabular fonts (like this). For this demonstration I simply used Helvetica because it gets the job done and everyone has access to it. The font size is 18pt for primary values and 12pt for secondary.
  • Qualitative values (calls, sales) will often be the text that should be treated with grey (50% black will do for most situations).
  • Quantitive values (559, 71,739) should be clear and easily distinguished from less immediately critcal information. Here they are bold, 80% black.
  • Superscript the dollar sign since its an unchanging qualitiative value.

Phase 2 | Sales + Calls / Product, Aggregate Performance

Phase 2, Phase 2 | Before and After

Before & After

Design Principles

  • Use color carefully
  • Use 50% grey carefully
  • Visual rhythm
  • Consider text style needs for dynamic content
  • Organize data visuals in a way that mimics thought process comparisons where appropriate

Design Reflection

  • Stacking the calls and sales bars should only be done with the right audience in mind. Though a dollar to calls value is not comparable in and of itself, in the midst of the context of other products, this makes it easier to visually compare the proportions of these values against each other from product to product. For example, immediately one can notice ’Ceramic Smoking Baby’ is a lucrative product.
  • Add consistent, distinct visual rhythm with light separation lines
  • Again, color should only be used to distinguish commonly changing quantitative values: numbers and bars in this case. But sometimes carefully using color on qualitative values can be helpful. The title (’Calls’), value (’202’), and visual representation (longest bar in this case) is an example good color management. No legend is needed, because the content itself explains visual relationships. The content is the legend.
  • Choose your 50% grey visuals wisely. Product names are secondary in visual weight to colored data values, because they are secondary mentally in the thought process of reading this chart.
  • Placing metric values to the left of the bars overcomes problematic rendering issues when values are very small.
  • Dollar signs are not superscripted because they would become unreadable.

Phase 3 | Sales + Calls / Time, Aggregate Performance

Phase 3, Phase 3 | Before and After

Before & After

Design Principles

  • Minimize chart junk
  • Use white space for comfortable reading
  • Remove text values that can easily be interpreted with visual counterparts

Design Reflection

  • Center trend values on vertical hash marks
  • Measurement dimensions should be grey
  • Distinguish current date with value and endpoint
  • Remove extraneous date values that can be easily interpreted with well placed light hash marks
  • Distinguish every 5 hash marks with length difference

Phase 4 | Sales + Calls / Product + Time, Aggregate Performance

Phase 4, Phase 4 | Before and After

Before & After

Design Principles

  • Give values context
  • Red is easily noticeable when used sparingly
  • Allow for easy comparison

Design Reflection

  • I put the sparklines first in the visual reading for two reasons: 1) the width of this graphic is always the same/dependable and 2) the context of data is often helpful to present first so subsequent values can be better understood. This little snapshot of time provides that context.
  • On the sparklines, distinguish today’s value and the lowest value (red dot). Use red carefully. You don’t need much to draw attention (where color blind issues aren’t an issue)
  • Be sure to provide ample space between elements, and that all graphical elements are aligned on your grid.

Memorable or Actionable or Both.

Recently, I saw the largest concentration of iPad users in the world, controlled a computer screen with my eyes, and learned about our looming robotic future. No, Apple doesn’t have a technology lab on the moon, but I did attend CHI 2010 (short for Computer Human Interaction - the entire program along with papers and authors are referenced here). I left with a bit bigger toolkit and plenty of research to consider further. One such effort investigating chart junk has been reviewed by EagerEyes’ Robert Kosara. I share his enthusiasm for research in visualization, but let’s look more closely at some issues the paper raises and consider how these findings fit into the goals of visualization.

Nothing gets information visualization designers’ feathers more ruffled than the thought of junky charts being more desirable than "Tufte-compliant" charts. I was skeptical, to say the least, in attending a presentation by Scott Bateman for a paper entitled, Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts. (The title is a bit misleading in that the paper is really about embellishments and illustration - not so much traditionally poor structural graphics often considered common "chart junk.")

Embellished vs. Plain chart

(Example of embellished vs. plain chart with same data, from the paper)

The aesthetic treatment of data presentation is a long-time debate, and Scott came all the way from Canada to answer the question: Should we use chart junk? The answer is an emphatic "maybe." The goal of the study was to look at interpretation accuracy and long-term recall, and the papers says,

our results question some of the premises of the minimalist approach to chart design.

Make charts Memorable.

Skipping the gritty details of the study, here are the findings of a provoking illustration with data embedded compared to an boring, "plain" chart:

  • more memorable over the long-term;
  • perceived as having more value and sense of chart bias; and
  • most enjoyable and easiest to remember.

More memorable is better, right? The question we should be asking is, better than what. Of course, more memorable is better than less memorable, but at what cost? And what do we really want people to remember? It’s doubtful the best way to drum up interest in data is by making it light up and do a dance to feed the public’s already marketing heavy information diet. | The Richest and Poorest Neighborhoods

Your data as is mostly marketing if it looks like this: | The Richest and Poorest Neighborhoods

Fully embellished charts


  • Draws attention, memorable imagery
  • Little analytical thinking needed, wider audience
  • Endless diversity
  • Creative exploration
  • Graphics and illustration heavy


  • It looks and feels glossy so people will treat it with the bias of a magazine or commercial TV ad
  • Little data depth
  • Non conclusive, likely not actionable
  • Few standards, wild chart organization
  • Production costs
  • Little research, relatively cheap
  • Illustration / Graphic artist talent required

Perhaps one’s attention is more likely to be drawn to these embellished charts if they are engaged in an entertaining or passive ritual, like watching TV, browsing the web, or shuffling through a newspaper. Perhaps they get the same personal impact as the funny pages. We should consider a greater sense of bias or value message is introduced through this style of data presentation (as confirmed by the study), and that can be detrimental to a viewer’s trust. It isn’t that imagery doesn’t have a place in the same conversation with data, but there are better ways to go about drawing attention than applying illustrations to data points.

In the data presentation arena, we definitely want data to be memorable, but even more so we want data to be actionable; therefore, valuable data remains the attraction.

Make charts Actionable.


Would you say this graphic is more or less plain than the example "plain" chart taken from the research paper earlier in the post? Would you say its more or less actionable? 

A chart is actionable if it answers enough questions of its viewer to instigate a meaningful decision or reaction to information presented. Therefore, charts are only actionable when the right information is presented to the right people with the right visual communication. 

Edward Tufte describes the use of this graphic by the New York Times that accompanied a data dense table along with a news column on the subject. It’s a simple point: in order to present meaningful, compelling, or personally motivating information, there either needs to be exactly the right data presented, given the context of the data and person, or enough dimensions and slices of data to be meaningful to a broader range of questions and needs. Supporting textual content always helps to tell the story, which builds the viewers mental model - thereby, making the data more understandable.

Non-embellished charts



No non-data graphics

Minimized distractions from data focus, no graphics or imagery suggesting bias,

Teachable, fundamental guidelines

little visual appeal unless the data density is high (which can feel overwhelming)

Sufficient data-depth emphasis

Actionable information

Requires more patience or experience from viewer.

Production costs

No illustration talent required

Research time and resources required, relatively expensive

The problem with embellishments as a primary style for getting the public engaged with data is that it continues to suggest that truly understanding how data impacts their world is beyond common thought or interest. The dimensions are minimal and value statements dominate.

But value statements aren’t always bad. Sometimes when you’re saying so little with an information-starved chart, its better to come out and say the point you’re trying to make with a single data point. Like this beautiful example from

Its Communications 101: say what you’re going to say, say it, and say what you said. When the information is somewhat clearly target and not exploratory in nature, this frank approach is often more effective. Embellished charts commonly stand alone with no supporting, meaningful story or conclusion. If the information is valid and valuable enough to be published, there should at least be enough effort to find and integrate a reliable source with more info to answer questions where the chart data left the viewer wondering.

Make charts Both.

When it comes to complicated information, stop treating it as if it can be polished nicely into a single chart and that will be sufficient to create understanding, motivation, and action. Charts make data visible and play off our innate human need to create a mental image of the information story we’re presented with. We need both visual attraction / definition and concrete factual data.

Illustration, graphics, and photography trigger emotion and interest in our right brain. They give us a chance to associate ideas and create mental connections to make sense of the world. Our right brain needs "embellishment" thinking to make connections.

Meanwhile, our left brain needs values, raw facts, and the ability to measure worth. Our left brain needs "plain chart" thinking to determine the cause and effect of connections; its interested in thinking about what really matters and impacts things at this moment.

There are few visualizations that even begin to approach the balance between imagery and data.

Example 1. The Tweet Tracker visualization is at least on the right track. One may say here that illustration is used as data points, but I would suggest the technique is appropriate here because the imagery is uniquely matched, within context, as another dimension to its data category.

Winter Olympics Tweet Tracker by Stamen.

Winter Olympics Tweet Tracker by Stamen.

Example 2. Embellishments come in diverse forms. You may have seen this presentation Al Gore gave on global warming. Notice what happens at 9:08 in the video as Al continues his commentary while riding a lift on stage up the side of the chart. Do you hear the background laughter? This kind of laughter is good. You know you’re audience is engaged. Duarte Design designed an embellished visual here to grab people’s attention and make the point memorable - alongside the data chart. This engaging visual device makes the data more memorable because the data is still the center of attention.

Visualization is simply the best language to create meaningful connections between data, thereby making it valuable. All charts are related to visualization, whether its good design or not. The conversation of whether embellishments are good or bad depends on many things, but the real question we should be asking is whether they are making your data more or less valuable. It is a fine thing to attract interest to data, but not when that is a device to overlook the real care needed in preparing sufficient information. Plain charts are fine also, but likely only for quick personal projects in excel where a mental model of the data connections are already well understood.

I’m thankful for Scott’s work with his colleagues on this research, and for people like Robert who also promote appreciation for the much needed research in visualization. The theme of graphical embellishment is thrown around so much in the visualization community that it rarely receives careful deliberation, and this paper starts a purposeful conversation. However, there is a long way in working towards conclusive goals.

Other visualization related papers presented at CHI 2010:

  • Useful Junk? The Effects of Visual Embellsihment on Comprehension and Memorability of Charts.
  • ManyNets: An Interface for Multiple Network Analysis and Visualization
  • Individual Models of Color Differentiation to Improve Interpretability of Information Visualization
  • High-Precision Magnification Lenses
  • Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design
  • Integrating Text with Video and 3D Graphics: The Effects of Text Drawing Styles on Text Readability
  • Animated UI Transitions and Perception of Time — a User Study on Animated Effects on a Mobile Screen

Important Dialogue

You hear what I’m saying twinkle toes?

There are many exclusive conversations going on in the world. Making sense of these conversations can be intriguing however may not be the most productive and satisfying process when you have a specific goal or specific information you would like to retrieve. Many interfaces often speak this ’I’m-a-computer-do-it-my-way" language, without introducing a visual language and workflow that maintains a holistic and ergonomic view of people’s goals, strengths, and weaknesses. And the way you build interfaces that engage and speak people rather than speaking computer, isn’t putting make-up and jingle bells on yesterday’s interface through wiz-bang graphics or merely adding features. Interfaces should maintain clear intentions with a non-exclusive language that stays true to their audience.

Put these methods into practice:

  • know how to dialogue with people, as people and not computer users (Donald Norman also has recently been advocating this. Word usage is important)
  • stay abreast of capital (money-making!) design decisions that speak people
  • embrace the cross-pollination of ideas. Since people are everywhere, take advantage of learning from new fields you don’t frequent.

In a design nut shell, this is about creating interfaces people love to use. When you see something you love using, seek to understand the fundamental reasons why that is so you can implement these in the future. Often you’ll find its the culmination of many design decisions creating a consistent language people understand and love.

Let’s put this into practice by looking at a how potentially foreign information space complimented a workflow for people that is more natural and less exclusive. Hopefully, as we dissect a few notable design decisions, you’ll be more comfortable with identifying and repurposing some fundamental principles. Adobe Lightroom 3 Beta is a professional photo editing program I downloaded recently. I noticed the Adobe team touted an improved "Import Dialogue box." Since, generally, all import dialogues seemed to be created equal, I was interested in how they handled this process.

Old Import Dialogue interface: [lightwindow href="" title="Lightroom 2 Import Dialogue"] [/lightwindow]

Click on the images below to take a look at the redesign and my annotations on it, and then I’ll describe how certain annotations support fundamentals of improved information design that can be appropriately applied on future interfaces.

Lightroom 3 Beta Import Dialogue - minimal, basic view: [lightwindow href="" title="Lightroom 3 Beta Import Dialogue - basic view"] [/lightwindow]

Lightroom 3 Beta Import Dialogue - maximized, advanced view: [lightwindow href="" title="Lightroom 3 Beta Import Dialogue - advanced view"] [/lightwindow]

Without being exhaustive, let’s look at some culminating design decisions associated with general design principles. To clarify, right now we are training an informed design language that will aid us in creating future interfaces with less fluff and more decisions truthful to the content and workflow.

Content promotes context. The content medium for information / data in this application is photography, and this part of the photography workflow is specific to importing, therefore, a structure is laid intuitively that matches this context. Concept supported by: flow of the header elements, dimming background, dark / desaturated palette that compliments the overall goal of focusing on altering the pixels of your photography.

Attention balance. Build a meaningful hierarchal language that emphasizes the content where decisions are made. Hierarchy of text styles or graphics match hierarchy of function or ramifications. Concept supported by: header text specifying the decision is brightest, purposeful icons, inverted preset tab, vignettes and blurring, highlighted mouseovers.

Intention balance. Some interfaces may only need to support casual or advanced use, but this process specific to importing photos now supports both, making it the most beneficial upgrade feature. Interfaces should support peoples’ intentions and maintain context while seamlessly transitioning between them. Concept supported by: expand / contract dialogue arrow, minimal information preview of selected photos, minimized and advanced views.

How is this interface now less exclusive? As people dialogue with this portion of the software, they have fewer hoops to jump through to accomplish the same goals and the new process preserves the context of the content and workflow. Naturally, there are many design fundamentals to build a language around. It can take some work making sense of everyone’s tidbits, top-ten lists, quotable quotes, and pattern libraries, but with a little intentional thought we can get more proficient, personally and collectively, at a common language that moves design forward in a methodical, tangible nature.

Start small. Identify design decisions out there grouped in these three fundamentals to get you started and post examples for the Juice community love if you feel so led. It will sharpen you toward purposeful reasoning on the drawing board and during concept presentation time.

Designing Great Dashboards – Part 3

Several weeks ago we published Part 1: Foundation of our Guide to Creating Dashboards People Love to Use, and a couple of weeks after that we released Part 2: Structure. Today, we’re making Part 3: Information Design available for download. In this part, we provide practical tips for putting information on the page in a way that communicates effectively to your audience.

If you’ve already registered, you will be receiving this volume automatically via email. However, if you’ve been waiting for "a better deal", you’re in luck. Right now, you can download all three parts for FREE! That’s right, free. As in $0. And we’re waiving the shipping and handling charges as well. Just click here to register and get your copy today!

(For those of you who are paying attention, we didn’t actually charge for the first two parts either. They’ve always been free, but sometimes folks need to feel like they’re getting a good deal. If you really want to give and get free stuff, check out - through it’s "reuse" charter, it helps our environment by keeping good stuff out of the landfill.)

Thanks again for reading!

Designing Great Dashboards – The Book

It’s been a busy summer for us here at Juice with more and more companies asking us to help them take their data and create dashboard applications that help them get more done. While working on these accounts, we’ve seen an ever increasing interest and awareness in proper dashboarding techniques.

We believe that the best software is the software that people like love to use. Typically they “love it” because it helps them get their job done quicker and/or better. This can be for any of a number of reasons, but it’s great to see that buyers are becoming less satisfied with junky information applications.

So, we’ve decided to share the wealth. We’ve decided to compile many of the design tips we’ve harvested from our client projects over the years. These learnings are collected into a 3 part paper entitled A Guide to Creating Dashboards People Love to Use (catchy, isn’t it?). We’ve written this to help people who want to create information applications that break out of the horrible constraints of the industry-standards we’ve all seen and have been disappointed with.

We’ve made this paper available to folks who we’ve done business with or who have registered with us in the past, but we didn’t want our readers to be left out. If you didn’t receive an invitation to download the paper (maybe because you’re one of those lurkers out there -shame on you ;-) now’s your chance to be part of the "in crowd". If you’re interested, register to download your own copy of Part 1: Foundation. For those who register, we’ll be mailing Parts 2 (Structure) and 3 (Information Design) over the next few weeks.

We think you’ll find it really useful and hope you’ll let us know how it helps you communicate your information more effectively.

Think Like a Designer

I’m a big fan of the work they’re doing over at Duarte Design. Great, practical, motivating presentation design practices. Rarely do I come away from their site un-inspired about something.

Recently, Nancy Duarte participated in an interview with Jimmy Guterman of the MIT Sloan Management Review, which resulted in the article "How to Become a Better Manager By Thinking Like a Designer" (sign up is required). The quote that summarizes the article is:

“Often managers… rely heavily on data and information to tell the story and miss the opportunity to create context and meaning…leaving lots of room for interpretation, which can spawn multiple cycles and limit advancement."

It’s the same with information presentation. A focus on design at the beginning expands the ability to deliver context and meaning. But before you discount design as a concept for well, you know, "those artsy types", keep in mind, as Nancy puts it:

"Design is... crafting communications to answer audience needs in the most effective way."

What this means is that the more you focus on design, the more you’ll "speak" to your audience - which means you’ll be more effective with your data presentation. It’s about the audience, not you.

Here are some dashboard design principles that we use (with a few enhancements from Nancy’s interview) to make sure we become better information presenters by thinking like designers:

  • Unity/Harmony - a sense that everything in the application belongs together, resulting in a "whole" that is greater than the sum of the parts. All the elements complement, augment, and enhance, as opposed to distract and detract from each other.

    Takeaway: Identify the problem you’re solving and make sure every element you place moves you closer to answering that question.

  • Proximity/Hierarchy - Things that are near each other are related. Hierarchy demonstrates relationships between items where appropriate. Proximity and Hierarchy both provide tremendous contextual cues leading to better understanding.

    Takeaway: Place related things near each other and separate unrelated things. Remember, dogs and cats don’t play well together.

  • Clear Space - White space in information display is very important and too often overlooked. Maximizing dashboard real estate means creating places for the eye to "rest" so that the non-white space is more effective.

    Takeaway: Use white space in conjunction with proximity to help your viewers follow the story the information is telling.

  • Balance - Dominant focal points either give the viewer a sense of comfort (balanced) or spur them to action (unbalanced). Nancy points out "that does not mean all things must be in balance all the time. It is often effective to jar people and thereby effect a change in behavior or thought. Be aware, though, that once something has been thrown out of balance, it is the nature of the universe to find a new state of equilibrium."

    Takeaway: Make sure the primary focal points in your information presentation tell the viewer either "it’s ok, move on" or "you need to do something."

  • Contrast - Contrast creates interest to focus attention or highlight differences. Again quoting from the article "The value of contrast lies neither in the black nor the white, but in the tension between them."

    Takeaway: Use Contrast to shift Balance so the viewer focusses and acts more quickly.

  • Proportion - More important elements deserve more real estate. It’s tempting to want to present an unbiased view of the data. However, as Amanda Cox of the NYT graphics department stated at the OEDC "Seminar on Innovative Approaches to Turn Statistics into Knowledge" "data isn’t like your kids, you don’t have to pretend to love them equally."

    Takeaway: Increase the size and emphasis of the values and decrease the size of labels and you’ll find dramatically better impact and speed of understanding.

  • Simplicity - Stay focused on the specific fact on which you’re trying to shine light. This sometimes means showing less data and a simpler display. I think Garr Reynolds sums it up best: "Don’t confuse ’simplicity’, which is hard to achieve, with ’simplistic’, which is easy and usually lacking value."

    Takeaway: Help your viewers focus on what’s really important by pointing them to the kernels and not the chaff.

Breaking Free of the One-Page Dashboard Rule

Conventional wisdom says that an executive dashboard must fit on a single page or screen. The argument hinges on a pair of assertions about this constraint: it provides necessary discipline to focus on only the most critical information; and it enables the audience to see results "at a glance."

The "discipline" argument is made forcefully by Avinash Kaushik (among others).

"if your dashboard does not fit on one page, you have a report, not a dashboard...This rule is important because it encourages rigorous thought to be applied in selecting the golden dashboard metric."

I buy wholeheartedly into the value of constraints. However, defining a useful constraint as a "rule" assumes there is only one viable means to achieve the desired ends. Confining visual real estate is but one way to focus your thinking. There are others: How about limiting yourself to five key measures? How about demanding that a dashboard can be understood in 3 minutes by a new user? How about only presenting exceptions?

The argument that a one-page dashboard necessarily provides an view of your business "at a glance" is more self-deceiving. Well-known information-ista Stephen Few uses this rationale in his definition of a dashboard:

A visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance. PDF

I check my speedometer "at a glance". I "glance" at a Heads-up Display (HUD) on a video game showing how much energy my character has remaining. These displays communicate but a single number that is already hovering on the corner of my consciousness. If we follow this advice literally, we’d show:

Acme Widgets Dashboard

Assuming one page gives you quick, easy comprehension is like assuming all red cars are fast. That’s simply not true. It must be duly noted, however, that all red cars are cool.

Stretch Trabant image courtesy

More often, people follow the one-page dashboard rule off a cliff like these folks.


There are real problems with this definition:

Dashboard definition
  • In reality, the one-page rule leads to jamming information into the available space.
  • When everything must fit on a page, there isn’t room to describe the connections between information or fashion a story from the data.
  • A good dashboard raises more questions than it can answer. Sticking to a static piece of paper limits any ability to find or present explanations.

Don’t get me wrong: A one-page dashboard is often an effective way to create "a visual display of the most important information needed to achieve one or more objectives." But with streaming video, interactive visualizations, podcasts, Kindles, smart phones, video it really necessary to limit ourselves to 8.5" x 11" piece of paper. Or might we open ourselves up to some more creative solutions to sharing the numbers; a short movie, a few slides, a short text narrative, or 140 characters.

I’d like to use this definition instead and will be back soon with some ideas on how to make your dashboards clear and concise.

Dashboard definition

Designed to be used

I have become curiously interested in this post that talks about how it’s difficult to correctly write an application for the iPhone. The assertion is that writing software for the iPhone is harder than for a desktop, not because of the technology, but because:

"everything counts so much — every design choice, every line of code, everything left in and everything left out."

Very eloquently and precisely put. If you’ve ever used any sort of mobile computing platform, not just the iPhone, you know how much proper design can make an application really useful - or totally useless.

But then again, isn’t this the case with any application? Aren’t the best ones those in which the designer applied Brent’s assertion for iPhone software? Some applications seem to have their genesis in the charter "build an application that allows the user to perform all these actions" while others are built on the charge "build an application that helps the user solve this problem" -- it’s the battle of functionality versus purpose.

Take a look at ChartChooser based on Andrew Abela’s "smart charting" guidelines. It doesn’t help users figure out how to pick a bar chart or pie chart. What it does is to help them answer the "what’s the right way to show this information" question. There’s not a lot buttons or features, it just does one thing well. There are certainly other good (better?) examples out there as well (FlipVideo, Evernote, Tivo, to name a few). The better the software, the less the user will think about it when using it to get their job done.

In line with this thinking, we put together a short list of some design principles that we use to keep the user productive:

  • Solve a problem - Make sure the end product provides a specific solution to a specific problem so the user can easily understand how it helps them.

  • Enable casual use - Minimize the "barrier to entry" for new users by avoiding feature overload, minimizing clicks for each task, and by not letting polish become bling.

  • Tell a story - Relate the data to the key questions, answering them in a logical order and revealing layers of detail as users express interest in knowing more, not before.

  • Lead to action - Empower the user to finish their task quickly (btw, the "task" is not "using software").

  • Encourage exploration - Use the experienced guide approach to give the user enough context to understand the problem and then point them in the right direction to learn about new factors that will expand their insight.

The Purpose Driven Design

Have you ever tried to define a word such as "design"? It’s not too easy. Here’s what the New Oxford American Dictionary says:

design |dəˈzīn| noun

2 purpose, planning, or intention that exists or is thought to exist behind an action, fact, or material object

I guess that probably covers it. But then again, I find myself asking my favorite question: "So what?". I mean, what does it help me actually get done?

It looks to me like the folks over at Duarte Design have it figured out. Nancy Duarte made this post regarding the recent DesignThinkers2008 conference. In it, she very astutely stated "[proper] design isn’t about decoration, it’s about meaning and access to information". Very cool.

It’s easy to "get your flash on" and decorate information visualization up with all sorts of glassy, bouncy and flying designs; they might even be considered "tastefully stylish". But if you haven’t focused on the meaning in the information and haven’t made it accessible to the observer (i.e. understandable so they can actually do something with it), you’ve missed the purpose of the whole design process. So when you’re designing a solution for those you love, make sure you stay purpose driven.

Thanks Duarte for helping us keep our eyes on the ball!

(For those of you who might not know who Duarte Design is, among other things, they were heavily involved in the design of the presentation Al Gore used in "An Inconvenient Truth." If you’re interested in how to communicate better through presentations, check out their blog slide:ology.)