This is the second part in a series about better dashboard design. This part, Flow, follows Message to highlight the importance of taking that message and making it easy to work through in light of the larger business process.

Having said that and before we continue, we wanted to reveal an internal conversation we've been having about the example (Federal IT Dashboard) that we've selected to demonstrate some of our thinking. We appreciate that it is hard to build dashboards that satisfy a broad audience. From initial conception to delivery, these forces, often at cross-purposes, can chip away at an intuitive and clear design. This series of posts isn't meant to disparage the hard work and deep thinking that clearly went into the design of the Fed IT Dashboard; it is meant to offer some perspective and hopefully useful lessons for others in their dashboard design projects.

Part 2: Flow

In Part 1: Message, Zach introduced the results of some thinking we’ve been having about the Federal IT dashboard and how to continue to improve the effectiveness of its ability to communicate with data. This week, we’ll take a look at the next step in the process: Flow.

Communicating with data is like telling a story: there’s a beginning, a middle, and an end. When you grab that latest book from your favorite author, you know just where to get started, and (if that author is any good) you know exactly when it’s the end. Well, telling a story with a data application is just the same. The information designer needs to lay out the components of the story in a way that facilitates starting, learning, and finishing strong. We call this the workflow of the application. A great application workflow is not evidenced by easy-to-use software (although this might very well be a byproduct), but rather a great application workflow is about helping the user transparently achieve the objectives that make them successful at their job.

So let’s look at some of the principles that we at Juice would use to take the flow of the Fed IT dashboard to the next level.

Principle 1: Know what objectives people are trying to achieve

The first step to knowing the objectives of the users is to know who the users are. Because of the tremendous reach of the Federal IT Dashboard, this is a particularly difficult problem as the audience is so broad. Generally speaking, we think there are three types of users for this system:

• Inquisitive masses - Scope: broad but shallow - These folks are the general public; those people who are most likely looking for high level information and are looking for answers to broadly curious questions.

• Informed but distant 3rd parties - Scope: medium breadth, medium depth - This second group includes people who are looking for information on a specific program to compare to another program that they are more familiar with. In the case of the Federal IT Dashboard, this may include the CIO of a related project, or the chair of a Senate subcommittee, or a political watchdog group doing some research.

• Involved 1st parties - Scope: narrow but deep - This third group represents those who are directly involved with a specific program and want to drill deep to learn as much as they can about a single specific program.

Principle 2: Know how the solution will fit into the broader workflow

Since most “normal” people are paid to get stuff done and not paid to use software, it’s important for the application designer to make sure the tools that they provide are, at a minimum, supporting the workflow, and preferably, transparent to the workflow. Questions that the designer wants to make sure the user doesn’t find themselves asking are “Where do I start?”, “What’s the next step through the app?”, “What’s the end point and how do I know I’m finished?”.

Looking at the Federal IT Dashboard homepage, it’s not clear to me that there’s actually a place to start. The very first image is the Performance summary on the left with the column chart on the right. But just as I’ve decided that I can click, the image changes. I find myself being confused by this almost every time I visit this site - especially since I can’t click on the other views in the image rotation. All of a sudden, I’ve gone from trying to complete my workflow to trying to figure out how to get back to the dashboard - not very transparent.

Using existing methods such as behavior diagrams (such as Interaction Diagrams, Event Diagrams, and Use Case Diagrams) can really help an application designer overcome these sorts of hurdles and define intuitive action flows.

Principle 3: Make navigating the application layout intuitive

When considering application navigation layout, use a single simple rule: start high and enable drill down.

Start with high level KPIs that indicate the overall performance with as few metrics as are possible so the first thing that the user sees on a dashboard is nearly instantly comprehensible. This sometimes requires the application designer to be ruthless about “who” makes the metric cut for the first view. The number should immediately indicate whether further investigation is required. In our mockup, the important numbers are just four: spending and change, and performance and change.

The goal is that it’s simple enough that a first time user can quickly determine what’s next, but an experienced user can quickly determine if anything significant has changed since their last visit.

Once the high level “first view” is identified, enable the user to easily drill down for additional information and exploration. For example, as the user is investigating a particular number, clicking directly on that number should reveal the next layer of information. This is where the Federal IT Dashboard excels, by the way. Users can drill down by clicking on program names, or chart segments, and can navigate back up the crumb trail by clicking “clear” at the top of the data table or on the current view parent.

Finally, we need to address the main navigation. Navigation elements that are positioned such that they imply some sort of relationship, such as menu items, should either be siblings, or parent-child entities. In the case of the main navigation tabs on the Federal IT Dashboard, the items Home, Portfolio, Tools, and Data Feeds are distinct areas but all have different relationships to each other - or worse aren’t related. This makes navigation difficult because the user has to context shift to navigate. It’s a little like “Apples”, “Transportation”, “Monday”, and “Swimming” - they don’t have any thing to do with each other.

It’s OK to use tabs, but make sure they contain distinct and separate domains or views. For the Federal IT Dashboard, I think navigation would be more intuitive if the Home, Portfolio, and Tools tabs were merged. Start all the users with the overview, then allow them to navigate via the visualization to the Portfolio view. Then, toggle that view with the views that under the Tools tab based on the view the user needs to see.

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

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

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

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

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.

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.")

(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.

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

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.

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 goingtorain.com

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.

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

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:

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: Lightroom 3 Beta Import Dialogue - maximized, advanced view:

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.

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 freecycle.org - through it's "reuse" charter, it helps our environment by keeping good stuff out of the landfill.)

Thanks again for reading!