Trust the Process

My son and I are really excited about the new NBA season. We are Atlanta Hawks fans, so we’re not too optimistic about this year. We know the team is young and has decided to undertake a rebuilding process. Our mantra for this season is the now familiar “trust the process”.

If you’re not aware of the phrase “Trust the Process” comes from the Philadelphia Sixers rebuilding efforts over the past couple of years. What’s most interesting to me is that the formula for team success is much broader now. It is no longer just about having great players, but free agency positioning, analytical prowess, superior facilities and developing long-term successful franchises.

It's all about the process now.

I find the same can be said for delivering customer data and dashboard solutions.

Much of the historical focus when deploying data applications (customer dashboards, embedded analytics, etc.) has been on selecting the right tool. However, despite so many more great tools and increased investment in the BI space, successful implementation rates have not improved.

In a research piece by Dresner Advisory Services from May of this year, they highlight the fact that successful BI implementations are most often tied to having a Chief Data Officer (CDO). This makes a lot of sense because the CDO is just like an NBA team’s general manager. They bring accountability and experience as well as a process to make customer data solutions successful.

Here are some elements that make process so valuable to delivering data applications and solutions.

  • Launch Dates - A process is the best way to mitigate against missing the launch date. The existence of checklists, status updates, and documentation offer a means to anticipate risks that cause delays. Remember that delays to the product launch or release directly impact revenue and reputation. Missing product launch dates is not something that goes unnoticed.

  • Customer Credibility - When delivery dates are missed, requirements miss the mark or dashboard designs don’t serve their audiences product confidence is lost. Its not only the customer’s confidence that we need to be concerned about, but also the sales and marketing teams. Once we lose the trust of these audiences it takes time to regain it, not unlike sports teams who fail to deliver winning teams over many years (see: New York Knicks).

  • User Engagement - When there is no process that means there’s no planned effort to understand the audience and deliver the dashboard design. If users can’t understand the data you’re sharing with them, a cancelled subscription is a near certainty.

  • Applications, not Dashboards - The best dashboards are purpose-driven applications. Tools don’t deliver purpose. The process undertaken to understand and solve a real problem delivers a purposeful solution.

  • A Complete Platform - A dashboard solution is only a means of displaying data. A process defines ALL the requirements. Having a process recognizes that a complete solution is needed which includes security, user administration and application performance optimization.

Much like NBA success, a successful customer dashboard implementation isn’t about picking a product (player), but sustained success over many years of increased subscription (tickets) revenue, fan engagement and loyalty. The path forward for distributing and delivering on valuable data applications is all about your process.

In the event that you don’t have a process or a CDO leading your efforts, click here to learn about the Juicebox Methodologies. It's our way to design and deliver successful, on-time applications as well as wildly loyal fans. Trust the process. It works.

5 Differences between Data Exploration and Data Presentation

Your toolbox for data exploration tools is flush with technology solutions such as Tableau, PowerBI, Qlik, Spotfire, and ClearStory. "Visual analytics" tools give analysts a super-powered version of Excel for dicing data to facilitate the search for valuable insights. Flexibility and breadth of features is critical; the user needs to handle lots of data sources and doesn’t know in which direction she will go with the analysis.

Data presentation is a different class of problem with distinct use cases, goals, and audience needs. Think about the incredible data stories delivered by the The Upshot, Fivethirtyeight, and Bloomberg. These data journalists often demonstrate data presentation at its finest, complete with guided storytelling, compelling visuals, and thoughtful text descriptions. When compared to these examples, it becomes obvious that the best efforts by a data exploration tool cannot deliver high-quality data presentation.

Data exploration tools generally try to cram all the information on a single page; data presentation needs better flow and explanation to tell the story properly.

Data exploration tools generally try to cram all the information on a single page; data presentation needs better flow and explanation to tell the story properly.

You need a specialized solution if you really want to communicate data in ways that engage your audience. To understand the differences between data exploration and data presentation tools, let me offer five key ways that the activities are fundamentally different.

1. Audience — Who is the data for?

For data exploration, the primary audience is the data analyst herself. She is the person who is both manipulating the data and seeing the results. She needs to work with tight feedback cycles of defining hypotheses, analyzing data, and visualizing results.

For data presentation, the audience is a separate group of end-users, not the author of the analysis. These end-users are often non-analytical, on the front-lines of business decision-making, and have difficulty connecting the dots between an analysis and the implications for their job.

The needs and interests of a non-analytical manager will be wildly different from the analyst who speaks the language of data.

The needs and interests of a non-analytical manager will be wildly different from the analyst who speaks the language of data.

2. Message — What do you want to say?

Data exploration is about the journey to find a message in your data. The analyst is trying to put together the pieces of a puzzle.

Data presentation is about sharing the solved puzzle with people who can take action on the insights. Authors of data presentations need to guide an audience through the content with a purpose and point of view.

Data exploration is a journey to find truth; data presentation should guide your audience to focus on the most important data and insights.

Data exploration is a journey to find truth; data presentation should guide your audience to focus on the most important data and insights.

3. Explanation — What does the data mean?

For the analysts using data exploration tools, the meaning of their analysis can be self-evident. A 1% jump in your conversion metric may represent a big change that changes your marketing tactics. The important challenge for the analysts is to answer why is this happening.

Data presentations carry a heavier burden in explaining the results of analysis. When the audience isn’t as familiar with the data, the data presentation author needs to start with more basic descriptions and context. How do we measure the conversion metric? Is a 1% change a big deal or not? What is the business impact of this change?

Fivethiryeight provides explanation surrounding their visualization to ensure readers understand what they are looking at.

Fivethiryeight provides explanation surrounding their visualization to ensure readers understand what they are looking at.

4. Visualizations — How do I show the data?

The visualizations for data exploration need to be easy to create and may often show multiple dimensions to unearth complex patterns.

For data presentation, it is important that visualizations be simple and intuitive. The audience doesn’t have the patience to decipher the meaning of a chart. I used to love presenting data in treemaps but found that as a visualization it could seldom stand-alone without a two-minute tutorial to teach new users how to read the content.

My love for treemaps has been replaced by visualizations (like the leaderboard) that are more immediately intuitive to users.

My love for treemaps has been replaced by visualizations (like the leaderboard) that are more immediately intuitive to users.

5. Goal — What should I do about the insights?

The goal of data exploration is often to ask a better question. The process of finding better questions gets to new insights and a better understanding of how your business works.

Data presentations are about guiding decision-makers to make smarter choices. Much of the learning (through data exploration) should be done, leaving the equally difficult task of communicating the insights and the actions that should result.

In all these ways, data exploration and data presentation are different beasts. This is why we’ve chosen to focus on building the best possible data presentation tool, Juicebox.

Guest Post: The To Do List

We met Raleigh Gresham recently at Atlanta Product Camp and immediately found a data kinship. We especially loved one of his blog posts on To Do Lists and got permission to post it here on the Juice blog. You can check out his post below and other writings here.


To-do list

To do lists. The pinnacle translation of any data set. The final act of simplification for any analysis.

They are reports in their most primal state. They achieve the ultimate goal of any applied datum, answering the core question “what do we do now?”

For the rare data user hoping to generate utility from their analytical efforts, this simplest of reports is worth fighting and editing for. They demand data isolate the next actions. Ignoring the excuses of technology and governance that are liberally used by so many in their field, they relentlessly “sculpt” the data with analytics until the simplicity of checkboxes is all that’s left.

When this data dharma is finally achieved, they are done. They add nothing more. They make no apologies for the simplicity or the unfamiliar clarity of the result.  A to do list leaves no room for the theory-making and hypothesis-spinning rendered by common reports. There is no buffer for interpretation. The comforts of second guessing dissolve. Someone becomes accountable for action.

To do lists are ruthlessly challenging to achieve. Most analysts do not have the stomach for them. To create to do lists, one must be willing to call action out — to recommend movement. Action is risky. Movement changes the status quo. It takes great resolve to settle for nothing less than a to do list.

Being a Data Gourmet

I grew up in a bilingual household where we spoke French and English. Many of us who've been exposed to other languages realize that there are some words that just don't translate well into English. One of the words that got used often in our family was the French word gourmand.  Its closest translation in English is gluttony, but how often does anybody ever say that word?  Probably the simplest way to think of it is the antithesis of gourmet, or even better, someone who prefers quantity over quality.

While there can sometimes be a negative connotation with the phrase, "Il est gourmand," ("He is gourmand"), it can also be just a recognition of someone's preferences.

To this day, even though my French has gotten pretty bad, I still occasionally refer to people as gourmet or gourmand.  It could be when I'm sitting in a restaurant, standing behind them in line at Costco or even hearing about their current data initiative.

What is a data gourmet?


Data is to an Information Connoisseur as Food is to a Gourmet Chef

Just like a food gourmet, a data gourmet is someone interested in something distinctive, visually appealing and inspired by results or action taken. It isn't about hordes of numbers or metrics. It's about getting the right metrics in place, putting them in the right context and letting them stand out.

Think of the chef who prepares the meal like the one in the picture. He or she not only wants to stimulate your taste buds, but also hopes that their use of color, plating and white space will appeal to you and your visual senses, as well.

What is your data gourmand?


Prioritize Data Quality Over Data Quantity

So, as I alluded to earlier, not everyone is a gourmet. Many people value quantity over quality. As it relates to data, someone who is a gourmand is probably unsure of what they really want to do with all the data they are requesting. They figure it best to get as much as they can while they can, especially if they aren't sure what they will do with it.

Unfortunately, they probably have never been exposed to a really useful dashboard or visualization. Ultimately, what they think will satiate them and potentially their users is as much data as possible. However, the volume of data would net a number of metrics, charts and gauges, etc. that would be more than they could ever consume.

Working with a Data Gourmand

When you find yourself in a situation where you are working with a data gourmand (and you will - it's just a matter of time), don't look down your well-trained visualization palate at them.  Instead, gently guide them along a path of visual-epicurean transformation.

Most likely, they're going to want to load up their dashboard plate with every bit of data junk they can find.  Start by getting them to see their dashboard as a blank palette to meet specific goals vs. an empty pallet to load up everything they don't need.

As they select different metrics, invest the extra time to train them to carefully select just the right information that provides the balance their data diet needs for a healthy body.  As they make their selections, help them to see that it's okay to have favorite metrics.  As Amanda Cox of the New York Times says, "Data isn't like your kids.  You don't have to pretend to love them equally."

Finally, if you need some help, refresh your skills with the Juice white paper, "A Guide to Creating Dashboards People Love to Use".

Once you've finished, ask yourself these questions.  Does everything in front of your gourmand now have a reason to be there? Did they pause in appreciation or comment that they can't wait to use it?  If so, you may be well on your way to executive data-chef status.

Have a data gourmand/gourmet story of your own?  We'd love to hear about it in the comments below.

Can familiarity trump usability?

Grocery shopping at a new store is a drag, no matter how thoughtful the supermarket layout or how clear the signage or how wide the aisles. I have a mental model of my local supermarket that makes my trip efficient and helps me avoid that frustrating "double back" to search for the peanut butter.

supermarket layout

This thought made me wonder about the importance of familiarity in dashboards. We spend a lot of time at Juice designing intuitive, simple-to-use dashboards. We want to create a logic and cohesiveness that ensures the right things are placed in the right proximity and order; sales leads should connect to prospects in the same way as the peanut butter and jelly is shelved near the bread.

If you are starting from scratch, this internal logic and consistency is paramount. But how about a dashboard that is already familiar to the target audience? Does it makes sense to redesign a dashboard for usability if it is already heavily used and understood?

For many dashboards, the purpose is simply to convey a few key nuggets of information. Without a series of interactions or tasks, the user’s only need is to locate and absorb data. In these cases, the measure of success is whether the user can find what they are looking for quickly.

I can appreciate the value of familiarity over usability. When the new Microsoft Office "menu ribbon" was introduced, it was described as a convenience to new users because it displays the most relevant features for any given context. For power-users it broke the experience; all the effort I’d put into memorizing static menus was lost.

Excel Ribbon

For all our concerns about poorly-designed dashboards, it may be familiarity that explains why it can makes sense to keep the status quo.

Juice’s Simple Font Framework

The following is an excerpt from our three-part series: "A Guide to Creating Dashboards People Love to Use". It is chock full of best practices and practical tips for designing dashboards. This particular nugget is something we’ve used to great effect and wanted to make sure our readers didn’t miss out simply because they were afraid of ending up on our mailing list. There is even a movie version.

We’d like to offer a simple framework for effective use of fonts in your dashboard. With a few simple decisions, you can ensure that the text on the dashboard will both look good and communicate effectively. The majority of text on the page falls into four categories:

  • Body text is clean, readable content
  • Headers separate and name major sections of your work
  • Notes describe additional things the reader should be aware of. These should fade into the background unless we call attention to them.
  • Emphasis text is what we want our reader to pay particular attention to.

The following table describes an approach for deciding how to display each of these text types. The yellow highlights indicate where you need to make decisions.

Simple Font Framework

It comes down to three basic decisions:

  • Choose size and font of the body text
  • Decide if the header is going to flip to serif or sans-serif—and whether it is going to have any style
  • Decide what to do about emphasis—color or (bold or italic)

A few things things don’t fit neatly into one of the four text categories listed above, such as table headers and graph titles. We tend to use a combination of styles to handle these exceptions.

Simple Font Framework Example 1

Stick to this framework and we guarantee your dashboard will look better. Take a look at this example, starting with a standard-looking Excel report without out much thought put toward the fonts:

The following version of the same report cleans up the table, chart, and fonts:

Simple Font Framework Example 2

A final version uses Georgia for the title font and brings in a new emphasis color. The result: a totally different but equally clean and readable report.

Simple Font Framework Example 3

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 freecycle.org - 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.

JuiceKit Sighted in Federal IT Dashboard

We were excited to see that Federal CIO Vivek Kundra and his team used our open-source JuiceKit™ treemap on the recently released Federal IT Spending Dashboard.

Fed IT dashboard treemap

While Tim O’Reilly mistakenly gave credit for all the visualizations to Fusion Charts, we know better. A mother always recognizes her baby. I bet Google also recognized their Motion Chart.

Fed IT dashboard treemap