The Rise of Analytical Apps — Are We Seeing the Last Days of Dashboards and Reports?


66,038,000 years ago, a massive asteroid smashed into the earth in what is now Mexico's Yucatan Peninsula. After this massive collision, it took only 33,000 years before the dinosaurs were entirely extinct — a blink of an eye in terms of the history of the earth.

This asteroid is considered to be the "final blow" after a series of ecosystem changes (other asteroids, volcanos, etc.) created a fragile environment for the poor dinosaurs. The climate changed, the dinosaurs died out, and the mammals took over.

Incumbent solutions for delivering data —dashboard and reporting tools— are facing their own "fragile environment." The big asteroid may not have hit yet, but it is only a matter of time. Here's why.

Exhibit A:

A thoughtful answer from an experienced Tableau user to the question “Why do people still use Tableau?”

We need to consider why (and when) people might stop using Tableau. My opinion is that Tableau has failed to realise two important things about their software and that if another company can solve this problem then Tableau could really lose out:

1. Companies need to create applications, not just reports

Yes, Tableau is interactive but you cannot use Tableau to make applications that write back to a database. It has maps, yes.. But you cannot use Tableau as the basis for an app like you might with MapBox (which has multiple SDKs for different platforms) or Leaflet.js for instance. Tableau is not designed for this, so if you need apps and not reports then it is not for you. You need a developer (or dev team) instead. This is a big gap in the product that other companies are also failing to see.

2. Tableau’s software does not directly generate revenue for (the majority) of their users

For a company to run several copies of Tableau desktop costs several thousand pounds. This is without the additional costs of Tableau Server or end-user licenses that you will need if you want your customers to use your hosted visualisations and dashboards. Any business that chooses to use Tableau to deliver interactive reports to its customers would need to consider passing some of that cost (or all of it) onto its end users. But when we’re talking about interactive reports, not applications, it is hard to justify data reporting as a stand-alone or additional cost.

That’s a real user wondering whether the paradigm of visual analytics tools for analysts, dashboards for executives, and reports delivered to customers and stakeholders is going to hold up for much longer.

Exhibit B:

Analytics vendors and market analysts are using language that leans more toward delivering "apps." 



PwC analytical app marketplace

PwC analytical app marketplace



Gartner's IT Glossary

Gartner's IT Glossary

IBM Cognos

IBM Cognos

Is “app” more than a rebranding of a decade of data visualization tools? We think so. Here’s why we see analytical apps are on the way to taking over the BI world:

1. Apps have a purpose. A report or dashboard may carry a title, but it is less common that they have a clear and specific purpose. A well-conceived analytical app knows the problem it is trying to solve and what data is necessary to solve it. In this way they are similar to the apps on your phone — they solve a problem the same way a mapping app shows you how to get to the Chuck E. Cheese and a weather app lets you know if you need to bring an umbrella.

2. Apps make data exploration easy. I’ve spent a decade railing against poorly designed dashboards that put the burden on users to find where to start, how to traverse the data, and what actions to take. Good analytics apps willingly carry that burden. Whether we call it “data storytelling,” narrative flow, or quality user experience design, the app should deliver a useful path through the data to make smart decisions.

3. Apps are collaborative. Most business decisions are made as a group. If that weren’t the case, you’d have a lot fewer meetings on your calendar. Why should data-driven decisions be any different? Historically, reports and dashboards treat data delivery as a broadcast medium — a one-way flow of information to a broad audience. But that’s just the start: the recipients need to explore, understand, and find and share insights. They should bring their own context to a discussion, then decisions should be made. Our belief is that data analysis should be more social than solitary. It is at the heart of the “discussions" feature built into our data storytelling platform, Juicebox.

4. Apps lead to action. "What would you do if you knew that information?” That’s the question we ask again and again in working with companies that want to make data useful. Understanding the connection between data and action creates a higher expectation of your data. Analytical apps connect the dots from data to exploration to insight to action.

5. Apps are personalized and role-specific. The attitude of "one size fits all" is typically applied when creating a dashboard or report, and then it is up to individuals to find their own meaning. Analytical apps strive to deliver the right information for each person. How? By utilizing permissions for a user to only see certain data, automatically saving views of the data, and presenting content relevant to the user’s role.

The mammals took over because conditions changed, and the outdated species — with its size and sharp teeth — couldn’t adapt. Expectations are changing the analytics world. Consumers of data want an experience like they enjoy on their mobile devices. They don’t have the attention to pour over a bulky, unfocused spreadsheet, and they expect the ability collaborate with their remote peers. The climate has changed, and so too must our approach to delivering data.

If you’re still churning out reports, we can help you do better. Or if you’ve constructed a one-page dashboard, we can show you a different approach. Drop us a line at info@juiceanalytics.com or send us a message using the form below.

Not Knowing Where To Start

Books, movies and music all have a beginning. Data, when presented or shared, often does not have an intuitive starting point.  The challenge of not having a clear beginning is that when you see a dashboard littered with a dozen competing charts it’s easy to disengage. Tables of raw data can be even worse. Dashboards or reports are often designed to deliver everything and the kitchen sink.         

Here are a couple of examples of dashboards that miss the mark in terms of telling their audience where to start.  In both of these cases the user has to be familiar with the data and know how to read the information correctly.  Beginner or infrequent users will struggle to understand the value of this data.  Without guiding them, the users can lose interest and choose to avoid using the information altogether.





Good dashboards or reports start with a high-level summary and then let users progressively and logically drill into more complex details and context. They are also simple and uncluttered. They use white space and have a clear visual hierarchy.   Here are a few of alternative examples to get the wheels turning.                        

Even this more advanced interactive visualization, called a TreeMap, offers clarity on where to start and how to use it.

To have your audience follow your story it’s important to get them started on the right path.  Think Steven Covey’s, Begin with the End in Mind.  Just like a story your audience is along for the ride.  Carry them from initial explanation to a new, shared understanding.   Only then will they begin to value the effort you put into assembling and presenting the information you’ve given them.

For a demo of our product, Juicebox, schedule an appointment.

Find out more on effective data visualization from our book, Data Fluency. Excerpted here with permission from the publisher, Wiley, from Data Fluency: Empowering Your Organization with Effective Data Communication by Zach Gemignani, Chris Gemignani, Richard Galentino, Patrick Schuermann.  Copyright © 2014.

The End of the One-Page Dashboard

The one-page dashboard is a relic. Its form makes little sense in an era of touch screens, on-demand data, and interfaces crafted for interaction and user experience. It is the single purpose, brick-sized mobile phone compared to your smart phone.

One-page dashboards came from the best of intentions (not all of them, but critique of poorly-designed dashboards is besides the point). The notion was to provide an audience with a single view that showed all the key information together. In this way, the viewer could monitor important data and see where performance was good or bad, all at a glance with the necessary context.

A lot has changed since this type of dashboard was considered the peak of dashboard design (no offense to Jason Lockwood who did a great job within the confines of this exercise):

The admirable use of color and layout cannot overcome the misguided one-page constraint and disconnect from the needs of the viewer.

Can I see all the important information at a glance? While there is a lot of information, not all the useful detail finds a place (axis scales, for one thing). Worse, the volume of information shown is difficult to absorb with the exception of the person who is experienced with the data.

Can you quickly spot the issue areas? The red dots are a start. But they skim the surface of the concerns that could be highlighted. And what if my definition of “concerns” changed based on the viewer's perspective? Furthermore, the viewer gets no guidance as to why certain items are highlighted and what they might do about it.

There is a broken assumption for one-page “monitoring” dashboards: they assume that seeing a problem (with whatever data can be fit on the page) is enough for the viewer. It seldom is. Any viewer with a passing interest will (or should) want to know more, drill deeper, and ask “why?”. A dashboard must not pass on this inherent responsibility to help the viewer. Identifying problems isn’t enough. A good dashboard attempts to help solve those problems.

Jerome Cukier describes the goal of purpose of dashboards: “It’s about putting the needs of your users first...What is something that your users would try to accomplish that could be supported by data and insights?” 

The one-page dashboard is “a man without a country.” It tries to do too much for an executive who would much rather get an alert for the two problem areas...or at least more guidance about the meaning and relevance of what they are seeing. For someone who wants to engage more deeply with the data, the one-pager offers far too little. If done well, it only starts the conversation.

Changes in technology also undermine the premise of single-page dashboards. Trends in how we interact with information also makes this information design form a thing of the past:

  1. The scrolling myth. A decade ago, asking users to scroll was nearly a sin. That’s no longer the case. Touch screens, mouse-scroll wheels, and gestures have made it easy and natural to move vertically on a screen. These interaction models have elongated what user experience designers consider a single screen. Many modern marketing sites are entirely navigated through vertical scrolling. Scrolling acts as a form of guided gradual reveal.
  2. The power of dynamic interfaces. It was once a fair assumption that a dashboard would be a static snapshot of data, lacking the ability for users to interact with the content. Excel was the tool of choice and it took advanced Excel skills to make it interactive. Today there are dozens of dashboard building tools, many of which offer features for connecting key metrics to details that help explain reasons behind changes or outliers. 
  3. The limits of attention. The information age has morphed into the (limited) attention age. Mobile apps, smart watches, and voice-activated interfaces recognize the need to deliver only the most critical information at the right time, and let the user ask for more. The person provides context and desires; the computer provides notifications and answers. This new model of information exchange is entirely at odds with the one-page dashboard. It is unreasonable and suboptimal to expect someone to stare deeply into the densely packed digits and sparklines of a one-page dashboard. There are better ways.

The goals of the one-page dashboard remain: How to show viewers the big picture and understand it in context? How to encourage people to connect the dots across different data points? Modern interfaces have brought us better means to these ends.

No longer is there any meaningful distinction between dashboards to monitor and dashboards to understand. Monitoring highlights problems — and should flow seamlessly into analysis of root cause. The best dashboards do even more: they guide viewers to details that are actionable, tell viewers what actions can be taken, and enable discussions between colleagues. All this doesn’t happen in a single page.

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.

Building High Performance Dashboards Using GWT

Juice's Jon Buffington took center stage at the National Capital Area Google Technology user's group in the D.C. area recently and busted some fancy moves.  And, you should have seen him once his presentation started. Taking the group through the process of designing and implementing an interactive data visualization using Google Web Toolkit (GWT), Jon also incorporated DOM, Canvas, SVG, ReST and Scala browser and server technologies to complete the information experience.

GWT is an open source development toolkit for building and optimizing complex browser-based applications, and is used by many products at Google, including Google Adwords and Orkut.

Armed with a tutorial, Jon compared browser graphical techniques and their respective technologies compatible with GWT. As exhibited in this little gem, Jon simplified the visualization down to a basic bar chart, making the similarities and differences between the technologies amazingly clear. (Yo, Jon.)

Download the presentation, and adopt some formidable moves of your own.

Jon presenting
Jon presenting

Jon leads our product development team here at Juice, and crafts ingenious software technology that transforms data into information experiences. You can check out more of his work, specifically, here.

We’ll let you guys know where we’ll be next. Or, if you really want to keep up, sign up for our RSS feed and/or follow us on Twitter. (Hint: We share lots of little tidbits on Twitter that we don’t share a-n-y-w-h-e-r-e else.)