For a famous person, Edward Tufte is adept at avoiding the papparazzi. You probably know this iconic Tufte teaching picture. But it is pretty hard to find another picture of him.

Until now. The clever folks at AdAgeStat were able to get a shot (undoubtably with a bowtie camera) of Tufte for an interview on their AdAgeStat blog.

Tufte in full color

The interview is worth a read. It covers some of the typical Tufte hobby-horses, like this rant about PowerPoint:

“PowerPoint benefits the bottom 10% of presenters by forcing them to have points, some points … any points at all. And the best 10% of presenters have such good content, style and self-awareness that PowerPoint does little damage. PowerPoint should be used solely as a projector operating system to show 100% content, without the bullet grunts, logos and the formatting nonsense from the Strategic Communications Department, and the $20 million Pentagram corporate format guidelines.”

That stuff aside, there were some great nuggets about data presentation. For example his take on presenters and credibility:

“Presenters need (1) to tell a coherent story and (2) to convince their audience of their credibility. A good way to gain credibility is not to have lied to the same audience last month. Another is to demonstrate that you are not a cherry picker, basing your case on evidence selection rather that on evidence. Another necessity is to demonstrate your mastery of detail.”

In my experience, providing your audience with some (limited) flexibility to interact with the data is a great mechanism for building credibility. Have the confidence to allow access to more than cherrypicked data and you won’t come across as manipulative.

Tufte pushes back on the notion of being “overwhelmed by data” by saying:

“Overload, clutter, and confusion are not attributes of information, they are failures of design. So if something is cluttered, fix your design, don’t throw out information. If something is confusing, don’t blame your victim — the audience — instead, fix the design.”

In the world of business intelligence and reporting software, there isn’t a lot of empathy with audiences. The focus is squarely on the user trying to create something, not the reader trying to understand the content.

Finally, he hits on a seldom-discussed gap in data analysis by noting that “good content reasoners and presenters are rare, designers are not.”

In conversations with people like Andrew Abela and Nancy Duarte, we’ve thought a lot about how tools can help people better present data. In the end, it is still a very human art form to synthesize understanding about a problem and construct a logical argument or story around it. Tools can only help facilitate and guide the process. That’s what we are trying to do with Slice.

This weekend is the start of the NFL Combine. It is where roughly 300 of the top college football players show off the physical prowess, strength, speed, agility to NFL teams to help their status in the upcoming April draft.

In case you end up catching a glance of the festivities and want to know a little bit more about the players, below you’ll find a few visualizations that might help you learn a little about that player from Lehigh or the guy who did 38 bench presses of 225 lbs.

Use the search capability on each of these to find the player, position, conference or grade that you want to learn more about. We grabbed the data from NFL.com and CBSsports.com. Enjoy!

Leaderboard: Ranks players across multiple measures.

Comment View: Read quick summaries of players

Table: Search, sort, and find player details

Ok, we’re gonna take an informal survey. Raise your hand if you’ve ever experienced this:

You’re sitting through yet another dull, data-heavy presentation packed full of repetitive charts. A question gets raised, and the presenter flips furiously to find a relevant chart on page 53. A colleague squints at a dense table of numbers, wondering what it all means.

We’ve all been there. And oh! how painful. Too many times we’ve seen the aftermath of the indiscriminate boardroom presentation bore-athons. Well, it’s time to make it stop!

As a result, we at Juice challenged ourselves to find a way for ordinary business folks to create engaging, interactive presentations that leave the dreary days of Death by PowerPoint behind and bring new life to the data-presentation experience. Our solution is called Slice.

Over the last year we’ve worked with dozens of organizations to refine and enhance how Slice works. Our customers come from a diverse array of industries, from research organizations to healthcare service providers to advertising agencies.

Here’s what we learned. There are many great data analysis tools out there like Tableau for ad hoc analysis, SAS and R for statisticians, and a myriad of others. However, we’ve heard repeatedly from real users that these tools fall flat on helping people become data presenters.

Slice solves that data presentation problem.

Once you’ve done the analysis and you know what to communicate, packaging the results in the proper way is critical. But, to do it right

• You want the design to be striking, but you’re not a designer;
• You want engaging interactivity, but you’re not a developer and the IT wait list is overflowing;
• You might cobble something together using Excel and PowerPoint, but mediocrity is not what you’re looking for.

Slice removes these constraints by focussing on the last mile of business intelligence: presenting data with the visual precision, interactivity and excellence in a way that sparks engagement.

We are really excited about how Slice makes a difference for people who have struggled too long with delivering data-rich presentations or reports. Interested in seeing the advantage Slice can give you? We’ve just released a new version and we’d be happy to set you up with a 30-day trial. Go to our Slice page, fill out the form, and we’ll be in touch.

Most of our work ends up as business-to-business data solutions (like US News’ Academic Insights), but occasionally we create visualization solutions for broader public consumption. One example is the new website for The Essential Economy Council, a non-profit and research organization based in Atlanta, GA. They’ve collected nine years Georgia Deptartment of Labor data and we’re helping them turn it into a compelling and easy to understand story.

Go ahead and check out the interactive map of Georgia to learn about an important and under-represented portion of our economy.

Today we are pleased to release another free tool on Juice Labs. The Comment visualization is the perfect way to exploring qualitative data like text survey responses, tweets, or product reviews. A few of the fun features:

• Color comments based on a selected value
• Filter comments using an interactive distribution chart at the top
• Highlight the most interesting comments by selecting the flags in the upper right
• Show the author and other contextual information about a comment

Below is an example with information about Wikipedia’s Lamest Edit Wars. 

For another example, browse data about the most popular Reddit IAmAs for 2012.

Like our other free visualization tools in Juice Labs, the Comments visualization is designed for ease of use and sharing. Just drop in your own data, choose what fields you want to show as text and as values, and the visualization will immediately reflect your choices. The save button gives you a link that includes your data and settings.

If you enjoy this tool, definitely try out our Leaderboard or searchable, sortable Table.  Or if you want to incorporate a series of these visualizations together in an interactive report or dashboard, contact us about Slice.

The mad scientists over in Juice Labs cooked up a new treat for you all just in time for Halloween Thanksgiving.  We’ve crossbred some NFL Data (courtesy of our fellow friend in data Brian Burke) with a visualization we’ve kept under wraps for a while called The Spider. Now before any of you that suffer from arachnophobia start to freak out, this isn’t the spider that you may be accustomed to.  The Spider visualization helps you understand the offensive rush tendencies for every NFL team for the last 4 seasons.  EVERY rush that ever happened in the NFL from 2008-2011 is captured in the visualization. Information about the average yards gained, total yards gained, and the number of plays in each direction are also included. You may be surprised to find out which direction the Green Bay Packers run to on 4th and inches or how unsuccessful Arian Foster has historically been running the football on 1st and long situations (he’s a pretty awesome RB otherwise). You can filter the data by week, season, down, distance, player, and/or the opposing defense. Try it out for yourself here for some deliciously filling insights.

How to Read the Chart:
The thickness of the spider leg represents the number of rushes in that direction. A thicker line means more rushes were attempted to that area. The length of the spider leg stops on the average yards gained per rush in that direction. Click or hover over each leg for more detailed information about the team’s offensive rush tendencies.

I’m not alone in feeling that the breathless excitement about “Big Data” is a bit much — just ask Stephen Few (Big Data, Big Deal). The skepticism isn’t directed at the vast possibilities inherent in broader use of data; we’re more concerned that “Big” isn’t the full answer. In fact, focusing on “Big” distracts from other fundamental barriers — particularly the very human skills required for thoughtful analysis and effective communication of insights.

These missing links are illustrated beautifully in an article by Felix Salmon, a blogging editor for Reuters, about the election — When Quants Tell Stories:

“If you think that the value of Nate Silver is in the model, you’re missing the most important part: there are lots of people with models, and most of those models are pretty similar to each other. The thing which sets Silver apart from the rest is that he can write: he can take a model and turn it into a narrative, walking his readers through to his conclusions.”

“At heart, the campaign was marrying quantitative skills with storytelling, to unbeatable effect. Which stories should the campaign tell, to any given group of people? How should it tell those stories? And who should it get to deliver those stories?”

“The thing that Silver and the Obama campaign have in common, then, is that they used their databases to tell stories. Or, more to the point, their databases and models were used so that Americans could tell stories to each other.”

All the work of collecting, combining, and modeling data is wasted if not enough attention is paid to how the data is shared. The data needs to be transformed into bite-sized (pre-chewed, even) stories that can easily stick in the brains of your audience. And as evidenced by the Obama campaign, there are often many different stories based on the context of each audience member. Years ago, we dubbed this The Last Mile of Business Intelligence. Despite new data trends, technologies, and buzz words, some fundamentals never change.

Despite the debacle that was known as the “replacement refs”, football is back!  And if football is being played, then that means fresh new data is being made. We are helping our friends over at FootballOutsiders.com (a.k.a. heaven for NFL stat junkies) display the 2012 NFL Snap Counts in our Leaderboard visualization. Each week you can view which players have played the most (or least) on offense, defense, and special teams. The data can be filtered by position or team and you can search for your favorite player (or fantasy sleeper pick) by last name.

After you finish, jump to Juice Labs  and try making a Leaderboard using your own data. It is as easy as 1) paste in your own CSV data; 2) configure the data elements you want to show (see the “Learn how” button in the Data area); 3) share a link to your newly created visualization or embed it in your website.

We are looking forward to adding more visualizations like this to Juice Labs over the coming months. In each case, you’ll be able to use your own data and easily share or embed the visualization. All free.

(Bonus) Football Outsiders Scavenger Hunt. See if you can find these 3 items in the 2012 NFL Snap Count Leaderboard:

1. Which offensive players played on a defensive snap in Week 3?
2. Where does Ryan Lilja from the Kansas City Chiefs rank for special teams snap percentage in Week 2?
3. Which linebackers in the NFC East have more than 150 total snaps thru Week 3?

Thanks to our summer intern Duane Rollins for his help on getting this together.

What would your perfect sales pipeline dashboard look like?

The tools that so effectively capture sales information (Salesforce, PipelineDeals, Highrise) tend to do a pretty lousy job of providing visibility into that very same data. The reporting or analytics is often just a table with lots of filtering features. That doesn’t begin to answer important questions like:

• What is the value of the pipeline?
• Where is it performing efficiently? Where is it failing?
• How are things likely to change in the next month?

I’ve been annoyed by this deficiency in sales dashboards for a while. Ken and I put together some thoughts about what a better sales pipeline information interface would look like and how it would function. Here’s what we came up with:

The dashboard flows from top to bottom and has five main parts:

1. Question-based navigation;
2. Filters to narrow the scope of your analysis;
3. Summary metrics built around the stages of your sales pipeline;
4. Top (or bottom) performers visualization to emphasize what factors are driving success (or failure);
5. Detailed table showing individual leads or deals.

Let’s look at some of these pieces in a bit more detail:

Zooming into the top section, we’d want to direct users to key and common questions. Once selected, the question would configure elements in the dashboard (primarily the sales pipeline key metrics) to lead the user to answers. For expert users, these questions could act like customized short-cuts. Novice users get help focusing on the important issues and can learn from best-practices.

The top performers visualization highlights the factors that are most aligned with success of the pipeline. These factors may be the product being sold, the sales representative who is selling it, or the source of the lead. The vertical position of each top item is based on the selected key metrics. The same visualization could be flipped around to show the characteristics that are leading to the poorest performance.

Finally, selecting elements in the visualization would refine the data in the table of deals/leads at the bottom to give the user to the specific items to act on.

By no means is this a perfect and comprehensive dashboard for sales data. But I haven’t seen anything as directed and functional. If you have, I’d love to see it.

Update: I just came across InsightSquared, and like some of the views they offer for sales data (e.g. sales pipeline visualization, sales trending)

Conventional

4-door sedan

Financial spreadsheet

Old-school conference

Un-conventional

Tesla Model S

Interactive model

Product Camp un-conference

Juice isn’t known for doing things in traditional ways. I guess that’s one of the reasons we’re good at what we do. So, when we had the opportunity to sponsor the 2012 Atlanta Product Camp un-conference, we knew we had to get involved.

If you’re not familiar with Product Camp, it’s based on the barcamp un-conference model where people who are interested in a particular concept come together and decide right then and there what sessions they think should occupy the day. In other words, the agenda just includes slots and potential topics, but the actual session topics are not settled until the day of the event. For Product Camp, this is all about product management and marketing: a full day of learning, discussing, and practicing great product management tips and techniques — all based on what those actually in attendance want to discuss.

So, if you’re a Juice fan, a product manager, and in Atlanta (or nearby), click through to register (it’s free) and join Juice and the other 300 folks who are already registered.

Here’s one more conventional/not conventional comparison for the road:

Conventional: donuts

Un-conventional: Sublime doughnuts (the breakfast Juice is providing at Product Camp)

(Oh yeah, I forgot to mention that we’ve proposed a topic for discussion: “Winning Friends and Influencing People… with Data!” So, we’d love to see our community show up and vote Juice into a session slot — let’s show the Atlanta product community how to communicate better with data!)