A lot of the applications that Juice creates are designed to make information more accessible to people who wouldn’t consider themselves to be data experts. They realize the value in the data that they have, and in many cases they have some sort of analytics solution in place, but they know they’re not getting as much value from their data as they should.
One of the hurdles we frequently come up against is that people who aren’t actively participating in the visualization discussion don’t know what’s possible. All they’ve ever seen, in many cases, are the confusing dashboards, charts, and graphs that are all too prevalent from the vendors in our space. You know the ones: a thick layer of technology slathered with some gloss and wiggle, between two slices of “do it yourself”.
In many cases, we find ourselves closing this gap by referring to some of the best examples of work out there. As we were thinking about this, the idea to provide a simple walk through of these examples came into being. The result: a 30 day calendar chocked full of some of the best samples of skills enhancing examples we could find.
Each day is a bite sized chunk and takes only a few minutes to watch, read, do, or play. Some of the days are comprised of Juice content, but most days are from other sources that we’ve found useful.
You can download it to use yourself, or to share with your friends who need to expand their info-viz horizons. Either way, we think it’ll get your creative juices flowing.
Listen up, all you Juice fans who live in Atlanta. We’ve finally nailed down all the details for the get together we announced a few weeks ago. We’re calling it the Viva Visualization Tour.
What you’ll have when you leave:
visualization best practices training around information layout and workflow,
information visualization, chart selection, and styling
networking within the Atlanta visualization community
a full breakfast buffet like only Magianno’s can put on
opportunity to pick the Juice collective for tidbits of vizo-knowledge
a few pieces of custom designed Juice schwag
What Juice gets out of this:
socializing with the people in our virtual and physical community who love making visual sense of data
opportunity to talk about the stuff we’re excited about with people who are actually willing to listen (besides our moms)
a big ol’ food bill
the joy of seeing some of the most respected members of the Atlanta visualization community all in one room
If this sounds like great fun to you (and who wouldn’t think so), register. We do have limited space, so don’t wait.
And, for those of you who aren’t in the Atlanta area, we’re also planning an August meeting in D.C. and a September meeting in Boston, so keep your eyes open for those (as well as other potential cities).
Ah… Summer in Atlanta.
Sunshine, green trees, Peachtree Road Race… and pollution. I love living in Atlanta, I really do, but one thing that most non-Atlantans don’t know is that we have a real problem with poor air quality. As someone who really enjoys biking, hiking, and running, I pay a lot of attention to the Georgia Department of Natural Resources Air Quality Index. So far this year we’ve had a handful of “orange” days, but no “red” or “purple” ones – which sounds anticlimactic, but is a real improvement over a few years ago (we haven’t registered a “code purple” day since 2002).
Anyway, as I was checking the air quality forecast this week, it occurred to me that the green/yellow/orange/red/purple/maroon categorization is based on an index. This started some thinking about measures, averages and indexes.
If you’ve never thought much about indexes, they are calculated by dividing the measured value by a base or expected value and then (usually) multiplying by 100. The result is that the target value is “100″.
The great thing about indexes is… they are super easy for casual users to interpret. This is the case because they remove the dependency on the user to understand and keep absolute values in their head. In the case of the Air Quality Index, it’s based on the national air quality standard for the pollutant measured. Since air quality in Georgia is primarily composed of 7 measures, it can get pretty confusing if you want to know what’s going on. To demonstrate, here’s a table of the national air quality standards that the Georgia Department of Natural Resources monitors:
Get the point? As an environmental layperson, it’s much easier for me to interpret current measurements if they are expressed with respect to the national index (100) as opposed to ppb, ug/m^3, etc. Most people don’t have a clue (nor do they care) about what a mg/m^3 or a ppb is, but they do care about their respiratory health. So, providing a common, simplified measure makes complex data oh so much more accessible to the populous. This is the power of indexes over absolute measures and average values. In Atlanta the use of indexes has unified nearly every Atlantan’s practical understanding of air quality.
What it means for you
So, when it comes to creating information applications and dashboards, if you’re presenting complex values, consider using indexes to reduce the barriers to entry for non-domain-expert users. Here are a few tips to keep in mind:
Get buy-in with your user group so they don’t feel like you’re pushing yet another meaningless value down their throat.
Don’t fall into the temptation to swap indexes with historical average values. Averages represent historical measures; indexes represent performance compared to a group.
Oh yeah, lest I forget, there’s always a tradeoff. As with most things, when you simplify, you lose some resolution. The draw back is that for those who want to delve deeper into the meaning of the measure, they now have to do some researching (just as I did) to understand how the actual metrics are measured and how the index is calculated. Take this into consideration in your information design and make the absolute measures readily available through alternate views, mouse overs, or similar.
One thing we really like doing here at Juice is meeting and talking with folks who are interested in the practical application of visualization techniques to make their jobs and businesses better. We know a lot of you out there feel the same. So, we’re planning meet-ups in three cities over the next few months — Atlanta, Washington, D.C. and Boston. In addition to giving those of you in these areas a chance to get together in one place at the same time, it will give us a great excuse to share some data visualization knowledge that we think will benefit you and enhance your skills.
Each Juice Tour event will start with a meet-and-greet followed by a presentation focused on some basic rules for effectively communicating data – where we will provide you with some easy-to-use principles that you will walk away with, leaving you to become far more proficient at presenting your data forward no matter who your audience.
Afterwards, you will have an opportunity to meet one-on-one with Juice in free mini-problem-solving sessions where we can talk specifically about your visualization problems and offer suggestions to help you work through them.
If you’re interested, register here and let us know your name, email and your location. We’d like to gauge your level of interest in the Juice Tour — starting with Atlanta, Washington, D.C. and Boston. If you’re not in these areas, but are interested in the Tour, please let us know that, as well. (If these go really well, who knows, maybe we’ll expand to include other cities, too.)
We look forward to hearing from you! (Oh, and did I mention, it’s free?)
For those of you who might be interested, we’re going to start adding our significance to the twitterverse through @JuiceAnalytics. If you’re already following us (@chrisgemignani, @zachgemignani, @khilburn, etc.) you can certainly keep doing that, but if you’re a Juice fan, we’d encourage you to follow us @JuiceAnalytics as well.
And to kick it all off, on Monday May 24th we’re going to begin with a series of tweets entitled “30 days to better visualizations.” Each day we’re going to direct our followers to an online resource that you can read, watch, play, or do something (each takes only about 5 minutes) that will help you hone your visualization skills. For these tweets, we’ll be using the hash tag #30Days2Viz.
A few weeks ago Juice asked our readers to give us a few insights into whether or not we and other info-viz sites are actually helping them and their organizations be more effective at communicating information.
Well, the time has come to take a look at the results (oooh – pins and needles). The survey was way more popular than we expected, receiving well over 500 responses.
We had a few questions that were of the form “select the answer that best describes you” but, for the most part, we focussed on text based answers so that we could try to avoid directing the answers and could demonstrate some non-traditional visualization styles to explore results. As a side note, the open ended answers to the text based questions were truly intriguing to read – hopefully the presentation of the results below will give you a small insight to what we learned.
So, here are the results.
The first section of questions dealt with getting some context about our readers. Since the questions were multiple choice, we’re showing the results in traditional bar chart format.
In terms of size, which of the following is your company most like?
A one man band
The Dirty Dozen
The University of Rhode Island
In terms of information presentation expertise, who do you see yourself as?
The Excel Chart Wizard incarnate (I’m happy with the quickest route)
Harold and the Purple Crayon (I’m pretty good, but not too finicky)
A Tufte clone (every chart is carefully and lovingly crafted with intention)
If your company were stuck on Gilligan’s Island, would you be able to use information presentation to get rescued?
No, Gilligan keeps using our Tufte books to prop up the break room table.
Maybe. The Skipper rigged up this island beacon system using coconuts, vines, and tiki torches.
You betcha! The Professor could build a huge island sized information display that could be seen, understood, and acted upon by the astronauts on the International Space Station.
What two information sources do you most frequently use for information presentation tips, trends, and best practices?
BI Vendor’s website (e.g., Business Objects, Tableau, Cognos, etc.)
The Dashboard Spy
Dashboards by Example
Jorge Camoes’ Charts
Tufte’s web Site
Visual Business Intelligence (Stephen Few’s site)
However, What we really want to know is what sites are most closely related. So we tried looking at them with a phrase net from ManyEyes:
This is a great way to demonstrate how sites are “connected”. We see a very strong relationship between Juice and the other non-Juice sites, but not a strong relationship between the non-Juice sites, themselves. In retrospect, the question would have been more effective had we asked respondents for their “top three or four” sites (approximately: total number of options Ã· 3).
The next group of questions were crafted to help us understand the problems our users and their organizations are encountering when it comes to presenting information to stakeholders and users. For most of these questions we broke the number one rule in surveys: stay away from text based answers.
Using one word for each, list three things that you most frequently find useful from these sources?
This was one of the most useful result sets and clearly shows that people like examples and new ideas for visualizations, followed by tips on how to get it done. (I’m hoping this post meets all of those criteria to some level.)
Within your organization, would you say the understanding of information visualization best practices is:
Staying the same
What one word describes the biggest barrier to improved information presentation at your company?
I selected a Wordle (as opposed to a tag cloud) for questions 7 and 8 because I wanted to see the results in a way that would give me the general feeling of the barriers and benefits – I wanted the answers to spur some sort of emotive response. I think a Wordle does this better than a tag cloud.
Finally, we’re going to post results on our blog for free download. However, if you want us to notify you when the report is ready, please provide your email address below. (And because we have a large international following, please add your country as well, if you don’t mind. Why? ’cuz we’re just curious. Thanks!)
So, we’re going to show only the countries here, no email addresses (whew!). Let’s start with looking at the standard distribution:
And here’s the geographic representation from Many Eyes:
But, having looked at that, I thought it might be a little more interesting to look at the country locations like this (text sized based on number of participants):
And that was all of the questions that were in the survey. However, I thought some of the multiple choice “context” question required just a bit more analysis; there were some questions I still had that weren’t yet answered. So, I loaded the data into Tableau’s Public version of their application to give a little more analysis flexibility. Here is the dashboard I created to better understand expertise:
A pretty nice linear correlation between company size and improvement trends, don’t you think?
You made it to the end!
This post turned out to be much longer than I wanted it to be, but hopefully you found it interesting and learned a few things about your fellow readers and how to display different kinds of survey responses. If you have other insights you think you see, please comment below! Thanks for participating!
Have you noticed that sometimes it’s hard to get your point across? Do you find you’re trying to do the right thing with your information, but the organization just won’t cooperate?
We think this is happening too often in the companies the Juice Community lives and works in. And we want to do something to change it.
We want to better understand if we’re helping you be more effective in your workplace as an information evangelist. To make this possible, we’d like to ask (yea, even beg) you to complete a short 10 question survey about how information presentation is making progress in your company and if you feel alone or supported by the info-viz pundits out there.
But you might ask “what’s in it for me?” Well, to begin with, we’re going to demonstrate how to summarize qualitative survey information. You’ll get some great examples of how to apply non-traditional charting styles to problems within your organization.
However, we can’t do it alone; we need you to complete the survey. And if we don’t get enough respondents, the results won’t lend themselves to what we have planned.
So what are you waiting for? Fill out the survey here and help us help you help us. And what does Gilligan’s Island have to do with information presentation? Well, you’ll just have to take the survey to find out!
Update: The survey is now officially closed. Thanks to all who responded. We’ll have the results out in a few days.
Seems like everyone’s trying to understand the future with respect to their customers. We see companies like Google, LinkedIn, and Facebook using predictive analytics to predict user user behavior. Even Stephen Few is giving predictive analytics air time, in classic Fewian cut-right-to-the-core style. So, when we recently had the opportunity to get some predictive analytics insights from one of the industry’s thought leaders, we just couldn’t pass it up.
Eric Siegel, Ph.D., is an expert in predictive analytics and data mining, and is the Conference Chair at the Predictive Analytics World 2010 conference. This is the premier predictive analytics conference and is the “business-focused event for predictive analytics professionals, managers and commercial practitioners.” We asked Eric some questions about the trends he’s seeing in this field and wanted to share them with our community.
(Also, don’t miss out on the Predictive Analytics World discount code at the end.)
Juice: BI visualization has certainly started to become more mainstream in the past few years. Where is predictive analytics on this maturation/adoption curve?
Eric: Predictive analytics has crossed the chasm and hit mainstream in many sectors, such as credit scoring for financial institutions, response modeling for large direct mail houses, fraud detection, and others. And it is mature in that most large and many mid-tier businesses have employed it in one way or another, if only in a first-stage fashion. All industry verticals are replete with success stories.
Juice: Would you say predictive analytics is used more for understanding or for action?
Eric: I’ve always had the impression that predictive analytics is employed with action more the central objective than understanding, although understanding is usually also enjoyed, at least as a “side effect.” A predictive model’s scores drive operational decisions for each customer – that’s the action for which it’s designed. But by taking a gander into the rules or patterns embedded in the predictive model, strategic insights are often also gained.
On the other hand, the results of the Predictive Analytics Survey put the two benefits as a near tie. This may be because, while fewer projects put insights ahead of action, those with action first also typically include insights as well (the pertinent survey question was a check-all-that-apply).
Juice: What are some of the best examples you’ve seen of predictive analytics applications that are designed for the “non-analysts”?
Eric: Well, there are two sorts of “action” that can be driven by predictive analytics: decision automation and decision support. In almost all cases of the latter, where staff “in the field” are provided additional information in order to make more informed their decisions – such as customer service agents providing cross-sell offers based in part on system recommendations, or consumer banking branch managers greeting their clients most at risk of churn – it is a non-analyst who “consumes” the predictive scores output by the analytics system.
Juice: How important is real-time to predictive analytics results and resulting actions?
Eric: This depends entirely on the application: what actions or decisions are being driven by predictive scores? So, no knowledge of analytics is required in order to answer this question. The good news is, when the predictive scores output by a predictive model are required in real-time – such as for selecting the optimal ad to serve to a user based on her profile and behavior – predictive models themselves operate quite quickly. They may involve sophisticated math, but they almost never have any iterative/repetitive “loops” in their programming, so they can turn a customer’s data into that customer’s predictive score very very quickly. It is the derivation of the predictive model in the first place, the application of predictive modeling over historical customer data, that may take hours or days, depending on the analytical method and analyst’s process employed; once you have the model, you are ready to fly.
Juice: How does scenario analysis fit into predictive analytics? What are some of the best practices around scenario analysis?
Eric: Predictive analytics generally works at a lower level than standard scenario analysis. It is doing such an analysis at the individual customer level, predicting the probability the customer will exhibit a certain behavior, such as a response, purchase, or defection. So, when considering a prospective predictive analytics initiative, its potential benefits could be put into a scenario analysis. For example, if predictive analytics is to be used to target a retention campaign, its target benefit of decreasing churn by, say, 10% more than current retention efforts could be plugged into a scenario analysis in order to calculate project ROI and gain further traction for the project.
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.)
About two weeks ago we released the first part of our Guide to Creating Dashboards People Love to Use. We hope that you’ve already downloaded that document and have found it to be useful.
Today, we’re making Part 2: Structure available for download. If you’ve already registered, you will be receiving this second installment automatically via email. However, if you’ve been denying that little voice in your head telling you to “just click it”, now’s your chance. Register today and get both parts!
Of course, all registrants will get part 3 when we make it available in a few weeks. Happy reading!