Data Fluency

New Years Resolutions to be a Better Data Product Manager

It is the the New Year, my favorite time for New Year’s resolutions. Time to look inward to see how we can change ourselves to change your world.

If you’re responsible for a data product or analytical solution, you might consider a little self-reflection in pursuit of a better solution for your customers. Here are a few places to start:



the ability to understand and share the feelings of another.

When it comes to data products, you’ll want to foster empathy for the users of your data. More likely than not, they have concerns such as:

  • Your data may replace their power in the decision-making process.

  • They don’t have the data fluency skills to properly interpret the data and what it means for their decisions.

  • They are afraid of changes that will impact how they do their work.

Appreciating and acknowledging these fears is a first step in building trust with your users.


Learn to flow

“I would love to live like a river flows, carried by the surprise of its own unfolding.” — John O’Donohue

We all a little guilty of wanting to make others bend to our view of how things should work. This year, you may resolve instead to “flow like water.”

Data products should enhance how people make decisions, giving them the right information at the right time. This is best accomplished when the data product can fit into the existing workflows so you are augmenting the user’s role rather than trying to change it.



“Wise to resolve, and patient to perform.” — Homer

Patience is accepting that progress takes baby steps. This is a critical skill to help manage your data product ambitions. The possibilities for analytical features can seem limitless — there are so many questions that should be asked and answered.

Beware this temptation. You’ll want to find the most impactful data first to allow your users to learn what they can learn. Before you try to do it all, have the patience to gather feedback and plan your next release.


Growth mindset

“People believe that their most basic abilities can be developed through dedication and hard work.” — Carol Dweck

Analytics is best served by a growth mindset, the belief that taking on a challenge (and sometimes failing) with expand one’s mind and open up new horizons. Useful analysis begets questions, which leads to more analysis and even better questions.

As a data product manager, you want to encourage this growth mindset in your customers, encouraging and enabling them to expand their understanding of their world.



“We are less when we don't include everyone.” — Stuart Milk

Every year I tell myself I need to be better at meeting new people and keeping up with old friends. It’s a good ambition if you are leading efforts on a data products. It takes a diverse set of roles to get the support and commitment in your organization. Have you gotten legal on board? How about IT security? Does marketing and sales understand the value of your data product and who you are trying to target? You may need to change the way people think about making use of data to build company-wide support for your solution.

Data Fluency Dorks Unite

How we communicate data is broken.

There. I said it.

It may not be nice to hear, but deep down you know it's true. You can see it in the way that data gets delivered to audiences: email attachments no one wants to open, 50-page slide decks filled with never-ending complex charts, and scrolling pages of dashboards with no context around them. It's not only messy, it interrupts the ability to adequately share and communicate important information about data.

So what's the solution? How do we deliver data to audience where they can draw out conclusions and information that is going to be meaningful to them? The answer: data fluency.

Data fluency, or data literacy, is something that we at Juice have been talking about for years (we literally wrote the book on it). We recently sat down with Dalton Ruer, or as he's more familiarly known around the web, QlikDork, to discuss the details of data fluency and how to achieve it. Check out the video below to hear from Juice CEO Zach Gemignani and Global Head of Data Literacy at Qlik Jordan Morrow and learn what having data literate consumers means, how to get good at choosing visualizations and weaving them into engaging stories, what a data fluent culture looks like, and so much more.

Gift Ideas for Data and Visualization Lovers: 2017

It's that time of year again. Thanksgiving is over, and the mad dash to find the perfect gift for everyone on your holiday shopping list is on. If you're anything like us, you've got a number of data visualization enthusiasts on that list that you just know are going to be particularly difficult to buy for. Thankfully, we're back with our annual gift guide created specifically for people who love data and visualization. Read on to find out exactly what to buy for your data-loving friends and family.*


Just like last year, we're kicking this gift guide off with a selection of books that we think any data lover would enjoy. While there are so many excellent books on data visualization to choose from, these are a few of our favorites that were released (or re-released) this past year, with a few old classics thrown in as well. 

The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave

Semiology of Graphics: Diagrams, Networks, Maps by Jacques Bertin

Visual Journalism: Infographics from the World's Best Newsrooms and Designers by Javier Errea

Infographics: Designing and Visualizing Data by Wang Shaoqiang

Presenting Data Effectively: Communicating Your Findings for Maximum Impact by Stephanie Evergreen

Storytelling with Data by Cole Nussbaumer Knaflic 

Beautiful Evidence by Edward Tufte

Data Fluency by Zach and Chris Gemignani


A few years back, Juice gave each of its employees a piece of sound wave art and it was a huge hit. One employee actually loved his painting so much that it now hangs permanently in Juice's Atlanta office. These pieces are not only custom and unique, they're absolutely beautiful visualizations of something that everyone loves: music.

For Kids

It’s never too early to start introducing the children in your life to the wonderful world of data, visualization, and technology. Instead of wandering through toy stores frantically searching for Fingerlings, consider instead one of the cuter, cuddlier, and less noisy distribution plushies from Etsy seller NausicaaDistribution. These visual guides to Star Wars and comic books make for great introductions for kids and teens to the wonderful world of visualization. And if you want to start them really young, check out the Code-A-Pillar from Fisher Price. It's a seriously cool toy that involves planning a path for the robotic caterpillar and getting it to follow that path using coding.

For the Data Lover Who Has Everything

What do you get for your data loving friends that already have everything on this list? How about the most customized visualization possible - one of their DNA! Give someone the ultimate information with either a 23andMe or AncestryDNA report that details his or her ancestry, food intolerances, and so much more! It will definitely be unlike any other gift they've ever received before.

These are just a few ideas for gifts for your data-loving friends. For more ideas and inspiration, check out our gift guides from previous years. And of course, have a very happy holiday season!

Related reading:

*Or for yourself. We don't judge here.



Gift Ideas for Data and Visualization Lovers: 2016 Edition

The trees have lost their beautiful fall foliage, the days grow shorter and icier, and our pants have gotten tighter from all of the pie that we ate at Thanksgiving. All of this can mean only one thing: it’s officially the holiday season! It may be the most wonderful time of the year, but it can also be the most stressful. There are always those people who are just impossible to shop for, and data viz lovers are no exception. To help with the dilemma, we’ve compiled a collection of what we think data and visualization fans would most like to receive. Grab a mug of steaming hot chocolate and get ready to shop!


I know, I know. Books are on every gift guide, but hear me out. 2016 saw the release of some incredible publications on topics such as daily data visualizations, how to pick the right chart for your data, and becoming a more persuasive speaker, just to name a few. These books are not just informative and interesting, they have also most likely been in your data viz enthusiast’s Amazon cart for some time. So while books may not be the flashiest gift, they're something that the people on your list truly want. Here are some of our favorites:

Better Presentations: A Guide for Scholars, Researchers, and Wonks by Jonathan Schwabish

Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel by Jorge Camões

Data Visualisation: A Handbook for Data-Driven Design by Andy Kirk

Dear Data by Giorgia Lupi and Stefanie Posavec

Effective Data Visualization: The Right Chart for the Right Data by Stephanie D.H. Evergreen

Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations by Scott Berinato

Illuminate: Ignite Change through Speeches, Stories, Ceremonies, and Symbols by Nancy Duarte

The Truthful Art by Alberto Cairo

Data Fluency: Empowering Your Organization with Effective Communication by Zach and Chris Gemignani

Prints & Posters

What could be a better gift for someone that loves data and visualization than an actual data visualization? And with so many options, you can easily match it to other interests and hobbies. Political junkies can enjoy visual histories of the Republican and Democratic parties available over at Timeplots. Your friend that happy-cried when the Cubs won the World Series can remember it forever with Chartball’s visualization of the 2016 season. And for everything else, there’s Popchart Lab. They have an incredible amount of visualizations ranging from a charted cheese wheel on an actual cheese platter, to all the varieties of beer, to a chart about nothing.

Data Products

Wearable technology that provides personalized data and information? Sign us up! Fitbit recently released the Charge 2, which not only tracks daily activity and sleep but also measures how your cardio health compares to people similar to you. An option for someone who may not want an attention-drawing wearable on their wrist is the jewelry from Ringly. Ringly offers rings and bracelets that track similar activities as the Fitbit (such as calories burned, steps, and floors climbed), but also syncs with your phone and sends app notifications. And who says data products are only for people? Let Fido in on the action and check out Nuzzle. Though currently only available for pre-order, Nuzzle is a smart pet collar that ensures that if your pet ever gets lost or sick, you’ll know. It uses GPS and temperature monitoring so that you can check in on your pets from your phone and see how they’re doing throughout the day.


There are two very useful card sets that debuted in 2016 that would both make great gifts. The first is the Data Visualization Chart Chooser Cards, a Kickstarter that quickly gained momentum not long ago. Similar to Juice’s own Chart Chooser, the cards help the user to select which chart is best for displaying and communicating specific data. The other card set that would make a great gift is the pretty and practical set of Graphic Continuum flash cards from Severino and Jonathan Schwabish. 


A few months back, Alberto Cairo demonstrated the importance of visualizing data before putting your blind trust in summary statistics with the Datasaurus. The tweet quickly gained popularity, and thanks to the power of the Internet you can now get the Datasaurus on t-shirts, mugs, pillows, and phone cases. Fashion meets function meets data viz, and something that the data nerd in your life will think is a hoot.

Subscriptions & Donations

Perhaps one of the best gifts you can give the data and visualization lover in your life is a subscription to a news source that routinely produces impeccable graphics and charts. Outlets such as the Washington Post, The New York Times, and The Guardian are all great options for someone looking for timely data visualizations. If the person already has a subscription to one (or all) of these, consider giving the gift that keeps on giving and make a donation in the recipient’s name to ProPublica.

Did we miss your favorite data-themed gift to give? Let us know! Send us a message at Most importantly, have a happy holiday season!

Driving Healthcare Data Culture Forward

Last week, Juice Analytics participated in the Health 2.0 Atlanta panel, a co-hosted event by the Data Science and BI Society of Atlanta and Health 2.0 Atlanta. The focus was on analytics and healthcare and it was a great event. There was so much interest, they had to move the event to a larger venue! That tells me two things - (1) people want to get more out of their data and (2) Healthcare is behind and they really want to catch up. Two of my favorite “tweetables” of the night, said by Jason Williams, VP of Analytics and Strategy at McKesson, backed up those assumptions.

Getting more out of your data

The first “tweetable”  was something we see at Juice all the time: “Nobody wants analytics, people want answers.” This relates back to people wanting more out of their data. Right now many people simply have data - and that’s it. But people want more than just a bunch of charts and numbers on a screen, they want insight. They want to be told where the problem is and given insight into how to fix it. If you’re simply delivering data either in a spreadsheet or just a series of charts, you’ve missed the mark. And for the record, this problem isn’t specific to healthcare. It’s all over.

Catching up in Healthcare and the path forward

My other favorite “tweetable”, originally said by W. Edwards Deming, was “In God we trust; all others bring data.” To get buy-in on a problem and solution, you need the data to support your position. The problem is that not everyone is ready to embrace data. As the quote alludes to, it’s all fine and well to think or believe you know the answer, but data helps you actually know the answer. Sure there can be a human element involved, but being informed with data to back up decisions is useful and important. In order to move data in healthcare forward, there needs to be a culture around data. It needs to be ingrained in an organization as useful and be included in everyday conversation.  

Embracing a data culture in healthcare will become even more important as we move into the future of what healthcare could look like. Much like Google Maps on your phone adjusts your course based on a wrong turn or an accident on the highway, it was said that healthcare will begin to use data in much the same way. Healthcare data should and will move in the direction of being event driven and using data to adjust as things are happening, rather than being reactionary. I don’t know about you, but that sounds exciting and full of promise! But to get there, you first need a good data culture.

The event was not only a great success, it was insightful - which is what we love! It would seem that to begin to move your healthcare organization forward, there are two things to focus on. One would be providing insight, not just data. The other is to promote a culture of data that is widely adopted within the organization. Without that, having insight won’t matter since nobody will want to use it.

To learn more about creating a data culture in your organization, check out Data Fluency: Empowering Your Organization with Effective Data Communication, written by Juice Analytics founders Zach and Chris Gemignani.

To learn more about how we help our healthcare clients provide data insights and succeed, check out our case studies or get in touch.


Data Discussion Etiquette from Brad Pitt

Before Matt Damon impersonates an investigator in Ocean’s Eleven, Brad Pitt’s character delivers a little pep talk. 

Watch the 40 sec clip:

Rusty Ryan (Brad Pitt) explains the rules of undercover conversation to Linus (Matt Damon). From: Ocean's Eleven (2001)

Now watch it again, but this time imagine yourself giving a pep talk to the next email, powerpoint slide, or dashboard finding that you are about to send out. 

Presumably your data is not meant to distort, yet we can mine the advice here for a few practical communication tips to improve data-informed discussions.  

Let’s break down the key moments.

Be natural.

[Damon takes an unnatural, stiff stance] “No good. Don’t touch your tie. Look at me.”



His first posture is fidgety and self-conscious with an overly professional stance. 

First impressions are holistic and endure when it comes to perceived levels of interest and credibility. Most of us have an uncanny ability to sniff out a fake, and how data enters discussion is no exception. We’re not computers, so we don’t enjoy an overwhelming data dump of facts, findings, and insights. Two paragraphs and 15 slides in everyone wonders, “Where is this going? What’s the point?” Messages must be clear and focused, but should aim to jettison the unnatural, mechanical chart headings and the unnecessarily encrypted statistical speak. 

Be honest.

“I ask you a question. You have to think of the answer. Where do you look? No good. You look down; they know you’re lying. And up; they know you don’t know the truth.”


Be honest with what you do and do not know and what data you do and do not have. Your audience expects to have certain questions answered in order to take your information seriously. Your audience wants to both hear and understand answers to questions like these:

  • How do I know I can trust this data? How was it collected and who was involved?
  • How exactly is this metric calculated?
  • I see the number is X, but how do I know whether that is good or bad? 
  • What’s the history of this number and the frequency of its collection? How quickly does this number usually change? How long does it typically take to influence it in the future? 
  • How does this compare to other locations with similar attributes?
  • Why is this useful for me to know? How will it change what I care about?

These questions aren’t novel. They follow the 5W’s basics. Yet they are often either left out or overcomplicated in most data discussions. The goal here is to acknowledge these needs in the simplest, most useful way.

Start with a (very) short story.

“Don’t use 7 words when 4 will do.”




With data, as with words, precision is as much an art as a science. Still, helpful tools exist. Ann Gibson wrote a relevant post and I highly recommend reading the article for all the details, but here’s the magical excerpt:

Once upon a time, there was a [main character] living in [this situation] who [had this problem]. [Some person] knows of this need and sends the [main character] out to [complete these steps]. They [do things] but it’s really hard because [insert challenges]. They overcome [list of challenges], and everyone lives happily ever after.

The beauty of this frame narrative is that it provides a structure for those who are too long-winded to focus on the essence of their own message, and it helps others whose ideas tend to dart all over the place to preserve a sequential flow.

Each of these [placeholders] are candidates for data context that help satisfy the previous "Be Honest" section. I mocked up a quick scenario that demonstrates a short story with useful data context:

Set your mark.

“Don’t shift your weight. Look always at your mark but don’t stare.”



You’ve likely heard of S.M.A.R.T. goals before, but are your charts smart? Something as simple as a target value by a specific date on a chart can work wonders at moving towards something tangible. People crave purpose, so set and communicate your goals. But don’t be that presenter who stares incessantly at your metrics and goals. 

Be enjoyably useful.

“Be specific, but not memorable. Be funny, but don’t make him laugh. He’s got to like you; then forget you the moment he’s left your sight.”



Jazz it up,” “Make it shine,” and “Make it pretty” are all phrases you’ve either heard or used yourself. Few situations are more disappointing then when a company tries to overcompensate with their insufficient, irrelevant data by lathering on the “wow factor.” Don’t succumb to making your data memorable for the wrong reasons. For business the goal isn’t memorable chart-junk, but that does not mean your data should be lifeless and shallow.

Don’t leave people hanging.

And for God’s sake whatever you do, don’t, under any circumstances…”



The worst move you can make is to omit the call to action. End with clear next steps, key questions posed, or an action button that allows your audience to engage with immediacy, while your solid ideas are fresh and ripe for action.

Thirsty for more? Check out these related blog posts:

Best Pie Chart Alternatives

We’ve all heard the sermons and lectures on the evils of pie charts, so why is it that they continue to be used in abundance? At Juice we’re regularly surprised by the use (and misuse) of pie charts in the market despite all the literature, blog posts, and funny tweets against them.

Perhaps there is some Illuminati connection to Pi and circles that ensures their existence. Whatever the reason, we felt it would be helpful to compile some of the best information on pie chart alternatives and share some examples. Special thanks to Cole Nussbaumer, Lee Feinberg, Nathan Yau, and Jorge Camoes for their always great work and examples.

  • When to use pie charts: Jorge Camoes does a great job in his blog post on the optimal number of categories in a pie chart. We won’t spoil it for you, but it’s probably not what you’d think. Have you gotten Jorge's book yet?  Maybe now you're convinced. 
  • Preference: One of the arguments we often hear in favor of pie chart is due to preference.  This article talks about the importance of preference and how it correlates with performance.
  • Default Setting: Another observation we’ve made is that pie charts are often the first or default option, so they get used more often. Check out these posts on default setting alternatives:

If you need more direction in your quest to branch out from pie charts, check out the Juice resource page for more valuable ideas.  

Top Signs Your Audience Isn't Data Fluent

We talk about Data Fluency a lot at Juice. We're so passionate about it, we wrote a whole book on the subject. Because of this, if you're a regular visitor to our blog there's a good chance that you're fairly data fluent. But even though you may be, oftentimes you have to present to an audience that isn't. If your audience doesn't understand and can't use the information you share with them, then all the time and effort spent into producing the data is wasted. To prevent this from happening, look for these signs to determine whether or not your audience is fluent with data.

1) They rarely use data - Understanding the frequency at which your audience uses data is key to assessing their level of data fluency. Ask yourself, how often are they looking at data? Is it daily, weekly, monthly? Once you know how much time they typically spend working with or looking at data, your strategy becomes much clearer. Plan on keeping your presentation simple, and be prepared to answer lots of questions.

2) They're surrounded by too much data - It may be the case that your audience has so much data coming at them regularly that they can't make sense out of what you're presenting to them through all the noise. These people are inundated with data daily, and are most likely pretty decent at talking the data talk (think "data conversationalist" rather than data fluent). Tailor your message to be brief, hitting only the key points and focusing on select metrics.

3) They're uncomfortable with technology - Do they have a smartphone with apps? Many apps rely heavily on data, and whether or not they're familiar with them could be a sign of their level of data fluency. If instead you notice that they have a flip phone clipped to their belt, they might be what we call data-phobic: they intentionally avoid or mistrust data. A person's lack of technology adoption may offer a clue to his or her resistance to consuming data. Be able to recognize data-phobes so that you can deliver your message without overwhelming them.

These are just a few indicators that your audience may not be data fluent. There are others, and each situation will vary by circumstance. Learn more about data fluency by checking out Juice founders Zach and Chris Gemignani's book, Data Fluency: Empowering Your Organization with Effective Data Communication. 

5 Lessons for Agencies to Become Data-Powered Partners

Guest blogger: Rob Getsy has over a decade of experience leading B2B and B2C marketing strategies and operations for companies in the Education, Telecom, and Tech industries. 

Client and Agency relationships are not unlike many personal relationships. Some are good-natured, trusting and fruitful, while others are more difficult with each party blaming the other when things go wrong. I spent more than a decade on the client-side of the table, managing multi-million dollar budgets, working with media and creative agencies. Here are few things I’ve learned that can make or break these relationships:

Weekly status reports are difficult.

No matter the business, weekly reporting calls are considered table stakes. Every Tuesday morning the agency is supposed to readout the previous week’s activities to tell the client what worked, what didn’t, and what changes they want to make. Oftentimes, the data jockeys on the agency struggle to aggregate the data in time for the call. The haste in which these reports are cobbled together is often quite obvious to the client. We don’t want to move the call every other week to give you more time, and we certainly don’t want to read a report with errors. 

Agencies need to bring insights, not raw data.

Reading raw data tables and trying to decipher patterns is an acquired skill. Most clients don’t have the time or data fluency to look at large Excel spreadsheets with their agency and figure out the implications. There is too much data to try to present it all in a way that we can comprehend. You should be telling us a coherent story with the most pertinent aspects of the data. Bring interesting trends and relationships in the data up for conversation. Tell us what you think it means and what you recommend.  Then, if I still want to dive down further, let me play in the Excel PivotTables after we’ve covered the key points. In some ways, the services of agencies are becoming a commodity. On more than one occasion, I’ve been swayed to sign with an agency that had unique reporting capabilities and a demonstrated ability to turn data into smarter actions.

I’m looking for partners, not vendors

Over the past 15 years in my marketing career, I’ve worked with many vendors but only a few partners. What’s the difference? Partners go above and beyond your expectations and become an extension of your business. They know your customers, your sales cycles, the quirks of every business line, the hours of your call center, and sometimes even news about your company that you hadn’t heard yet. They even help you strategize and plan media spend across tactics they aren’t responsible for.  Vendors are outsiders that never get to know your company acronyms, do only what they are asked to do, and make errors in their reporting that demonstrate they don’t understand the business. The worst part about those errors is that, as the client, we can see them immediately and you can’t. I’m selling cupcakes… I wish the average revenue per sale was $150.00, but it’s not. It’s $15.00. You fat-fingered a decimal point, didn’t catch it and now I’m skeptical about the rest of the report. 

Talk to me about the future too.

The past is great, that’s what we’re reporting on every week.  But I want you to take the next step and start using that data to plan and predict the future. That’s one of the main reasons we’re looking at past performance -- it’s not just to pat ourselves on the back.  I want a partner to look at a broad set of my historical data and build predictive trends based on variables like media efficiency, attribution, and seasonality.    

Excel is amazing, but not for socializing learnings within your team.

I’m an Excel power user. In fact, I use it for just about everything (including things I shouldn’t). But I only had to be yelled at once for sending an exciting piece of data to my CMO in an Excel file.  Executives don’t have time to dig through an Excel file.  In today’s social world, reports should be sharable with a click of a button. Find a technology that summarizes the data for you and makes your life more efficient. 

Who will step up and bring it all together? That’s the question that those of us on the marketing client side are always asking ourselves. Who will be our partner, not vendor? Who will bring us the next level reporting solution so we can have discussions worth having and share those insights easily? And who will help use all that ‘big data’ to optimize for the future? 

Contact us to find out more about how you can partner with us to share insights and create valuable discussions. And for more information on how we create dashboards and insights people love to use, check out our white paper, "A Guide to Creating Dashboards People Love to Use".

10 Screenwriting Lessons for the Aspiring Data Author

The art of data communication is in its infancy. Fortunately we can learn from other forms. Photography, cartoons, literature, painting, poetry, graphic design -- these are all about using language (visual, aural, written, etc.) to capture attention, convey information and ideas, and move an audience in some way. (In fact, helping organizations understand the power of data communication was the goal of our book Data Fluency.)

When I came across John August’s blog post about how to write a scene, I saw parallels with dashboard and visualization design. John is an accomplished screenwriter (Big Fish, Charlie and the Chocolate Factory, Frankenweenie) and popular blogger and podcaster.

His first piece of guidance: “What needs to happen in this scene? ...The question is not, “What could happen?” or “What should happen?” It is only, “What needs to happen?”

This is the critical concept in all of information design. It isn't a question of what data can you show, it is a question of what data you need to show. How do you need to propel your users forward in their role? Give your audience data that they can use to be better at what they do.

Next, he asks the screenwriter: “What’s the worst that would happen if this scene were omitted?...One thing you learn after a few produced movies is that anything that can be cut will be cut, so put your best material into moments that will absolutely be there when it’s done."

Like a movie audience, your audience has a limited attention span (unfortunately the data presentation business has fewer built-in constraints than the movie business). What data can you remove from the report that won't leave decision-makers misguided or confused? In our work, we always ask: What action is someone going to take when they see this data? If there isn't a clear answer, then leaving it out will help the reader focus on things that are more important.

John emphasizes the importance of choosing your setting..."A father-and-son bonding moment at a slaughter house will play differently than the same dialogue at a lawn bowling tournament."

It is no different for considering how information is presented to your audience. Information designers may overlook the different ways for presenting and wrapping context around the data. A daily email report, a printed slide deck, or an interactive dashboard will have very different impacts on your target audience.

"What’s the most surprising thing that could happen in the scene?"

In other words, what options do you have for grabbing the attention of the your audience? Great data visualizations do this by making data emotionally resonant. A couple good examples include The Fallen of WWII and US Gun Deaths (both grim data stories). In a more mundane example, we designed a data app that showed the costs of training programs in hospitals. By putting a dollar figure on this everyday investment, we were able to capture attention in a new way.

"Is this a long scene or a short scene?"

Edit yourself, show less data, and say more. We all have experienced the scourge of the neverending powerpoint deck or Excel report with endless sheets. Extraneous content comes at a high cost.

"Brainstorm three different ways it could begin."

Dashboards seldom consider a beginning or an end. But your audience will, one way or another, find a starting point and explore data in a sequence. Will you help them with this path? I believe it is crucial to offer an obvious place to begin and useful end-points. It is a feature we've baked into the fundamental design of our Juicebox platform

"Play it on the screen in your head."

I love this advice as applied to information design. Imagine your visualizations with different amounts of data, different values, different results and insights. Pretty soon you'll find the weaknesses. This is my first critique of the pretty dashboards designed on Dribbble. The data will never look so pretty as this in real life and the design will become incomprehensible.

Finally, John ends with advice on the writing process: 1. Outline; 2. Write the full scene; 3. Repeat 200 times. He wants screenwriters to start with the bones of the story, fill in the flesh, then iterate — without fear of tearing the whole thing down if it isn’t working.

Every form of communication has its challenges. Films face constraints and audience expectations, and yet have creative breadth in what can be put on the screen. Communicating data also has an interesting challenge for data authors. It takes a rigorous, analytical mind to understand the data and its meaning, but also requires the artistic skills of a screenwriter. It is a rare combination that needs to be taught and cultivated. If you don’t fit in the slim overlap of this Venn diagram, there is more to learn.