What’s Inside

• 0:00 Intro
• 0:44 What Canva looks like inside
• 1:11 Making a new infographic in Canva
• 1:20 Paid vs. free Canva
• 1:55 Bad infographics are probably still better than 100-page Dusty Shelf Reports
• 2:15 Brand presets
• 2:39 Mixed case is fastest to read
• 2:46 Left-aligned text is fastest to read
• 3:01 Adjusting the step-by-step diagram
• 3:57 Adjusting the icon array of the gingerbread people
• 4:11 Avoid red-green combos
• 4:22 Adjusting the 3D column chart
• 5:52 Adjusting the donut charts
• 6:40 Adjusting the org chart
• 7:16 Adjusting the honeycomb diagram
• 8:05 Change my mind? Do you have an example of a GOOD Canva infographic??

The post Why I’m Not in Love with Canva for Infographics & Dataviz appeared first on Depict Data Studio.

She’s here this week sharing time-saving tips on using a voice command and dictation software called Dragon to help with data viz. Thanks for sharing, Lauren!

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Hey everyone!  Lauren Fox here from the Research & Evaluation Division (RED) of the University of Arkansas for Medical Sciences. Our group focuses on translating research into practice in fields like early childhood education, child nutrition, abuse prevention, and HIV education.

With that comes the need to communicate our work to both expert and layperson audiences, and with that comes… a lot of data viz.

Don’t get me wrong, I love doing this kind of work and I readily describe myself as a data viz nerd.

Even as a novice, however, it quickly became apparent that Microsoft Office wasn’t designed with data viz in mind.

 There are so many things we need to access that are buried three or four clicks deep (think the align objects sub-menu) and just so happen to be the kinds of actions that need to be repeated over and over and over again.

And yet, for many readers of this blog (whether due to budgets, clientele, or our type of projects/deliverables) working in Office is our only option. Luckily, a voice command and dictation software called Dragon can help overcome some of Office’s limitations.

When I originally thought of Dragon as a potential solution, it seemed like it would help with writing emails or even transcribing interviews, but that the data viz process would be too complex for it to be very useful.

Oh, was I wrong!

Dragon does have some limitations that need to be worked around to handle data viz work, but once I put in the upfront time to find those workarounds and set them up, it has really increased my productivity.

In today’s blog post, I’m going to walk you through how to set up your Microsoft Office programs and Dragon custom commands to use this program to your advantage.

As a bonus, I’m also going to give you the custom commands file exported from my Dragon profile and my Office Quick Access Toolbar files so the setup process is much faster for you than it was for me!

Purchasing the Right Version of Dragon

First, it’s important to note that not all versions of Dragon are compatible with data viz work. There are currently 5 different categories: home, premium, professional, legal, and medical.

At minimum, you’ll need to purchase the professional version because it’s compatible with Excel, PowerPoint, and Publisher, and it gives you the ability to create and use custom commands.

A single license of Dragon Professional Individual version 15 will cost you $500. If you’re upgrading from a previous version of Dragon, it should be about $250.

Technically, Dragon is supposed to work better if you use a Dragon-approved headset for voice recognition, but I’ve actually found that a $40 external mic from Amazon works better than the cheaper of the two Dragon-approved headsets I saw.

How to Create/Edit a Custom Command in Dragon

To create new commands from scratch, go to Tools –> Manage Custom Commands –> New –> Advanced.

Make sure your Command Type is set to “Step-by-Step” and your New Step is set to “Keystrokes”.

Then use the Insert button to add the keyboard combos you want to assign to each verbal command.

Finally, hit the Train button to train the software how to recognize that command with your voice.

The (Strange) Limitations of Custom Commands

If you press Alt in any Office program, a list of Alt + combinations appear for most clickable options, giving you the commands to enter. Because there are so many clickable options, many of those have multiple characters, such as “Alt + AA”.

Should be simple to enter right? Not so much.

Dragon can only recognize one character after your Alt when programing the Keystrokes custom command, making it all but useless for data viz, as all the relevant functions you’ll need have multiple characters after Alt.

Dragon also has a Record Macro option in the command type. That should be the easiest and most flexible option because it records your clicks and keystrokes as you do them and repeats those actions exactly. You can even watch your mouse cursor move just as you did when recording it.

This seemed like a great option because no matter how long you take to record a macro in Excel, the macro finishes the whole process almost instantly once activated.

For whatever reason though, when you create a Dragon command based on a macro, it executes incredibly slowly. In my testing, I recorded a macro that took less than a second to perform, yet I watched my mouse take roughly 5 seconds to follow the same path. Ideally, it would just execute it near-instantly, like macros in Excel.

It seemed like I was at a dead end.

The Alt + function through Keystrokes wasn’t flexible enough and the Record Macro function was too slow to be practical.

But after a little more research, I found a workaround.

The Workaround

Every Office program has an area that’s called the Quick Access Toolbar. It may not be enabled by default, but you can turn it on and set a variety of shortcuts for you to easily get to.

In our case, the big advantage of using the Quick Access Toolbar is that the first nine icons are always coded as Alt + 1 to Alt + 9, no matter what you set to appear in the toolbar.

Jackpot!

(Sort of…but more on that later)

Rather than take forever to set your Quick Access Toolbar icons to be the exact same items in the exact same order across Publisher, Excel, Word, and PowerPoint, I’m going to give you the shortcut.

All you have to do is click the drop-down menu on the Import/Export button and import the matching Quick Access Toolbar files I’ve created for each of these programs (download at the bottom of the page).

This will replace your current Quick Access Toolbar setup with the one that I use and that matches my custom Dragon commands (download also below).

Other than save yourself time, there’s an important reason why you want to replace your current Quick Access Toolbar setup with the one that I use.

Most Office programs have multiple options you can place in your toolbar for essentially the same command (like Align Objects as a single option or Align Objects as a drop-down menu), BUT not all Office programs have all the same options for shortcuts.

For example, some only have Align Object as a drop-down instead of both the single object and drop-down menu symbols.

Importing my setup will make sure you have the shortcuts that are compatible across all four programs.

Uploading my Dragon Commands & Retraining for Your Voice

Now that you have my Quick Access Toolbar setup files uploaded for PowerPoint, Publisher, Excel, and Word, I’ve got another shortcut for you—my Dragon custom commands backup file.

All you need to do is import this file and retrain the individual commands for your voice and you’ll be ready to go!

From the Dragon Bar, hit Tools –> Command Browser –> MyCommands –> Import and select the import file.

Once those are uploaded go to Tools –> Manage Custom Commands –> Click a command –> Edit –> Train –> Train (again) to replace my voice with yours.

Why My Custom Commands Say Things Like “Level Left” Instead of “Align Left”

There are a set of viz-related commands that are natively programmed into Dragon but only work in PowerPoint; this includes the Align Object commands.

When Dragon hears you start a custom command that sounds like one it has natively, it gets confused and won’t execute either command.

That’s why I’ve set many of my commands to be slightly different verbally than how they actually read, such as “level left” instead of “align left”.

Final Thoughts

I’m sure many of you almost closed this browser window as soon as you read the price of a Dragon license. For most of us, $500 is no joke, and for others, it’s completely out of the question. I’m fortunate to work for an organization large enough to afford occasional purchases like this when there’s a clear efficiency or effectiveness advantage.

There are some things that Dragon can’t help with very well, like customizing individual charts in Excel (those menus go way too deep). For nearly everything else, however, it allows me to do data viz work at 2x – 4x the speed, with only a fraction of the keystrokes and clicks.

As the years go on, data viz is becoming more and more in-demand and both the volume and complexity of our work are increasing. While $500 seems like a lot up-front, you could easily make it up based on the efficiency gains alone, especially now that you have my shortcut files to make setup really simple.

Even if your organization isn’t convinced, there’s another good reason you should try to find a way to pay for it yourself: Human hands aren’t built to sustain the extraordinary volume of keystrokes and clicks we subject them to year after year. Ask practically any health care worker you know, and they’ll say the same.

Consider this a down payment in preventing (or at least delaying) injuries like carpal tunnel, which affects many knowledge workers, and in severe cases, could hamper both your career and quality of life down the line.

Download Files

As a bonus, I’m giving you the custom commands file exported from my Dragon profile and my Office Quick Access Toolbar files so the setup process is much faster for you than it was for me!

Download the files here: https://depictdatastudio.gumroad.com/l/DragonCustomCommands

Connect with Lauren

LinkedIn: https://www.linkedin.com/in/lbfox/

The post Speeding Up Your Data Viz (& Preventing Future Injuries) Using Custom Commands in Dragon appeared first on Depict Data Studio.

We connected through our mutual speaking coach, Heather Sager’s Speak Up to Level Up class. We’ve since followed each other’s careers and were excited to talk together. 

Listen to the Podcast 

Watch the Conversation

3 Tips for Visualizing Social Change Data 

In the podcast, we discussed three tips for coalitions, foundations, and nonprofits that are visualizing social change data. 

Involve Others in the Data Process Early and Often 

First, get the staff, partners, and community members involved in the data sense-making process early and often.  

My favorite technique for involving others is the data placemat process, which I learned from my previous supervisor, Veena Pankaj. 

It goes like this: 

1. First, we compile preliminary findings into a few handouts, or data placemats. Lots of ugly graphs. Lots of unformatted graphs. 

2. Second, we share those data placemats with stakeholders during a data interpretation meeting. We ask the attendees whether they were surprised by any graphs, what additional information they need, etc. We get them to talk about the graphs in their own words. 

3. Finally, we go back and write the final report (or design the final slideshow, or the final infographic) with the stakeholders’ interpretations of the graphs included. 

You can read more about data placemats in this article that Veena and I wrote for the American Evaluation Association. 

Share Aggregated or Disaggregated Data as Appropriate 

Next, figure out whether audiences need aggregated or disaggregated data. 

Let’s pretend that a nonprofit is running a GRE test prep program for high schoolers. As part of the program, the students take lots of practice tests to see when they’re ready to go take the actual GRE test.  

The students in the program need disaggregated data. They need to see their own individual data to determine how they’re doing and if they’re ready individually.  

A lot of times, the staff who are running the programs also care most about disaggregated data. That means they want to see data specific to each student so that they can individualize their instruction.  

There are also some aggregated summary statistics that might be helpful for those staff. For example, the staff might need to see averages.  

Current funders, prospective funders, and other collaborators will also benefit from aggregated data like averages. For example, they might want to see people in this year’s class compared to last year’s class, or this location’s class compared to a different location’s class. 

Problems can arise when there’s a mismatch.  

For example, if you only show the students the aggregated data, it feels too distant. Finding out the group’s average scores is helpful… but not as helpful as knowing your own scores. Or, if you only show the funders the disaggregated data, they’ll miss the big-picture patterns. 

Remember that Data Visualization Isn’t Supposed to be Hard 

You can use everyday software, like Excel. Just tweak the default settings to make the graphs easier to understand. 

You don’t have to learn coding or programming, unless you want to. 

You don’t need to go to school for graphic design, unless you want to. 

Stay in Touch with Ann Price 

LinkedIn: https://www.linkedin.com/in/awpriceces/ 

Twitter: https://twitter.com/annwprice  

Podcast: https://communitypossibilities.buzzsprout.com/ 

Website: https://www.communityevaluationsolutions.com/ 

The post 3 Tips for Visualizing Social Change Data appeared first on Depict Data Studio.

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Thank you to Ann Emery, Depict Data Studio, and her Simple Spreadsheets class for inviting us to talk to them about the use of statistics in nonprofit program evaluation! If there’s one thing that we never want to miss, it’s an opportunity to tell people their job is easier than they think!

This is why we created ImpactStory Coaching – because it’s actually within reach of small- and medium-sized nonprofits to be clear, confident, and convincing when talking about their impact!

It was also just nice to talk to a group of smart, creative, data-minded professionals who also (yes – that’s right – also) feel overwhelmed by the prospect of having to use statistics.

We used to think our feelings of statistical overwhelm in the nonprofit space was because we were wimps (even though we have literally taken a combined SIX YEARS of graduate-level statistics*).

But then we realized that much of the time, statistics just don’t have much of a role in nonprofit work. And here’s why!

Why Nonprofits Shouldn’t Use Statistics

When working in the nonprofit world sample size is usually very small (i.e., the number of clients served in any given year is usually 40 to 400 people).

Even if you have more people than that (e.g., a school district’s worth of students), it’s still unlikely you need statistics, unless you are trying to answer a scientific-type question (and what scientific-type questions nonprofits with a lot of data might ask is for another blog post on another day).

Simply having a statistically significant group of survey respondents for such a small number of people means you have to get surveys from A LOT of people: 37 of 40 and 196 of 400! This is really hard to do (although we do have tricks for making sure you get surveys from almost 100% of your clients)!

Statistical significance is often mistaken to mean a big difference, but what it really means is a not random difference (e.g., if you looked at a different group of people, you’d find that difference again… it’s a reliable difference). When you have a small number of people, it also means you must have a GREAT BIG DIFFERENCE to get statistical significance.

The math just works out that if you look at 1 million people, just about any finding is statistically significant (e.g., a tiny difference in a big group is almost always not random), but when you’re looking at 100 people, you must have a really big difference to get statistical significance. In the science world, if you have a small group of people and do not find statistical significance, one thing you can do is test a much bigger group!

A Nonprofit’s Mission is to Serve as Many People as Possible to Address an Identified Need

In order to use statistics to identify the impact of a program, you usually need a comparison group (e.g., a random group of people who do not get the program) to which you compare your clients. Ideally, both groups are selected randomly: the people getting the program, and the people not getting the program. (We all know that’s not happening!)

Realistically, the comparison groups available to a nonprofit are either people the nonprofit randomly refused serve – or – a very nonrandom group of people who didn’t want the services the nonprofit was offering. Scientifically, neither of these are good options for comparison groups.

And we’ve never met a nonprofit so flush that they had money to track people they don’t serve. Even if a nonprofit had money to spare, spending this way would not be aligned with its mission to serve as many people as possible.

Nonprofits are Not Set Up to Follow People for a Long Time after Service Provision (e.g., 6 Months to 40 Years)

Most nonprofits provide a service for a specific amount of time, people graduate from that service, and then they go on with their lives (hopefully with more strategies to reach their goals). Staying in touch with people over time is very time consuming and very, very expensive – especially if you want to stay in touch with at least 80% of people (which is a minimum in the scientific world).

If you’re a smaller nonprofit that means you have to track 32 to 320 people over time (to follow up on those 40 to 400 clients you served). Frankly, this is both impossible and still too small to analyze with statistics (see point #1 about statistics with small groups of people).

Using scientific methods to test hypotheses (which are what statistics test) are what scientists do; delivering programming and tracking client progress is what nonprofit practitioners do. 

We have used this example before:  Scientists discover and test medicines to make sure they work. Doctors deliver what’s been shown to work and make sure the people they treat get better.

Two. Separate. Jobs. 

You – our nonprofit friends – are doctors.

Nonprofits Focus on Working with Individual People and Complexity Not Populations and Averages (Which is the Realm of Science)

It’s a cognitive error to assume that statistics (which typically focus on averages) applies to individuals.

For example, the average number of car crashes a person gets into in a lifetime is four (this is scientific knowledge derived from statistics) – but we all know people who get in many more crashes and people who never get in a crash (this is the reality of being an individual in the complexity of life).

And, if you – as an individual – get into four crashes that does not mean that you are now immune to getting in crashes (this is the cognitive error of applying statistics to individuals)!

So, drive safe and buckle up!

Also, if you are concerned about diversity and equity then you need to have more people from marginalized groups from whom you gather data so you can really hear what they have to say. Period.

You do not want to just have a representative number (e.g., a number equal to the proportion in the larger population) because their voices get washed out in the average.

When doing nonprofit work: Each. Individual. Voice. Matters.

What Can Nonprofits Do?

Nonprofits Should Think of Themselves as Conducting Qualitative Analysis with Numbers and Stories

Qualitative analysis basically means you are looking for patterns and changes in patterns in both your numbers data (what people report on surveys) and your stories data (what people tell you in words).

You’re examining how the data look – the shape, the themes, the patterns that emerge, and when the patterns change.

Your Data Team is the litmus test for determining which things are important and meaningful and which things are not.  Data Teams are for answering questions in real life; experimental design and statistics are for answering scientific questions. (Ask us more about Data Teams!  We love to talk about them!)

You HAVE TO GRAPH Your Data to See How it Looks

If you do use math at all it’s probably only to calculate the percent difference, the percent change, and maybe a risk ratio. This means you count how many people say something and how many people didn’t say that.

Graph all the answers in both groups. Then break the groups up differently to better understand the patterns of responses (e.g., males and females, comparisons based on race or income or zip code or classroom or age. . . you get the picture). If you don’t graph your data, you’re sunk. 

You simply have to graph it to see what it’s doing. Mostly bar charts (to compare groups) and line graphs (to look at stuff over time).

Here are some examples:

• Count how many people said “Strongly Agree” and “Agree” compared to “Disagree” and “Strongly Disagree.” What’s the percent difference between the two groups?
• Decide how different these counts are: meaningfully different or slightly different? The best way to make the most valid assessments of how meaningful the differences are is to use a Data Team. (We love a good Data Team!)
• Based on what you know about the people you serve, as well as changes in the community and at your organization, what do you think might be the reasons for those differences? (These are follow-up questions your Data Team can ask during their data review meetings.)
• Think about how you might divide the groups into different groups, or subgroups, to explore deeper questions (e.g., males and females, wealthy and financially struggling, graduated and not graduated, etc.). If you are looking at disparities, what’s the risk ratio of one group having a poor outcome compared to the other?
• If you have data over time (i.e., surveys from the same people at different times) – you may want to look at percent change happened over time?

What Software Should Nonprofits Use?

99% of the time. . . Excel.

If you have data with lots of complex relationships (e.g., data from parents and children, over time, in different programs) you probably want to be using a database like Apricot.

Then you can create and run reports that graph your data with the touch of a button!  And you can still can create downloads of the data behind those reports and create your own graphs in Excel.

If you have many hundreds or thousands of people you are serving, then it’s just easier to clean and sort that data in a statistical package like SAS, SPSS, or R. 

In these cases, we choose to hire someone who’s very good at these programs (like a graduate student taking a stats class) and pay them like $30-$40/hour to clean the data, maybe do some descriptive statistics and show us some averages. Then we have them download the clean dataset (a delimited CSV) and we pull that into Excel for graphing!

Tableau is great for being able to create dashboards you can manipulate and post on the web. But you actually have to know what graphs you want before creating them.

So, we’ll create the graphs we want (in Excel!), and then hire someone to transform the data and recreate those graphs in Tableau so nonprofit leadership can manipulate them or post them on the web.

We hope all this is some weight off your shoulders!  Sign up here to stay connected with us and follow us on all the social media! We have lots more to share!

Connect with MaryFrances Porter & Alison Nagel

Partnerships for Strategic Impact: https://impactstorycoaching.com/

Maryfrances Porter, Ph.D.  – LinkedIn: @maryfrances-porter-psi/

Alison Nagel, Ph.D. – LinkedIn: @alison-nagel-41493a125

The post Why Nonprofits Shouldn’t Use Statistics appeared first on Depict Data Studio.

Samir Sharma is a data strategy and analytics leader, CEO and Founder of datazuum. He has a history of helping data executives and leaders craft and execute their data strategies. His passion for data strategy led him to launch the Data Accelerator Workshop and host the Data Strategy Show.

Watch the Podcast

Listen to the Podcast

You can also listen to the podcast here:

• Stitcher
• Apple Podcasts

What’s Inside 

Here are some of the topics we talked about.

Challenges Faced by Companies Trying to Visualize Their Data

Samir asked what are typical data visualization challenges that come up again and again. Ann said, “I think a big challenge I see with organizations is the people with data backgrounds, I think it’s so easy for us to forget that not everybody is a data person. I have to constantly remind myself, ‘Most people hate spreadsheets. They see it as a chore, and a burden, it’s just overly detailed and they can’t find what they need.”

While Samir serves as the bridge between business leaders and more data focused people, Ann noted that “if you’re trained in the weeds and details like I was, you’re never exposed to those business leaders. You have no training on how to work with those people necessarily.

Ann said she sees, “Organizations that will spend weeks or months creating the perfect dashboard or the perfect such and such tool. But they’ve never really tested it along the way. And they’ll get user feedback like, “I don’t like the colors.” Something really irrelevant but it just show the user is not really thinking deeply about the data because they weren’t engaged in the process.”

What We Should be Thinking About When Creating or Re-Designing Dashboards

“I see people assuming that developing a dashboard is going to take forever and cost a ton of money. That it’s going to be this months long process where they have to buy this new software program, they have to send their staff to training on this software program, they have to link all these data sources…”, Ann said. “They think it’s going to be this huge process so they think as long as this dashboard is taking forever, it better serve all of our needs. It better be this audience and this audience and this audience.”

Ann shared that during the planning process of each new project, she asks, “Who is this dashboard for?”

How to Learn More about Data Visualization

Samir asked what Ann’s advice would be for someone who wants was starting out in data visualization. Ann said, “I think a lot of us get wrapped up in tools, but there are so many tools available, more being invented. I think it’s really stressful, daunting, overwhelming for someone entering the field [to think], do I learn coding? Do I do the spreadsheet route? Do I do a drag-and-drop-dashboard route like Tableau or Power BI? There’s also the more graphic design route like do you specialize in Illustrator? Publisher? I think we feel like we have to master all of them and that’s just not possible. You’d spend your whole career just learning tools.

She advises to earn what’s out there and then specialize in just one tool. “I had this big crossroads maybe five years ago where I felt this pressure to go learn R. I just felt so much pressure and I just had to kind of let that go,” Ann said.

“The first step to getting started is letting go of this ridiculous, ambitious goal that we have that, ‘I’m going to learn every single tool, get certifications in it. I’m going to put all these skills in my resume.’ Just learn a tool and very, very comfortable and confident with that.”

Connect with Samir Sharma

LinkedIn: @samirsharma1

Website: www.datazuum.com

The post The Data Strategy Show with Samir Sharma appeared first on Depict Data Studio.

Women in Data is an international non-profit organization started in 2015 whose mission is to bring women together for career advancement and an opportunity to uplift one another. They have chapters throughout the world and each hold quarterly symposiums that include enlightening talks, expert panels and networking opportunities. 

Co-presenter Rebecca Pop is the founder of Vizlogue, a data visualization and storytelling lab that offers training and consulting services. 

Watch the Recorded Panel 

What’s Inside 

Here are some of the topics addressed during the panel. 

• Can you share your personal journey and how you got started with data visualization? 
• How do you approach data visualization problems? When you are working on a dataset, do you have standard steps/best practices that you follow every time? Are there any key focus areas one should be mindful of? Ann said, “Something so important to know in advance, is whether your audience is technical or non-technical. Technical audiences are people who like data, who love opening a spreadsheet, and are in a data career on purpose. Non-technical audiences are the opposite. They’d rather hire a consultant or let another staff member handle it. It’s probably the last thing on their to do that they want to tackle (and they probably procrastinate!)” 
• Important aspects to keep in mind while working with data are data integrity and data ethics. What is your take on data integrity and data ethics?  
• For someone just getting started in data visualization, it can be overwhelming with the number of tools and courses available these days, what is your advice for beginners? Can you also share some resources? Ann said, “At first, learn the one-hour version of about 10 different tools, but then take a 10-hour training on just one tool and go deeper and specialize. There’s a lot of great courses out there.”  
• What is the future of data visualization? How do you anticipate data visualization to differ in the coming years? 
• Data visualization is a very competitive field, how can one stand out from the crowd and make an impression? Ann said, “Don’t worry too much about having to be the best at everything, I don’t think it’s even possible. Just pick one and play on the strength that you already have and make that public in some way… For example, if you like Tableau post a lot of visualizations on your Tableau public profile. If you like R, post to your code on Github and connect with other people.” 
• What are the key skills required to be successful in data viz? How important is the tool? Ann said, “Chart choosing [is so important]. Are you going to use a pie chart, bar chart or something else altogether? It’s very difficult to take a table, rows and columns of summary statistics and figure out what chart that is going to be. I think a lot of people go to the standards like pie charts or bar charts.” She added, “One activity that you can try for yourself is find a table of data, set a timer for 10-15 minutes and see how many ideas you can come up with in that time period. When I started doing this, I could only come up with a couple of ideas in a 15-minute brainstorming session. Now I come up with 15 ideas in that same time period.” 

Learn More 

Here are some of the resources we mentioned during the panel: 

• The 3-step process for sharing data with users through data placemats: https://onlinelibrary.wiley.com/doi/full/10.1002/ev.20181  
• Ann’s favorite dataviz podcasts, which were mentioned in the Q&A after the recording ended: Explore Explain with Andy Kirk, Data Stories with Enrico Bertini and Moritz Stefaner, Data + Love with Zach Bowders, Data Viz Today with Alli Torban and Storytelling with Data with Cole Knaflic.

The post Women in Data appeared first on Depict Data Studio.