An interview with Equity Task Force member Candra McRae

Get to know Equity Task Force member Candra McRae through her conversation with fellow Task Force member Allen Hillery. 

Get to know Equity Task Force member Candra McRae through her conversation with fellow Task Force member Allen Hillery

Candra is a Seattle native currently residing in Columbus, GA. CEO of Lumodis that loves a thrill for the “data chase”. She shares her data journey and how her non-traditional background influences her simple and focused approach to visualizing data. Check out her insights on the joys (and pains) of running her own business, building passion projects and her take on how we can all begin to embrace data.

Getting to know Candra

Allen Hillery: Can you tell us a bit about yourself? 

Candra McRae: I’m a Seattle native, Columbus (GA) transplant, entrepreneur, wife, and mom of one. I’m a seeker of knowledge, understanding, and meaning, and about 800 other things on any given day. 

AH: How would you describe your data journey?

CM: I have a really non-traditional background for an analytics leader. I’m a liberal arts graduate with a lifelong aversion to numbers. My career hasn’t been built on my ability to make robust models or dynamic vizzes. While those certainly have helped me, I’ve built my expertise on my ability to ask solid questions and communicate complex “number things” in ways that most people can understand.  

AH: It sounds like your journey has been a non-traditional one?

CM: My data journey is a “happy accident” in that someone took a chance on me and stretched me in ways that helped me grow. Earlier in my career, I had a boss, now mentor, that exposed me to projects that required me to hone my technical skills. After he would tell me to “figure it out”, I immediately spent a lot of time Googling, scouring Stack Overflow and many tech forums.

I soon discovered that I loved the thrill of the “data chase”. I outworked my lack of natural talent until it became my talent, and actively sought mentors to help me navigate the waters. In summary, my data journey is one of constant evolution spurred on by my constant search for the intersection of what I’m passionate about and what’s fulfilling.

AH: I like that your data journey can be viewed as “non-traditional” in the sense that you didn’t come to data visualization by way of coding or a more technical background. How do we encourage people with more critical thinking skills to take a data journey?

CM: By reminding them that they already deal with data in everyday contexts. Explaining “the why” just as much “the how” opens up the audience to so much more insights. This actually puts them at an advantage. Using simple language versus technical jargon further broadens who participates in the discussion.

AH: Do you feel that your journey has inspired your counterparts to hone their critical thinking and communication skills when it comes to analyzing data?

CM: I hope so. From a communication perspective, I have definitely taught people that I’ve led to have a bias toward efficient communication and impact vs. overly verbose novel takeaways as a means to adapting to notoriously short attention spans of decision-makers.

AH: On your Tableau Public profile, you describe yourself as a Data Geek that loves to help people understand their data and solve meaningful problems with a little math, creativity and sweat equity. 

CM: Yes, helping people get to an a-ha moment with data that they've seen every day, but didn't really understand really makes the journey of getting there worth it. The journey often involves a bit of sweat equity in that I may find myself spending an absurd amount of time cleaning the data to use for my model or throwing away a stack of paper while I tried to figure out the right design for my viz.  

AH: What motivated you to found your own company Lumodis? How has this experience been running your own business? 

CM: It’s so cliche and seems so naive in hindsight, but I wanted to be my own boss and only work on things I cared about. I dreamed of creating a legacy for future generations. This experience has absolutely been the best and worst experience ever! I thought as soon as I turned on my website and let people know I was open for business, potential clients would start flooding my lead forms. For the first year or so, outside of the international bots filling out my web forms, my client pipeline was DRY (think Sahara desert).  

I had to figure out that business development/marketing was just as important, if not more so, as the talent to execute well. As an introvert with an aversion to sales pitches, BD is not my comfort zone and this has been where I’ve needed to spend the most time in order for the business to survive. So, from that perspective, it’s been challenging.  

The power of simple and focused data visualizations

AH: Your America's Schools - Still Separate, Still Unequal data viz peaks at almost 17K views. Why do you think this data story has received so much engagement? 
 
CM: I was honestly surprised because it wasn’t overly novel or cutting edge in terms of design. I believe it resonated with viewers because it busted a myth and made them think about their own experiences in the context of this data. Many people commented it made them think about how everyone they went to school with looked like them. They hadn’t really consciously processed that until now. It’s a widely held belief that segregation in America ended with Brown v. Board of Education and MLK’s “I Have A Dream” speech. Segregation is a relic of a past we want to forget but, this data viz slaps the reader back to the reality that it’s still alive and well.  

AH: What was your journey like building this visualization? 

CM: My journey to build this started, like most of my passion project vizzes. I wanted to learn more about something for my own knowledge after seeing something outrageous in the news or timeline. For this one, I think I saw something on the news about a school district being embroiled in controversy because they still had segregated proms. I know based on observation and other data, America is still segregated in every major way from housing, worship, schools, and jobs. So, I went digging for the data and started storyboarding the findings on a few pieces of paper. I wrapped it up with why this matters and recommended where they can potentially direct their advocacy to become agents of change.  

AH: What is your process of “pulling the story” out of data?

CM: I love getting to be a part of building solutions for people that I like for things that I’m actually interested in. I start by focusing on a single thread and then building - brick by brick - eliminating everything but the meat. I also remain open to the possibility that there may not be a story...or at least an interesting one. 

AH: What other data visualization in your gallery did you have a special time putting together?

CM: My data viz on Hate Crimes in the US is also a personal favorite because it was a subject I wanted to become more knowledgeable about plus I think there are a lot of myths that people wear as comfort blankets. For example, my home state of Washington - which people assume is this post-racial utopia is actually a hotbed for hate crimes. I got hyper-focused on it once I shaped my data and ended up skipping my 4th day of skiing at Park City, UT to build this.

AH: You describe your data viz personality as “simple and focused”. How has the approach of making complex things come in simple packages helped with your work and advising clients?

CM: My bias toward simple viz (that has complexity baked into its bones) allows me to cut down on any noise and focus on what the data is saying. It’s like preparing a dish where you let the ingredients stand out and truly speak for themselves. The fact is, I won’t always be there to explain something to my audience - so I create solutions intended to be consumed in my absence. This approach makes the insights absorption faster and cuts down on the need for long explanations of what they’re seeing. 

I love a sexy chart as much as any other data visualization specialist - but sometimes you need to study those charts vs. getting hit with the point at first glance. People have short attention-spans so, if I want them to see and act...the seeing part can’t take a long time.   

Why we have to embrace data

AH: Based on your career journey, what do you feel companies need to do to better embrace data?

CM: Honestly, focus on closing internal data literacy gaps. It’s basic, but very misunderstood. There’s rarely a shortage of data at most companies - most are actually drowning in it. There is a shortage of people that are comfortable with it. In the hands of a few, it will continue to drive some value - no doubt. It is only in the hands of many that we will begin to see truly transformational work being done in organizations. Companies have to begin looking at capturing efficiencies like self-service, reducing the layers between insight generation and activation. This is going to call for more collaboration and a wider adoption of both data literacy and business context.

AH: One way that you are helping with data literacy is being a Workout Wednesdays Coach! How has that experience been?

CM: The biggest thing for me is keeping track of all the things I get stuck on during a normal week and remembering that those are potential use-cases for #WorkoutWednesday.  

But, it’s been super fun and a little exercise in vulnerability because you release these challenges and cross your fingers that the community participants got something out of it. It’s been really fun getting to know my fellow coaches a lot better outside of Twitter or looking at them on-stage during #TC - it takes a real dedication and love of the community to do this for free...weekly. Creating technical challenges are hard as hell - so I have an appreciation for the fact that most of them have been doing this for years and I’m just happy I get to be a part of this magical crew.

The road to inclusive and equitable communities

AH: We talked about having diversity of thought when it comes to data journeys. What can we do to further diversify data communities? 

CM: I’m less concerned with overtures toward diversity and more focused on how the data (and tech more broadly) can be more inclusive and equitable. I think there’s a quote that says “Diversity is being brought to the party, inclusion is being asked to dance.” Diversity is important, but diversity in the absence of inclusion (making people feel welcome when they show up as their authentic selves) or equity (removing barriers that have prevented the full participation of some groups) is a marketing gesture.  

AH: Yes, it’s a quote from Verna Myers. It’s been extended by some to say that equity is ensuring everyone has appropriate transportation to the dance regardless of where they are commuting from. I believe a lot of companies are fulfilling their diversity quotas but have yet to gain any substantial ground with inclusion and equity.

CM: So, I think the way we can make the data community more inclusive is by making unwritten community rules obvious, leaning into significant cultural moments instead of being a bubble of neutrality, and having true buy-in from the top (influencers, sponsoring companies).  

To become more equitable, we need to actively dismantle barriers like lack of access due to cost, supporting data literacy and exposure in schools and programs targeting underrepresented communities, and just continuing to do the work once the spotlight has moved on.