Communicating in a data profession

Notice: It feels like every other month, some tragedy is taking over the psyche. It has been a crazy few days with the announcement of Roe v. Wade being overturned, and coming to terms means for the future. The doom scrolling has been real, and I want to acknowledge that terror. So once again, hugely distracted by the world, so take what you will from my musings this month.

A social profession

What do you imagine when someone tells you they are in data science or analytics? I feel that many folks who are far removed from the field (and maybe some within it) imagine this:

I, too, once upon a time, considered this profession to be the kind of space where I could go off in my little corner and try to answer life’s questions with data. This certainly can be a reality when you are high up the ivory tower in a magical, mythically available tenure professorship and research position or have resources to sustain your livelihood to do just that, but most folks do not. In my true INFJ fashion, I think I was attracted to this data profession field because I would have the space to be in my little world of facts and information. But as I have grown older and shifted around my career, I would argue that being in the data profession is one of the most (unexpectedly) social careers you can have.

One of the top skills all employers are looking for is good communication, and that is especially true in data and analytics. You will often work on teams or need to deliver findings to an audience outside your field to make critical decisions. You can find these buzz phrases across job descriptions like “experience working cross-functionally” or “experience working with technical and non-technical audiences.” And as much as industries expect this, I don’t think it is taught effectively or prioritized much in the classroom (I can get into my love and critiques of higher education another day).

Communicating in data

Outside of cleaning data and figuring out what to do with it, so much more of my time is spent managing how to effectively communicate to the people I need to hear my message or ask me the question. Because I pride myself on being a human-centered kind of person, I am taking into account (when I can):

• How does this person best receive new information?
• What is their learning style?
• What is the bare minimum information I need to tell my story?
• What final product do they need to walk away with that will be most helpful in achieving their goal?

Lessons learned in communicating findings

With my experiences in different settings, I have picked up some tips and learned some lessons on what it means to be a good communicator (in the context of data analytics and research):

Less is more

It is cliche and oversaid, but it is true – from your choices to visualizations, to the numbers of words on a page, to the number of slides in your deck. I still have to remind myself that no one cares as much as me about everything I do and what I learn in the process. People need the point to move on to the next thing. However, there is a balance to this. You do not want to do this to the point of misleading or risking the integrity of your work. Finding that balance takes some practice, but one helpful resource I have seen on visualizations and communication is from Storytelling with Data.

Continuous updates

When you can, I think it is essential to check in with your audience as much as possible without being redundant. There have been times when I made assumptions that I was on the right track and answering the right question to deliver something the audience wasn’t intentionally asking for. It will help in the long run to build in time for feedback in flexible stages in your process. I like to do this by laying out a scope of work for a project, injecting times I think work for getting feedback, and adding the buffer of time it will take to hear back. This might be something that will take longer than you want, but people are often receptive when they see you taking the time and care to get it right.

Go back to basics

When you have been doing analytics for long enough, I feel like (or maybe it is just me) you start to forget why you do what you do. Then when it comes down to breaking down the basics to someone non-technical, when they ask you to do something that seems reasonable but is not, you are stuck for words to break down the concept. To keep my skills sharp, I like taking beginner courses or watching Youtube videos that provide a crash course in concepts I am familiar with. This was I got to be reminded of things I forgot and see examples of how to explain concepts that I could keep note of later. My favorite videos to watch these days come from Emma Ding. They are mostly interviewing prep videos, but I like the short content, and in interviews, you often have to break down basic concepts, so it works for me to get a refresher and, often, learn something new.

When it doesn’t go as planned

So what happens when you have to say something the audience does not want to hear? The best you can do is your due diligence to get as close to the truth as possible. If the results are trending negatively, and your audience is looking for something to support their claims, you have to share those results. Still, you can also couple it by directing their attention to changes that leaders in the organization can make.

And what if they want to bury the information you are finding? Well, is this a Timit Gebru situation? Or is this something minor in the scale of impact it would have if folks shared all the details? I think it is hard balancing the needs of an organization with the integrity of research, and I don’t have a good answer to that. Regardless, I know that I trust my instincts, take note of what I observe, and keep the receipts if anyone new comes in with questions.

Overall thoughts

Being a good communicator is not a one-size-fits-all situation. Every company is different, and you bring your uniqueness to the table. Communicating is just one of those things you learn by doing, and it can be done.