Adam Kovarik serves as the vice president of data science and business analytics at the Career Education Corporation. He is a devoted father, blessed husband, and passionate soccer fan.
As statisticians, mathematicians, data scientists, and the like, we (generally) know much more about the numbers in front of us than our peers do. This truism often compels us to dive directly into the deep end of an analysis; we are prone to lose sight of the team members treading water in the shallows.
As I have spent several years in the corporate world, allow me to share with you a few lessons I have learned along the way. Before we dig in, I know this will seem like I am dismissing the value of our technical expertise. Quite the contrary. Your expertise is what will make you the most indispensable individual in your company’s arsenal. What I hope to convey in the next several paragraphs is how valuable your expertise is when paired with the needs of your organization.
Remember Your Audience
Do you see those people sitting around the table during your presentation on predicting a customer’s value? They are business majors, engineers, marketing minds, operations managers, and human resource consultants, to name a few. They do not want nor do they need the nominal difference in AICc for the three models you ran. They do not want nor do they need a discourse on the importance of bootstrapping as a validation method. They have decisions to make and a bottom line to impact. You are in that room giving that presentation for one simple reason: to improve the business.
If you are not in that room giving the presentation, perhaps it is because you need to learn this lesson. Your business could be making widgets, selling software, or catering parties; it does not matter. Those people at the desk want the tools and information at their fingertips to make the business better. Focusing on the minutia may sell your intellect, but it may also disconnect you from the true goals of the organization. Once this happens, your analysis becomes a footnote.
Quality Is Paramount
You spent eight hours putting together an analysis on revenue impact. Now spend eight hours validating your outcome. Perhaps that is overkill, but I exaggerate if only to stress the importance. You will be unambiguously judged by the accuracy of your figures, more so than by any other characteristic a “data person” is presumed to possess. This means you must unconditionally adopt a routine inclusive of quality assurance.
Clear your mind, go for a walk, have a bite to eat, watch some Netflix in the cafeteria; do whatever fits to remove your brain from the task. I find surfing /r/funny on Reddit to be a great resource here. Once you are back, it is time to review the analysis you just put together. Start with the basics. If your analysis involves organization revenue, review the detail in one P/L group. Do you have a robust model that predicts customer retention? Make sure your independent variables are accurate by reviewing a sample of customers one-by-one.
The swiftest way to lose your credibility is to overlook an obviously noticeable data error. There will be irregularities you did not see coming, or alternative views you did not prepare. However, if your senior vice president is the one to spot that the number of customers in your analysis only added up to 50% of the actual, do not expect him/her to accept your conclusion so readily and resolutely. We all want to hit the long ball, but fail to pick up a routine grounder and you will quickly lose your chance to be in the starting lineup next game.
Focus on the Finish
Planes, Trains, and Automobiles is one of my favorite movies of all time. Tradition in my household demands we watch it every Thanksgiving between football games. For those who do not know the plot, Neal (Steve Martin) is determinedly trying to get home for the holiday after wrapping up a business trip. Along the way, he befriends a traveling salesman by the name of Del (John Candy). After a bevy of mishaps, unfortunate circumstances, and a few tears—ostensibly the result of Del’s involvement—Neal finally makes it home to see his family on Thanksgiving. Alongside him as he walks into his house is none other than Del.
The beauty I have always found in this concluding scene is the pure delight expressed by Neal’s wife, notwithstanding her husband’s extreme tardiness and the apparent stranger standing in her foyer. She focused on what was important—that her husband was home—not on the trial and tribulations he overcame to make it there.
A long-winded analogy to express this point: Do not detail your journey when you are at the table. We do not want to treat your model like a black box; however, we do not want to be so caught up in the nuance that we lose sight of the core discussion. Believe me, this will be to your benefit, as well. The more background you present, the more opportunity there will be for individuals to take the discussion down a rabbit hole. Again, remember you are in that seat to help the company get to the right answer. If the journey you took to get that answer involved a canceled flight, a disgusting motel room, and a horrendous car accident, save those stories for sidebar conversations.
Listen, Listen, Listen (and Write)
The other day, my wife was explaining to me the Saturday plans for our kids’ soccer games. With two boys on two teams playing at two locations, it takes a bit of logistical magic to get everyone where they need to be on time. Unfortunately, for everyone involved, she was telling me these plans while How It’s Made was on. It was an especially intriguing segment involving the construction of ballpoint pens. Suffice to say, I had no idea what the plans were when Saturday morning arrived. I winged it, got my older son to soccer on time, but forgot the team snacks.
When you are in a meeting or on a call to take in a request or prepare for a project, listen. Listen to what the problem statement is. Listen to the key stakeholders as they express their needs. Then write down what you hear. If I had a nickel for every time I watched a junior analyst passively participate in a meeting while failing to take notes, I would have a large bag of nickels. Worse yet, be the individual who starts solving the problem in his/her head in the midst of the meeting. That’s a sure-fire way for your deliverable to miss the mark. Establish a note-taking system early and consistently. Use OneNote, Evernote, Notepad, paper and pencil. … It does not matter. Your future self will thank you.
The Tools Might Actually Be Irrelevant
Blasphemy, I know; however, hear me out on this one. Who reading this does not receive the typical monthly invite to participate in a “do you prefer R or Python” survey from some content provider looking for a quick hit? Meanwhile, SAS users are screaming from the corner. Can you code in Java? How strong are your Shiny skills? Have you ever met Cassandra? In this era of warp-speed technological advancement, the tools at our disposal seem endless. The truth is the sooner you recognize the tools are a means to an end, the sooner you will focus more on the “end” and less on the “tool.” If you know how to build a house, using a hammer or a nail gun will both work. Sure, one is quicker than the other, but people will appreciate the building—not the construction method—in the end.
Keep Learning
Now that I told you the tools are not quite as critical as you presume, let me remind you to keep learning. If you do not know R yet, start learning. If you spend all day in SAS but have trouble understanding how your BI team pulled the data you are analyzing, pick up a book on SQL. In your current role, do not focus on the tools; focus on the outcome. However, if you want your insights to be stronger, your turnaround times shorter, your presentations more impactful and—perhaps most importantly—your paychecks to be bigger, build your skillset.
A good article to get started as a data analysis student,