Getting into the business

Alex Antic: You’ve completed an MBA and obviously have a strong strategic focus. You then pivoted and became an expert in the field of data science and AI. I’d like to better understand your career trajectory. Were there any pivotal points or people that influenced you along the way? What led to you becoming a global leader in the field of data science?

Cortnie Abercrombie: Thanks for the acknowledgment. There was actually a pivotal moment in my life. When I left college, I started in the marketing department of a rapidly growing internet start-up during the dot-com days. My business degree was concentrated on marketing. The founders of the start-up wanted to figure out how to sell services better than the next company – especially the big multinational companies – and how to take advantage of the unique growth and first-mover market dynamics.

I had this fantastic boss and he was like, “You know what? We’ve all been relegated to marketing.” That’s not the fantastic part. He felt like marketing was a lesser-than type of function because he had been in sales, and 20-30 years ago, sales was the be-all and end-all. It was like the TV show Mad Men – they had all the power. There was an overarching and incorrect perception of marketing that it was just those two ladies over there who did some random thing that nobody knew anything about except for it having to do with advertising and tchotchkes: “Go get me some more things with our logo on it,” or whatever. But my boss said, “No, we’ve got to rethink this whole entire function so that it is strategic and customer-driven, and I want to use databases and data to do that.”

At that time, that was actually pretty forward-thinking. I did not realize it then, but I was one of only a few marketing people in the market who knew how to sift through data to find insights. That was why he hired me – though my data skills were basic at first. This was almost 30 years ago and the people who knew how to do “data mining,” as we called it back then, were few and far between. You would typically find them in actuarial fields or theoretical science fields, such as astrophysics, or even biological research areas where data collection and analysis were key.

In business, most people who knew anything about data had computer science backgrounds and worked as Database Administrators (DBAs) in the IT department. The IT department and the marketing department did not get along at all. The IT department did not consider marketing to be of strategic importance in that era, which meant that of all the project backlogs they had, we were the lowest priority. This meant our projects never got done. They saw marketing as the “swag” department, who gave out logoed stuff and threw parties. They did not take it seriously when I would ask for their help in getting more data to understand how we could grow our share of the wallet with customers or increase revenue by targeting specific customer segments.

Because of this extremely off-putting attitude, I was forced to take matters into my own hands, and I began amassing data directly for the marketing department. My boss, who was just as frustrated with IT as I was, said, “OK, what do you need?” I said, “Give me a server,” and he replied, “OK. Done! What else?” (Marketing had money, you know!) I said, “Well, I’m probably going to need more data classes.” At that time, Oracle had a university – literally called Oracle University – where they offered week-long courses right down the street from the company. I took a bunch of classes there, and then I took a bunch of classes from SPSS. My thinking was that if the IT people could learn it, then I could learn it better. Then I befriended and bought pizzas for as many DBAs as I could on the IT side of the house to get their help in properly setting up the data pipelines to my server.

Then voilà! I was putting out strategic segment analyses based on product types and where we needed growth. I dug into which customers were the most profitable and how we could deepen our share of the wallet with each one – including the use of VIP programs. I focused on customer churn, including understanding the triggering events and root causes as well as what could bring them back. As that progressed, I realized I had executives flocking to me in the company, asking me more and more about the customers, how to sell to them, and how to create models – almost like the Amazon recommender system idea, but internal; if my client buys this, what else might they buy? What patterns are you seeing? My boss also added his own perspectives and we produced the analyses in what became an anticipated quarterly report called “the red book.” Every major leader in the company wanted a readout and Q&A session of the analyses for their department, and the analytics from it ultimately helped the company to be acquired at top dollar by a major international internet group that you would recognize today.

My boss’ persistence and insistence made me believe, at a very early point in my career, that you can learn anything – just get over there and learn it! That defined my career and the way that I look at data scientists now. The way I see data science as a profession is that it’s all about asking the right questions and looking across the business at the business needs in the same way that I did when I was sitting there as a 20-something-year-old, trying to figure out what kind of analytics to put forward to an executive team who wanted to know everything about our customers. I needed to think about what we were trying to do as a company. I still take that approach to this day.

I think that many data scientists lose themselves – sometimes they put their blinders on or just find that it’s an uncomfortable thing to get out and talk to other parts of the business. I think they forget that what they have to do is stick to the strategic plans of the business. It’s been a struggle, with everybody I’ve worked with or that I bring on, to try and convince them to have that tenacious, persistent personality. I can teach a person any skill. Tech skills change with the times.

The way that you think about solving problems and home in on the things that matter: that’s going to determine the longevity and relevance you have in your career.