How did I get to where I am today as a data leader?

I started my career as a mainframe guy doing UI development and got exposed to an analytics tool that processes and analyzes data. When I moved on from that legacy mainframe system, I went to a bank where they were using the same software but needed more deep-dive data analysis. This was my first exposure to using the same proprietary tool to gain insight into how we were supporting marketing and sales, which included a customized data-driven list of customers to pursue. 

It was then I started seeing how valuable it was to run our campaigns in a way that converted data into actionable insights and successful data-driven decision-making. After that I never looked back.

Startups and data

In 2016, I arrived at my current company, which is a global company offering an open-source hotel revenue platform for tens of thousands of hotels around the world. SiteMinder was a startup at the time, and I quickly learned that the fast pace of startups tended to overlook the power of data, but that there was tremendous value if data was leveraged well. When you’re working for a startup, what’s critical is that you’re helping to hit multiple short-term goals, but that those short-term wins add up to a longer-term achievement. To the extent you can offer executives true visibility into how each business unit is performing, they will begin to see you as a source of truth and question the traditional Excel-driven way of doing things.  

Two ways to win with data in practice

One important thing I’ve learned in becoming a data leader is that your data education does not end at school. Most of the skills you gain are on the job, so expect to be constantly learning. You have to bring a passion to dig deep down, get your hands dirty, and learn from previous analyses to make the next analysis much better. 

In terms of skillset, obviously you have to get very good on tools like Tableau and SQL because they will help you to analyze data even more deeply without having to do hardcore programming.

In addition, there is so much innovation happening in the data space that every new project may present more tools you have to figure out and other skills you have to pick up. The whole data landscape constantly evolves and changes, which argues for jumping out of your comfort zone on a regular basis. Some of the technologies we’ve been looking at this year are so much better than the technologies we looked at only two years back.

Importantly, I’d say that in order to be a better analyst, you have to understand the business and constantly engage with stakeholders to grasp how and why they use data. Sometimes they won’t open up right away about their challenges, but it’s up to you to have those conversations so you’re confident that whatever you give them will be useful.

The right kind of choice-confirmation

It probably hit me in my third year of working in data analysis that the core of my passion wasn’t just that I was building tools, but that better analysis and ROI were happening in the field because of them. As a programmer I would receive a requirement, develop the code, deploy the code, and move on to the next requirement. It was monotonous to me because I wasn’t learning new skills and I certainly wasn’t learning anything to help me to understand the business.

That’s why I wouldn't jump from what I'm doing now. I have to have something to solve that goes beyond my current comfort zone because that is going to drive my passion. If I only know legacy technologies, I become something of a legacy myself. As a data leader, you've got to be constantly evolving and looking at opportunities.

Management teams today want to see the source of truth. They want to know what’s happening in the operational units and what that adds up to. Once they are convinced that modern data analysis is the way to go, management teams will start to see your work as source of truth reporting and not just data reporting. That’s what they need to help them make decisions. They don't want to be constantly told, “I don't agree with that number.” 

In conclusion, I’d reiterate my two golden rules for becoming a data leader:

  1. Pick up the right data technology skills
  2. Find opportunities that will give you more exposure to learn the business.

Of course, the best of all possible worlds is to look for opportunities that will give you exposure to do both.