The setting: A not-so-large conference room in a new office in Bangalore
The timestamp: 17 years back
The characters: A bunch of youngsters with varied backgrounds and educational degrees: statisticians, econometricians, MBAs, ex-consultants, ex-investment bankers, ex-credit raters
The goal: All part of a new joinee orientation at one of the first firms that started proving that there is something called ‘analytics’. Each one of them armed with big dreams to make a mark.
The hurdle: Dreams were great, but for the new, yet-to-be-defined industry, what constituted career growth and career path?
Sounds like the opening line of a new book?
Well, this was a reality for a lot of us when we joined the analytics industry at a time when problem-solving with data was yet to start its now explosive journey. Today, with more people accepting the power of data science and youngsters flocking to join this profession, the question is still getting asked.
What sort of a career can I look forward to if I pursue analytics?
And the buzzwords and the hype are creating a lot more confusion for youngsters who struggle with questions around how to build depth vs. breadth; whether to choose to specialize early or to experiment till they figure out their niche.
Well, what I would like to answer through this blog is that a career in analytics is not any different from the way you would look at any other career choice. It starts from the fundamental principles that were discussed in Jim Collins’ classic book — Good to Great (Hedgehog Principle).
The intersection in the graphic above is where you want to be in your career. Much has been written about the job of a data scientist and the unicorn-type mixture of skills he or she needs to possess. In my view, not all data science professionals need to possess all those skills; in fact, they cannot. However, the profession needs a multidisciplinary skill set that is best suited to solve businesses problems, not just people who seem to be clones of each other.
As analytics professionals, we are used to creating buyer personas to understand our customers better and segment the offerings that would suit them. Let’s apply the same logic here. I am going to create four career personas in analytics — four completely different individuals with different skill sets who have had highly successful careers in the industry. As they could say in the movies, any resemblance to your boss or ex-boss is purely coincidental.
Four personas. Four different choices. Do you think they knew which direction they would eventually take while starting their careers? Probably not. Did they have the same skill set as that of a unicorn data scientist? Definitely not. What they possessed instead were the following:
- An inordinate curiosity to understand and solve problems
- A willingness to learn, unlearn, re-learn, and help
- A tendency to deliver on the roles that mattered instead of worrying about designations
- Increased exposure to discover their own strengths
- Mentors and a broader network to explore new opportunities
And they found their paths. Just as we design different offers for different buyer personas, not all analytics jobs are the same. The industry has roles that span multiple personas. So, why are we just trying to create clones? And yes, with the industry being so dynamic and evolving at such a fast rate, we will soon see new personas evolving, from the ‘business model disruptor’ to the ‘dream designer’ to the ‘whole brain marketer’.
So, all the very best to all of you who are just beginning your career journeys in this field and also to the ones who are currently at the crossroads, deciding their personas.
As a famous cartoon put it:
You can’t stay in your corner of the forest waiting for others to come to you. You have to go to them sometimes.
– Winnie the Pooh
Recognize yourself in one of the personas? Let me know if this helps you think through your analytics career choices. I would love to hear your thoughts.