How I Became a Data Strategist and the Value of Data Strategy
Analyzing data is easy — but generating value is not
A lot of people nowadays are curious about working in Data. This is not surprising because it is now visibly present in our lives more than ever. I personally love it and I’ve dedicated my entire career exploring all about it.
When I talk to aspiring graduates or to experienced people wanting to transition, they pretty much ask the same first question: “What are the skills needed to transition into Data?” People usually think it’s all about R, Python, or SQL — which is only partially accurate!
My aim in this post is to clear some of the ambiguity by sharing how I became a Data Strategist at First Circle and how the role evolved in our team. My hope is that I would be able to raise discussions with fellow practitioners and those who work with data people, and perhaps shed some light for those curious about what the role entails!
For Context…
I used to call myself a Data Analyst. Eventually, when the hype for Data Science was spreading, I eventually adopted the title “Data Scientist” to get on the bandwagon. After all this time, there was still too much ambiguity on what these roles meant. What was clear, though, was that I had the same mindset as many who enter the field:
Regardless of the title, I just knew I was passionate about work that solved real-world problems using data.
This was a bit problematic because there were a lot of roles that intersect with that passion. I started as an Operations Associate at Uber, yet most of what I did then were jobs that a person in a Data Scientist or a Business Intelligence role would do under a different company.
The Strategist and the “Data” Strategist
Rather than go through a job description for a Data Strategist, I’d share key phrases that a person in this role would hold true:
- Strategists would tell you: “We shouldn’t care about what’s simple or complex. We should care about what’s effective.” I can’t count how many times I’ve fallen into the trap of trying to bang out code to try every single method imaginable, only to have the simplest method win out in the end.
- Strategists would tell you: “We need to lead the team to understand the objective. We need to make strategies communicable.” The only time my contributions were really recognized was when I chose to communicate and speak my stakeholder’s language. Depending on your stakeholder, this can range from nice visuals and slides, to summary tables and fancy charts.
In a way, strategic thinking is really the core requirement. This is a skill that anyone develops as they work in their respective fields. This is also why I think anyone can start a career in data, especially when I see remarkable individuals who already deliver significant value by being subject matter experts.
However, there are some statements that I find only Data Strategists have trained and built the confidence to say:
- Data Strategists would tell you: “We have data and this analysis is possible. If not, here is the closest we can get to the truth, and here’s what we can do to collect the data needed.” The more I drill down and get to know more data tools like SQL and R to do my work, the more I notice I build the confidence to assess and accept tasks. I would never argue that for most jobs, Excel would probably be able to do it. However, the aspect of being able to deliver faster and more reproducible analysis with larger sets of data built quite an edge for me!
- Data Strategists would tell you: “We can use method X to solve problem Y. Here are the tradeoffs and potential rewards.” What set me apart from fellow analysts was a pre-trained intuition from my quantitative background. I know we like to say formal coursework doesn’t really apply in the real world, but you never know when the stored knowledge we accumulated at the back of our heads suddenly light up.
“If the only tool you have is a hammer, you see every single problem as a nail” — Abraham Maslow
I find that the differentiator between what the industry would normally call strategists against data strategists is not the ability to come up with, assess, and implement strategies, but it is how comfortable we are in handling data to extract complex and extraordinary ideas.
However, data prowess alone is not enough.
How I Transitioned to Become a Data Strategist
Whenever my parents ask me what I do for a living, I say these two things (Disclaimer: they still don’t get it):
- Data Strategists solidify Core Strategies
- Data Strategists uncover the multitude of Critical Strategies
Below are some examples that demonstrate the difference:
I’m happy when I get discounts though usually the guy beside me is happier cause he gets even higher discounts. In sales, the straightforward way to boost volume is by giving a discount to all customers (blanket promotion). There comes a point however, where the incremental uplift will plateau. Now if you target (hyper-personalize) and offer promos specifically designed for every person, it is likely you will extract even more value. They know I will still buy with a low discount, but that other guy needs a higher discount for the push.
The core strategy (blanket promotion) can do most of the job, but a critical strategy (hyper-personalisation) can amplify the value. The thing with critical strategies though, is the difficulty to identify and execute them.
As a data practitioner, I wasted so much time arguing and discussing conflicting methodologies relating to a problem. In these cases, data analysts like myself will tend to rabbit hole into analysis paralysis — where we look for a multitude of solutions that may end up causing more confusion. This is usually because we rush to find elusive critical strategies, while no core strategy has been built or solidified yet.
Me and every Analyst ever: “I am tired of doing so much modelling and building many dashboards only for them to be left unused or deprecated.”
Meanwhile, the experts just go back to their roots and say something like “Can’t we just do X?” then their straightforward and untangled approach usually saves the day. This is where I realized that for any critical strategy to be effective, it always has to be grounded on the core strategies.
Also Me and every Analyst ever: “I want to deliver value. I am determined for my data work to be impactful and to be recognised.”
Taking these learnings to heart, I made sure to engage, question, and listen to the experts to pinpoint the core strategies, and I always start from there. As I did this, I made sure to connect it back to our team’s competitive advantage, and brought the structure of data and numbers to the complexity of domain expertise. Soon enough, I began adopting phrases like these:
- “Our business objective/target should be X instead of Y.”
- “We can test or experiment X first. We can later improve it with Y.”
- “We don’t need too many top-line metrics. We just need one or two.”
- “The effort needed for X does not match the value we can get from it.”
- “Let’s figure out the non-negotiables first before the good-to-knows.”
This mentality radically changed how I worked as a data practitioner. I no longer engage people as a “smart” analyst that churns our reports and data, but as someone who can collaborate to define business objectives.
As Data Strategists, we train to have the ever-so-crucial business skill of being grounded in the Core Strategies, and it is only then that we efficiently outline all the other Critical Strategies as amplifiers using our technical know-how. We are the ones who will be going back to first principles and then build upon those principles using strategies that unlock true competitive advantage. We dedicated ourselves to master data as our main weapon, and we always anchor on ideas borne out of collaboration with the experts closest to the business.
Once I realized and internalized this, I started to call myself a Data Strategist.
The data strategist is the master of solving real world problems using data
At First Circle, Data Strategists are trained to use tools that allow faster insight generation from data. However, a Data Strategist’s competence is NOT primarily hinged on the variety of models they know, but on how well they can lead a team into the direction that leads to action and results. We deliberately test and challenge each other on strategic thinking and communication, and we bias towards identifying the most collaborative efforts.
At the end of the day, the passion of the Data Strategist is to collaborate with teams and develop strategies to drive value to the world with the recommendations and insights extracted from Data.
What are the core and critical strategies your company uses? If you find this post or parts of the post to resonate with you, please feel free to reach out to me and we can discuss further! I’m always glad to enrich how we perceive as a community what the functions under data entail. Don’t hesitate to reach out via LinkedIn or email us at data-team@firstcircle.com!
