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The work I do involves looking at the data a lot. Or I have kind of made it a habit of looking at the data. More often than not, once you look at the data in the Excel sheet, you start getting a sense of it. This is also one of the reasons why I prefer notebooks (like R Notebook, VS Code notebook etc) to a simple script. With these notebooks, looking at the data becomes much more convenient and easy. You can run a chunk of code and then you can notice the changes in the dataframe.
When conducting data analysis, we often focus on the overall trends and summary statistics. We ask questions like, “What is the median salary of this population?” or “How much did this KPI change compared to last quarter?” Stakeholders and CXOs dissect parameters in terms of these summary statistics. It’s a logical approach when managing a large business, where understanding the big picture is crucial.
However, over time, I’ve started to appreciate the value of individual data points.
My previous company was one of the largest logistics companies in the country. Operating at such a scale in a challenging environment like India, shipment delays are sometimes inevitable. Working with the data, I came to accept these delays as a natural occurrence. Even when I saw some people freaking out a bit because of the delay in delivery, I somehow accepted it as something ordinary.
However, it was not until I started paying attention to individual data points that I began to see the human stories behind these numbers. A recent encounter brought this realization to life.
I never paid any attention to the airline crews whatsoever until very recently. While working with some rostering data for my current company, I came across data points where the duty allocations were not ‘uniform’. A crew member might work an early-morning flight one day, an evening flight the next, and a late-night flight the day after. This erratic schedule could wreak havoc on their sleep cycle. It’s not an uncommon scenario in the industry, but I had never given it much thought until I saw the data.
On a recent flight from my hometown to Delhi, the cabin crew overlooked a passenger’s complimentary meal. When I alerted the crew, they apologized and promptly served the meal. It was then that I noticed the visible fatigue on the crew member’s face.
“She must have been a rostering outlier,” I thought to myself. This incident was intriguing because, until that moment, I had hardly paid any attention to the crew or considered their lifestyle. But looking at the data had drawn my attention to that.
In the grand scheme of things, data is more than just numbers on a spreadsheet. It’s a collection of individual stories, each with its own nuances and implications. When we take the time to look beyond the summary statistics and pay attention to these individual data points, we begin to see the human stories behind the numbers. We start to understand the challenges, the triumphs, the struggles, and the victories that each data point represents.
This understanding breeds empathy. It allows us to connect with the data on a deeper level, to see the faces behind the figures, and to hear the voices behind the values. It reminds us that behind every delayed shipment, there is a delivery executive overloaded with shipments. Behind every erratic flight schedule, there’s a crew member struggling to maintain a healthy sleep cycle.
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