My One-Year Writing Journey
Consistency pays off.
Background
A year has 52 weeks. And this is my 52nd weekly article.
I started this “experiment” a year ago (see my first article) — to write and post an article every single week on the practice of data analytics / data science. Why? It was a confluence of a couple of events. I was then consulting for the national press on their data analytics activities and wanted to supplement with a first-hand experience on publishing and readership. I was already an avid reader of Medium articles, having discovered it a little while back; in particular, I was inspired by Roger Martin (a well-known former strategy professor) who was posting an article every week on Strategy for the past few years. I was curious how someone could write about a singular theme for such a long time and not exhaust all the angles.
Now 52 weeks out, what did I learn? Was it worth it? And so I dedicate my 52nd weekly article to the key learnings that I have discovered during my writing journey.
(I write a weekly series of articles where I call out bad thinking and bad practices in data analytics / data science which you can find here.)
Clear Your Intentions
My writing inspired some friends to also pick up the proverbial pen and embark on their own writing journey. The first question they always ask is: “What should I write about, and how do I not run out of things to say?” There are many reasons for embarking on a writing journey. For me, it was 2-fold: firstly, I was in the process of co-authoring a book on problem framing and needed to get in as much writing practice as possible, and secondly, after nearly 2 decades on data analytics practice, I wanted to contribute back to the community on my experiences and perspectives. Regarding the latter, I was very clear that I wanted to fill in the gaps that I saw in the data analytics domain — a lack of solid critical thinking in many of the practical aspects of data analytics. Many data scientists were great at the algorithmic stuff, but missed the forest from the trees when it came to problem-framing and creating value. There was also a dearth of constructive discussions about data analytics functional design and talent management, and even how data analytics could be better applied in sub-domains such as HR, Sales, Marketing, Operations, etc..
For me, getting the desired level of readership was important. I wasn’t just writing for myself. If I was truly contributing to the practice community, the readership would be an appropriate proxy on whether I was getting it right. My tone and writing was contrarian, reflecting the default approach that I’ve generally taken during my data analytics career. As shared in an earlier article, I was the asshole in the room who enjoys challenging the status quo.
At the very beginning, I had meticulously planned out at least 10 weeks of topics that I could write about. I would mind-map each topic, conduct supporting research, and outline the stories. It was challenging but interesting work. I knew I would run out of topics soon enough, but figured I would cross that bridge when I get to it …
Situational Sensitivity
As my stock of planned story ideas started to deplete, I went on the hunt for new ones. I thought that increasing my reading would help trigger fresh ideas, but it turns out that ideas were abound everywhere. As long as I was actively engaged in conversations with clients and practitioners friends, or if I was actively consulting or teaching, I found that every interaction gave rise to ideas that could be developed further into stories. Someone would ask a question or share a personal rant. If it intersected with my experience domain, and I had a specific point of view or perspective that was different and interesting, I would then do some research to see there was sufficient evidence to flesh it out.
There are obviously times when I discovered, during the research process, that my point of view about a particular topic was misinformed. Depending on whether I could give a meaningful contrarian perspective, I would either abandon the story or chase it down a different path. Either way, I was learning. And I enjoyed that.
Over the year, I have found myself becoming more sensitive to conversations; constantly looking for hidden gems. In some ways, it has changed the nature of my interactions, making them more thoughtful and reflective.
Mental Agility
One of the most interesting outcomes from one year of consistent writing on the topic of data analytics was the re-wiring of the brain. I have found that my thinking has become more agile. Because of my contrarian slant, I’ve had to work harder to make the non-obvious connections across a range of subject matters. The brain was constantly working, constantly sensemaking. It was excellent exercise!
Mental agility meant that I’m quicker in ingesting new concepts, seeing the common foundational principles, perceiving the operating, and often hidden, assumptions.
Final Thoughts
Now, circling back on the first reason I embarked on this writing journey — to supplement my research on the writing and publishing industry. What did I learn? One main thing: consistency.
You must write consistently. Stand for something, develop a signature that your audience recognises and becomes familiar with. It’s a “personality” that your audience can build a relationship with.
You must publish consistently. It’s a 2-way relationship — you publish and your audience reads. It needs to be a habit for the relationship to harden. Create the expectation and deliver against it. Rinse and repeat.
As I close out the experiment, I’m thankful for the audience readership. I’ve decided to press on into my 2nd year of writing. Stay tuned for more alternative practitioner views :)
