As I turned Thirty Three yesterday, my wife dug up some letters (emails to be precise) I’d written to her over the years and compiled them for me, urging me to create at “Project Thirty Four” (on the lines of my Project Thirty). What is pleasantly surprising is that I’ve actually managed to make a life plan for myself, and execute it (surprising considering I don’t consider myself to be too good a planner in general).
In February 2011, after having returned from a rather strenuous work trip to New York, this is what I had to say (emphasis added later, typos as in original):
For me steady state is when I’ll be doing lots of part-time jobs, consulting gigs, where I’m mostly owrking from home, getting out only to meet people, getting to meet a lot of people (somethign taht doesn’t happen in this job), having fun in the evenings and all that
I wrote this six months before I exited my last job, and it is interesting that it almost perfectly reflects my life nowadays (except for the “have fun in the evenings” bit, but that can be put down to being long distance).
I’ve just started a part time job. I have a couple of consulting gigs going. I write for a newspaper (and get paid for it). I mostly work from home. I’ve had one “general catch up” a day on an average (this data is from this Quantified Life sheet my wife set up for me).
A week later I had already started planning what I wanted to do next. Some excerpts from a letter I wrote in March 2011:
Ok so I plan to start a business. I don’t know when I’ll start, but I’m targeting sometime mid 2012.
I want to offer data consultancy services.
Basically companies will have shitloads of data that they can’t make sense of. They need someone who is well-versed in working with and looking at data, who can help them make sense of all that they’ve got. And I’m going to be that person.
Too many people think of data analysis as a science and just through at data all the analytical and statistical weapons that they’ve got. I believe that is the wrong approach and leads to spurious results that can be harmful for the client’s business.
However, I think it is an art. Making sense of data is like taming a pet dog. There is a way you communicate with it. There is a way you make it do tricks (give you the required information). And one needs to proceed slowly and cautiously in order to get the desired results.
I think of myself as a “semi-quant”. While I am well-versed in all the quantitative techniques in data analysis and financial modeling, I’m also deeply aware that using quantitative tools indiscriminately can lead to mismanagement of risks, which can be harmful to the client. I believe in limited and “sustainable” use of quantitative tools, so that it can lead without misleading.
My past experience with working with data is that data analysis can be disruptive. I don’t promise results that will be of particular liking for the client – but I promise that what I diagnose is good for the client’s business. When you dig through mountains of data, you are bound to get some bitter pills. I expect my clients to handle the bad news professionally and not shoot the messenger.
I don’t promise to find a “signal” in every data set that I’m given. There are chances that what I’m working with is pure noise, and in case I find that, I’ll make efforts to prove that to the client (I think that is also valuable information).
And these paragraphs, written a full year before I started out doing what I’m doing now, pretty much encapsulate what I’m doing now. Very little has changed over nearly five years! I feel rather proud of myself!
And a thousand thanks to my wife for picking out these emails I had sent her and showing me that I can work to a plan.
Now on to making Project Thirty Four, which I hope to publish by the end of today, and hope to execute by the end of next year.