Narratives Hidden in 20 Years of Personal Financial Data

From Personal Science Wiki
Jump to navigation Jump to search
Project Infobox Question-icon.png
Self researcher(s) Peter Torelli
Related tools Quicken
Related topics Money, Ficial spending

Builds on project(s)
Has inspired Projects (0)
Show and Tell Talk Infobox
Featured image Narratives-hidden-in-20-years-of-personal-financial-data.jpg
Date 2016/11/28
Event name Bay Area Meetup
Slides
UI icon information.png This content was automatically imported. See here how to improve it if any information is missing or out outdated.

Narratives Hidden in 20 Years of Personal Financial Data is a Show & Tell talk by Peter Torelli that has been imported from the Quantified Self Show & Tell library.The talk was given on 2016/11/28 and is about Money, and Ficial spending.

Description[edit | edit source]

A description of this project as introduced by Quantified Self follows:

Peter Torelli collected detailed financial information on every dollar he spent for 25 years. He began tracking in college in 1990 due to a fear that he might loose all of his money. In this talk, Peter shares the significant depth he's discovered in his financial data beyond just numbers.

Video and transcript[edit | edit source]

A transcript of this talk is below:

Hi! My name’s Peter Torelli and for 25 years, I collected detailed financial information on every dollar I spent, and I discovered a significant depth to financial data beyond just numbers. So why did I do this?

Someone once said that Rockefeller told the son the way to become rich is to leger every penny. They were already kind of rich so that’s kind of bullshit. I did it out of fear. I was scared I was going to lose money. I was scared I would suffer a setback, I wouldn’t be able to pay for it, or it would be stolen somehow. This started in college in 1990. I went to school with $2000 and I had no idea how long it was going to last. So I said okay, I’m going to learn how to use a spreadsheet and I can estimate a burn rate. So I switched from cash to a credit card and started tracking every single transaction I made. And this worked well for several years until I got a real job, and discovered Quicken, which actually makes it a very sophisticated way of what’s going on. So this talks going to be about a database from 1995 to 2015. So by the numbers, this is a 1036 week of data, about 25 transactions per week. In terms of the categories, less than half a percent of the total dollars were miscellaneous, so I pretty much knew where everything was going. There are a large number of challenges to make this happen. First is storage. In the 90’s you owned your data, but it was on floppies, and it was a huge pain in the ass to protect it. I moved up to the cloud by 2008, which was great and it solved the backup problem but I don’t know if I own my data, which is kind of a problem because upgrade cycles and product lock in is a big problem. I tried switching to other software but the proprietary made that almost impossible. And actually a bug in one version of Quicken caused me to lose five years of data. In terms of repeating this, I forced myself to save every single credit card receipt in my big wallet and every Friday at lunchtime was receipt entry day, and then a the end of every month I played a game where I could see if I could reconcile my account and have no unknown transactions, so I made that a habit, a fun habit. Another challenge is hierarchical tagging is really difficult. If you go on a trip and buy dinner, is that travel food or going out food. Tag clouds didn’t exist back then and I wish they did. Another challenge around too is the fear, a slave to yourself costs. Once you have done this for 10 years you don’t want to stop. Like something bad might happen if I stopped collecting data. And I thee was this really weight on me. And eventually I hit the status of sweet, sweet inertia, where I was secure and I knew where my money was going and I wasn’t getting screwed by anybody. And I also started going back and looking at data, and looking at trends and looking at transactions and reconstructing what was happening at that point in time, and I was having these visceral memories of what was actually happening. And I was like, oh my god. I’m scrapbooking, except I’m using line graphs instead of photographs. And I was trying to understand you know, why is the line graphs so compelling, so let me share some of the line graphs that I enjoy looking at. The first one is, every time I filled up my car for 20 years. And if you normalize that, the first row you see is the price per gallon of gas, but there’s some other interesting peaks. So I wanted to normalize that and take that out to see what those peaks were. And when I do that, it flattens out a little bit – it’s hard to see, bummer. But I can see some, the averages are up on top and I can see when I had my really shitty car, and then I can see when I quit my job. I didn’t drive anywhere, and I can see seasonal changes, and the trips that I took. And speaking of trips, some of these big peaks actually turn out to be road trips like really memorable road trips that I’d taken. And some of these lower peaks were times I’d just given friends a 20 for gas, so I done all these other trips and you know, there’s a lot of memories coming out of this. Other weird categories that I looked at were money I spent on groceries. So here’s a weird contour, like what does this contour mean. I started looking into the transactions of that period of time and I notice that oh, I was in my 20s when I first started, and I was eating crap at Safeway. And it was really interesting seeing Safeway, food Co-op, Safeway, food Co-op, and so I was spending more money and then it became a full on you know food snob, shopping at whole foods the whole time. And I was really interested in food habits, because that was the bulk of my spending, and then I sought dining out. Any ideas why there might be big peaks here? Exactly, I actually tracked on who I went out with and where we went. So there’s periods when I was dating, and then married, and dating. And some of these peaks are like, there’s Valentine’s Date dinners in there and wedding dinners, and trips to Michelin star restaurants. And there’s all these narratives of fun things that I had done that I enjoyed looking at. Another way that I tried looking at it was, when I looked at my hobbies spending, I took my top 10 hobbies and tried to graph out if I could understand distinct phases in my life, and how I evolved to who I am today. And so the first cluster that I saw was when I was in my 20s, I was doing a lot of arts and going to a lot of shows, and playing in bands, and skydiving, and kind of pretty hip indie dude. And then I got married in 2004, and what do married dudes do? They take up a hobby of carpentry, and then I got a little older and working out. Then I found the World of Watercraft, and then I got back into working out again. Then, I got unmarried in 2011 and what do you think I did after I got married? Well, dating, guns and SM. This is what I started doing recently is what other things can I find out about myself, but more importantly, how do we actually capture moments and why is this lying graph so compelling. A line graph has 20 years of data compressed into one page. If you take photographs, photographs are digital imagery that’s one way that everyone is keeping track of their lives now. But you can’t really look at 20 years of pictures at once, because the big picture is obscured by the little pictures and you can’t actually make out the resolution. So you can’t make a one-page representation of your life. Audio and video are another way of doing it, but they have a temporal component and you have to listen to it in real-time. You have to play back in almost the time it took to record. And you can dictate audio or have it translated, and which you end up with a journal. But journals tend to be biased by your emotions and experience, where the financial data is really honest, at least in its dimension of a recording. The funny thing was I stop doing this about a year ago, well in September. I hit this point where I left my job at Intel for 20 years at the beginning of 2014, and I floated for a year. Then at the end of 2014 I almost died, and then shortly after that I realized, what are all these things that are taking up the time in my life, and the fear and the pressure of recording all this data was taking up a huge chunk of it, and like that’s one more thing I don’t need to do.

I don’t regret doing the work. I don’t regret collecting all the data, I mean it answered a lot of questions, and it enabled me to leave my job and be secure in my choices. But I think that’s one thing when you’re quantifying your data, this is just one data stream. With all the stuff we’re wearing now that’s collecting data, I mean there’s a lot of overhead. There’s a lot of emotions tied, and we’re going to have to decide if you really want to invest that amount of time, and is the reward really worth it. I thought it was, so that’s all I had.

About the presenter[edit | edit source]

Peter Torelli gave this talk.