[brodo]

The takeaways at the very bottom of the page are valuable:

> Overall, having spent a significant amount of time building this project, scaling it up to the size it’s at now, as well as analysing the data, the main conclusion is that it is not worth building your own solution, and investing this much time. When I first started building this project 3 years ago, I expected to learn way more surprising and interesting facts. There were some, and it’s super interesting to look through those graphs, however retrospectively, it did not justify the hundreds of hours I invested in this project.

The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

/edit: quantified, not qualified

[noemit]

A counter example:

I've been wearing an Apple Watch for close to 10 years. I've tracked my weight as well along those years but nothing crazy like OP. The Apple watch tracked plenty.

I had some strange symptoms and two doctors insisted I had a weak heart and potential heart failure. This was shocking! Turns out I do have a really "weak" rhythm, but heart failure is when your heart is progressively getting worse in it's pumping. I don't even remember which metric he looked at in my Apple health - but basically my heart has always been this way. A doctor looking at a single data point might think I have abnormally low blood pressure/heart rate, but if I've had this for 10 years with no change, the medical assessment is very different - it means nothing. Sometimes boring data is exactly what you need. For this reason, I will probably always wear an Apple watch (or equivalent) moving forward.

Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

[nkrisc]

But you didn’t spend hundreds of hours on it, so when it did happen to be useful it seemed like an outsized benefit.

I would wager that for most people, most data about themselves will be useless and not worth collecting.

Of course you can’t know what data will be useless or not, so unless the cost of collecting it is minimal or nil (wearing a smart watch, writing down your weight each day/week), it’s probably not worth it.

Spending hundreds of hours to build a solution to capture all data about yourself to find interesting patterns has a huge assumption baked into it: that there are interesting patterns to find.

[markh1967]

About 9 years ago I had a run-in with stomach cancer. After a few months of chemo and a 7 hour operation I was eventually declared cancer free and have been ever since, but still have to live with the consequences of the treatment and be vigilant for any signs of it returning.

I still suffer intermittent stomach aches, especially in the early hours of the morning, and had a terrible time trying to decide if they were getting better or worse over time.

Our narrative voice is awful at detecting long term trends and tends to overcompensate for particularly good or bad patches so it was impossible for me to judge and I started keeping records of how bad the aches were each day.

Long story short, the average severity was mostly decreasing over time and the average time between bad aches was slowly increasing but it would have been impossible to tell if this was happening without keeping detailed records because it wasn't consistent - some months were much worse than others and completely skewed my perception of long term trends.

While most people hopefully won't ever need to do something like this, it did make me realise just how bad we are at picking up on long term trends so I can definitely see keeping daily records of, for instance, average daily happiness being eye-opening.

[nkrisc]

Sounds like you had a very good reason to be tracking your stomachaches. But almost everyone else aside from you And people In similar situations would be wasting their time doing that, I would imagine.

[necovek]

Yes, when you have an obvious reason to track some data, do it: I do not think anyone questions that.

Proactively capturing and tracking everything you can to prep for any future is too much work that would really steal your time from, you know, actually living a life.

[cj]

Like anything else, I think it comes down to having a good use case.

I've gotten deep into weightlifting/bodybuilding over the past couple of years, and that's the kind of hobby where micro-optimizations and data tracking can have a pretty big impact on results (and sort of necessary, you can't fly blind with things like diet, especially)

E.g. I track and weigh everything I eat, take body measuraments on a weekly basis, Dexa scans every few months, etc - for me it's worth it because I know what I want to do with the data. If I didn't have a goal, all that tracking would clearly be overkill.

[afc]

How long have you been tracking? Can you share an insight you've had from your data?

I've been weight lighting for ten years and initially tried to track things (down to how many reps I did of which exercise, with how much weight) and quickly came to the conclusion that is want worth it for me.

[kworks]

I initially came to the same conclusion. Though I lifted in accord with decent training principles regarding reps and sets, I didn't track for years. As I entered middle age, I started keeping a training log (just one big org file in emacs), mostly out of curiousity. As I entered my 50s, I experienced what Haruki Murakami references in "What I Talk About When I Talk About Running" --- Fat is easy to gain and hard to lose. Muscle is hard to gain and easy to lose. Now I track a couple of critical metrics and it's working great. I weigh first thing every day, track all kcals (even if I overeat), plan and track workouts. I write my own plans pulled from principles in these books (don't work for the company, just a satisfied customer) https://muscleandstrengthpyramids.com/ I don't use the vast majority of the info in those books as I'm just a hobbyist who wants to be healthy and strong. The biggest shift came from learning I was doing waaay too much training volume at the gym while trying to lose fat too quickly; a fine recipe for injury. Now, when I'm in a fat loss phase, I try to lose it as slowly as possible while still making progress. Strength training and fat loss is a very long very slow marathon, not a sprint. Perhaps paradoxically, the awareness that's come from tracking has helped me relax. No need to major in the minors; pretty good is pretty good. The tools I use are a scale, loseit, and org-mode.

[cj]

The goal in bodybuilding during a gaining phase is to be in a very slight calories surplus (200-300 calories above maintenance, at most) to maximize the amount of time you're building muscle before you need to cut again (bring calories back to a deficit to shed body fat).

Tracking scale weight is difficult because shifts in water weight and hydration can swing the scale 5+ pounds in either direction without any change in body fat. So I pair scale weight with a 7-point skin caliper measurements taken on a weekly basis, along with waist circumference, in order to infer whether body fat is trending up or down. And also take weekly progress photos of 6 angles/poses with consistent lighting, which I share with a coach.

And then you pair that with weighing and logging everything you eat, and you can make small adjustments to your meal plan on a monthly basis to try to stay in that 200-300 calorie per day surplus for as long as possible. (Although most bodybuilding coaches adjust diet based purely on how your physique is changing in weekly check-in photos without the need for measurements, but I like extra data)

> down to how many reps I did of which exercise, with how much weight)

I also do this. Track every exercise, every weight, number of reps. It's necessary for knowing whether you're progressively overloading over long periods of time. Progressive overload becomes harder to measure once you're past newbie gains because you can't increase weight every week, so some weeks the goal is just to squeeze out an extra couple of reps. Which adds up over time

This is obviously excessive for 99% of people. But I enjoy doing it as a hobby. I would absolutely not recommend this level of tracking for health reasons (not necessary) - I find enjoyment in the process.

[yoz-y]

I track the reps weights of every exercise (in my own app). But the historical values are only useful up to last couple of weeks just to now if the general trends go up and what is stalled. Unless your goals are the numbers themselves and not health, I don’t think there is a reason to track everything. But it is fun.

[nkrisc]

True, if you have a current and real need for the data, then it makes sense to collect it. But that’s an entirely different scenario.

[Ajedi32]

Right, but you don't necessarily need to spend hundreds of hours to capture most of this; the data is already out there. If there were a tool that could collect it all in one place and give you insights with minimal effort that would be pretty neat.

[icos]

Yes, I developed Health Hub https://biomarkeroptimizers.com/tools/health-hub/ to visualize and analyze my blood work, food, exercise, and sensor data from various sources, thinking it can be also useful for others.

[noemit]

agree. I would never do what OP did. But I also won't throw out my smart watch (Context: other people in the thread said they stopped using them because the data was useless)

[austy69]

> Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

Not sure if in your case the data was critical, since the doctor likely would have just had you wear a monitor for a while after to come to the same conclusion.

[panlana]

My first car had a broken speedometer. It was a "hand" style like a clock. Instead of moving to the speed, it would spin 365 degrees. The faster the car went, the faster it would spin. Turns out, I acclimated to it and generally knew what speed i was going (relatively speaking).

The lesson, I think, is everything is relative. Even a dashboard with flawed data that is "consistent" can highlight anomalies. And often, that's all you really need out of them. (Or the lack of anomaly)

[necovek]

This is the obvious "benefit" of hindsight. Yes, you accidentally had access to data that provided historical patterns you exactly could use.

But, for anyone who does, there is another 1000 who do not when something hits them: many illnesses develop gradually, and all of our tests (thousands of blood tests, scans and imaging tech...) would benefit from having historical data when we were "ok".

Similarly, you probably did not have more data than what Apple provided to help narrow the problem you still had, right?

And if everyone was put under so many tests, we'd actually be "solving" a bunch of non-issues for people over-reacting to small deviations from "normal" range.

Apple watch helps you with a few parameters — not to be discounted — but I don't really see it as a counter.

[harrall]

Collecting data is great.

But I see people start min-maxing these numbers as a replacement for big picture health goals.

From the outside, I see someone spending a lot of time focusing on numbers while they are actually regularly stressed, who doesn’t get good sleep, and has somewhat bare minimum exercise.

Collecting data is great but don’t sink so much effort into it until you have a problem.

[BeetleB]

This was great because you didn't put much effort into it. Whereas the conclusion was about "it is not worth building your own solution".

[ambicapter]

So what happened with your symptoms?

[stevekemp]

I had a similar epiphany a few years back when I started wearing a step-tracker/sleep monitor.

It was kinda interesting to see how many times I woke up, or track hours, but to be honest I realised after a few months that when my tracker said "You had good sleep", or "You had bad sleep" I was already aware - I woke up smiling, or grumpy depending on how I'd done.

I didn't ever look at the data and think "I want to go to bed now to catch up on the four hours I missed yesterday". I continued to have mostly consistent hours, but if I was doing something interesting I'd stay awake, and if I was tired I'd go to bed earlier naturally. The graphs and data wasn't providing anything of value, or encouraging me to change my behaviour in any significant way.

[azan_]

I've found one very interesting thing from these trackers - namely how even small amount of alcohol destroy sleep quality metrics. One beer is enough for my sleep scores to drop by like 20-30% and it's consistent and reproducible for me every time. Whether it actually matters - I don't know, but it made me drink much less (from maybe once a week to maybe once every two months) which is good outcome I guess.

[revolvingthrow]

Eh, I found several interesting things from various tracking tools. Take a nap? Sleep is destroyed this night. Exercise in the evening? Same. Not something I’d pay attention to without noticing the chart afterwards.

There’s also the motivation factor. I’m not sure of the total %, but I certainly did some exercising just to fill the daily goal. Nothing life-changing, but for the price of a cheapo apple watch se once every 5 years or so, more than worth it.

It’s not unlike simplistic time tracking on my iphone. I spent a lot of time on bullshit websites. Obviously I knew it was happening, but the sheer magnitude was surprising. It’s akin to acute pain letting you know there’s a health problem vs something brewing in the background that you are vaguely aware of, but have no motivation to truly care about - one is far more noticeable than the other

[oldandboring]

Same. I had a Garmin for about 6 months and I eventually just stopped wearing it and sold it. Knowing how many steps I took today, checking it several times a day to see if I was meeting my goal, knowing how many vertical feet I skied.. none of this data ended up meaning anything to me.

[piva00]

The best use I got from my Apple Watch was to use the companion app of my gym routine tracker (to track current loads and personal best) and play music so I didn't have to bring the phone to the gym.

That was it, I got extremely annoyed by notifications so over time just disabled them. Also for some reason the heart rate monitor glitched a couple times, got alerts about my BPM at 180+ while I was sitting on the couch.

Eventually I just stopped using it and now sits in some drawer.

[koliber]

Being aware, and being aware that you are aware are very similar things that are subtly different.

I was aware that alcohol affects your next day, even a little. That's because people always say that alcohol is bad for you (surprise surprise). I heard this, so you could say that I was aware. I generally thought about this as "a hangover is bad for you." and was somewhat dismissive of the "even a single drink has a bad effect" mantra.

I did some experimenting, and slowly realized that even a single drink can indeed have an impact on the next day. It's not a hangover, but an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness. I am now aware that I am aware.

[andsoitis]

> an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness.

If you could feel it why beed the stats?

[koliber]

I don't think I was clear.

There is a difference between knowing something, and believing it to be true.

I know that sometimes I feel good when I wake up. I know people say that drinking makes you feel not good when you wake up, sometimes.

It takes a bit of observation and some statistical sampling to connect those two together. Now I know it, and also believe it to be true.

Perhaps "aware" vs "aware that I am aware" was a bad way of phrasing it.

[sdwr]

It's like any good cryptographic challenge - easier to validate the answer than to come up with it from scratch

[angiolillo]

> it did not justify the hundreds of hours I invested in this project.

I agree with this but minimizing the cost changes the ROI.

Personally, I've discovered useful insights tracking various life metrics. But I also found quickly diminishing returns after a few weeks or months -- if an association isn't obvious within that timeframe it's either too much effort to isolate or too slow or small to matter.

At various points I've tracked calories, macronutrients, weight, allergens, supplements, sleep, exercise volume, exercise timing, nighttime screen use, spending/budget, air quality, and mood. Now I know what kind of cooking wrecks the air quality in my house, what foods I don't digest well, what various protein/carb/fat ratios look like on my plate, how much effort it takes to improve fitness, that exercise in the morning or early afternoon improves my sleep while exercise in the evening harms it, and that any alcohol or caffeine wreck my sleep while screens at night have no measurable effect. But once I understand the associations I can alter my behavior and move on.

> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

I would agree that continuing to track metrics every day long after they've stopped yielding new insights is often compulsive behavior. But I think that's an argument for time-boxing experiments, not necessarily avoiding them altogether.

[visarga]

I did something similar - I put 18 years of comments on reddit, HN, slashdot, and 3 years of LLM chats in the system. I ended with a similar conclusion - it was less useful than I expected. My intent was to do RAG over my corpus, have a LLM get direct access to what I commented over the years, but unfortunately this much information has a negative effect on LLM creativity. Its responses started to fall in line too much with my ideas and it lost its spark. In the end my conclusion was that all that data was facing towards the past while I desire LLMs to improve in the other temporal direction.

[arjie]

I did the same but with GPT embeddings. My primary problem was different though. I wanted to find when I talked about a related subject somewhere. Search works really well.

[nicbou]

I have built a much more limited version of this that combines my journals, sketches, photos, geolocation etc. I found it useful for noticing patterns in my behaviour and in my irrationality. Journaling helped the most, because recording my feelings means acknowledging them and reviewing them.

Above all, it's just interesting. I enjoy reading about the day-by-day progression of a crush or my brutally honest feelings about a trip that produced stunning pictures. It weaves nuance into my history.

[andsoitis]

Yours is qualitatively different because you’re not quantifying your life.

A good thing.

[vidarh]

For me it's about managing ADHD-like (never diagnosed, and I don't care to assume) patterns, coupled with self-accountability. I have a self-improving dashboard (it kicks off Claude to propose additions based my positive/negative feedback on past attempts, and then builds them) that feels quite helpful. E.g. one of the things it added was fitbit integration that shoves my step count and resting heart rate in my face every day, and it's helped me drive my step count back up towards where I want it to be.

I do think it's not worth spending a whole lot of time on, though - hence why the first thing I did was add that mechanism to have Claude build it for me, with me mostly glancing at a plan and saying yes/no. It's the perfect thing to vibe-code - if it breaks, I revert a commit and it doesn't matter because nobody depends on it but me.

[andout_]

It's important to tell the readers how long you've been doing this - especially to those that also manage ADHD or ADHD-like symptoms.

Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.

The result then ends up being a false signal for others in the same boat. People who read it, feel a spark of recognition ("someone like me actually figured this out"), and then invest real time, energy, maybe money, into replicating something the author themselves quietly abandoned two weeks later.

Just a small heads up from someone who used to get burned in the past :)

[drivers99]

> Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.

That's definitely me (most recent ones: using engineering notebook techniques but for my own life, and WOOP method), but I recognize that feeling like I've found THE solution when I'm only a few days into it, so I tend to wait and see, or if I tell someone I say "...but ask me again in a week or a month if I'm still doing it." (At least with the engineering notebook, I can still go back and use it to remember what steps and settings I used in KiCad or use WOOP on a new goal at any time. So it's not a total loss.)

I will say one thing that I have stuck with and is pretty useful is a morning checking and an evening checklist. I'm currently using a paper version with the days of March in the columns and the checklists in the rows, and X them off as I go. A slash for the one I'm doing now/next and X when it's done. Leave it blank (or write N) if I choose to skip it. As a back-up, when I can't get around to make a paper version (I'm planning to type in the steps in a spreadsheet so I can just revise and print it each month) I keep the lists in two Google Keep checklists. Those are great because you can reset the checklist each day for reuse, and you can drag to reorder it as you edit it, and you can indent one level to organize it a bit. The disadvantage is I might get distracted by notifications and stuff on my phone.

[vidarh]

I have data going back many years, but this recent effort is a few months old at this point. It's however notably an iteration that has reduced the amount of time I spend on collating and reviewing data, by automating away most of my previous manual effort, including most of the coding, and so I do suspect I'll stick with this for a very long time. A significant part of the prompt to the Claude part of it is to focus a substantial portion of plans on how to automate little things that costs me time, and it's doing a decent job at that.

I've absolutely not figured it out, but I now have an agent throwing stuff at the wall (with guidance from read access to e.g. my journal and a few other data sources) to figure it out for me, and it's gotten steadily better.

[JCattheATM]

> managing ADHD-like (never diagnosed, and I don't care to assume)

What's the difference here between assuming and saying 'ADHD-like' instead?

[vidarh]

The difference is that I know what my "symptoms" are, but I don't know whether the combination of them are sufficient to justify an ADHD diagnosis. I don't like to assume because there's a tendency for a lot people in tech to self-diagnose and in the process sometimes diminish the difficultly others have with them.

[matusp]

It's pure armchair psychology, but this type of project always makes me think about anxiety. Who really needs this level of self observation and control? At the same time, I really enjoy reading about it and I find the window into somebody else's world intriguing.

[efilife]

> Who really needs this level of self observation and control

I liked doing similar things in the past. There's no anxiety in the equation, just pure curiosity. How many times have I done a thing a month/year? I was always curious about stuff like this, much like the OP. There's also the hacker spirit in play - designing the apps for tracking stuff.

[runjake]

You're equating two different things here: "building a custom web application" with "quantified self". These are two entirely different things.

Felix's statement isn't a condemnation of quantified self. I think that sometimes, when you're applying algorithms that aren't well-studied, you get pointless or bogus data. I feel much this way about sleep tracking algorithms from the likes of Apple and Whoop. Vitals, too, although it seems remarkably good at detecting when I'm about to get sick.

As a person in the older demographic of HN, having an Apple Watch quietly collect useful data over years and store it in a database has been immensely useful in helping resolve medical issues.

I used to really be into QS, and if I'm training for a marathon, I'm still studying graphs and drawing conclusions. I'm still into QS, but now I just silently log data to Apple Health and use it for medical histories or to identify certain trends (vo2max, cardio fitness, blood pressure, etc) a couple times a year.

[driverdan]

I never spent as much time as OP on this but I did collect a lot of data during peak quantified self. I liked having automatic data collection and being able to see trends, for example. I stopped because of a few issues, not related to time:

* Hardware companies went out of business, stopped supporting devices, etc. It became obvious that there was no long term commitment to make good quality hardware that lasted a long time.

* Many devices and/or data collection was consolidated big, data hungry companies Google and Apple. Competitors have similar anti-consumer uses of data. I don't want any of these companies to have my data.

* Related to the last one, limited to no offline or local only data collection.

It is very hard to gather most of this data with off the shelf hardware and keep your data private.

[skyberrys]

This provides some insight into startup ideas around privacy, local first, offline only self data collection. I agree this kind of personal life data is something you don't want to contribute unknowingly to big data. I could see wanting to share it particularly around a health problem where only massive compute has a chance at providing answers.

[cobertos]

> however retrospectively, it did not justify the hundreds of hours I invested in this project.

Trying to extrapolate this conclusion to the entire "quantified self" movement is not correct. The issue is the time cost, not the act itself. If a trusted company came along (as if...) that sucked up this much data to allow you to answer these questions with minimal effort, I'm sure this would be a different story.

Anything at the fringes of tech with no tried and true solution requires hundreds of hours of effort. The author's conclusions are also personal, there are other styles of living and conclusions to be drawn that change the calculus on whether to do it or not.

[aurmc]

I ended up doing something similar to this project a year or so ago: for nearly an entire year, I tracked every single thing I ate or drank.

Who knows how many hours I spent scanning nutritional facts on the backs of boxes, estimating amounts of liquids, and even tracking sips of water. And weighing myself! Thank goodness I used a "smart" scale at least, and I didn't have to worry about carefully inputting my weight to an app each time.

But the whole project was an exercise in perfectionism. "I have to remember this sandwich and log it the next time I'm alone" made me anxious, but once I logged it, I felt a sense of completion. The database and my personal history are now at nirvana. Everything is complete.

All for me to learn things every human alive knows today: eat more food and you'll gain weight; eat less food and you'll lose weight. Yes, I can now tell you the exact average difference in calories I'll eat, statistically speaking, on a day that I have adderall in the morning vs a day that I don't. Yes, there's a similar (but much smaller) difference in average calories per day if I have caffeine in the morning as well. And I can tell you that I generally eat an additional 200-400 calories per day on a Fri-Sun than on a Mon-Thu. Wow, groundbreaking.

I've always had a lot of water, but matching foodanddrink.csv to my HealthKit data showed that I have more water on days that I walk more steps. Mildly interesting to see it written out for me? I guess. But was it worth cataloguing every cup of water? Absolutely not.

Was any of [gestures broadly at me pulling out my phone and cataloguing each item I ate] necessary to learn that? Of course not. It gave me a chance to look back at the database and say "Wowee! I did that! Every day for a year, wow, I'm so cool!" and not much else.

[fxwin]

extensive tracking of self-related metrics to improve ones health is the equivalent to reading tons of self-help books to improve ones life/social skills/...

We already mostly know what makes people happy/healthy: personal connections, physical activity, healthy diet and some sort of purpose/goal in life that goes beyond day-to-day activities. The problem is that these things generally require (hard) work and can be unpleasant sometimes, so humans do what humans do and spend unreasonable amounts of time doing the more pleasant things such as reading and gathering info rather than applying these and what they already know. (That's not to say that a project like this can't be fun or lead to insights, especially across longer time spans, but i feel like all of the questions in the first paragraph have fairly obvious answers if you know yourself at all, that don't require extensive tracking of stats to get)

[Noaidi]

If you are not sick, tracking your life like this is, like he said, is useless. Enjoy your life!

On the other hand, if you are sick like me, charting your long term heath data from doctors visits and photographing skin issues can lead to great discoveries. I have been diagnosed with Erythrocytosis and a susceptibility to mycobacteria infection which caused pulmonary nodules and skin lesions. Only after showing my data collection to my doctor. Since I have mental illness they constantly over looked my physical issues so I needed hard data to convince them of my ideas.

For those curious, I have an minor IL12B deficiency and a partial immune deficiency leading to mildly elevated levels of DexoyATP which is partially corrected with zinc supplements.

[WarcrimeActual]

This whole site is a rich persons humblebrag. That renders all of it moot as far as value.

[BloondAndDoom]

Agreed, I have tendency to do this to “fix” something in my life, after doing it for 2 weeks I already know, just the consciously pay attention to something even without recording make it very obvious what’s going on.

[alexfoo]

Sometimes it's the journey not the destination.

I did something similar to pull data from my Garmin watch. This meant writing all manner of code to pull data out of FIT files (interesting and often infuriating self-describing file format), coming up with schemas to hold that data to make it queryable, adding visualisations, performing analysis, pattern matching, etc.

The end result is nothing really useful, I had a bunch of scripts that semi-automated some jobs that would have taken 1 minute to do manually and only ever needed to be done a max of five times a day, but I learned a load of things along the way. Often these were useful lessons that can be applied to many other things when developing software.

In a similar vein I've gone to lots of trouble to build a cooling system for my homelab rack (ESP32 to control PWM fans, Dallas 1-wire for reading temp/humidity, exposing measurements as metrics for scraping/observability, designing things to deal with the different voltages involved, etc). I could have just gone and bought an off-the-shelf solution from AC Infinity and installed it in minutes but where would the fun in that be.

[behehebd]

I wouldnt have minded if I kept a simple daily journal with a photo a day. If I had that now with LLMs I could ask it "what year did xyz happen".

[nemo1618]

yep, I do a simple version of this in Google Sheets. Very useful to be able to "Ctrl-F" your life, especially when combined with Google Maps location history.

[jives]

> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

As someone who has dealt with OCD and perfectionism, I think that could be the case for a lot of people. And the urge to obsessively track everything can be debilitating.

[Bullhorn9268]

I too learned this the hard way. I still haven't figured out why this is the case - like, is the inherent incidental irreducible complexity of human life too high, so it dominates majority of our actions?

[flexagoon]

> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

Quantified Self, at least in the intended form, is focused on testing specific theories, not on collecting large amounts of data and trying to find something interesting in them.

See, for example:

https://gwern.net/zeo/zeo#what-qs-is-not-just-data-gathering

[coldtea]

One interesting actionable takeaway fact is that if you do such a project spending so much time on it, your life outside of it likely sucks.

[karlitooo]

Having set up Analytics on all my websites, I noticed absolutely zero change in sales volume therefore Analytics is a waste of time.

[coffeefirst]

Yep. Same goes for elaborate note-taking and productivity systems. The simpler, the less bookkeeping and cognitive overhead, the better.

[a3w]

*quantified self

[swarnie]

This is disappointing.... Last year i noticed large chunks of my life were being monitored via many spreadsheets and i endeavoured to bring them all together in to one Oracle DB. My plan was to eventually put some ui and graphing on top very similar to OP but seeing this is making me think twice.

[ericyd]

Cynical take: I didn't need to read to the bottom to know it was useless to track the correlation between drinking alcohol and dancing

[cyanydeez]

The whole "this is a movement" thing might be more about mental health issues than anything else.

[PurpleRamen]

I kinda disagree. Doing something about open questions which are bothering you can be valuable in itself, even if the result of the process is useless in the end. And usually you are also learning some valuable things along the way, or just push your life into a necessary direction. That isn't related to OCD or perfectionism, it's just gaining more control and insight about some aspects of your life.

[brodo]

> it's just gaining more control

Yes it is! And if you control everything, you won‘t make mistakes.