I've just come across: Computer Stupidities. Its a lot of fun. I think my favourite so far is:
When I was studying programming, one of my classmates was having serious troubles with his program. When he asked me for help, I leaned over his screen and saw all of his code in comments. The reason: "Well, it compiles much faster that way."
Much like Daily WTF... though most of the CS stories are very early era
Corporations and governments spend staggering amounts of money on forecasting, and one might think they would be keenly interested in determining the worth of their purchases and ensuring they are the very best available. But most aren’t. They spend little or nothing analyzing the accuracy of forecasts and not much more on research to develop and compare forecasting methods. Some even persist in using forecasts that are manifestly unreliable. … This widespread lack of curiosity … is a phenomenon worthy of investigation.
An eye-opening article by Robin Hanson, called Who Cares About Forecast Accuracy?, describes how and why corporations spend heaps of money on making predictions... but almost none on testing whether those predictions actually worked out.
The article discusses the fact that actually recording the accuracy of pie-in-the-sky forecasts means that it's much harder to hide a poor track-record for leadership. That a lot of forecasting is more about signaling affiliation to the company ("yeah, we're doing great, I predict we'll be done by tomorrow!") than actual accuracy. Quite possibly just another effect of bosses preferring overconfidence to accuracy.
From my own experience - I find that many "leaders" don't want you to say that the project might be in trouble... and the article discusses how this can happen because the middle-managers don't want somebody to go on record as having questioned their vision... because it'll reflect badly on them down the line should something go wrong. It's much harder to sweep losses under the carpet if nobody officially takes notice of how often it happens.
I think there's also another reason, not mentioned in the article. That being the long-term vs short-term payoffs. The strategic echelons of an organisation need your predictions so that they can make their own overall predictions of how long a plan will take to implement. But they don't want to bother with the long-term cost of implementing a full system with all the process-change and downtime that it will take. I've personally found it extremely difficult to "sell" both management and fellow-programmers on changing to to a methodology which will allow for recording and feedback of prediction accuracy. These are methodologies that aren't particularly heavy or difficult to implement (compared, say, with six-sigma), but which provide a quick and easy way to get better at providing an accurate estimate of your times.
The problem seems to be, that it takes more time and effort to implement, and people don't want to do the "work". They want to make their guesses *and* make t more accurate... but not to have it impact the "bottom ilne" in any way. This is a bit like saying "we'd like to buy faster computers, but won't give you any budget for their increased cost". You somehow have to just improve anyway.
What normally ends up happening is that you don't properly implement any system of accuracy, so you end up simply guessing and just hope for the best. Actually spending the effort to make those guesses meaningful is too much like hard work, and nobody wants to add to their workload. This is understandable... but not exactly helpful (or realistic). Instead of improving over time, we continually wallow in a world of wild guesstimates and "fudge-factors" that never seem to quite cover the extra time it always seems to take.
To get back to the article, Hanson suggests that we use a betting-system to literally "put your money where your mouth is"... the intention being that if you personally stand to win/lose by your prediction, then it would be in your best interest to start being more accurate.
I think I'd balk at my own actual money, but I'm sure some kind of system could be set up for "points" where you "win" various rewards (eg an extra day off, or even just the ability to work on "the fun project") if you do especially well.
Has anybody had any experience with estimates and measuring their accuracy? Either from the trenches or the strategic side of things?
To me, freedom is the ability to choose my own timetable; to choose in which direction I can travel, and what level of quality to aim for. Freedom does not mean being completely unburdened (as you cannot go very far when you choose to do nothing). It is the freedom to choose which burden to carry - rather than accepting the one forced upon you.
We are all constrained to one degree or another. I'd rather choose my own constraints than to wear shackles chosen by others.
What does freedom mean to you?
Consulting is like selling crack. If you get hooked on the consulting lifestyle (and income), it can be hard to give that up to work on your own startups, yet many people get into consulting with the dream of working on their own projects on the side.
Yet it seems that consulting work can actually be detrimental to your startup-founding prospects. Read more from the original article
I have to admit I've fallen foul of this myself. It's very hard to prioritise spending a lot of time on a "maybe it'll go nowhere" startup, if you've got definite paid work to do right now (especially if it's well paid). In my case, my startup is MatchFounders, a site dedicated to matching potential founders for startups.
When prioritising, the "bird in the hand" mentality kicks in automatically - and there's a lot to be said about that particular proverb. But I also have to think hard about whether or not I'm selling my long-term future for short-term cash results.
It's not an easy choice to make, by any stretch.
Just how much do I want to work my own startup (and build something for the future) vs current, well-paid consulting.
Don't hold your breath for an answer - I'll probably struggle with this for a long time. But it has served as a reminder that I also have my own ideas on the boil - and should maybe give a little more love on their behalf.
What about you? Are you struggling to make the choice? Have you already made it? Do you have any advice?
I've recently read the Jeff Atwood's post: A blog without comments is not a blog, and realised that, while I don't have comments turned off - I don't exactly go out of my way to encourage much commenting on this blog.
I'd just like to say that I really do want to hear your opinions on the stuff I say. I'm frequently quite opinionated, and more often wrong than I like.
I may not give this impression, but I like to hear what other people say about a topic to get other points-of-view or even just to figure out my own blind-spots (by having them pointed out to me by somebody else).
So I've decided I should do what I can to encourage more frequent commenting here.
I'm not entirely sure how to go about it... but I figured I should start with a small change. From now on, I'm going to try and end each post with a question - in the hopes of sparking a conversation about what I've been talking about. Maybe it's a dumb idea - but I figured I should begin somewhere.
Does that work for you? If not, what does? Do you have other examples of good ways of getting regular comments on a blog?
Jason Freedman has clearly been asked one too-many times how to find technical co-founders and has written this excellent post so people will please please please stop asking how to find technical co-founders. :)
Fun to read if you are technical and, from my perspective it seems really useful if you're looking for one.
