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Software Effort Estimation Considered Harmful

122 points by MattRogish 14y ago

gpcz 14y ago
I'm fascinated to know the author's opinion about Joel Spolsky's "Evidence-Based Scheduling" approach. The author mentions that breaking the schedule into the smallest possible pieces can lead to "overfitting," but Evidence-Based Scheduling uses previous programmer estimates vs. actual time to give a probabilistic schedule that changes with new events. Instead of a rigid ship date, Joel's method can give you a probability of shipping on a given date with the current information. Is Evidence-Based Scheduling still harmful, or is it basically the equivalent of the relative points-based estimation the author brought up at the end of the article?
- jacques_chester 14y ago
  EBS looks to me like an elaboration of the old-school PERT 3-point estimation technique. By the Laws of Agile, everything invented before 2001 is busted and useless, so I guess EBS would go out with the bathwater for being tainted by association.
abhimishra 14y ago
A good read, and more-or-less in line with my observations from working at a couple big software companies. I think there is generally less value in estimating versus doing, especially for tasks/projects that are inevitable.
logn 14y ago
I think estimation can mostly be forgotten. The planning part which the author identifies is always helpful. Sure, get the team together to plan features and get a feel for the goals. Even get biz analysts together with folks to determine req's. But do we really have to tell you how long it will take? When a lot of managers just take the estimate and multiply by three can these estimates really be trusted? What's the end game? Is it any different than just building it out? If you have a hard set of features then it will get done when it gets done. Just predict what half of what year. If you're an agile enterprise, then timebox the release and build out from there. Why must we all do this absurd dance of time estimating?
- sliverstorm 14y ago
  The goal is be able to effectively load-balance and prioritize. If something won't take long, for example, it can be deferred (if needed) if it depends on something else that will. Additionally, depending on the market and how important schedule is, it lets you know if the project will be hopelessly late and as a result whether it should be canned.
  - mattvanhorn 14y ago
    Any project whose only value comes from being there first is a loser and should be canned before the estimating. "Hey Sergei, Larry says Alta Vista is on track to beat us to market, so lets scrap this search thing and invest in new DRM schemes"
    - btilly 14y ago
      Time to market sensitivity does not always mean "loser". An example that comes to mind (because a story about it was on HN in the last day) is that the first edition of Warcraft was aimed for the 1994 Christmas season. If it had arrived 2 months late, they would have missed that season, and technology improves quickly enough that they would have been unlikely to be as successful if they delivered the same product in the 1995 Christmas season. Do you think that Warcraft is a product that is a loser and should have been canned immediately because they had a schedule that they really needed to deliver it on?
      - j-kidd 14y ago
        That sounds like a weird example. I have never associated the gaming demographics with Christmas shopping.
        sliverstorm 14y ago
        How about the gaming demographics' parents?
thisisnotmyname 14y ago
There is a great deal of philosophy here, but I'd prefer to see some data that backs up his point. Can you show me a project in which investing in an estimate harmed it?
- MattRogish 14y ago
  Peopleware, DeMarco and Lister, pg 27-29, alluded to in the post. Namely: "The most surprising part of the 1985 Jeffery-Lawrence study appeared at the very end, when they investigated the productivity of 24 projects for which no estimates were prepared at all. These projects far outperformed all the others..." Study refers to Jeffery and Lawrence, 1985 study, to which I cannot find the raw data, unfortunately.
  - MattRogish 14y ago
    I found the study: http://www.sciencedirect.com/science/article/pii/0164121285900068 http://www.sciencedirect.com/science/article/pii/01641212859... Jeffrey, D.R. and M.J. Lawrence, "Managing Programming Productivity", The Journal of Systems and Software 5, (1985), 49-58.
tmurray 14y ago
First, continuous deployment works fine for web projects, but it's not an option if you've got a packaged product that you have to ship at some point. Agile is not a panacea for these environments. It's important to differentiate between the two kinds of software that you can write. This is post is dead-on for developing truly new software (new features, stuff that fundamentally hasn't existed before, etc). However, estimation (even the kind of project-manager-driven estimation that most engineers, myself included, generally hate) can work really well for software where you're doing basically the same thing you've already done in the past such that the risk of unknown unknowns is extremely low. I've seen it in practice, and when you have a checklist of stuff to do that you've already done with very minor changes in the past that can't be automated for whatever reason (e.g., support a new piece of hardware, except that the new piece of hardware is basically the same as the old piece of hardware with very minor well-documented changes), you can estimate with surprisingly good accuracy.
- pnathan 14y ago
  Yes, but a decent amount of software is doing things that are relatively unique to the time, place, and organization creating it. For those sorts of projects, you might as well use this equation for time to completion: sum of(number of lines in the spec/request * d4)*3 = days to complete.
- arohner 14y ago
  > continuous deployment works fine for web projects, but it's not an option if you've got a packaged product that you have to ship at some point. Agile is not a panacea for these environments. I think that misses one of the key insights of continuous deployment. The biggest gain in CD is not about actually pushing code to production on every commit, but working as you actually do push to production on every commit. This means that commits are small, contain tests, are delivered frequently and don't break the build. That workflow is a good idea, regardless of the final product or industry. I practice CD (hell, I built a company to do CD), but if I ever had to go back to shipping desktop software or whatever, I'd still practice CD.
- jasonhanley 14y ago
  What is this "packaged" software you speak of?
btilly 14y ago
He's sometimes right. There are lots of good reasons why you might need software schedule estimation. When you do, there is no point in throwing up your hands and saying, "You can't do that, everybody knows it." Instead get http://www.amazon.com/Software-Estimation-Demystifying-Practices-Microsoft/dp/0735605351/ref=sr_1_1 http://www.amazon.com/Software-Estimation-Demystifying-Pract... and teach yourself how to do it. Why would software estimation matter? For many companies it matters a lot if you can announce something in time for Christmas. Or you might have to hit a deadline for compliance with a legal contract. Or you may be trying to prioritize two different possible products - without a sense of the effort involved you're lacking one of the parameters you need for such an estimation. That doesn't mean that you always estimate. If the value proposition is clear enough, you're going to work on it until you're done and then you will be very happy. But the real world does not usually work like that.
- MattRogish 14y ago
  "For many companies it matters a lot if you can announce something in time for Christmas." It will be done by xmas or it won't. I don't recommend "no estimation", but intense estimating won't make you hit xmas. Not estimating may give you several weeks that you could be coding. Either way you're takin a mighty big risk when you publicly commit to that. Welcome to hell, population: Dev Team. I've known of no major software project that has a public date that hasn't resulted in major delays, feature cuts, or massive overtime to try and hit that date. "Or you might have to hit a deadline for compliance with a legal contract." That is also a suitably terrible position to be in. I recommend you don't take such contracts. Again, your estimates will be wrong. Even if you spend months doing them. Then you're in the same spot. "Or you may be trying to prioritize two different possible products - without a sense of the effort involved you're lacking one of the parameters you need for such an estimation." Which delivers most business value? I find it farfetched that both are of equal importance.
  - swalkergibson 14y ago
    How does this apply in an agency context? I would like to see if this can be applied to my company, but I am a little fuzzy on how this theory can work with paying customers who want to get an idea of cost up front.
dools 14y ago
This is the best article on software I've ever read.
iandanforth 14y ago
The flip side of lie-based estimation is arbitrary deadlines. I'm not the first to notice that work expands to fill the time allotted. There can be real value in setting a hard deadline with almost no regard for difficulty. This eliminates the 'process' overhead and often produces amazing amounts of work in a shorter period of time than anyone would have estimated. I really like working to deadlines because my motivation is inversely correlated to the time till deadline.
- freshhawk 14y ago
  It might work for you but it's a horrible way to manage people in general. Motivation by arbitrary imposed deadline is a standard dev nightmare isn't it? I've watched two companies destroy themselves with this tactic. Personal motivation and goal setting and even team based motivation and goal setting is important, sure, but you better have other motivation techniques ready when your "hard deadline with almost no regard for difficulty" gets completely missed and the team is depressed and bitter about missing it even after all the effort that was put in. Also, your team isn't stupid (hopefully). So when they bust their asses to hit that deadline and the next day nothing happens, because it was arbitrary, they learn not to listen to your deadlines.
  - iandanforth 14y ago
    Good point, I was assuming this was done transparently. In the same way that contests are run, a date is chosen, announced and then met with the full knowledge that pride and perhaps a reward are on the line. Also this can't be the only way you set deadlines as any team would rapidly burn out.
    - freshhawk 14y ago
      Ah, gotcha. That type of push or stretch goal is something different. I've never tried it though, anyone have any experience with this type of motivation?
- jacques_chester 14y ago
  In one of DeMarco's other books -- I can't now recall if it was PeopleWare or The Deadline -- he explains how arbitrary deadlines come unstuck. Because people learn that they are arbitrary. When the Super Serious Urgent Red Alert All Hands Man Battle Stations deadline whistles by without much more than a frown from management, the team quickly realises that it was total horseshit to begin with. Software engineers are, it has been observed, a smart bunch. If deadlines are being used a "motivational" technique, they are quickly degraded into meaninglessness. Which will hurt the company when an actual hard deadline pops up. Boy who cried "Wolf!" and all that.
X4 14y ago
"The roughness of the fractal dimension of a problem that needs to be solved can be calculated more easily in my opinion than with classical estimation techniques." We're always applying the Roman "divide and conquer" strategy without thinking about it. It wouldn't make sense to apply this, or any other strategy ignorantly! The D&C strategy works because a naive solution to count the fingers in this picture without knowing the fractal dimension is: "divide and conquer". http://mark.rehorst.com/Bug_Photos/fractal_hands_c.jpg http://mark.rehorst.com/Bug_Photos/fractal_hands_c.jpg (mirror: http://i.minus.com/ibz9NsZ6ET32aV.jpg http://i.minus.com/ibz9NsZ6ET32aV.jpg ) I think this is also the reason why some autistic people feel uncomfortable when they don't know each detail of a not yet happened situation in advance. Because communicating the fractal dimension, or "roughness" of a problem or situation is the most time consuming and fragile phase in a project. Here's an article about: "Roughness of fracture surfaces and compressive strength of hydrated cement pastes", which appears to be completely out of topic. But I believe it's nearer to the best estimation technique than other techniques. (Fig. 3) http://www.sciencedirect.com/science/article/pii/S0008884610000311 http://www.sciencedirect.com/science/article/pii/S0008884610... While you may critique that I've not contributed to solving the problem, you may also notice that I've helped to shed some light on the roughness of the problem to be solved :) (Am lazy, it's very late and I'm just back from training to be honest=)
- X4 14y ago
  Hey cool, I've found a solution :) The Fractal Planning Solution – Jim Stone, PhD. PDF http://www.fractalplanner.com/clear_mind.pdf http://www.fractalplanner.com/clear_mind.pdf He also offers a hosted planning tool. James Theiler has found a formula on estimating the fractal dimension. See Google Doc: http://tinyurl.com/cantjjp http://tinyurl.com/cantjjp
akeefer 14y ago
There are two serious problems with this post, and it really saddens me that I see these sorts of posts so frequently here, with so many concurring voices. First of all, cost absolutely 100% has to factor into prioritization decisions. That doesn't require absolute estimation, but it does demand relative estimation (which he mentions tangentially at the end of the post). If Feature A will deliver $100,000 in revenue but take 18 months and Feature B will deliver $10,000 in revenue but take 1 week, the choice is pretty obvious. What matters is never "return" but always "return on investment." If you don't know anything about the I side of the ROI equation, you're doomed to make bad decisions. With no estimate at all, and just a snarky "it'll take as long as it takes, shut up and let me work" response, you'll inevitably focus on the wrong things. Secondly, many of us do in fact have deadlines, and they're not just total BS. If you have a customer that you're building something for, they have to be able to plan their own schedule, and just telling them "well, maybe we'll ship it to you in 10/2012 or maybe in 6/2013, you'll get it when you get it" doesn't fly. And it's totally reasonable that it doesn't fly: if they have to, say, install the software, or buy hardware to run it on, or train users, or migrate data from an old system, or roll out new products of their own that are dependent on the new system, they clearly can't plan or budget those activities if they have no clue whatsoever when they'll get the new system. And if you do have a deadline, you kind of want to know, to the extent that you can, if you're going to make it or not so you can take corrective action (adding people, cutting scope, pushing the date) if need be. You can't do that if you have no estimates at all. Relative estimation of tasks with empirical measurement of the team's velocity works pretty well; it doesn't work in all cases, but it's pretty much always better than absolutely nothing. There's a huge, huge difference between doing relative point-based estimation and date-driven, pointy-haired-boss estimation, and it's a total disservice to the software community that so many engineers seem to not really understand that difference, and seem to think that the only two options are "unrealistic date-based estimates" and "no estimates." TL;DR - Don't just rant for 3000 words about how estimation is horrible and then add in one sentence about relative estimation. You'll do the world much more good if you just help educate people how to do things the right way and spare the ranting.
- five18pm 14y ago
  You took the words out of me. Even if there are no external customers waiting for the release, a business' other departments have to plan their activities. When will marketing start their pre-release activities without engineering's estimates? When will sales start talking to customers about the new release? There is just too many things that need engineering's estimates.
arkitaip 14y ago
So what do you do as a freelancer working on projects that last weeks or months? Tell your clients to go screw themselves, that you'll be ready when you're ready?
- mbell 14y ago
  You tell them to define a minimal feature set, and impose that it is actually minimal. This feature set you estimate and give a hard deadline on. Then you tell them that you will iterate based on feedback and add features as directed until such a time as they choose to stop paying you. There is no such thing as "done" in software development.
  - jasonhanley 14y ago
    'There is no such thing as "done" in software development.' Exactly! That's what makes it so different from physical world projects. You can keep adding/changing things forever.
tmoertel 14y ago
Software effort estimation causes three problems. First, most estimation processes model the uncertainty about the effort required for tasks but fail to model the uncertainty about the tasks themselves, leading to unreliable estimates. Second, people are overly confident of the estimates, in any case, because the estimation process looks impressive and produces impressive looking artifacts. Third, the estimation artifacts obscure the coupling between the stakeholders and the implementers by not transmitting how the one group’s decisions affect the other; the estimates, in effect, form a barrier that makes it harder for people on opposites sides of the estimates to take shared responsibility for business goals. If you understand these problems and can solve them for your projects, estimation can help you to make better decisions and to allocate your resources more effectively. But, in a lot of organizations, these problems have no good solutions (for cultural reasons), and there you might be better off not sharing your estimates if you do them.
URSpider94 14y ago
@akeefer nailed it. This is an essay about why project management is bad, written by someone who it seems like has never actually studied project management. Good planning and estimation is the tool of the worker, not of management. It keeps pointy-haired bosses from coming in and asking "is it done yet?" When done properly, it help justify the number of resources that will be needed to deliver the project on time, and the amount of cash/resources that it will take to complete the project. Good project management results in a not-to-exceed date that is 90% confident (only 10% of projects will exceed this date), so the team has time to tackle unknowns that pop up along the way. And, yes, at the end of the day, project management is a tool for accountability. Like it or not, everyone has to be accountable for their performance at the end of the day, whether as parents, life partners, or employees. Saying that you don't want to be held accountable by some stupid boss is naive and unrealistic.
- freshhawk 14y ago
  "the tool of the worker, not of management" If you have a stereotypical corporate antagonistic divide between workers and management then I completely agree. Good planning and estimation is about managing upwards and managing expectations. If you are in the context that this post was about, with no or very little divide between management and workers, where blame for delays or praise for being ahead of schedule is equally or nearly equally shared among everyone it's quite a good essay imo.
mille562 14y ago
FYI: Flights are on-time if they are within 15 minutes of their scheduled arrival. Arriving 16 minutes early is not an on-time flight.
- MattRogish 14y ago
  "A flight is counted as "on time" if it operated less than 15 minutes later the scheduled time shown in the carriers' Computerized Reservations Systems (CRS). Arrival performance is based on arrival at the gate. Departure performance is based on departure from the gate." http://www.bts.gov/help/aviation/index.html http://www.bts.gov/help/aviation/index.html
meej 14y ago
I'm still reading the essay -- I had to stop and comment about the following paragraph: "This results in folks that think adding more developers to a project at the beginning will allow them to hit an arbitrary date by spreading out the workload. Unfortunately new software doesn’t work this way, either, as the same exponential communication overhead occurs in the beginning, too. You merely end up with a giant mass of incoherent code. And you waste a lot of money employing people who don’t add much value, sitting on the bench waiting for their part of the project to begin." These must be folks who stopped reading The Mythical Man-Month after chapter 2? I would think the following chapter about The Surgical Team would counter such thinking. Unless people are only taking away the lesson about the programmer productivity gap?
mistercow 14y ago
>In machine learning, overfitting generally results from having too much test data or focusing on irrelevant metrics. Huh? Overfitting usually happens when your training set is too small. The size of the test set does not affect overfitting because the test set is, by definition, only used to evaluate the accuracy of the final learned function. In addition, overfitting doesn't happen because of "focusing on irrelevant metrics". It happens because your data set is noisy, or because your learning model is too simplistic to fully model the observed phenomenon (which is known as deterministic noise). If your model focuses on irrelevant metrics, that won't actually be a problem as long as your training set is large enough to reveal their irrelevance. After training, those metrics will not have much bearing on the output function. This misinterpretation of overfitting really hurts the analogy.
- MattRogish 14y ago
  You're right, I had a brain hiccup with respect to the test/training sets (I used it correctly later on). However, it was my understanding that too many attributes can cause overfitting, and the wiki article suggests this, too. Where am I wrong? "Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. " http://en.wikipedia.org/wiki/Overfitting http://en.wikipedia.org/wiki/Overfitting
  - mistercow 14y ago
    > I had a brain hiccup with respect to the test/training sets (I used it correctly later on). Just to be clear, it's not just that you said "test data" instead of "training data", but that you said that too much is a bad thing. More data is always a good thing for ML. [Edit: Actually, there are times where it may not be. If you're doing something like image classification and your data is being created by hand qualitatively, you can actually get overfitting from adding data. As far as I understand, this is because the measurement based on fuzzy perceptual qualities is biased, so the algorithm will overfit to that bias. Maybe this applies with your analogy; I'm not sure.] >"Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. " Well, that's in reference to overfitting as it applies to statistical models, not machine learning. To apply that reasoning to machine learning you have to look at the output of the machine learning algorithm rather than the parameters fed into the algorithm itself. That is, an overfit learned function will often be characterized by excessive complexity, but this is not a result of telling the learning ML algorithm to look at too many parameters. It's a result of telling the ML algorithm to train for too long given the size of its training set. A key point to note is that an overfit function can be excessively complex even based on very few input parameters if it builds the learned function out of overly complex relationships between those parameters. Conversely, it can build a very simple function, even if many of the parameters prove to be irrelevant, by simply not making the learned function depend on those parameters at all.
aut0mat0n1c 14y ago
Using the phrase 'considered harmful' in the title of a blog post is considered harmful
- stcredzero 14y ago
  Comments using the phrase "using the phrase" considered as harmful as comments using the phrase "considered harmful." :)
ljw1001 14y ago
I've spent a fair amount of time criticizing the way estimates are done (for example: http://deathrayresearch.tumblr.com/post/4503505772/the-pathology-of-estimates http://deathrayresearch.tumblr.com/post/4503505772/the-patho...) but although I empathize, this post missed the flight deck completely. First, as other have pointed out, sometimes estimates are needed (If the guys at YouTube finish their work for the Olympics next month, they have a problem.) Second, if people only work on software where there's a clear a 50 to 1 payback (as the post suggests), there would be demand for about 10,000 programmers in the world. Competition forces most companies to fight for small, temporary advantages in their products and for incrementally lower costs with their backend systems. (And this ignores entirely the relationship between time to market and returns. Sometimes software is worth a lot if you could have it today, not so much a year from now.) Third, story points? Not the panacea they're made out to be. I wrote a post on that, too, but one self-referential link is enough for one comment. Finally, if you're not going to estimate a completion date, why estimate at all? The reasons he gives for estimation are actually reasons to spend time on design. Estimation done that way adds nothing.
sharingancoder 14y ago
Agreed! No real point throwing out random estimations instead of actually sitting down and writing the code
drawkbox 14y ago
Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's Law or Parkinson's Law: Work expands so as to fill the time available for its completion. There is always some probability that software estimation is wrong no matter how well planned out. The greater the size/scope, amount of people and the bigger the timeline is the more chance it will be late. Like Valve Time proves (https://developer.valvesoftware.com/wiki/Valve_Time https://developer.valvesoftware.com/wiki/Valve_Time), sometimes product trumps time you put in and making games is hard. Sliding deadlines are the most successful because they take into account reality of changing scope/product during development. Or short task sprints/windows like week long or month long product delivery stretches with complete task freedom in between. Software estimation is hard because there are so many factors and it is a constant ship vs quality balance.
scotty79 14y ago
Perfect system for me as a software developer: 1. When considering what is to be done, ask me to asses how hard it is in points. Also ask me to tag the task with words that I consider important like "database schema change" or "attach legacy system" or "IE7" or "find third party library". You can also ask me about additional things like, what subsystems I think I'll have to touch or source written in what languages I think I'm going to touch. 2. Use the prior knowledge of how long similarly hard, similarly tagged tasks took to guess how long this task will take, but do not tell me that because I'm not really the one that is interested. 3. If I'm given any input from people who want to get this done ask me how it changes hardness of the task and the tags. 4. After the task is done ask me again about same things and update your knowledge according to measured time the task was actually worked on, my initial predictions of initial hardness and tags and my final evaluation of actual hardness and tags and any other information you chose to gather. Worst thing you can do to get an estimate is just ask me how long will it take. I'd rather you, not I make the WAG because then everyone is aware of the fact that it's a WAG.
DanielBMarkham 14y ago
As akeefer pointed out, this was a long rant which finally got to the point: separate effort and scheduling. Take a quick chop at estimating effort, but not in terms of duration/dates on a schedule. Relative size works fine. It's better to take a quick hit at estimation over and over again as you begin to see empirical results than it is to spend a lot of time up-front trying to do the perfect estimate. Software management is not like programming. It's also not like other kinds of management. Any group of people needs some sort of management function. The trick is to put in the most lightweight structure possible. For some reason many technical people of great intelligence, when faced with planning activities, begin to construct various kinds of paper and mathematical wonderlands to live in. We naturally enjoy creating complex models. Don't do that.
emjimenez 14y ago
In a 2001 article, J.P. Lewis demonstrated using the Kolgomorov-Chaitin-Solomonov noncomputability theorem that there are large limits to software Estimation: http://scribblethink.org/Work/kcsest.pdf http://scribblethink.org/Work/kcsest.pdf Algorithmic complexity is not computable, then: 1. Program size and complexity cannot be feasibly estimated a priori. 2. Development time cannot be objectively predicted. 3. Absolute productivity cannot be objectively determined. In fact, Software Estimation methods have an error margin of 100-400% (see Kemerer, C. 1987: An Empirical Validation of Software Cost Estimation Models"). Software Effort Estimation is harmfull because trusting in anything with a 400% margin of error is risky.
gadders 14y ago
As a PM, the other reason developers (or anyone else) doesn't like making estimates: 1) it's hard 2) you are accountable for them No "My dog ate my homework" type excuses, no leaving at 5pm for a week and telling me on the last day your work will be late. When you make an estimate, you are putting your credibility on the line. No-one is 100% perfect, but you should at least give meeting the given dates a solid try. Not "Whoops, didn't make it, can I have another week please?"
- ken 14y ago
  I think there's more to it than that. There are other things I do which are hard, and hold me accountable, but which are not painful in the way that software estimation is. The difference that I see is that software estimation has a third component: lack of control. Every couple days Alice is going to stop by and say "you know we need feature XYZ, too, right?" (which was never in the spec). Then I'm going to overhear at lunch that Bob rewrote the account-management system so I need to rewrite part of my code to integrate with that new interface. And Charlie is going to walk into my office 3 times a day and say "hey, did you see the new video game?". Oh, and this release we're also upgrading to a new version of the foobar library, which works fine for everyone else but mysteriously crashes on my machine, so I spend a day and a half fighting that. I love being held accountable for hard things. (2 quickdraws on the side of the cliff that I need to retrieve? Great! I'm performing a solo next week and I need to get up to speed on something I've never played before? Bring it on!) But only if I'm being held accountable for something I have control over. Accountability - control = pain. See also: traffic jams, delayed flights.

122 points by MattRogish 14y ago

gpcz 14y ago

I'm fascinated to know the author's opinion about Joel Spolsky's "Evidence-Based Scheduling" approach. The author mentions that breaking the schedule into the smallest possible pieces can lead to "overfitting," but Evidence-Based Scheduling uses previous programmer estimates vs. actual time to give a probabilistic schedule that changes with new events. Instead of a rigid ship date, Joel's method can give you a probability of shipping on a given date with the current information. Is Evidence-Based Scheduling still harmful, or is it basically the equivalent of the relative points-based estimation the author brought up at the end of the article?

jacques_chester 14y ago
EBS looks to me like an elaboration of the old-school PERT 3-point estimation technique. By the Laws of Agile, everything invented before 2001 is busted and useless, so I guess EBS would go out with the bathwater for being tainted by association.

abhimishra 14y ago

A good read, and more-or-less in line with my observations from working at a couple big software companies. I think there is generally less value in estimating versus doing, especially for tasks/projects that are inevitable.

logn 14y ago

I think estimation can mostly be forgotten. The planning part which the author identifies is always helpful. Sure, get the team together to plan features and get a feel for the goals. Even get biz analysts together with folks to determine req's. But do we really have to tell you how long it will take? When a lot of managers just take the estimate and multiply by three can these estimates really be trusted? What's the end game? Is it any different than just building it out? If you have a hard set of features then it will get done when it gets done. Just predict what half of what year. If you're an agile enterprise, then timebox the release and build out from there. Why must we all do this absurd dance of time estimating?

sliverstorm 14y ago
The goal is be able to effectively load-balance and prioritize. If something won't take long, for example, it can be deferred (if needed) if it depends on something else that will. Additionally, depending on the market and how important schedule is, it lets you know if the project will be hopelessly late and as a result whether it should be canned.
- mattvanhorn 14y ago
  Any project whose only value comes from being there first is a loser and should be canned before the estimating. "Hey Sergei, Larry says Alta Vista is on track to beat us to market, so lets scrap this search thing and invest in new DRM schemes"
  - btilly 14y ago
    Time to market sensitivity does not always mean "loser". An example that comes to mind (because a story about it was on HN in the last day) is that the first edition of Warcraft was aimed for the 1994 Christmas season. If it had arrived 2 months late, they would have missed that season, and technology improves quickly enough that they would have been unlikely to be as successful if they delivered the same product in the 1995 Christmas season. Do you think that Warcraft is a product that is a loser and should have been canned immediately because they had a schedule that they really needed to deliver it on?
    - j-kidd 14y ago
      That sounds like a weird example. I have never associated the gaming demographics with Christmas shopping.
      - sliverstorm 14y ago
        How about the gaming demographics' parents?

thisisnotmyname 14y ago

There is a great deal of philosophy here, but I'd prefer to see some data that backs up his point. Can you show me a project in which investing in an estimate harmed it?

MattRogish 14y ago
Peopleware, DeMarco and Lister, pg 27-29, alluded to in the post. Namely: "The most surprising part of the 1985 Jeffery-Lawrence study appeared at the very end, when they investigated the productivity of 24 projects for which no estimates were prepared at all. These projects far outperformed all the others..." Study refers to Jeffery and Lawrence, 1985 study, to which I cannot find the raw data, unfortunately.
- MattRogish 14y ago
  I found the study: http://www.sciencedirect.com/science/article/pii/0164121285900068 http://www.sciencedirect.com/science/article/pii/01641212859... Jeffrey, D.R. and M.J. Lawrence, "Managing Programming Productivity", The Journal of Systems and Software 5, (1985), 49-58.

tmurray 14y ago

First, continuous deployment works fine for web projects, but it's not an option if you've got a packaged product that you have to ship at some point. Agile is not a panacea for these environments. It's important to differentiate between the two kinds of software that you can write. This is post is dead-on for developing truly new software (new features, stuff that fundamentally hasn't existed before, etc). However, estimation (even the kind of project-manager-driven estimation that most engineers, myself included, generally hate) can work really well for software where you're doing basically the same thing you've already done in the past such that the risk of unknown unknowns is extremely low. I've seen it in practice, and when you have a checklist of stuff to do that you've already done with very minor changes in the past that can't be automated for whatever reason (e.g., support a new piece of hardware, except that the new piece of hardware is basically the same as the old piece of hardware with very minor well-documented changes), you can estimate with surprisingly good accuracy.

pnathan 14y ago
Yes, but a decent amount of software is doing things that are relatively unique to the time, place, and organization creating it. For those sorts of projects, you might as well use this equation for time to completion: sum of(number of lines in the spec/request * d4)*3 = days to complete.
arohner 14y ago
> continuous deployment works fine for web projects, but it's not an option if you've got a packaged product that you have to ship at some point. Agile is not a panacea for these environments. I think that misses one of the key insights of continuous deployment. The biggest gain in CD is not about actually pushing code to production on every commit, but working as you actually do push to production on every commit. This means that commits are small, contain tests, are delivered frequently and don't break the build. That workflow is a good idea, regardless of the final product or industry. I practice CD (hell, I built a company to do CD), but if I ever had to go back to shipping desktop software or whatever, I'd still practice CD.
jasonhanley 14y ago
What is this "packaged" software you speak of?

btilly 14y ago

He's sometimes right. There are lots of good reasons why you might need software schedule estimation. When you do, there is no point in throwing up your hands and saying, "You can't do that, everybody knows it." Instead get http://www.amazon.com/Software-Estimation-Demystifying-Practices-Microsoft/dp/0735605351/ref=sr_1_1 http://www.amazon.com/Software-Estimation-Demystifying-Pract... and teach yourself how to do it. Why would software estimation matter? For many companies it matters a lot if you can announce something in time for Christmas. Or you might have to hit a deadline for compliance with a legal contract. Or you may be trying to prioritize two different possible products - without a sense of the effort involved you're lacking one of the parameters you need for such an estimation. That doesn't mean that you always estimate. If the value proposition is clear enough, you're going to work on it until you're done and then you will be very happy. But the real world does not usually work like that.

MattRogish 14y ago
"For many companies it matters a lot if you can announce something in time for Christmas." It will be done by xmas or it won't. I don't recommend "no estimation", but intense estimating won't make you hit xmas. Not estimating may give you several weeks that you could be coding. Either way you're takin a mighty big risk when you publicly commit to that. Welcome to hell, population: Dev Team. I've known of no major software project that has a public date that hasn't resulted in major delays, feature cuts, or massive overtime to try and hit that date. "Or you might have to hit a deadline for compliance with a legal contract." That is also a suitably terrible position to be in. I recommend you don't take such contracts. Again, your estimates will be wrong. Even if you spend months doing them. Then you're in the same spot. "Or you may be trying to prioritize two different possible products - without a sense of the effort involved you're lacking one of the parameters you need for such an estimation." Which delivers most business value? I find it farfetched that both are of equal importance.
- swalkergibson 14y ago
  How does this apply in an agency context? I would like to see if this can be applied to my company, but I am a little fuzzy on how this theory can work with paying customers who want to get an idea of cost up front.

dools 14y ago

This is the best article on software I've ever read.

iandanforth 14y ago

The flip side of lie-based estimation is arbitrary deadlines. I'm not the first to notice that work expands to fill the time allotted. There can be real value in setting a hard deadline with almost no regard for difficulty. This eliminates the 'process' overhead and often produces amazing amounts of work in a shorter period of time than anyone would have estimated. I really like working to deadlines because my motivation is inversely correlated to the time till deadline.

freshhawk 14y ago
It might work for you but it's a horrible way to manage people in general. Motivation by arbitrary imposed deadline is a standard dev nightmare isn't it? I've watched two companies destroy themselves with this tactic. Personal motivation and goal setting and even team based motivation and goal setting is important, sure, but you better have other motivation techniques ready when your "hard deadline with almost no regard for difficulty" gets completely missed and the team is depressed and bitter about missing it even after all the effort that was put in. Also, your team isn't stupid (hopefully). So when they bust their asses to hit that deadline and the next day nothing happens, because it was arbitrary, they learn not to listen to your deadlines.
- iandanforth 14y ago
  Good point, I was assuming this was done transparently. In the same way that contests are run, a date is chosen, announced and then met with the full knowledge that pride and perhaps a reward are on the line. Also this can't be the only way you set deadlines as any team would rapidly burn out.
  - freshhawk 14y ago
    Ah, gotcha. That type of push or stretch goal is something different. I've never tried it though, anyone have any experience with this type of motivation?
jacques_chester 14y ago
In one of DeMarco's other books -- I can't now recall if it was PeopleWare or The Deadline -- he explains how arbitrary deadlines come unstuck. Because people learn that they are arbitrary. When the Super Serious Urgent Red Alert All Hands Man Battle Stations deadline whistles by without much more than a frown from management, the team quickly realises that it was total horseshit to begin with. Software engineers are, it has been observed, a smart bunch. If deadlines are being used a "motivational" technique, they are quickly degraded into meaninglessness. Which will hurt the company when an actual hard deadline pops up. Boy who cried "Wolf!" and all that.

X4 14y ago

"The roughness of the fractal dimension of a problem that needs to be solved can be calculated more easily in my opinion than with classical estimation techniques." We're always applying the Roman "divide and conquer" strategy without thinking about it. It wouldn't make sense to apply this, or any other strategy ignorantly! The D&C strategy works because a naive solution to count the fingers in this picture without knowing the fractal dimension is: "divide and conquer". http://mark.rehorst.com/Bug_Photos/fractal_hands_c.jpg http://mark.rehorst.com/Bug_Photos/fractal_hands_c.jpg (mirror: http://i.minus.com/ibz9NsZ6ET32aV.jpg http://i.minus.com/ibz9NsZ6ET32aV.jpg ) I think this is also the reason why some autistic people feel uncomfortable when they don't know each detail of a not yet happened situation in advance. Because communicating the fractal dimension, or "roughness" of a problem or situation is the most time consuming and fragile phase in a project. Here's an article about: "Roughness of fracture surfaces and compressive strength of hydrated cement pastes", which appears to be completely out of topic. But I believe it's nearer to the best estimation technique than other techniques. (Fig. 3) http://www.sciencedirect.com/science/article/pii/S0008884610000311 http://www.sciencedirect.com/science/article/pii/S0008884610... While you may critique that I've not contributed to solving the problem, you may also notice that I've helped to shed some light on the roughness of the problem to be solved :) (Am lazy, it's very late and I'm just back from training to be honest=)

X4 14y ago
Hey cool, I've found a solution :) The Fractal Planning Solution – Jim Stone, PhD. PDF http://www.fractalplanner.com/clear_mind.pdf http://www.fractalplanner.com/clear_mind.pdf He also offers a hosted planning tool. James Theiler has found a formula on estimating the fractal dimension. See Google Doc: http://tinyurl.com/cantjjp http://tinyurl.com/cantjjp

akeefer 14y ago

There are two serious problems with this post, and it really saddens me that I see these sorts of posts so frequently here, with so many concurring voices. First of all, cost absolutely 100% has to factor into prioritization decisions. That doesn't require absolute estimation, but it does demand relative estimation (which he mentions tangentially at the end of the post). If Feature A will deliver $100,000 in revenue but take 18 months and Feature B will deliver $10,000 in revenue but take 1 week, the choice is pretty obvious. What matters is never "return" but always "return on investment." If you don't know anything about the I side of the ROI equation, you're doomed to make bad decisions. With no estimate at all, and just a snarky "it'll take as long as it takes, shut up and let me work" response, you'll inevitably focus on the wrong things. Secondly, many of us do in fact have deadlines, and they're not just total BS. If you have a customer that you're building something for, they have to be able to plan their own schedule, and just telling them "well, maybe we'll ship it to you in 10/2012 or maybe in 6/2013, you'll get it when you get it" doesn't fly. And it's totally reasonable that it doesn't fly: if they have to, say, install the software, or buy hardware to run it on, or train users, or migrate data from an old system, or roll out new products of their own that are dependent on the new system, they clearly can't plan or budget those activities if they have no clue whatsoever when they'll get the new system. And if you do have a deadline, you kind of want to know, to the extent that you can, if you're going to make it or not so you can take corrective action (adding people, cutting scope, pushing the date) if need be. You can't do that if you have no estimates at all. Relative estimation of tasks with empirical measurement of the team's velocity works pretty well; it doesn't work in all cases, but it's pretty much always better than absolutely nothing. There's a huge, huge difference between doing relative point-based estimation and date-driven, pointy-haired-boss estimation, and it's a total disservice to the software community that so many engineers seem to not really understand that difference, and seem to think that the only two options are "unrealistic date-based estimates" and "no estimates." TL;DR - Don't just rant for 3000 words about how estimation is horrible and then add in one sentence about relative estimation. You'll do the world much more good if you just help educate people how to do things the right way and spare the ranting.

five18pm 14y ago
You took the words out of me. Even if there are no external customers waiting for the release, a business' other departments have to plan their activities. When will marketing start their pre-release activities without engineering's estimates? When will sales start talking to customers about the new release? There is just too many things that need engineering's estimates.

arkitaip 14y ago

So what do you do as a freelancer working on projects that last weeks or months? Tell your clients to go screw themselves, that you'll be ready when you're ready?

mbell 14y ago
You tell them to define a minimal feature set, and impose that it is actually minimal. This feature set you estimate and give a hard deadline on. Then you tell them that you will iterate based on feedback and add features as directed until such a time as they choose to stop paying you. There is no such thing as "done" in software development.
- jasonhanley 14y ago
  'There is no such thing as "done" in software development.' Exactly! That's what makes it so different from physical world projects. You can keep adding/changing things forever.

tmoertel 14y ago

Software effort estimation causes three problems. First, most estimation processes model the uncertainty about the effort required for tasks but fail to model the uncertainty about the tasks themselves, leading to unreliable estimates. Second, people are overly confident of the estimates, in any case, because the estimation process looks impressive and produces impressive looking artifacts. Third, the estimation artifacts obscure the coupling between the stakeholders and the implementers by not transmitting how the one group’s decisions affect the other; the estimates, in effect, form a barrier that makes it harder for people on opposites sides of the estimates to take shared responsibility for business goals. If you understand these problems and can solve them for your projects, estimation can help you to make better decisions and to allocate your resources more effectively. But, in a lot of organizations, these problems have no good solutions (for cultural reasons), and there you might be better off not sharing your estimates if you do them.

URSpider94 14y ago

@akeefer nailed it. This is an essay about why project management is bad, written by someone who it seems like has never actually studied project management. Good planning and estimation is the tool of the worker, not of management. It keeps pointy-haired bosses from coming in and asking "is it done yet?" When done properly, it help justify the number of resources that will be needed to deliver the project on time, and the amount of cash/resources that it will take to complete the project. Good project management results in a not-to-exceed date that is 90% confident (only 10% of projects will exceed this date), so the team has time to tackle unknowns that pop up along the way. And, yes, at the end of the day, project management is a tool for accountability. Like it or not, everyone has to be accountable for their performance at the end of the day, whether as parents, life partners, or employees. Saying that you don't want to be held accountable by some stupid boss is naive and unrealistic.

freshhawk 14y ago
"the tool of the worker, not of management" If you have a stereotypical corporate antagonistic divide between workers and management then I completely agree. Good planning and estimation is about managing upwards and managing expectations. If you are in the context that this post was about, with no or very little divide between management and workers, where blame for delays or praise for being ahead of schedule is equally or nearly equally shared among everyone it's quite a good essay imo.

mille562 14y ago

FYI: Flights are on-time if they are within 15 minutes of their scheduled arrival. Arriving 16 minutes early is not an on-time flight.

MattRogish 14y ago
"A flight is counted as "on time" if it operated less than 15 minutes later the scheduled time shown in the carriers' Computerized Reservations Systems (CRS). Arrival performance is based on arrival at the gate. Departure performance is based on departure from the gate." http://www.bts.gov/help/aviation/index.html http://www.bts.gov/help/aviation/index.html

meej 14y ago

I'm still reading the essay -- I had to stop and comment about the following paragraph: "This results in folks that think adding more developers to a project at the beginning will allow them to hit an arbitrary date by spreading out the workload. Unfortunately new software doesn’t work this way, either, as the same exponential communication overhead occurs in the beginning, too. You merely end up with a giant mass of incoherent code. And you waste a lot of money employing people who don’t add much value, sitting on the bench waiting for their part of the project to begin." These must be folks who stopped reading The Mythical Man-Month after chapter 2? I would think the following chapter about The Surgical Team would counter such thinking. Unless people are only taking away the lesson about the programmer productivity gap?

mistercow 14y ago

>In machine learning, overfitting generally results from having too much test data or focusing on irrelevant metrics. Huh? Overfitting usually happens when your training set is too small. The size of the test set does not affect overfitting because the test set is, by definition, only used to evaluate the accuracy of the final learned function. In addition, overfitting doesn't happen because of "focusing on irrelevant metrics". It happens because your data set is noisy, or because your learning model is too simplistic to fully model the observed phenomenon (which is known as deterministic noise). If your model focuses on irrelevant metrics, that won't actually be a problem as long as your training set is large enough to reveal their irrelevance. After training, those metrics will not have much bearing on the output function. This misinterpretation of overfitting really hurts the analogy.

MattRogish 14y ago
You're right, I had a brain hiccup with respect to the test/training sets (I used it correctly later on). However, it was my understanding that too many attributes can cause overfitting, and the wiki article suggests this, too. Where am I wrong? "Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. " http://en.wikipedia.org/wiki/Overfitting http://en.wikipedia.org/wiki/Overfitting
- mistercow 14y ago
  > I had a brain hiccup with respect to the test/training sets (I used it correctly later on). Just to be clear, it's not just that you said "test data" instead of "training data", but that you said that too much is a bad thing. More data is always a good thing for ML. [Edit: Actually, there are times where it may not be. If you're doing something like image classification and your data is being created by hand qualitatively, you can actually get overfitting from adding data. As far as I understand, this is because the measurement based on fuzzy perceptual qualities is biased, so the algorithm will overfit to that bias. Maybe this applies with your analogy; I'm not sure.] >"Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. " Well, that's in reference to overfitting as it applies to statistical models, not machine learning. To apply that reasoning to machine learning you have to look at the output of the machine learning algorithm rather than the parameters fed into the algorithm itself. That is, an overfit learned function will often be characterized by excessive complexity, but this is not a result of telling the learning ML algorithm to look at too many parameters. It's a result of telling the ML algorithm to train for too long given the size of its training set. A key point to note is that an overfit function can be excessively complex even based on very few input parameters if it builds the learned function out of overly complex relationships between those parameters. Conversely, it can build a very simple function, even if many of the parameters prove to be irrelevant, by simply not making the learned function depend on those parameters at all.

aut0mat0n1c 14y ago

Using the phrase 'considered harmful' in the title of a blog post is considered harmful

stcredzero 14y ago
Comments using the phrase "using the phrase" considered as harmful as comments using the phrase "considered harmful." :)

ljw1001 14y ago

I've spent a fair amount of time criticizing the way estimates are done (for example: http://deathrayresearch.tumblr.com/post/4503505772/the-pathology-of-estimates http://deathrayresearch.tumblr.com/post/4503505772/the-patho...) but although I empathize, this post missed the flight deck completely. First, as other have pointed out, sometimes estimates are needed (If the guys at YouTube finish their work for the Olympics next month, they have a problem.) Second, if people only work on software where there's a clear a 50 to 1 payback (as the post suggests), there would be demand for about 10,000 programmers in the world. Competition forces most companies to fight for small, temporary advantages in their products and for incrementally lower costs with their backend systems. (And this ignores entirely the relationship between time to market and returns. Sometimes software is worth a lot if you could have it today, not so much a year from now.) Third, story points? Not the panacea they're made out to be. I wrote a post on that, too, but one self-referential link is enough for one comment. Finally, if you're not going to estimate a completion date, why estimate at all? The reasons he gives for estimation are actually reasons to spend time on design. Estimation done that way adds nothing.

sharingancoder 14y ago

Agreed! No real point throwing out random estimations instead of actually sitting down and writing the code

drawkbox 14y ago

Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's Law or Parkinson's Law: Work expands so as to fill the time available for its completion. There is always some probability that software estimation is wrong no matter how well planned out. The greater the size/scope, amount of people and the bigger the timeline is the more chance it will be late. Like Valve Time proves (https://developer.valvesoftware.com/wiki/Valve_Time https://developer.valvesoftware.com/wiki/Valve_Time), sometimes product trumps time you put in and making games is hard. Sliding deadlines are the most successful because they take into account reality of changing scope/product during development. Or short task sprints/windows like week long or month long product delivery stretches with complete task freedom in between. Software estimation is hard because there are so many factors and it is a constant ship vs quality balance.

scotty79 14y ago

Perfect system for me as a software developer: 1. When considering what is to be done, ask me to asses how hard it is in points. Also ask me to tag the task with words that I consider important like "database schema change" or "attach legacy system" or "IE7" or "find third party library". You can also ask me about additional things like, what subsystems I think I'll have to touch or source written in what languages I think I'm going to touch. 2. Use the prior knowledge of how long similarly hard, similarly tagged tasks took to guess how long this task will take, but do not tell me that because I'm not really the one that is interested. 3. If I'm given any input from people who want to get this done ask me how it changes hardness of the task and the tags. 4. After the task is done ask me again about same things and update your knowledge according to measured time the task was actually worked on, my initial predictions of initial hardness and tags and my final evaluation of actual hardness and tags and any other information you chose to gather. Worst thing you can do to get an estimate is just ask me how long will it take. I'd rather you, not I make the WAG because then everyone is aware of the fact that it's a WAG.

DanielBMarkham 14y ago

As akeefer pointed out, this was a long rant which finally got to the point: separate effort and scheduling. Take a quick chop at estimating effort, but not in terms of duration/dates on a schedule. Relative size works fine. It's better to take a quick hit at estimation over and over again as you begin to see empirical results than it is to spend a lot of time up-front trying to do the perfect estimate. Software management is not like programming. It's also not like other kinds of management. Any group of people needs some sort of management function. The trick is to put in the most lightweight structure possible. For some reason many technical people of great intelligence, when faced with planning activities, begin to construct various kinds of paper and mathematical wonderlands to live in. We naturally enjoy creating complex models. Don't do that.

emjimenez 14y ago

In a 2001 article, J.P. Lewis demonstrated using the Kolgomorov-Chaitin-Solomonov noncomputability theorem that there are large limits to software Estimation: http://scribblethink.org/Work/kcsest.pdf http://scribblethink.org/Work/kcsest.pdf Algorithmic complexity is not computable, then: 1. Program size and complexity cannot be feasibly estimated a priori. 2. Development time cannot be objectively predicted. 3. Absolute productivity cannot be objectively determined. In fact, Software Estimation methods have an error margin of 100-400% (see Kemerer, C. 1987: An Empirical Validation of Software Cost Estimation Models"). Software Effort Estimation is harmfull because trusting in anything with a 400% margin of error is risky.

gadders 14y ago

As a PM, the other reason developers (or anyone else) doesn't like making estimates: 1) it's hard 2) you are accountable for them No "My dog ate my homework" type excuses, no leaving at 5pm for a week and telling me on the last day your work will be late. When you make an estimate, you are putting your credibility on the line. No-one is 100% perfect, but you should at least give meeting the given dates a solid try. Not "Whoops, didn't make it, can I have another week please?"

ken 14y ago
I think there's more to it than that. There are other things I do which are hard, and hold me accountable, but which are not painful in the way that software estimation is. The difference that I see is that software estimation has a third component: lack of control. Every couple days Alice is going to stop by and say "you know we need feature XYZ, too, right?" (which was never in the spec). Then I'm going to overhear at lunch that Bob rewrote the account-management system so I need to rewrite part of my code to integrate with that new interface. And Charlie is going to walk into my office 3 times a day and say "hey, did you see the new video game?". Oh, and this release we're also upgrading to a new version of the foobar library, which works fine for everyone else but mysteriously crashes on my machine, so I spend a day and a half fighting that. I love being held accountable for hard things. (2 quickdraws on the side of the cliff that I need to retrieve? Great! I'm performing a solo next week and I need to get up to speed on something I've never played before? Bring it on!) But only if I'm being held accountable for something I have control over. Accountability - control = pain. See also: traffic jams, delayed flights.