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Ahhhw, every time is so frustrating..
We have a dedicated server in our hosting company, and everytime i have to write down a new app (or an add to an pre-existing app), i use to 'lose' some time to optimize the code for many behaviors (reducing the db query, optimizing the db structure, reducing the bandwith, etc..) depending on what the app is supposed to do.
Obviously, is the point is not that i write bad code and then rebuild it, its just that after the project is complete, i allways find somethings that could be done better.
And everytime, if my boss catch me doing this, he say 'Your wasting your time! if the application need more resources, we buy more RAM, more CPU, or more bandwith!'.
What is the best (and simplyest) way to explain he that optimization is still important, and that is not so easy or automagically upgrating the hardware of an (production!) server?
EDIT: im not talking just about database optimization, but every aspect of an application
Chances are you are really wasting time. Most of the optimizations that you learn in college or university are sort of irrelevant in the business world. I recommend concentrating on those optimizations where you can quantify WHY your optimization is worth your company's money (your time spent is their money spent).
When trying to optimise code you need to follow the optimisation cycle. There are no short-cuts.
Define specific, detailed, measurable, performance requirements.
Measure your application's performance.
If it meets the requirements, stop, as continuing is a waste of time/money.
Determine where the bottleneck is (which machine? CPU, memory, disk, etc.?).
Fix the bottleneck (either hardware or software fix, whichever is faster/cheaper).
Go to 2.
From your post it doesn't sound like you have done 1 or 2, so you've skipped over 3 and 4 because you don't know enough to do them, and are now stumbling blindly around in 5 attempting to optimise whatever you think needs optimising.
So from what you've said I'd have to agree with your boss. You are wasting your time. Or at least you haven't followed enough process to prove otherwise, which is essentially the same thing.
Keep detailed notes and time sheets the next time you make a server move/upgrade, and protocol every minute of work that arose from it (including things in the weeks after). Then you'll have hard evidence that upgrading is expensive, and optimizations help delay the investment.
In the current situation, you might be able to do something with benchmarks and statistics along the line of "without my optimization, the server will be at 90% capacity with X number of users. With my optimization, we can cater for Y users more, before we have to get a new machine."
On the other hand, the line between optimization and over-optimization is thin. While writing code that doesn't waste resources is good craftsmanship and should be a human right, RAM and disk space are awfully cheap these days. Optimizations also tend to make code more complicated, and harder to maintain for others. When you control your own hardware, code optimization may not always be the top goal.
Do you have performance objectives for the application(s)? Free capacity, response time, bandwidth usage etc. Without them you will find it difficult to justify why an improvement needs to be made. You need to be able to quantify the problem before people will spend money on it.
If the application is already meeting the requirements then your boss is probably right.
To ensure reserve capacity for future customers you (and your boss) could set a threashold such that once performance comes within a percentage of the requirements you need to investigate the problem. This is the time for you to request/push/negociate for performing optimisations as he will be aware of the problem and the risk of doing nothing. If you can recommend some changes to correct the problem that will cost less than the hardware then hopefully he should agree to let you do it. Of course the reverse still applies. If the total cost of the hardware upgrade is cheaper then that is probably the better option.
Wait until buying RAM and CPU becomes more expensive than paying you to optimize the code. Then you have a case.
There's a break even point between improving software vs. improving hardware. For desktop systems, a good threshold is by purchase time:
If that machine fails, can you go to the next mall and buy a replacement within an hour?
As long as you can answer yes, optimization is futile - an investment into the future maybe, but is that really your decision alone?
A similar rule for web sites might be "how long would it take to get a new hosting contract on that?"
This isn't perfect, it covers just a single aspect of scalability. I like it because it's an easy to understand aspect outside of technical concerns.
Of course, you should have more material if that aspect suddenly gets brushed away. It helps to just ask what are the companies/bosses plans for a few key scenarios. - e.g. what contingency plans for DDOS attacks, for "rush events" etc. Having some data to back that up, some key stories ("company foo was mentioned on popular night show, web server broke down under requests, business lost, potential customers angered") helps a lot.
The key to realize is that (assuming from your description alone) it is your responsibility to forsee such events, and provide the technical solutions, but it's not your responsibility to mke these decisions.
Also, getting a written statement from your boss that "five hours downtime isn't a problem, get bck to work on the important things!" is a good CYA.
about the same way one would explain a developer that code/resources optimization is unimportant ...
i guess this problem arises because your way to measure importance is different than his ...
his job is to care about money and make sure he gets the "most" out of it ... and frankly, servers are cheaper than developers ... and managed servers are cheaper than admins ... and the ugly truth is, that many people think that way ... personally, I think PHP isn't really the right choice for performance-critical parts of an app ... neither are RMDBSs ... but nearly every managed server runs PHP and MySQL and business clients prefer to have an app they can run everywhere, based on a technology widely known, which turns out to be PHP and MySQL on the server side ... the world is a cruel place and the truth is ugly ... now when it comes to you, you have only 2 choices:
live with it
work with people who are more like you, and who share the same ambitions
your boss does the job right, from his perspective ... what you do is a waste of company money, because the company's goal is not to write beautiful and highly optimized code ... whatever your company does, in the end you only provide a tool ... and the value of a tool is measured by the use it provides in relation to the money it costs ...
if your optimizations were economically reasonable, then the easiest way would be not to optimize anymore and wait for the moment until your boss comes to you, asking for speedup ...
i suggest, you either look for a new job, or focus on other important things:
good design and use of best practices such as KISS, DRY, SOLID and GRASP
scalable architecture (doesn't mean you have to actually implement it, just have an idea how the whole thing could scale well)
maintainability, including readability and good documentation
flexibility & extensibility
robustness & correctness
do not reinvent the wheel and use the right tools for a job - use adequate technologies, libraries and frameworks
fast developement
these goals are important for the present and the future of a software project (also when it comes to money (especially the bold ones)) ... and they provide the possibility of doing optimization when actually needed ...
this probably isn't the answer you wanted, but I hope it helps ...
Optimizing is often really just a waste of time, what is more important is optimizing for maintainability:
- keep the code simple (see: KISS)
- move duplicate code into functions (see: DRY)
- optimize comments (as few comments as possible, as many as necessary)
- remove unused code
Those changes do not necessarily affect the speed of the program but they reduce the time needed to implement changes and fix bugs so they have real business value as they save expensive developer time.
If you're having to explain why there is a need for optimisation, then you're already on a low-win-rate path. Unfortunately, the best argument is when there is a situation where performance is becoming a noticeable problem (e.g. customers complaining) - this makes people sit up and listen if they're getting constant ear-ache about it. Often, the solution can be that throwing hardware at it is the best/cheapest solution.
However for me, performance is important, when working on highly scalable systems, you need to spend time on optimisations. It should at the very least be on your mind while you're developing and a lot of things can be swallowed up in the dev process (as opposed to after you've finished, then going back to optimise).
e.g.
- What happens if my database has 100,000,000 records instead of 100,000? (you can easily fool SQL Server into thinking there are more records in a table than there actually are to see what the effect on the execution plan would be).
If you're being pro-active about optimisation (which I personally think is good), then you need to try and come with a real-world meaning to your boss. e.g. "if we optimise our site by cutting down the page size, we could save x amount of bandwidth a month, saving us xx much money".
You do have to be careful about micro-optimisations though as you can micro-optimise until the cows come home, for much lower benefit.
You could just wait until your boss says "Why is it taking so long?" Then you could say "Hey, boss, we could buy 10 times as much hardware, or I could spend a couple days and make it 10 times faster". Here's an example.
Added: If your boss says "Well, why did you make it slow in the first place?" I would have no trouble explaining that he could hire God's Right Hand Programmer, and the code as first written would still have room for optimizing.
If you are on a relational database (and your not working with trivial applications).... you cannot afford to write bad database queries. Since you are you using a red-gate tag I assume you are on SQL server. If you design a bad schema (including queries) on SQL Server a database server when you start getting moderate traffic you will be forced to scale in horrendous ways. Once you get a high level of traffic you will be screwed -- and will need to hire a very expensive consultant/DBA to undo the mess -- use this argument with your boss :D.
What I am trying to get at is even though SQL is declarative and it doesn't appear that you have to pay attention to performance -- it doesn't really work that way. You have to design your data model by keeping in mind the way it is going to be used.
If you are writing business logic in application code ... well that doesn't matter much -- you can fix that latter with less trouble if performance becomes an issue. Most business logic these days is stateless (especially if its web-based or web-service based) meaning you can just chuck more machines at the problem -- if it's not than its just a bit harder.
Every time something takes long than it would have if the refactoring had been done ahead of time make sure your boss hears about it.
IMO, It's less a case of convincing that optimizations need to be done (and based on your Boss's responses, you're not going to win this fight), and more a case of always building in refactoring time into your estimates.
Do a cost analysis...
This will take me X hours and will mean every project needs 50% less data storage. Based on us doing 2 projects a year using on average 100Gb space, that will save $Y after a year, $Z after 3 years.
Crude example but it suffices.
Ultimately you and your boss are both wrong... you think code has to be fast (primarily) to satisfy your idealism, he doesn't care at all as he wants to deliver products.
Let's say you have a project that will involve two web applications (that will share DAL/DAO/BO assemblies and some OSS libraries):
a semi complex management application that uses Windows Live ID for authentication and is also capable of communicating with various notifier services (email, sms, twitter etc.), targeted notifiers being about 10% of functionality
a low to semi complex user application with less functionality but more robustness that also uses Windows Live ID for authentication
There are two of us with medium estimation capabilities and we won't be able to do it in two days even if we wanted/have to. At least it would be a far off estimate.
Questions
How long would/does it normally take you to make a reliable/valuable estimate?
What would you suggest to speed-up estimation without sacrificing accuracy?
How much slack (in terms of cost/time) would you add depending on estimation speed (when you would say: I could estimate it a bit more, because I think it's still quite off)
Since we use Agile methods (Scrum, specifically) it takes us about an hour longer than it takes the users to prioritize.
More time doesn't lead to more accuracy.
The hard part, then, is getting the users to prioritize. We hear this discussion all the time "if the whole thing isn't completed on time, it's all worthless." "Except for the XYZZY component, which does have some value." That argument can go on for hours until it's resolved that XYZZY should be first.
Generally, we try to create 4-week sprints. The first few are complicated because there's always something new. After the first two (or three) we seem to set a steady pace.
Each use case has a relatively simple, subjective valuation of how the effort it will take to finish it. Anything over one full sprint in duration has to be decomposed. Most times a few use cases are bundled into a single sprint.
The are formal ways of scoring each use case to better handle the cost and schedule issues. We don't use them because the extra effort doesn't help.
After the first two sprints,
There's new and different functionality,
The priorities have all changed,
The details of each use case have been dramatically revised.
What does "accuracy" mean when the thing you're trying to estimate changes at the end of each sprint?
One lesson learned. Parts of my company spend a long time fully defining exactly what will be delivered, and then measuring that they are delivering precisely what they want.
Customers notice this, and one said we "spend a lot of time delivering what the contract says, but it isn't what we needed."
The problem with firm up-front estimates is that they take on a life of their own. The more you "invest" in the estimating, the more the estimates seem to be a useful deliverable. They aren't useful because they're generally totally wrong. They're based on up-front assumptions that are totally wrong.
It's a bad policy to invest more time in estimating. The "accurate" answers aren't more accurate, but they are more treasured by every layer of management. As you and the customer learn, you invalidate numerous assumptions and you absolutely must re-estimate constantly.
Don't do it up front. If your contract requires you to do it up front, then make sure you have a change control provision and tell the customer that you absolutely will make changes as you go forward. As both you and the customer learn, you both must make changes.
Interesting question. I'm afraid the answer is "it really depends!" I know that's not terribly useful (although it IS true) so here are some factors:
1) Quality and completeness of requirements and their specification. This is, to me, most often the project-estimate killer. If you don't have quality requirements, you have no reasonable basis for an estimate. We use a "RUP-lite" style of product development here, so as the engineering manager I won't give anything but the coarsest-grain estimate until we've completed our "elaboration" phase and gotten sign-off from product management that the core 80% of the product features are in fact accurately covered.
2) The scope & nature of the product. Bigger/more expensive/more complicated = substantially longer to estimate. I've spent years working in telco-carrier land delivering solutions which have the normal robust carrier requirements ("5 9's" of uptime required by SLA mean you must really do a good job of solution design and failure recovery!). In that sort of environment with all the moving parts across functional areas of the business, the estimation of work is going to hinge on getting the whole picture...specifically, cross-functional dependencies and external dependencies can be a REAL killer here. That said, I've also built lots of shrink-wrapped and enterprise software, too. In those environments it's much easier as the scope is typically substantially smaller, so thus easier to estimate.
3) How "new" is this project? How "new" is the team to this product or technology set? The newer the product or team, the longer and more buffer you should allocate.
4) How specific do we need to be? If this is a "rough guess" then I'll lean on my engineering leads to provide a conservative estimate, then I'll pad that. If we need a "real" estimate (e.g., one which is used by my boss and which I'll be responsible for hitting), I'd need the input from a number of different managers and team members, who will need time to analyze the requirements and confer amongst themselves.
That can take as little as a couple days, or weeks..it all depends on the size. "Two or three days" is, frankly, not long enough for sizing anything but the most trivial of projects.
The best thing you can do to improve the quality of your estimates to to improve the quality of your requirements, and be ruthless in identifying hidden dependencies.
One final thing: FWIW, I've been doing this since '81 and I regard accurately estimating a project's duration/cost as the single most difficult/fraught with peril part of engineering management.
To make a reliable estimate you really would need to create a list of tasks to be done. Break it down into stories/tasks (even if you don't use agile) and evaluate them. This can take a lot of time already - especially the amount of research (to look for libraries to do this notifier stuff to reduce the cost). I would take at least 3 days - however 1-2 week(s) sound more reasonable for me. This doesn't seem to be a small project.
I wouldn't dare to speed-up the estimation process if you wan't to have somewhat reasonable results. Estimations are never accurate and you will just make things worse.
An option would be to make a totally rough guess within a few hours and then start to work on it already (for a week or so). At the end of the week you might be able to give a better estimation based on your current progress. However it's important to create a good prototype (which looks like crap but has a little bit of code in all of the regions).
Well, a common quote is "The price will be between 50% and 400% of our initial estimates". The reason that this quote has grown large is that it's true. Estimation accuracy largely depends on your domain-knowledge. If this is the 100th time you sold a given type of blog-engine than you're pretty sure about the estimates. However, more often than not, you don't have that indepth knowledge of the domain (If the app already exists, why create a new one?).
Agile development has become popular because people largely recognize that the traditional "waterfall" type of thinking just doesn't work for most real-world projects. You should apply the same way of thinking to your estimates. Obviously, you need some kind of selling point, but be sure to tell your customers that this information is very vague (and that no matter what any competitor will tell them, their estimates are vague as well).
You need to sell iterations, and therefore also estimate iterations. I'm sure some marketing-guy in any company will know how to handle the paperwork and the legal stuff for this, so it shouldn't be that big a deal.
Consider a 5 iterations project:
Start out by putting up milestones. These are subject to change, but will provide your vargue first estimates for the final product.
Plan iteration #1.
Estimate iteration #1, adjust total estimates accordingly.
Do iteration #1
Rinse / repeat till iteration #5
You're done :)
Reflect over your project. How did your estimates evolve? Reasons? Learn by doing :)
Most customers would rather have part-estimates and part-deliverances than some unrealistic goal that some suit sold them :)
Straying slightly from your original question but it's also important to learn from the estimates that you have produced in the past by keeping information about how long it actually took to do the things that you estimated.
We estimated 5 days to produce these pages, it actually took 10 days, and etc.
In the long term information like this will (hopefully!) enable you to produce more accurate estimates.
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I am looking after some ways to measure the performance of a software development team. Is it a good idea to use the build tool? We use Hudson as an automatic build tool. I wonder if I can take the information from Hudson reports and obtain from it the progress of each of the programmers.
The main problem with performance metrics like this, is that humans are VERY good at gaming any system that measures their own performance to maximize that exact performance metric - usually at the expense of something else that is valuable.
Lets say we do use the hudson build to gather stats on programmer output. What could you look for, and what would be the unintended side effects of measuring that once programmers are clued onto it?
Lines of code (developers just churn out mountains of boilerplate code, and other needless overengineering, or simply just inline every damn method)
Unit test failures (don't write any unit tests, then they won't fail)
Unit test coverage (write weak tests that exercise the code, but don't really test it properly)
Number of bugs found in their code (don't do any coding, then you won't get bugs)
Number of bugs fixed (choose the easy/trivial bugs to work on)
Actual time to finish a task based against their own estimate (estimate higher to give more room)
And it goes on.
The point is, no matter what you measure, humans (not just programmers) get very good at optimizing to meet exactly that thing.
So how should you look at the performance of your developers? Well, that's hard. And it involves human managers, who are good at understanding people (and the BS they pull), and can look at each person subjectively in the context of who/where/what they are to figure out if they are doing a good job or not.
What you do once you've figured out who is/isn't performing is a whole different question though.
(I can't take credit for this line of thinking. It's originally from Joel Spolsky. Here and here)
Do NOT measure the performance of each individual programmer simply using the build tool. You can measure the team as a whole, sure, or you can certainly measure the progress of each programmer, but you cannot measure their performance with such a tool. Some modules are more complicated than others, some programmers are tasked with other projects, etc. It's not a recommended way of doing this, and it will encourage programmers to write sloppy code so that it looks like they did the most work.
No.
Metrics like that are doomed to failure. Different people work on different parts of the code, on different classes of problem, and absolute measurements are misleading at best.
The way to measure developer performance is to have excellent managers that do their job well, have good specs that accurately reflect requirements, and track everyone's progress carefully against those specs.
It's hard to do right. A software solution won't work.
I think this needs a very careful approach when deciding the ways to measure developers performance as most the traditional methods such as line of codes, number of check ins, number of bugs fixed etc. are proven to be subjective with todays software engineering concepts. We need to value team performance approach rather measuring individual KPIs in a project. However working in commercial development environment its important to keep a track and a close look at following factors of individual developers;
Code review comments – Each project, we can decide the number of code reviews need to be conducted for a given period. Based on the code reviews individuals get remarks about their coding standard improvements. Recurring issues of code reviews of same individual’s code needs to be brought in to attention. You can use automated code reviews tools or manual code reviews.
Test coverage and completeness of tests. – The % covered needs to be decided upfront and if certain developer fails to attempt it often, it needs to be taken care of.
Willingness to sign in to complex tasks and deliver them without much struggle
Achieving what’s defined as “Done” in a user story
Mastery level of each technical area.
With agile approach in some of the projects, the measurements of the development team and the expected performance are decided based on the releases. At each release planning there are different ‘contracts’ negotiated with the team members for the expected performance. I find this approach is more successful as there is no reason of adhering to UI related measurements in a release where there is a complex algorithm to be released.
I would NOT recommend using build tool information as a way to measure the performance / progress of software developers. Some of the confounding problems: possibly one task is considerably harder than another; possibly one task is much more involved in "design space" than "implementation space"; possibly (probably) the more efficient solution is the better solution, but that better solution contributes less lines of code than a terribly inefficient one which provides many many more lines of code; etc.
Speaking of KPI in software developers. www.smartKPIs.com may be a good resource for you. It contains a user friendly library of well-documented performance measures. At the moment it lists over 3300 KPI examples, grouped in 73 functional areas, as well as 83 industries and sub-categories.
KPI examples for the software developers are available on this page www.smartKPIs.com - application development They include but not limited to:
Defects removal efficiency
Data redundancy
In addition to examples of performance measures, www.smartKPIs.com also contains a catalogue of performance reports that illustrate the use of KPIs in practice.
Examples of such reports for information technology are available on: www.smartKPIs.com - KPIs in practice - information technology
The website is updated daily with new content, so check it from time to time for additional content.
Please note that while examples of performance measures are useful to inform decisions, each performance measure needs to be selected and customized based on the objectives and priorities of each organisation.
You would probably do better measuring how well your team tracks to schedules. If a team member (or entire team) is consistantly late, you will need to work with them to improve performance.
Don't short-cut or look for quick and easy ways to measure performance/progress of developers. There are many many factors that affect the output of a developer. I've seen alot of people try various metrics ...
Lines of code produced - encourages developers to churn out inefficient garbage
Complexity measures - encourages over analysis and refactoring
Number of bugs produced - encourages people to seek out really simple tasks and to hate your testers
... the list goes on.
When reviewing a developer you really need to look at how good their work is and define "good" in the context of what the comany needs and what situations/positions the company has put that indivual in. Progress should be evaluated with equal consideration and thought.
There are many different ways of doing this. Entire books written on the subject. You could use reports from Hudson but I think that would lead to misinformation and provide crude results. Really you need to have task tracking methodology.
Check how many lines of the codes each has written.
Then fire the bottom 70%.. NO 90%!... EVERY DAY!
(for the folks that aren't sure, YES, I am joking. Serious answer here)
We get 360 feedback from everyone on the team. If all your team members think you are crap, then you probably are.
There is a common mistake that many businesses make when setting up their release management tool. The Salesforce release management toolkit is one of the best ones available in the market today, but if you do not follow the vital steps of setting it up, you will definitely have some very bad results. You will get to use it but not to its full capacity. Establishing release management processes in isolation from the business processes is one of the worst mistakes to make. Release management tools go hand in hand with the enterprise strategy, objectives, governance, change management plus some other aspects. The processes of release management need to be formed in such a way that everyone in the business is on the same page.
Goals of release management
The main goal of release management is to have a consistent set of reliable and repeatable processes that are resource independent. This enables the achievement of the most favorable business value while at the same time optimizing the utilization of resources available. Considering that most organizations focus on running short, high-yield business projects, it is essential for optimization of the delivery value chain of the application to make certain that there are no holdups in the delivery of the business value.
Take for instance the force.com migration toolkit, as this tool has proven to be great in governance. A release management tool should allow for optimal visibility and accountability in governance.
Processes and release cycles
The release management processes must be consistent for the whole business. It is necessary to have streamlined and standardized processes across the various tool users. This is because they will be using the same platform and resources that enable efficient completion of their tasks. Having different processes for different divisions of your business can lead to grievous failures in tool management. The different sets of users will need to have visibility into what the others are doing. As aforementioned, visibility is of great importance in any business process.
When it comes to the release cycles, it is also imperative to have one centralized system that will track all the requirements of the different sets of users. It is also necessary to have this system centralized so that software development teams get insight into the features and changes requested by the business. Requests have to become priorities to make sure that the business gets to enjoy maximum benefit. Having a steering team is important because it is involved in the reviewing of business requirements plus also prioritizing the most appropriate changes that the business needs to make.
The changes that should happen to the Salesforce system can be very tricky and therefore having a regular meet up between the business and IT is good. This will help to determine the best changes to make to the system that will benefit the business. By considering the cost and value of implementing a feature, the steering committee has the task of deciding on the most important feature changes to make.
Here also good research http://intersog.com/blog/tech-tips/how-to-manage-millennials-on-software-development-teams
This is an old question but still, something you can do is borrow Velocity from Agile Software Development, where you assign a weight to each task and then you calculate how much "weight" you solve in each sprint (or iteration or whatever DLC you use). Of course this comes in hand with the fact that, like a commenter mentioned before, you need to actively keep track yourself of whether your developers are working or chatting online.
If you know your developers are working responsively, then you can rely on that velocity to give you an estimate of how much work the team can do. If at any iteration this number drops (considerably), then either it was poorly estimated or the team worked less.
Ultimately, the use of KPIs together with velocity can give you per-developer (or per-team) insights on performance.
Typically, directly using metrics for performance measurement is considered a Bad Idea, and one of the easy ways to run a team into the ground.
Now, you can use metrics like % of projects completed on-time, % of churn as code goes toward completion, etc...it's a wide field.
Here's an example:
60% of mission-critical bugs were written by Joe. That's a simple, straightforward metric. Fire Joe, right?
But wait, there's more!
Joe is the Senior Developer. He's the only guy trusted to write ultra-reliable code, every time. He's written about 80% of the mission-critical software, because he's the best.
Metrics are a bad measurement of developers.
I would share my experience and how I learnt a very valuable process on measuring the team performance. I must admit, I have fallen on tracking KPI simply because most of the departments would do the same but not really for the insight until I had the responsibility to evaluate developers performance where after a number of reading I evolved with the following solution.
One every project, I would entertain the team in a discussion on the project requirements and involve them so everyone knows what is to be done. In the same discussion through collaboration we would break the projects in to tasks and weight those tasks. Now previously we would estimate the project completion as 100% where each task has a percentage contribution. Well this did work for a while but was not the best solution. Now we would based the task on weight or points to be exact and use relative measurements to compare the task and differentiate the weights for example. There is a requirement to develop a web form to gather user data.
Task would go about like
1. User Interface - 2 Points
2. Database CRUD - 5 Points
3. Validation - 4 Points
4. Design (css) - 3 Points
With this strategy We can pin point a weekly approximate on how much we have completed and what is pending on the task force. We can also be able to pin point who has performed best.
I must admit that I still face some challenges on this strategy such as not every developer is comfortable on every technology. Somehow some are excited to learn technologies simply because they find 2015 high % of points fall in that section some would do what they can.
Remember, do not track a KPI for their own sake, track it for it's insight.
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I currently work for a bespoke software agency. Does anyone have any experience of how to win well priced work?
It seems there is so much competition from offshore/bedroom programming teams, that cost is extremely competetive these days. I feel that it is very different compared to a software product company or an internal IT department in terms of budget.
As someone else said before, we only ever really get to version 1.0 of a lot of our software, unless the client is big enough. In this case it doesn't make business sense to spend ages making the software the best we can. It's like we are doing the same quality of work as internal IT staff. Also a lot of our clients are not technically minded and so therefore will not pay for things they don't understand.
As our company does not have the money to turn down work it often goes that we take on complicated work for far too little money. I have gotten a lot better at managing change and keeping tight specs, etc. It is still hard.
Edit-----------------------
Almost 3 years on from this post and I can list some important lessons that I have learnt since then.
Please see below for my answer
If you are concerned with doing too much work for too little money then work on an hourly basis. Yes, that is harder to sell in most situations.
Maybe you can try a two-phased approach instead. Have a very short initial engagement where the deliverables are very specific requirements documents that become the property of the client. You risk having to compete for the actual development but you take away the risk of pricing the project too low because you will already understand what the client is like to work with, as well as, the application requirements.
Once you win the work at a fair price then use the best practices suggested by mathieu to help ensure quality and productivity which both lower the cost you incur.
What you described in your post, (not your question), I think is a sales, management and marketing question first and foremost.
You say that your clients are not technically minded, this will require to have a cohesive sales, consulting and communications strategy, this isn't about programming skills.
Also, if your company constantly accepts projects that are too complex or expensive for your team, and you deliver low quality products you'll sooner or later be stuck in a hole. You will attract customers that you do not want, and existing clients will be turned off by your 'incompetence' and sooner or later find another company on which they'll try to play the same price game. Those clients are worth nothing in my opinion.
You ask 'how do you win well priced work'? People are social animals, they talk with each other. If there's a market perception that you are an unreliable company, people and future clients will sooner or later know. Customers don't care whether you offered them a product at a really low price, on a too tight schedule - It's not really their error, it's you who accepted it. So once again, I think whole ordeal is a bad business practice.
I found that you really have to define tight specs on jobs with low budgets, define what you will and can deliver, tell them the price, stop your boss from offering too many long term customer discount price tags because they are too afraid to lose the client. Communicate early and often when things start to get out of hand. Write precise offers for additional features. Write these precisely down, don't rely on phone conversations (you: "that's an additional 4 hours of work", client: "ok"... 4 months later, client "what was that again??? why am i supposed to pay for this").
Now of course, one way you keep prices down is by not hiring complete morons that might be initially cheaper than better qualified programmers. This is a shortsighted approach and will fail miserably.
It is the relationship with your customer that will win you additional business. One developer actually stepped forward and halted a project because his sales consultant basically lied to us concerning a solution set. The developer then offered a straight forward, bare bones solution within the same budget and he delivered on time.
This guy and his team has been consulting at my company now for over 6 years. His integrity and earnest, hard working nature has been an immense advantage, and he has found quality people to work for him as his reputation has grown. His honesty is worth more than any savings I could get by shipping my company's intellectual assets overseas.
"so much competition from offshore/bedroom program teams" - sounds like you guys need to put some time into networking. At the end of the day, people like to do business with people, not with businesses. If you're well known and liked in your client communities, you'll be the front-runners and you'll get a better price from the confidence you have built. And referrals will give you a powerful edge - ask for them.
"our company does not have the money to turn down work" - lot's of companies have this as a start point, but ultimately you have to get past this approach The time you spend on these types of jobs stands in the way of being successful. You need to make decisions about what type of work you want to do (and who the customers will be) and just as importantly what you don't do.
As a consultant, I have personally moved to an hourly-rate-only model for just this reason. I have been burned by too many contracts-gone-wild, and I feel your pain.
In the end, people who only ever go with the lowest priced proposal will be trouble for your company. While you can't be so choosy, such that you don't ever get projects, you definitely want to steer clear of contracts whose supporting management are so agnostic about the actual software development process that they only look at the initial price tag for something. Usually, it's the stuff not in the contract or specification that changes the profit margins and timelines.
It's often in you best interest to be picky up front rather than lowering prices in order to receive a wave of what end up to be trouble-clients anyway. In your case, while there's always the contention between an RFP that is not as concise as a technical requirements specification, initial quotes should be understood as a general estimate based on the level of clarity in the RFP.
And I definitely agree kitsune, that if your company is consistently accepting contracts that don't fit your company's development expertise or bandwidth, all that will result is overhead and bad reputation.
This could be seen as quick guide to the above problem.
Proposal Document
Start with a proposal document that explains your understanding of the clients needs as best as possible. This can be done in 1-2 pages of writing as a minimum. It can start heading towards requirements, but it should be more casual than that.
Budget Document
Now go to Excel and list all the tasks in the project you think you will have to do. Put down the times in days, none bigger than 2 (0.25, 0.5, etc.).
Add a column for testing, and make it a percentage of the development time (20-30% is normal)
Now add a column for management (project + account) and add a % of time for that (over the previous two columns). 20-40% is normal. (70-30 split pm/am)
Set a day rate for your company. You can get more complex and have different rates for different user functions, but as a minimum set a rate that will mean that you will have a good margin whatever the work is being performed.
Work out what the value is for the total days that has been recorded so far. Then add a contingency amount on top of this (for fixed price work) 10-20% is normal here, but can change based on experience with the client and the amount of change you are used to with them.
At this point you can discount the total amount, which is better than lowering any other part of this document, as it will show the client that you are not magically making jobs go faster, rather you are removing some of your margin. They should therefore not expect you to reduce the timeframe of the project.
**Important - Analyze your client's budget and business when developing a costing. There is no point in you delivering a costing designed for a huge enterprise to your mate who wants an application done cost effectively. Likewise, make sure that you charge correctly to an organisation that will be used to high end freelancer rates.
Think like a business analyst. Not only will it help you make the client happy when they see your costs, but it will probably give you a greater insight into their business. If they are going to make money by using you, then you are probably onto a winner. If you can't ask directly how much money they have to spend with you, work it out by asking how many customers they have, what they charge, how many employees they have, etc. You should then be able to work out if what you are proposing is going to be profitable for them.**
Go back to your proposal document, and add a table with sections for design, development, management, etc... You could show the client your costing sheet in certain circumstances, but it is better to avoid complexity in most cases. It's there as a backup though, and you didn't just cough up a number.
Timeline Document
Take the list of design and development tasks from the budget, and put it into a new sheet (or Project if you're posh like me). Put in the start and end dates of each section adding roughly 30-50% extra on top.
Add some graphical representation of the days as blocks in Excel or use a Gantt template like this one.
Go back to your proposal document and add key milestones from the timing document.
Proposal stage completed
Send or present your proposal to your prospective client. Hopefully they are excited with what you have proposed and happy to proceed to the next stage, full requirements gathering. In subsequent projects with the same client you may be able to go straight to requirements.
Requirements stage
List each requirement against a separate id, either 1,2,4,5 or 1.1,1.2,1.3. It doesn't really matter, but the second one can help with large lists.
There are some tests for requirements and you can try to follow these, but sometimes they don't apply (some requirements might be design led for example). Some of these are: Is the requirement testable, is it singular, is it clear? I'll try to find a link to this somewhere.
This is my developer standpoint:
Version control best practices: Keep the trunk clean, don't commit code that doesn't compile, and commit frequently
Continuous integration
Unit testing (with code coverage)
Automatic deployment on test servers
Automatic packaging of the application
Automate as much as you can :)
Also, hire good developers, and treat them well :)
Sell fixed price, fixed scope work, not hourly work. That mitigates your customer's risk of an over-run (you absorb all the risk, but you're doing that anyway), and frames the project in terms of the value of the software, not the quality of the effort going into it.
We are trying to build a product and reuse existing experience. Comparing to UK in Ukraine (where I work) salaries are lower, but still 4-5 times higher than in India.
So far, the best result is to get two new clients, which need a similar solution, so we can offer better pricing and we are more confident in our estimate.
BTW, I checked out whywaitdigital.com, and it seems that we have a product which your clients might need. We do portals - editorial, B2C, geo-enabled product catalogs and we use ASP.NET MVC also. You can find contact information on our website, www.socialtalents.com.
It's a tricky question I was asked the other day... We're working on a pretty complex telephony (SIP) application with mixed C++ and PHP code with MySQL databases and several open source components.
A telecom engineer asked us to estimate the performance of the application (which is not ready yet). He went like 'well, you know how many packets can pass through the Linux kernel per second, plus you might know how quick your app is, so tell me how many calls will pass through your stuff per second'.
Seems nonsense to me, as there are a million scenarios that might happen (well, literally...)
However... is there a way to estimate application performance (knowing the hardware it will run on, being able to run standard benchmarks on it, etc) before actual testing?
You certainly can bound the problem with upper (max throughput) limits. There is nothing nonsense about that. In fact, not knowing that stuff indicates a pretty haphazard approach to a problem - especially in the telephony world.
You can work through the problem yourself - what is the minimum "work" you have to accomplish for a transaction or whatever unit of task you have in your app?
Some messages to and from, some processing and a database hit for example? Getting information on the individual pieces will give you an idea of the fastest possible throughput. If you load up the system and see significantly lower performance then you can take time to figure out where you are possibly losing throughput with inefficient algorithms, etc.
EDIT
To do this exercise you need to know all the steps your app does for each use case. Then you can identify the max throughput for each use case. You should definitely know this stuff prior to release and going live.
I'm ignoring the worst case analysis as that - as you point out - is quite a bit harder.
See Capacity Planning for Web Performance: Metrics, Models, and Methods. There are also some tools that can do this sort of discrete event simulation:
Hyperformix
SimPy
WikiPedia list of simulation tools
This stuff ain't easy, and the commercial tools will cost ya. The Capacity Planning book comes with a CD with lots of Excel workbook templates and examples of models that can jump start you.
Good luck :)
If you really have to answer this you could say something like this:
"I don't know off the top of my head. I am will to estimate this for you but it will take time. Obviously the accuracy of my answer depends upon how much effort (I.E. time) I put into calculating my estimate. How much time should I put into calculating my estimate?"
Put the burden back on them. If they really want an accurate answer, they're going to have to let you build at least some test applications that can simulate the actual environment.
You can spike to measure performance. Your whole system may not be working yet, but you know how the parts are intended to fit together. You can whip something up in a few hours that does the same kind of work as the final app will, across all the layers, and use it to measure performance of your design.
Remember: prototypes are broad, spikes are deep.
You should do the estimate. An estimate won't give you the right answer. It will however make you to think about the problem. Right now it sounds like your coding and hoping that everything will be OK. Or you are in panic mode and feel you don't have time for estimates.
Spend some time thinking about it. Analyse the important use cases. Think about the memory you may need; think about database access; think about network access (local and remote). These will effect the performance of your system. Get the whole team together to do this.
Regularly measure your system's performance during development for these important use cases. Mock up components/other systems if you have to. Analyse the results. How do these compare to your estimate. Maybe components are memory/database/network bound. Maybe you need more memory; less database access; simpler queries; caching. You don't have to make these changes straight away. However you do know how your system operates and what you need to do.
Result: Fewer nasty surprises at system test. Less panic as the release date looms.
You can definitely do capacity planning in advance, but the quality of the estimate will depend on the quality of the data available.
The best estimate is to build the system in test, run simulated workloads, then predict capacity as a function of performance requirements and workload. These 3 form a prediction space - given 2 of the 3, you can predict the third:
Given performance requirements and capacity (i.e. hardware) you can calculate the workload you can handle.
Given performance requirements and workload, you can calculate the capacity (i.e. hardware) that you need.
Given Workload and capacity, you can predict your expected performance.
This is true in some domains, but unless you are an expert in that domain then you don't have any idea. For example I write code to controlling industrial robots. The speed is limited by the robot motion, not by the execution speed of the code. Knowing how fast the robot is and how far it has to go, we can make fairly good estimates of "speed". I'd have no idea how to estimate time for your application.