Lets take a look at what is required to manage the development of medium to large scale software products.
Someone has a big idea. From my perspective, someone identifies a need and a customer base.
This boils down to a set of vague features. You can group features in several different ways, but you need to decide on a hierarchy of them; each level could be a release.
This is where the first set of problems come in. Picking the features. You need to, as constructively and objectively as possible figure out which features are going to hit the sweet spot of not a lot of work for a shitload of cash.
As a small aside, what it boils down to for me is the most functionality for the fewest lines of code. I look at every single line in the system as a liability; something that needs to be tested, verified, refactored, and all manner of other forms of maintained.
In the real world, however, not in Chris' world, what it boils down to is amount of cash made per line which I guess has a direct correlation to hourly rate. What the entire company should be interested in is making the most money with the smallest, tightest code base. You *don't* want your developers writing code as fast as they can every day. Ideally you want them refactoring old code, redesigning modules to take in new information, and shaking the last few bugs out of old features.
Anyway, we have features. Lets say some miracle happened and your expert marketing department did their job and picked a set that would be dynamite.
So far we have:
Idea -> Customer Research -> Master Feature Set -> Badass telepathic marketing research -> Beta, Alpha, and Release Feature set.
OK, we just got that far. There is another factor in the equation, however, and that is how much work each feature requires. The design and dev team need to figure out some kind of rough map and communicate this back to marketing so that the feature set hits the sweet spot between the least amount of effort for the most money.
But we haven't talked about the design or dev team yet, but there is an iterative sequence and feedback loop that happens throughout the process and one iteration looks like this:
Feature -> Design -> Dev -> Cost Analysis -> Badass telepathic marketing research -> New Better Simpler Feature
The cheapest feature to implement is the one you don't do. Never ever forget this. It is far *far* cheaper to remove details at this level, the highest level than at the design or the pump-code level. Nothing comes for free and each new feature has an n^2 effect on complexity because it will interact with existing features and make adding a new feature harder. In addition it makes the testing matrix larger and gives your sales team another detail to get tripped up on while they are trying to figure out where a potential customer is coming from.
Each piece of implemented system brings, along with the promise of cold, hard cash, the threat of carrying heavy chains of senseless complexity and pointless detail into each and every design decision later on. So think long and very very hard about exactly what you are going to do before you begin the process of doing it.
OK, lets say we have a feature set we are confident in. Now comes the fun part; you have an iterative process between a design and customer advocation team and the development team where the look, feel, and functionality of the product is hammered out to meet each largish feature. This should involve mock-ups, prototypes, using existing programs to see what the customer base is used to, artistic talent and a good, pragmatic eye towards a minimal cost route.
We the break features down into stories, stories into lists of requirements, and requirements into lists of tasks. The more thorough you are with this breakdown the better as it allows a clearer picture of the work required to move forward.
There isn't any software that does this well but really what you want is to build a large graph of dependencies here. This is because a given set of stories may generate interleaving requirements on any given software module.
What is useful is to be able to ask a question like "If we eliminate X, how much less work is it". Along with this you have the converse: "If we add Y, what is the impact on the system?".
So, in a hierarch of generators, we have:
Feature -> Stories -> Requirements -> Tasks.
This maps reasonably well to the actual work required to do anything. Each of these arrows is a 1 -> N relationship although multiple stories may generate the same requirement from the software's perspective. For example if you have a good serialization system then you can save/load the system as well as cut/paste between applications.
In any case, this should highlight just exactly how important it is that you come up with a minimal feature set. Then the design must be very good but also very smart so each feature generates the minimal set of stories. Finally the dev team needs to be careful with how they break down stories to end up with minimal requirements and minimal tasks.
Now we get into the details of what happens when you stop thinking about doing something and start doing it.
People, when testing the software will come up with all sorts of things. Some things they come up with are additional features of new stories. Other things they come up with will be actual defects where a given piece of software does not meet the specifications. Finally there will be details that are annoying but outside the scope of what was specified but they still should be tracked.
The design that I like is to have an issue database. This database is filtered by the design and product development teams to product a defect database, additional story features, and requests to redesign sections of the product.
The reason I have an issue database is that bugs are things that should require fairly immediate developer attention. These are defects in the system and release with a large number of them indicates a faulty process for creating software. These are like development gold; you rush to them, fix them to the best of your ability, and think about how they happened as these teach you a lot about how you are developing software.
Good design, both at the product level and at the engineering level is key to minimizing everything in the issue database. A good design at the product level makes certain kinds of problems impossible. A perfect design from the product design point of view means the customer *can't* make a mistake. A perfect design from an engineering point of view means that bugs can't happen.
It isn't that you have such a badass developer that they --do not-- make a mistake but they think about their code so much that they implement a design that --can not-- fail. There is a large difference between don't and can't. One requires discipline and one requires genius.
This is, btw, my problem with a lot of software. It is written with too much discipline and not enough genius but I digress...
Now lets think about what implementing something actually means. Lets start with a simple but perhaps non-obvious assumption.
Every time you add a line of code to the system you destabilize it to some extent. Thus when you are writing a bunch of code and adding capabilities you *will* have bugs there is not way around it. You will break old pieces that were working, even with unit tests and all manner of other stabilization devices. This is a fact of life; change means both moving forward and in some senses moving backwards and of course no one wants to move back.
Also lets make another assumption; the number of bugs, issues, and various other forms of feedback a feature or story will generate is directly dependent upon is complexity. This should be obvious; with two engines you are exactly twice as likely to have an engine failure as with one.
This, btw, is why a lot of dual engine airplanes are less safe than their single engine counterpart. It took people a long time to design a dual engine design that could fly capably with only one engine. This meant that there are a lot of aircraft designs that are twice as likely to crash when the initial idea was to have redundancy and thus greater safety.
In order to have a stable beta, alpha, and release you need to *not* be changing the software that much. Lets take a graph capabilities added to a software system. You want it to look like a bell curve, where the hump in the middle is that area of highest activity and you ramp into such development as well as ramp out of it.
This is because you want a stable product in the end. Thus you ramp up slowly, thinking a lot about design and how to accomplish what you are doing. Next you pump code and you QA team starts ripping you a new arse hole. Now you start switching resources to fixing QA issues and not so much adding new capabilities. As the release gets closer you begin to really focus on bugs and capabilities take a back seat.
The graph of bugs that people find will mirror your graph of adding capabilities to the system, just later in time. How much later depends on your ability to test the software effectively and in your ability to fix bugs where their solution will reveal or cause new bugs. You want your release to coincide with the point where your bugs have hit their point of largely diminishing return in terms of new bugs being found are by in large not worth fixing as they will have minimal customer impact or will be fixed by stories that are scheduled for after release.
You really want a good QA team. You want a rare combination of smart and disciplined for QA more than anything else. This is because if you QA team isn't smart then your best and brightest customers will find your worst bugs; thus you have lost some of your greatest advocates. If they aren't disciplined then they will not test all the combinations of features they could and your average customers will run into random issues just messing around with the product in an interesting way.
The QA team and the dev team should be drinking buddies but there shouldn't be animosity either. During a long release cycle, however, I know that I start to get aggravated and so does our QA dept and we stop speaking nearly as much.
In any case, a new story or capability is an issue generator but they don't generate all the issues right away. Bugs fixed will reveal new bugs and you will get chains of bugs that are very difficult to fix quickly.
Finally, there is a point when you want to show the world what you have done. You have faith in your marketing dept and their research is solid and smart. You have confidence in your customer research system, and of course in your big idea. Your product design team has been creative and done a great job of delineating a clear vision of how the product will look and feel from a customer perspective. The dev team is a team of patient, smart, tough geniuses who have produced smart, tight software design from day 1. You QA team doesn't take bullshit from anyone and while they can break most pieces of software just by looking at it they can't do touch your current hotness.
It is time for the demo, it is time to for everyone to work together and think out a set of scripts that will shock and awe, amaze and delight all potential customers and it is time to mobilize the sales force. These people shouldn't think about anything but cash. They need to be cut throat, they need to be able to really get into what they are selling but also be capable of reading each new prospect like a book. They are the front line, the marines, so to speak and now the fate of the entire operation rests on their shoulders. They need to take ground and what they do will ultimately make you all the money in the world or provide an excuse in your next job interview.
They will feed ideas back into the feature and story databases and will provide another source of information about how the product is working in the real world.
In any case, get a great idea and bring all of this complex machinery together and you are a long way above most companies in terms of your ability to bring great software to market. If any of these pieces are weak then your software, regardless of the vision or idea behind it, will not stand the test of time or customers.
