Controlling an Unpredictable Process - Iterations

　　So how do we control ourselves in an unpredictable world? The most important, and still difficult part is to know accurately where we are. We need an honest feedback mechanism which can accurately tell us what the situation is at frequent intervals.

　　The key to this feedback is iterative development. This is not a new idea. Iterative development has been around for a while under many names: incremental, evolutionary, staged, spiral... lots of names. The key to iterative development is to frequently produce working versions of the final system that have a subset of the required features. These working systems are short on functionality, but should otherwise be faithful to the demands of the final system. They should be fully integrated and as carefully tested as a final delivery.

　　The point of this is that there is nothing like a tested, integrated system for bringing a forceful dose of reality into any project. Documents can hide all sorts of flaws. Untested code can hide plenty of flaws. But when people actually sit in front of a system and work with it, then flaws become truly apparent: both in terms of bugs and in terms of misunderstood requirements.

　　Iterative development makes sense in predictable processes as well. But it is essential in adaptive processes because an adaptive process needs to be able to deal with changes in required features. This leads to a style of planning where long term plans are very fluid, and the only stable plans are short term plans that are made for a single iteration. Iterative development gives you a firm foundation in each iteration that you can base your later plans around.

　　A key question for this is how long an iteration should be. Different people give different answers. XP suggests iterations of between one and three weeks. SCRUM suggests a length of a month. Crystal will stretch further. The tendency, however, is to make each iteration as short as you can get away with. This provides more frequent feedback, so you know where you are more often.

　　The Adaptive Customer

　　This kind of adaptive process requires a different kind of relationship with a customer than the ones that are often considered, particularly when development is done by a separate firm. When you hire a separate firm to do software development, most customers would prefer a fixed-price contract. Tell the developers what they want, ask for bids, accept a bid, and then the onus is on the development organization to build the software.

　　A fixed price contract requires stable requirements and hence a predictive process. Adaptive processes and unstable requirements imply you cannot work with the usual notion of fixed-price. Trying to fit a fixed price model to an adaptive process ends up in a very painful explosion. The nasty part of this explosion is that the customer gets hurt every bit as much as the software development company. After all the customer wouldn't be wanting some software unless their business needed it. If they don't get it their business suffers. So even if they pay the development company nothing, they still lose. Indeed they lose more than they would pay for the software (why would they pay for the software if the business value of that software were less?)

　　So there's dangers for both sides in signing a fixed price contract in conditions where a predictive process cannot be used. This means that the customer has to work differently.

　　This doesn't mean that you can't fix a budget for software up-front. What it does mean is that you cannot fix time, price and scope. The usual agile approach is to fix time and price, and to allow the scope to vary in a controlled manner.

　　In an adaptive process the customer has much finer-grained control over the software development process. At every iteration they get both to check progress and to alter the direction of the software development. This leads to much closer relationship with the software developers, a true business partnership. This level of engagement is not for every customer organization, nor for every software developer; but it's essential to make an adaptive process work properly.

　　All this yields a number of advantages for the customer. For a start they get much more responsive software development. A usable, although minimal, system can go into production early on. The customer can then change its capabilities according to changes in the business, and also from learning from how the system is used in reality.

　　Every bit as important as this is greater visibility into the true state of the project. The problem with predictive processes is that project quality is measured by conformance to plan. This makes it difficult for people to signal when reality and the plan diverge. The common result is a big slip in the schedule late in the project. In an agile project there is a constant reworking of the plan with every iteration. If bad news is lurking it tends to come earlier, when there is still time to do something about it. Indeed this risk control is a key advantage of iterative development. Agile methods take this further by keeping the iteration lengths small, but also by seeing these variations as opportunities.

　　This has an important bearing what constitutes a successful project. A predictive project is often measured by how well it met its plan. A project that's on-time and on-cost is considered to be a success. This measurement is nonsense to an agile environment. For agilists the question is business value - did the customer get software that's more valuable to them them than the cost put into it. A good predictive project will go according to plan, a good agile project will build something different and better than the original plan foresaw.

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