Posts Tagged delivery
Posted by Alex Kell in Agile, Automation, Management, Testing on April 16, 2012
My company has a Director of Innovation. Joe is, predictably, a pretty inspiring guy and often sends out emails with interesting thoughts and ideas to spur innovation. Recently he sent out a message talking about the benefits of Failing Fast. In it he referenced the Gossamer Condor, the first human-powered aircraft capable of flying in a controlled fashion for more than a mile. Paul MacCready won the contest in 1977, 20 years after the contest began. Why did it take so long? Well, the biggest challenge was that failure was too costly. The designs were often good, but cycles of assembling the materials, testing, repairing and retrying could take as long as a year. As the attempts wore on, it became more and more difficult to get them financed.
MacCready took a different approach. He knew that no matter how good his designs, the likely result would be failure, just like all the others before him. As a result, he expected failure and built his prototypes with that in mind. He use common and cheap materials that were easy to work with and easy to repair and replace. As a result he could test new designs in a matter of weeks rather than years.
So how do we apply a fail-first thinking in software development? Here are some approaches, techniques and models that are borne of this philosophy that can have effects at all levels of your organization:
Test Driven Development (TDD) –
This is an approach used by programmers at the lowest level of software development. The idea here is you write a test that will initially fail because the code hasn’t been written yet. Then you write code until it passes. Certainly this helps you fail fast, in fact, it encourages you to fail first! The true power, though, is in the freedom it gives developers to try things they otherwise wouldn’t for fear of failure. With a battery of tests already created, the programmer is free to experiment and try out more innovative designs because they know they have that safety net. Failures are reported instantaneously, as are successes.
Executable Specifications –
With this approach, analysts and designers are called upon to work with programmers and testers to create requirements which are written with examples that can be hooked to the code. When the code is written to do what the business wants, these examples pass. If it isn’t, the tests won’t pass. Now that’s fast failure. In the past, such problems (programmers and testers misunderstanding requirements) might not have gotten caught until much later in the process. Of course, all this presumes the design or feature was correct.
If you’ve been doing this all along, a new feature might be proposed; the tests are written and the feature is coded and the tests pass, however an older test fails. Just as in TDD, you now have a safety net of “living” documentation. Before you had to pore through the requirements documents to find the inconsistencies; now all you need to do is run them. Additionally, if done properly, these specifications become the documentation. There’s no worry about them becoming out of date or inaccurate with respect to the code because they are directly tied to the code.
Short Iterations –
This is a tenet of Agile methodologies. Teams complete releasable units of prioritized work in a short and predictable amount of time. If we need to change course because of some unexpected event, we don’t have to scrap the foundations of work that won’t be complete for months, we only have to scrap, at most the amount of work related to the length of the iteration (or, for you Kanban folks, the cycle-time for the largest unit of work in process).
Small, more frequent releases –
In some situations, there are restrictions on how frequent and how small we can make our releases due to overhead (training, deployment, regulatory testing) but we should be working on making these as small as possible. Just like with iterations, if we make the wrong call on a feature, we can react faster – instead of 6 months to a year to implement a change, we can potentially do it in an iteration’s time, with no disruption to the business as would be the case with emergency hotfixes/patches, etc.
Business level –
Feature flow and prioritization –
Too often businesses decide on goals unique to each business unit and then those units create projects independently to meet those goals. Often these projects compete with each other for resources and capital when only parts of them are actually directed at the business goals. We shouldn’t be focused on the projects, but rather the features in those projects that are most important. Models exist that show how to link these goals to prioritized features. The business units are now not concerned with independent projects, but rather they are working on those aspects of the features that they have the capability to produce. The business units can then speak in terms of continuous delivery of features within products rather than entire projects released all at once. This keeps us focused on what we believe are the most important things given the best information we have at that time. If it’s wrong, we can adjust our backlog of features based on the new priorities. The alternative is to release updates based on information from a year or more ago and to cancel projects with nothing to show for them.