Lessons from Sim City Limited
So a blast from the past was released this week. The new SimCity, descendant of one of my great childhood joys, SimCity 2000. I pre-ordered this game, and had it running the night I got it. But fate is a cruel mistress... Or more accurately, products released before they are ready are cruel mistresses. I had trouble at just about every step of the pipe. My install failed on my Microsoft Surface Pro, claiming that it was a virtual machine and thus, ineligible. After installing it on my desktop, it crashed about every 10 minutes, and did nothing to restore games from a checkpoint. After a patch came out on day 2, the servers became impossible to log in. It is clear that EA had a deadline to be hit come hell or highwater, and their engineers were left to compromise the product's quality. This is a dangerous game to play.
The first problem I would argue is the cost axis. We all recognize that there are non-linear costs associated with adding people to projects. Larger teams have more complicated communication structures, require more time integrating pieces developed independently together, contain more bugs because of failed assumptions at the interfaces, and have the problem of running into irreducible complexities. Nine women can't make a baby in one month. Brook's law, so eloquently stated in the Mythical Man Month is that adding late people to an already late project makes it later. New people have a spin-up time which lowers the productivity of everyone else on that project. The only real time to trade on this axis is at the start of a project. If ever you get way ahead, it is much easier to remove people from a project than add them to it. The effect of this is typically that cost really moves to the center of the triangle, and teams trade on quality, even as every fiber of their being scream that this should not be traded on.
Time is the hairy beast on the triangle. Engineers are bad at projecting how long something is going to take. Even over short intervals such as Agile sprints, it is hard to gauge the timelines accurately. To compound the problems, engineers usually error to the side of estimating low. That means that management is really only supposed to be left with scope to trade on, when timelines begin to balloon. And the pin that pops this bubble is how stakeholders force teams to be deadline driven. Customers have expectations as to when a feature should be released. Management needs a backbone to push back on customers if expectations have been already made. Release schedule should be the deep dark secret that customers don't see coming, giving the time tent pole more room to grow.
Being able to trade scope requires developers to heavily focus on loosely coupling their products, so simpler solutions can be dropped in place of planned ones. Developers often lack the foresight to adequately plan for these contingencies, and waterfall projects tied to long term design plans can fail if dependent features are incomplete when a deadline is reached. If any given feature is missing come deadline day, it has the potential to cascade down the line, blocking feature after feature.
Quality starts out as the least tangible aspect for management. They have their budgets projecting costs, their requirements detailing feature requests, and their timelines that they rigidly stick to. Code rot can quietly be swept under the rug. Test plans can be silently neglected. Acceptance criteria can be too incomplete to fully capture a feature. And it isn't until release, when many hands are all touching your product, then you realize what was traded on over the course of your product.
I appreciate the fresh look Agile has for dealing with this triangle. By always having a stable product that can be re-evaluated every sprint, you make tangible the quality part of the triangle, and can force it to remain high. By reducing the features to smallest working extension, you can shrink the timescales allowing them to become more predictable for engineers. By allowing engineers to decide the time frame on a feature by feature basis, it helps deconstruct artificial deadlines that serve to press against quality. And finally, it forces product owners to focus on trading on the right part that managers should really be focused on in the first place: features. Prioritization becomes their sword, because it is the most effective weapon a PO or PM has in their arsenal.
Sim City obviously has traded on quality, and that is going to cost them a lot of money, as well as make them an example for others to learn from.