The video games industry is a fertile breeding ground for anxiety and stress. Almost every game is an entrepreneurial endeavor. Expeditionary. And uncertain. Uncertain schedules, uncertain results, uncertain job security. It’s not for the faint of heart. In this article, I’m going to take a break from the usual managerial tone of Breaking The Wheel in order to focus on something more important than any game: your mental health.
This post is a bit of a capstone. It utilizes all of the tools to make video games scientifically that I covered in the Parts 1-6 of “Game Planning With Science”. Make sure you’ve reviewed those weighty tomes before digging in here. In this post, I’m going to walk you through how to utilize capacity charts, story points, user stories, variance, and the central limit theorem to forecast development time lines.
There’s a saying in data science: Garbage In, Garbage Out (or GIGO, if you prefer). The most advanced formulas and models won’t provide outputs worth a dead cat if you don’t have high quality inputs. When it comes to something as difficult and uncertain as feature planning and estimation, that’s quadruply so. In this post I’m going to walk you through the system I’ve used successfully, how it works, and why. And it’s all based on the counter part to the story points from Part 5, user stories.
In Part 4 of “Game Planning With Science!”, I covered the central limit theorem, and how we can use it for forecasting feature development. At the end of the post I acknowledged that it’s no mean feat to track the time per individual feature without some heavy duty project management software and a team that is superlatively disciplined about tracking their time. In Part 5, I’m going to give you my favorite tool for getting around this problem: Story Points.
In Part 4 of “Game Planning With Science”, I’m going to wrap up the statistics primer I started in Part 3. This time, I’ll cover one of the most fascinating aspects of statistics: the Central Limit Theorem. Why does one aspect of statistics deserve its own post? BECAUSE IT’S FRIGGIN’ RAD, THAT’S WHY! Also (and probably more importantly) it allows us to make predictions when planning games, even if we don’t have a lot of data.