Thursday, March 17, 2011

Metrics (Part I)

In this article, game designer Ian Schreiber outlines the debate between metrics-driven design and the more touchy-feely intuition-based design.


Here’s a common pattern in artistic and creative fields, particularly things like archaeology or art preservation or psychology or medicine where it requires a certain amount of intuition but at the same time there is still a “right answer” or “best way” to do things. The progression goes something like this:

  1. Practitioners see their field as a “soft science”; they don’t know a whole lot about best principles or practices. They do learn how things work, eventually, but it’s mostly through trial and error.
  2. Someone creates a technology that seems to solve a lot of these problems algorithmically. Practitioners rejoice. Finally, we’re a hard science! No more guesswork! Most younger practitioners abandon the “old ways” and embrace “science” as a way to solve all their field’s problems. The old guard, meanwhile, sees it as a threat to how they’ve always done things, and eyes it skeptically.
  3. The limitations of the technology become apparent after much use. Practitioners realize that there is still a mysterious, touchy-feely element to what they do, and that while some day the tech might answer everything, that day is a lot farther off than it first appeared. Widespread disillusionment occurs as people no longer want to trust their instincts because theoretically technology can do it better, but people don’t want to trust the current technology because it doesn’t work that great yet. The young turks acknowledge that this wasn’t the panacea they thought; the old guard acknowledge that it’s still a lot more useful than they assumed at first. Everyone kisses and makes up.
  4. Eventually, people settle into a pattern where they learn what parts can be done by computer algorithms, and what parts need an actual creative human thinking, and the field becomes stronger as the best parts of each get combined. But learning which parts go best with humans and which parts are best left to computers is a learning process that takes a while.
Currently, game design seems to be just starting Step 2. We’re hearing more and more people anecdotally saying why metrics and statistical analysis saved their company. We hear about MMOs that are able to solve their game balance problems by looking at player patterns, before the players themselves learn enough to exploit them. We hear of Zynga changing the font color from red to pink which generates exponentially more click-throughs from players to try out other games. We have entire companies that have sprung up solely to help game developers capture and analyze their metrics. The industry is falling in love with metrics, and I’ll go on record predicting that at least one company that relies entirely on metrics-driven design will fail, badly, by the time this whole thing shakes out, because they will be looking so hard at the numbers that they’ll forget that there are actually human players out there who are trying to have fun in a way that can’t really be measured directly. Or maybe not. I’ve been wrong before.

At any rate, right now there seems to be three schools of thought on the use of metrics:
  • The old school Zynga model: design almost exclusively by metrics. Love it or hate it, 60 Million monthly active unique players laugh at your feeble intuition-based design.
  • Rebellion against the old school Zynga model: metrics are easy to misunderstand, easy to manipulate, and are therefore dangerous and do more harm than good. If you measure player activity and find out that more players use the login screen than any other in-game action, that doesn’t mean you should add more login screens to your game out of some preconceived notion that if a player does it, it’s fun. If you design using metrics, you push yourself into designing the kinds of games that can be designed solely by metrics, which pushes you away from a lot of really interesting video game genres.
  • The moderate road: metrics have their uses, they help you tune your game to find local “peaks” of joy. They help you take a good game and make it just a little bit better, by helping you explore the nearby design space. However, intuition also has its uses; sometimes you need to take broad leaps in unexplored territory to find the global “peaks,” and metrics alone will not get you there, because sometimes you have to make a game a little worse in one way before it gets a lot better in another, and metrics won’t ever let you do that.
Think about it for a bit and decide where you stand, personally, as a designer. What about the people you work with on a team (if you work with others on a team)?

[This article is an excerpt from Level 8: Metrics and Statistics, part of Ian Schreiber's course on game balance called Game Balance Concepts.]

Ian Schreiber has been making games professionally since 2000, first as a programmer and then as a game designer. He currently teaches game design classes for Savannah College of Art and Design and Columbus State Community College. He has worked on five shipped games and hundreds of shipped students. You can learn more about Ian at his blog, Teaching Game Design.


Anonymous said...

Re-reading this, I realize that things have changed since it was originally written. I should probably have called it the "old school Zynga model" from before Brian Reynolds changed the paradigm over there. I'm aware that these days, Zynga uses a combination of metrics and design.

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