作者：Ian Schreiber

艺术和创意领域存在普遍模式，尤其是对于考古、艺术保护、心理学或医学而言，它们既依靠一定直觉，同时也存在某种“正确答案”或“最佳方式”。其发展过程如下：（请点击此处阅读本系列第2、3篇）

1. 实践者将他们的领域看作“软科学”；他们并不知道最佳原则或实践。他们最终会把握事情的运作方式，但这多半是通过反复试验。

2. 有人创造某种技术，其从算法上解决许多相关问题。实践者颇为高兴。最终，这变成硬科学。我们无需再进行猜测。许多传统实践者摒弃“传统方式”，将“技术”视作解决行业问题的方式。而保守派则认为这对传统制作方式构成威胁，持怀疑态度看待。

3. 经过广泛应用后，技术的局限性变得显而易见。实践者发现他们所进行的工作依然包含神秘和情感元素，虽然总有一天技术会解决此问题，但这天非常遥远。广大业内人士之所以瞬间醒悟是因为人们不再相信自己的直觉，因为从理论角度看，技术在此表现更突出，但人们之所以不信任当前技术是因为其实现效果尚不那么明显。在年轻人士看来，这并没有他们想象中那般万能；而保守派人士表示，其所起的作用比他们想象的显著。

4. 最终，大家会习惯于这样的模式：他们清楚什么元素能够由计算机程序完成，什么元素需要真正的人类创意思维，随着各优质元素的相互结合，行业变得日益强大（游戏邦注：但掌握什么元素最适合由人类完成，什么适合留给电脑操作是个学习过程，需耗费一定时间）。

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目前，游戏设计刚步入第二步。我们逐渐听到越来越多人谈论参数和数据分析之所以能够拯救他们的公司的原因所在。我们开始发现能够在玩家充分掌握应用知识前通过瞄准玩家模式解决游戏平衡问题的MMO内容。我们听说Zynga通过将字体由红色调成粉色，吸引更多玩家体验其游戏。如今行业还出现专门帮助开发者获取和分析参数信息的专业公司。行业开始着迷于参数，但我猜测未来至少有一家完全依靠参数的公司会以失败告终，到那时局面就会发生变化，他们过于执着于数据，完全忘记有些用户体验行为无法通过参数体现。或者也许不会出现这种情况。

无论如何，如今关于参数的运用，业内存在3种派别：

* 传统Zynga模式：设计完全基于参数。无论你讨厌，还是喜欢，Zynga庞大的MAUU（monthly active unique user）就足以证实这种这种模式的效果。

* Zynga模式反对派：参数容易被误读，被操纵，因此非常危险，弊大于利。假设你衡量用户行为，发现很多玩家点击登陆页面，而非进行其他游戏操作，这并不意味着你应该在游戏中融入更多登陆页面（游戏邦注：认为说玩家进行此操作就意味着此内容极富趣味）。若你的设计采用参数，你就会将自己局限于仅凭参数设计的内容，错过众多有趣的电子游戏类型。

* 中间派：参数有其价值，它们帮你调节游戏，发现特定趣味“高潮点”。通过这些信息，你能够将原本颇突出的作品变得更杰出，它们帮你挖掘临近设计空间。但直觉也起到一定的作用；有时你需要大步跨至尚未开拓的领域，寻找总体“高潮点”，单凭参数无法让你到达此处，因为有时特定趣味性的实现会以牺牲其他趣味为代价，参数无法帮我们判断出这一点。（本文为游戏邦/gamerboom.com编译，拒绝任何不保留版权的转载，如需转载请联系：游戏邦）

Metrics

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)?（Source：gamedesignaspect）