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【翻译完成删除原文添加译文】20160808 Why measuring IT productivity is so challenging.md
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[WangYueScream 翻译中]
===========================
Why measuring IT productivity is so challenging
===========================
![](https://enterprisersproject.com/sites/default/files/styles/620x350/public/images/cio_talent_6.png?itok=JV-zSor3)
In some professions, there are metrics that one can use to determine an individual’s productivity. If you’re a widget maker, for instance, you might be measured on how many widgets you can make in a month. If you work in a call center – how many calls did you answer, and what’s your average handle time? These are over-simplified examples, but even if you're a doctor, you may be measured on how many operations you perform, or how many patients you can see in a month. Whether or not these are the right metrics, they offer a general picture of how an individual performed within a set timeframe.
In the case of technology, however, it becomes almost impossible to measure a person’s productivity because there is so much variability. For example, it may be tempting to measure a developer's time by lines of code built. But, depending on the coding language, one line of code in one language versus another might be significantly more or less time consuming or difficult.
Has it always been this nuanced? Many years ago, you might have heard about or experienced IT measurement in terms of function points. These measurements were about the critical features that developers were able to create. But that, too, is becoming harder to do in today’s environment, where developers are often encapsulating logic that may already exist, such as integration of function points through a vendor. This makes it harder to measure productivity based simply on the number of function points built.
These two examples shed light on why CIOs sometimes struggle when we talk to our peers about IT productivity. Consider this hypothetical conversation:
>IT leader: “Wow, I think this developer is great.”
>HR: “Really? What do they do?”
>IT leader: “They built this excellent application.”
>HR: “Well, are they better than the other developer who built ten applications?”
>IT leader: “That depends on what you mean by 'better.'”
Typically, when in the midst of a conversation like the above, there is so much subjectivity involved that it's difficult to answer the question. This is just the tip of the iceberg when it comes to measuring IT performance in a meaningful way. And it doesn't just make conversations harder – it makes it harder for CIOs to showcase the value of their organization to the business.
This certainly isn't a new problem. I’ve been trying to figure this out for the last 30 years, and I’ve mostly come to the conclusion that we really shouldn’t bother with productivity – we'll never get there.
I believe we need to change the conversation and stop trying to speak in terms of throughput and cost and productivity but instead, focus on measuring the overall business value of IT. Again, it won't be easy. Business value realization is a hard thing to do. But if CIOs can partner with the business to figure that out, then attributing real value can become more of a science than an art form.
--------------------------------------------------------------------------------
via: https://enterprisersproject.com/article/2016/8/why-measuring-it-productivity-so-challenging
作者：[Anil Cheriyan][a]
译者：[译者ID](https://github.com/译者ID)
校对：[校对者ID](https://github.com/校对者ID)
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
[a]: https://enterprisersproject.com/user/anil-cheriyan

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为什么测试 IT 的生产效率如此具有挑战性
===========================
![](https://enterprisersproject.com/sites/default/files/styles/620x350/public/images/cio_talent_6.png?itok=JV-zSor3)
在某些行业里，人们可以根据一些测量标准判定一个人的生产力。比如，如果你是一个小部件制造商，可以通过一个月你能够制造的小部件数量来确定你的生产效率。如果你在客户服务中心工作，你解答了多少个客户来电，你的平均解答时间都会成为评判你的生产效率的依据。即便你是一位医生，也可以通过你主刀的临床手术次数或者一个月你确诊的患者数量来确定你的生产效率，但这些都是相当简单的案例。虽然这些评判标准不是完全正确的，但他们提供了一个通用的方法来在给定时间内评断一个人的执行能力。
然而在 IT 这方面，通过上述方法来衡量一个人的生产力是不可能的，因为 IT 有太多的变化性。比如，通过一个开发者编写的代码行数和耗费的时间来衡量开发者的生产效率看起来很诱人。但是，编程的语言很大程度上能影响到根据这种方法得到的结论。因为一种编程语言编辑的一行代码比用其他编程语言编写所花费的时间和难度可能会明显的多或少。
它总是这样微妙吗？多年以前，你可能听说过或者经历过根据功能点衡量 IT 工作人员的生产效率。这些措施是针对开发者们能够创建的关键特征来衡量开发者的生产效率的。但这种方法在今天也变得逐渐难以实施，开发者经常将可能已经存在逻辑封装进内部。比如，通过供应商来整合功能点。这使得仅仅是基于功能点的数目来估量生产效率难度加大。
这两个例子能够阐述为什么当我们与同事谈论 IT 生产效率的时候有时会引起 CIO 之间的争论。考虑以下这个假想中的谈话：
>IT leader：“天啊，我想这些开发者一定很厉害。”
>HR：“真的假的，他们做了什么？”
>IT leader：“他们做了个相当好的应用。”
>HR：“好吧，那他们比那些做了 10 个应用的开发者更好吗”
>IT leader：“这要看你怎么理解 ‘更好’。”
这个对话比较有代表性。当我们处于上诉的这种交谈时，这里面有太多的主观因素导致我们很难回答这个问题。当我们用一种有意义的方法来测试 IT 的效率时，类似上诉谈话的这种问题仅仅是冰山一角。这不仅仅使谈话更加困难－它还会使 CIO 很难展示他们的团队在商业上的价值。
可以确实这不是一个新出现的问题。我已经花费差不多 30 年的时间来思考这个问题。我得出的结论是我们真的不应该在谈论 IT 的生产效率这件事上面相互烦扰－因为我们的 IT 生产效率永远不可能能到达到值得我们为此争论的程度。
我认为我们需要改变这种对话同时停止根据生产能力和成本来谈论 IT 的生产效率，将目光集中于衡量 IT 的整体商业价值。这个过程不会很容易。商业价值的实现是一件困难的事情。但如果 CIO 能够和商业人员合作来解决这个问题，就可以将实际价值变的更加科学而非一种艺术形式。
--------------------------------------------------------------------------------
via: https://enterprisersproject.com/article/2016/8/why-measuring-it-productivity-so-challenging
作者：[Anil Cheriyan][a]
译者：[LemonDemo](https://github.com/LemonDemo)　[WangYueScream](https://github.com/WangYueScream)
校对：[校对者ID](https://github.com/校对者ID)
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
[a]: https://enterprisersproject.com/user/anil-cheriyan