本文标题为“Wartet nicht auf Perfektion – lernt aus euren Fehlern!" appeared in German last week in the "Digitaliserung" column ofwirtschaftwoche.

"Man errs as long as he doth strive." Goethe, the German prince of poets, knew that already more than 200 years ago. His words still ring true today, but with a crucial difference: Striving alone is not enough. You have to strive faster than the rest. And while there's nothing wrong with striving for perfection, in today's digital world you can no longer wait until your products are near perfection before offering them to your customers. If so, you will fall behind in your market.

So if you can't wait for perfection, what should you do instead? I believe the answer is to experiment aggressively with your product development, accepting the possibility that some of your experiments will fail.

任何听力或合作的人管理大师都知道他们的口头禅:失败是进步的必要部分。这是真的,但管理理论与地面的现实之间经常存在巨大差距。人们想尝试并从出错的事情中学习。但在日常生业的势利中,他们没有足够的时间来真正反思错误的原因,下次做出不同的事情。

该解决方案是找到一种系统方法,可以防止错误重复误差。

从完美到抗脆性

在寻找这种系统的方式时,您首先需要区分公司中可能发生的两种类型的错误:技术和人为决策的误差。好的事情是:如果你知道如何用第一个有效处理,你可能最终在第二中更好,做出更好的决定。金融数学家和Essayist Nassim Taleb提供了一个有趣的对这个问题。他认为错误是非常有价值的,因为它们导致创新。他使用术语“反脆弱”来达到他的观点。今天的数字商业模式需要更小,频繁的释放,以降低风险。这意味着支撑这些新商业模式的技术必须不仅仅是强大的。他们必须“反脆弱”。反脆弱技术的主要特点是它可以“错误”而不会分开。事实上,危机可以让它变得更好。

在亚马逊,我们还要求我们的系统和客户解决方案成为反脆弱,我们通过设计我们的系统来进行时间考验。我们的系统必须能够发展并变得更具弹性。由于从客户反馈和在操作系统时可能遇到的任何故障模式,它们必须变得更加强大和更具功能丰富的时间。

An example of a German company that has become 'anti-fragile' is HARTING, the world's leading provider of heavy pluggable connectors for machines and plants. HARTING shows how to think a step ahead about the meaning of quality standards in the digital world. Quality and trust are the most important values for this traditional company, and Industry 4.0 and the digital transformation have already been important focus areas for them since 2011. Even though it was hard to accept at first, HARTING has meanwhile realized that errors are inevitable. For that reason, its development switched to agile methods. It also uses the "minimum-viable-product" approach and relies on microservices for its software. Working this way, HARTING can discard things and create new things more easily. All in all, HARTING has become faster.

可以用Harting MICA可以看到一个优势计算解决方案,使较旧的机器和植物能够获得数字改造。身体和硬件仍然反映了HARTING的完美标准。但对于软件来说,目标是“足够好”,因为微服既不完整也不完美。结果,错误的决策和错误可以非常快速地纠正,系统可以更快地成熟,接近抗灰度状态。如果要求更改或更好的软件技术可用,则可以抛出每个微服务并创建新的微服务。这就是你如何获得速度,快速向旧机器数字化并将其连接到默认的成本框架内。

Taking the dread out of mistakes

如果您想成为反脆弱,比Harting和其他公司就像强大,你需要在试验时主动地寻找系统中的弱点。在应该发展的系统中,您无法预测的各种错误,尤其是当系统需要扩展到未知的地区时。因此,您的系统将系统进行连续故障,并使用Netflix的Chaos Monkey等工具构造失败的子系统。

If you do all of this, you will start to objectify errors at your company and make dealing with errors a matter of normality. And when errors become 'business as usual', no one will be afraid of taking a risk, trying out a new idea, a new product or a new service and seeing what happens when customers interact with it. That's how you quickly find solutions that really work in the future.

At Amazon, our approach for systematically and constructively dealing with errors is called the "cause of error" method. It refrains from seeking "culprits". Instead it documents learning experiences and derives actions that ultimately improve the availability of our systems.

从根本原因到创新

该方法首先要求通过分析其立即根本原因并采取步骤来修复错误,以便尽快缓解损坏并恢复初始运行状态。但是我们并不包含该结果的内容。我们进一步进一步,试图从事件中提取最大的洞察力。这个过程很快就开始了一切努力为客户工作。

A key element of our cause-of-error method is asking 5 'Why?' questions (a technique that originated in quality control in manufacturing). This is important because it determines the fundamental root of the problem.

拿一个网站的案例:为什么去周五下来?Web服务器报告超时。为什么没有超级时间?因为我们的Web服务过载,无法应对高流量。为什么Web服务器过载?因为我们没有足够的Web服务器来处理高峰时段的所有请求。为什么我们没有足够的Web服务器?因为我们在计划中没有考虑可能的需求峰值。我们为什么不考虑我们的规划需求的峰值?在这个过程结束时,我们确切地知道发生了什么,包括哪些客户受到影响。 Then we're in a position to distill an action plan that ensures that specific error doesn't happen again.

通常,应用这种cause-of-error方法allows us to find breakthrough innovations, in the spirit of Nassim Taleb. That's how the solution Auto Scaling was created, after a certain client segment was fighting with strongly fluctuating hits on their website. When the load increases for a website, Auto Scaling automatically spins up an additional web server to service the rising number of requests. Conversely, when the load subsides, Auto Scaling turns off web servers that are not needed in order to save cost.

它揭示的是:组织需要超越肤浅的成功。这对于系统的开发以及商业模式是如此。必威体育精装版app官网如果您希望在复杂的环境中保持敏捷,即使意味着离开舒适区,也必须遵循此路径。如果我们将这些想法转移到组织背景下,可能会考虑三个方面:

1.事实上拥抱错误

杰夫贝罗斯曾经说过亚马逊:“我相信我们是世界上最好的地方失败。”激发了很多人来试验,发现错误并将它们转化为创新的东西。这样的声明鼓励你的人积极寻找错误,并将它们变成创新。和:当他们发现错误时奖励员工。我们从亚马逊的开发工作中学到的是,您需要始终超越错误的表面。必威体育精装版app官网我们最好的产品来自错误。

2. Make due with incomplete information

德国公司拥有彻底和完美主义者的传统。但是,在数字世界中,您需要稍微松开这些原则。技术正在变化如此之快;你也需要快。即使您所拥有的信息也不像你想要的信息一样做出决定。当他在他最近给股东写入股东的最新信中写下时,“大多数决定可能会在约70%的地方作出的信息时,杰夫贝佐斯的信息你希望你有。如果你等到90%,在大多数情况下,你可能很慢。加上,无论哪种方式,你都需要迅速认识和纠正不良决策。如果你擅长纠正,出错可能比你想象的要少得多,而缓慢则肯定会昂贵。“

3. Praise the value of learning

I've stressed the need for companies to have a systematic approach to how they deal with errors. But your approach will only work if it's part of your overall culture. Make sure you understand your DNAandknow what people are thinking and talking about on the work floor. Openly praising experimentation in product development and encouraging people to find errors will come across as empty rhetoric if your employees really do have reason to fear repercussions for themselves personally if they make mistakes.

It is a matter of leadership to foster and shape a culture of experimentation that is practiced day in, day out.

Whatever companies come up with in order to systematically learn from mistakes, it will make them better in competing in the digital world. And it will give them the freedom and courage to take their systems, solutions and business models to a higher level.

Comments