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.




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。


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.



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.




2. Make due with incomplete information


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.