However, this appraisal does not quite match the mood as we see it. On the contrary, we're on the fast track to actually demonizing Germany's status as an economic hub. Despite all our successes.
That fact inspired us to ask whether this skepticism and dissatisfaction is the foundation of our success, or whether a less critical view and evaluation would lead to even greater success. The answer is somewhat banal: if the dissatisfaction, German 'Angst', and concern are justified, then they're helpful. But if the dissatisfaction, German 'Angst', and concern are not justified because they are the result of uncertainty and false assumptions, then they are a hindrance. As such, a solid analysis of reality and sophisticated forecast models would be ideal here. That is more or less achievable in systems that are at least reasonably stable. Still, what is the answer when circumstances are increasingly influenced by VUCA – volatility, uncertainty, complexity, and ambiguity?
There are models and methods to help those seeking answers. These include the Cynefin framework that recognizes four basic problem types in complex systems:
1. In simple (or obvious) problems, the relationship between cause and effect is clear. Obvious problems can be resolved using empiric knowledge and judgment.
2. Stable causality is also a feature in complicated problems, though the number of influencing parameters is so high that the relationship between cause and effect is no longer discernible using intuition or experience alone. Analytics is useful in these cases.
3. When dealing with complex issues, analytical capacity will sooner or later fail due to the sheer number of variables where there is quite possibly no stable cause and effect relationship (over time). Experimentation is the most suitable solution in complex scenarios.
4. The fourth domain is the realm of the chaotic, meaning a state where there is no longer any causality, just pure, random chance. There's only one thing that works here: luck.
Each problem type calls for different potential solutions, and so for different organizational capabilities. If our past experience is based on skills in resolving the first and second type of problems, then VUCA is going to be a challenge:
We'll have to learn to deal with greater complexity, speed, and uncertainty, and to find alternatives, or at least things to supplement, our conventional competencies. Empirical knowledge and analysis of stable cause and effect relationships are essential, but possibly no longer enough. Methods such as big data, design thinking, early prototyping, and agile are elbowing their way in. No doubt our "Teutonic virtues" will ensure that we can learn these methods quickly, although they will only deliver their full impact when we also modify our values and behaviors, i.e., our mindset. There must be movement in the trade-offs between speed, security, and perfect quality.
Summary: We should be proud of those capabilities we already possess – without resting on our laurels. Let's instead look forward to actively shaping the future! To do this we need to understand what obstacles might emerge in future and develop solutions to overcome, work around, or sweep them out of the way.