Complex issues in the economy

Complex issues in the economy: a definition

Complex situations are characterised by the mutual influence of many participants. Each influence triggers a change in the behaviour of the influenced party, which in turn affects all other parties involved. Completely unexpected events can result from such a constellation: Excalating developments or stagnating situations can arise, and it can lead to a trend reversal. The faster the interactions between the participants take place, the more dynamic these developments become. Dynamic complexity then occurs.

Examples of complexity in business

To illustrate complex behaviour, the following examples are useful:

Electromobility: The market development of electromobility is an example of complex interrelationships. Several actors depend on each other for the market for electromobility to emerge and grow. Vehicle manufacturers need battery manufacturers. Drivers need not only vehicles, but also a charging infrastructure. However, the charging infrastructure will only come into being if there are enough electric vehicles on the road. Society has an interest in sustainable business. This presupposes that batteries are either put to subsequent use or recycled. The market participants who want to create after-use or recycling opportunities need sufficient old batteries from the electric vehicles. Orchestration of all stakeholders is needed to develop the market for electric mobility. Development can be supported through subsidies and communication.

Global economy: With the effectiveness of the Corona-related restrictions since March 2020, the German SME economy was significantly weakened. Asian producers dropped out, and the German economy suffered. Politicians took it upon themselves to promote independence from Asian companies. The opposite was achieved: many large companies stopped production completely during this period in order to protect their employees. They were either sufficiently capitalised to bridge the difficult period or were propped up as systemically important companies. This had an impact on the entire supply chain. From one day to the next, many large companies, especially in the automotive industry, stopped calling their suppliers. Many of these suppliers were medium-sized German companies, not all of which had the necessary capital strength to withstand such a cut-off of orders. The announced state support came too late for some of these companies. They ended up in insolvency. Asian companies quickly appropriated the know-how of German suppliers and took over the role of German companies in the supply chains. Thus, the dependence of German companies on Asian suppliers increased instead of decreasing during this period. Complexity was underestimated.

Understanding complex issues and dealing with them sensibly

In complex situations, there is typically no immediate solution. Decisions have to be made on the basis of incomplete information. One must even recognise and accept that certain knowledge is not available (non-knowledge). This is a very important first step. Since, as a rule, it is not immediately recognisable through mathematical functions that describe the interrelationships, simple logical approaches to solutions do not work. Unpredictability and change are closely connected with complex situations.

There seem to be no justifiable “right” answers that will last. Examples include the observation of ever larger budget rejections and planned scenarios that do not materialise. Unconventional approaches such as pattern recognition combined with guided experimentation and maintaining as much flexibility as possible can bring about workable solutions in complex environments. But simply waiting until contours emerge that allow a better assessment of the situation can also be a promising approach. In complex environments, neither clerks nor experts who are familiar with the underlying issues are likely to come up with solutions. What is needed are experts who search for solutions on a meta-level, for example through data mining and data-based business analytics.

In complex environments, it is especially important to position companies so flexibly that they can react flexibly to changing environmental conditions. The more adaptable your company is, the more resilient it is. In other words: The more agile your company is, the better you can stabilise it. The supposed contradiction contained in this sentence is now probably self-evident.

But vigilant observation also helps. Instead of thinking in terms of uncertainties, think in terms of probabilities. This leads you mentally out of the perception of not being able to react sensibly at all to complex developments. You can also train your awareness of factors that accelerate or dampen developments. You can install “sensors” in your company to receive relevant information that allows you to recognise developments and introduce “feedback processes” to react effectively to them. In this way, you can stabilise your business by dampening the impact of changes in your environment on your business.

The next level is chaotic circumstances.


What are your challenges?

Restart Dialogue