What is the most efficient path selection

Leo Mattes

In the first two posts I first derived a utopia for maximum prosperity and then gave further explanations about maximum productivity. In the post about my motivation for this blog, I often talked about path dependencies. This article is about the properties of path dependencies.

The theory of path dependencies calls into question the statement that the most efficient technology will always prevail on the market. The theory is based on three cornerstones, which are responsible for stabilizing and continuing a chosen path.

Increasing returns

“Increasing returns” means the consideration that it is more economical to keep a known solution or to develop it further than to look for a completely new solution. Once you have invested in something and received a result, it is difficult to discard it because the result can be used even if it is not the perfect solution.

Momentum

“Momentum” means the fact that further products or services are being developed around the existing solution. A growing ecosystem is thus developing around the existing solution.

Lock-in effect

The continuation and expansion of an already known solution thus lead to the fact that the path taken is further developed and trodden on. This is called the “lock-in effect”. This leads to a degree of irreversibility to which the actors continue to submit, whether they want it or not. These structures are not easy to break.

Path dependencies arise from the fact that the selection process for finding a solution is influenced by historical decisions ("history matters"). Small events in the past influence the path and other processes deterministically, since the states outside the started path become improbable. This theory is very similar to the theory of evolution, in which a path of irreversibility is followed through variation and subsequent selection.

An example: Up until the 1910s it was by no means clear whether electric, steam or combustion engines (petrol, diesel, gas) would prevail for road traffic. Around 4,200 automobiles were built in the United States in 1900. 1572 of these were operated with electricity, 1600 with steam and 1028 had an internal combustion engine or another drive concept. Today we know that the internal combustion engine has prevailed. A large ecosystem has developed around this internal combustion engine. In the car, units such as the turbocharger, an exhaust system or a cooling system were added, which are part of this path dependence. Furthermore, a large infrastructure of pipelines, filling stations and workshops developed around cars with combustion engines, which are also the result of the first technology decision.

Path termination

Now, of course, the question arises as to how such a path can be broken. The path dependence theory states that it takes external shocks from entrepreneurs or legislators to break and leave paths. Internal processes find it difficult to leave a path, as a self-reinforcing lock sets in due to the tendency to persist. There is therefore almost no space for the actors to strategically and systematically influence path development.

Path creation and breakout

In order to create a path or to break out of an existing path, the actors must consciously deviate from the known rules and procedures. However, no arbitrary deviation is possible. If the deviation is too great, this leads to rejection and incomprehension. If the deviation is too small, this does not lead to any significant innovation. Current structures must therefore be modified in such a way that they can serve as the basis for a new path. In addition to a deliberate deviation, there are other challenges. On the one hand, the new path must be embedded in parts of the old one; on the other hand, it requires a mobilization of resources as well as a translation of the change for an understanding and higher acceptance.

How do we find the global optimum?

Path dependencies are local optima. But if we want to achieve maximum prosperity or maximum productivity, then we have to look at how we can find a global optimum based on physics and the developed technologies.

In mathematical terms: in order to be able to say with certainty that we have found the global optimum, we would have to try out all the possibilities of the parameters. Since we don't have the time to do this, we need good search algorithms.

I'm a big fan of the books and speeches by Gunter Dueck, former mathematics professor, IBM Chief Technology Officer. It describes the search for an optimum from the point of view of a hiking group that wants to climb the highest peak but does not have a map.

A group of hikers in search of the highest peak

At the beginning, the curious and adventurous hikers look around near their starting point. You measure the slope and decide to head in the direction with the greatest slope. The hiking group therefore always runs uphill until the slope becomes zero and a summit is reached. Once at the top, however, they do not know whether it is the highest peak. But first you make yourself comfortable and set up a kiosk, consolidate the paths and enjoy the view. But now there is one hiker in the group who is too bored and needs an adventure. He sets off and of course has to climb downhill again first. Once in a valley, he decides to walk uphill in the other direction. After a while he also reached a summit, which is much higher than the previous one. He decides to turn back and convince the hiking group of the new mountain. The group is of course not enthusiastic, because they have now built a cable car, hotels and a summit cross, so of course nobody wants to climb downhill again and start building the infrastructure again on another mountain. The hiking group is in a path dependency.

During my studies in mechanical engineering and technology management, the theory of path dependence did not come up. Only the “innovators dilemma” and “sunk costs” were briefly discussed. But I am convinced that understanding path dependencies is extremely important. It shows that leaps in productivity and the discovery of new peaks are necessary to find the global optimum. There is also an explanation for the persistence tendencies of the actors.

I would like to conclude with advice from Gunter Dueck for all innovators and discoverers of new paths on how best to escape the tendency to persist.

"Work underground as long as you can." - Gunter Dueck

I am happy if I was able to inspire you with the explanations on path dependencies and if you subscribe to my newsletter so that you don't miss any more posts.

Best Regards

Leo Mattes