Strategy Talk with Christian Underwood and Professor Dr. Jürgen Weigand
Who could have foreseen: Corona, Ukraine-Russia war, inflation and a shortage of many important resources? Nobody? Or is there a crystal ball that can help you prepare your company in time for different scenarios? There is! Even if not in the form of a glowing crystal ball with a fortune teller.
Simulations in the corporate context can help to run through scenarios, to analyze them and to train the decisions of those involved. In this episode, you'll learn what's behind it all, how to successfully set up and run such a simulation, and what benefits your company can gain from it for the future.
SHOWNOTES:
Christian Underwood
Prof. Jürgen Weigand and https://www.juergenweigand.com
Underwood GmbH
Hope is not a strategy
WHU
Simulations
Pre-order the book Hope is not a strategy now here.
Detailed episode description:
Table of Contents:
- Simulations in the context of strategy
- Business wargaming
- Collecting and using data
- Intelligent algorithms
- Training decision-making with simulations
- Strengthening awareness through scenarios
- Simulations as preparation for the future
- Learning and thinking outside the box
- Tips for implementation
- Contact
- Shownotes
Today's episode is themed around the question: Can we make better decisions with simulations?
The direct answer to the question is, yes, you can. However, the most important thing here is how you define a simulation and how you then use it.
Therefore, the importance of simulations in the strategy context should be clarified first.
Simulations in the context of strategy
Simulations originated in the military - as an application of strategy. Often the famous sandbox games are shown in movies. There, elderly gentlemen stand around a sandbox, move troops and simulate attacks and defenses. This is the basic idea behind a simulation. The idea is to play through different, predefined scenarios to see how they develop in the interaction. In technical language, this is also called wargaming or, in the corporate context, business wargaming.
Business wargaming
Business wargaming is primarily a role-playing game in which the various scenarios are played out from the perspectives of different parties. For example, the company, its customers, competitors and members of the company take on different roles. Often, external parties are also invited to participate. The goal is to test the previously logical, rational considerations. In addition, emotions are also involved in the role play, as each actor takes the approach of winning out of his or her current role. This is a good way to test what goes beyond normal rationality and what possibilities or what results might emerge.
Collect and use data
Data is needed as a basis for the investigation of different scenarios. Here it is to be distinguished whether something is to be analyzed on its highest level, only very generalized or whether also quantitative things are to be derived. The more quantitatively oriented the analysis, the better and the more data must be used. For the company, this means that it needs data from within the company. Similarly, if scenarios involve competitors or market conditions, data about them will also be needed. If, on the other hand, scenarios are only to be examined at an upper level, then a general question can often be asked, for example if an already existing product is to be repositioned with competitors. Then the question can be formulated generally, how the reaction of the customers will be, if the enterprise changes its position in its market orientation somewhat upward or downward.
Aldi and Lidl provide an example of this. They are currently pushing up various areas of their stores in the direction of Rewe and Edeka. Wargaming would be a good way to test how customers react at certain points and what stumbling blocks could arise. In addition, it is possible to see how competitors move in different scenarios in order to then derive an optimal decision. Any existing tools can also be used for this purpose. For example, if data on customer behavior is to be generated, traditional market research with surveys, test markets, etc. can be conducted. These results can then in turn be used for wargaming to define the scenarios as well as possible. At this point it may sound like a lot of complicated programming work. However, it is not, provided you know where the data is located in the company and how the data can be used where it is needed. That is, you have to find out where the interfaces are. But usually, at least cost data is always available in the company - otherwise the company would basically be doing something wrong. On the market demand side, on the other hand, market research can be done. However, clever people in the own company, who are responsible for sales, for example, and are therefore close to the customer, can often provide information. These can additionally provide answers to perhaps quantitative, but definitely qualitative questions.
Intelligent algorithms
In the past, one would have said that the results are only as good as what I have programmed. In the meantime, however, there are self-learning algorithms. This gives you much more options and these algorithms can, if they are really ideally formulated, generate scenarios on their own. In this way, completely different solutions may be thrown up than were initially thought. For example, Google managed to beat the best Go player in the world with Go - with your simulation. Of course, one has to consider to what extent this is really transferable to normal companies. But a lot is possible in this direction - either programmed with apps, artificial intelligence or just on the qualitative level.
In practice, this is mainly used by companies that make extensive use of Big Data. At Amazon, for example, the entire background of the pricing topic is simulated automatically. If Big Data is to be used, it must always be automated. This is because no single person can survey the entire variety and recognize patterns at a glance. Automated processes fed with intelligent algorithms, on the other hand, are quite capable of doing this. However, a bit of caution must also be exercised here, because ultimately it should be known for strategy development whether we are dealing with symptoms or consequences that have causes. In order to change something, therefore, an attempt must first be made to establish a cause-effect relationship. With Big Data, as applied by Amazon and others, the focus is on correlation. This is a very good concept. Because it means that when a customer wants to buy a certain product on Amazon, they are immediately offered similar products that other customers with similar interests have also bought. These are correlation analyses. Which work absolutely brilliantly. But, if a strategy is to be developed and implemented for the company, it must become clear what is cause and what is effect.
Train decision-making with simulations
Now we return thematically to the implementation of business wargames and how simulations can help to make better decisions. For this purpose, the topic of simulation can also be used excellently in teaching. Because only when you apply and practice things on your own, you get better. It's the same with decision-making. Because when you practice making decisions, you also become more aware of where your own decision-making errors may have been made. At this point, topics such as cognitive biases or bounded rationality come into play. All of this can be trained in a simulation in a protected setting. One could compare it with the Lufthansa flight simulator. There the pilots have to train all possible situations, even a crash, and at the same time they do not put themselves in any danger.
Insights that come to light through such simulations in companies are often already known scenarios. For example, understanding how interdependent the different elements in the company are. This is something that everyone actually knows, but to really feel it in a business wargame and to realize that interdependencies have been recognized too late as a result, possibly missing one's own goals, strengthens awareness of this. The important thing about simulations is to be able to make the dumbest decisions in a protected environment and to check them afterwards. This gives the opportunity to test the "what if". Especially this can often really help. Decisions with good results tend to make you happy, but the crucial question should be whether even better results could have been achieved. In addition, whether the results might only have turned out well because others made decisions that were beneficial for one's own company and the success therefore cannot be attributed to one's own strategy or tactical measures. At this point, a simulation offers the possibility to clearly recognize correlations and to train to perceive as many things as possible at the same time.
Raising awareness through scenarios
Experience shows that teams in companies often work in a very interdisciplinary way and on their own silo topics. This means that everyone thinks for themselves, often only for their own organizational unit, but in the context when the simulation is specifically about making decisions under time pressure, there is often the exciting realization that close cooperation and communication with other colleagues and departments plays an incredibly important role. This factor should also take place and be practiced in simulations, because in reality there is time pressure. Decisions can't be thought about and reworked for an arbitrary amount of time. Decisions have to be made at some point and they have consequences. If these are positive, as expected - wonderful. Some managers think they can make intuitive decisions because of their extensive experience, but there is a danger that something is extrapolated from the current situation into the future that will not necessarily be the case in any form. In addition, it is always helpful, beyond one's own convictions, to re-examine the decision and to play out a scenario for the future, which may also look quite different from what is expected.
Simulations as preparation for the future
In these volatile times, time horizons are getting shorter and shorter. No one can foresee the changes, disruptions and factors such as the Corona crisis or the Ukraine war. Therefore, it is even more important to be prepared for things that are not necessarily expected in the future. Thinking ahead and possibly writing down and outlining the different scenarios can really help here. After all, that's how simulations came about in the corporate environment. Shell was the first company to introduce that to themselves in the '60s. There was an entire unit just dedicated to thinking forward and exploring possible scenarios. At the end of the 60s, there was a scenario, the so-called oil price shock, which actually happened in the early 70s. So mentally, Shell was already prepared for that. This is exactly what is meant by the use of simulations. No matter if they are qualitative or quantitative, driven by artificial intelligence or not. There is an attempt to make educated guesses. The future is uncertain, it is always a guess as to how it will really turn out, but this guessing can be improved and to a certain extent also tested.
Learning and thinking beyond one's limits
It is possible to learn how to react in unexpected situations. This learning never stops. To briefly refer to the book "Hope is not a strategy", where the theme is even taken a bit further: From simulation, to continue learning - along the workflow at the moment it is actually applied, to get exactly the piece of knowledge that is needed to solve the problem that occurred at the point and also to simulate it in a very small way. Here, however, a certain amount of thinking and possibly resource input is also required. The strategy simulations do not always have to be large ones. Many simulations are also used in the logistics area, in the operations area, where those responsible want to explore the consequences of, for example, aligning or replacing a machine differently. What is very important here, as already mentioned, is to get out of "silo thinking" and think beyond one's own boundaries. This moves the company forward. The connection should also be seen here, if simulations are used in different forms and in different parts of the company, then there should also be someone who thinks in a higher level and can concretely point out the meanings and repercussions for other areas.
Tips for implementation
Finally, here is some advice on how to take the first steps towards successful simulations and how your company can also benefit from them.First of all, the easiest way to simulate something based on available data is with Excel, where you plug in the data and try it out, change parameters and analyze how the results turn out. In addition, you can also look at supply and demand based on data. The simplest form is to observe what effects occur when data is changed. Since Excel is the only tool here, no investments have to be made.If you want to go further and look at a specific problem, there are problem solvers. For example, the software developed independently by Jürgen Weigand, which can be used for this purpose. It must only be clear that this simulation or such a software only works well if the data entered is also that which is really needed. For example, if decisions are to be made in pricing, data about the cost side and the market, as well as an idea of the price, must be available. Then scenarios can be tested and simulations can be made as complex as desired. However, the following applies here: The more complex, the more varied the results can be. Therefore Jürgen's recommendation at this point: keep it short and simple. The result is a prediction, a recommendation, which can then possibly be checked again internally in a business wargaming. The truth is on the pitch.ContactForall who are interested in running their own simulation with his team, there are several simulation software solutions from Jürgen Weigand. In the Shownotes you will find all important information. You are also welcome to contact us at this point and we will help you to make better decisions with the help of simulations.
SHOWNOTES:
Christian Underwood
Prof. Jürgen Weigand and https://www.juergenweigand.com
Underwood GmbH
Hope is not a strategy
WHU
Simulations
Pre-order the book Hope is not a strategy now here.