#23 How to get a grip on the future with simulations
Who could have foreseen this? Corona, the Ukraine-Russia war, inflation and a shortage of many important resources? No one? Or is there a crystal ball that can help you prepare your company for various scenarios in good time? 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, analyze them and train the decisions of those involved. In this episode, you will find out what is behind it all, how to successfully set up and carry out such a simulation and what advantages your company can gain from it for the future.
SHOWNOTES:
Christian UnderwoodProf.JürgenWeigandandhttps://www.juergenweigand.comUnderwoodGmbHHopeis not astrategyWHUSimulations
The book Hoffnung ist keine Strategie jetzthiervorbestellen.
Detailed episode description:
Table of contents:
- Simulations in the strategy context- Business wargaming- Collecting and using data- Intelligent algorithms- Training decision-making with simulations- Raising awareness through scenarios- Simulations as preparation for the future- Learning and thinking beyond your own limits- Tips for implementation - Contact- Shownotes
Today's episode focuses on the key question: Can you make better decisions with simulations?
The direct answer to the question is yes, you can. However, the decisive factor here is how you define a simulation and how you then use it.
Therefore, the significance of simulations in the strategy context should first be clarified.
Simulations in the strategy context
Simulations were originally developed in the military as an application of strategy. The famous sandbox games are often shown in films. Older men stand around a sandbox, move troops around and simulate attacks and defenses. This is the basic idea behind a simulation. Different, previously defined scenarios are played out to see how they develop in the interaction. In technical terms, this is also known as wargaming or, in a 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. External parties are also often invited to participate. The aim is to test the previously logical, rational considerations. Emotions are also added to the role play, as each actor takes the approach of winning from their current role. This is a good way of testing what goes beyond normal rationality and what possibilities or outcomes could arise.
Collect and use data
Data is required as a basis for analyzing various scenarios. A distinction must be made here as to whether something is to be analyzed at its highest level, only very generalized or whether quantitative things are also to be derived. The more quantitative 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, scenarios in which competitors or market conditions play a role also require data about them. 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 existing product is to be repositioned with competitors. The question can then be formulated in general terms as to how customers will react if the company changes its market orientation slightly upwards or downwards.
Aldi and Lidl provide an example of this. They are currently pushing various areas of their stores upwards in the direction of Rewe and Edeka. Wargaming is a good way of testing how customers react in certain areas and what stumbling blocks could arise. You can also see how the competitors move in different scenarios in order to derive an optimal decision. All existing tools can also be used for this purpose. For example, if data on customer behavior is to be generated, traditional market research can be carried out with surveys, test markets, etc. These results can then be used for the product strategy. These results can then be used for wargaming in order 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. In other words, 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 be doing something fundamentally wrong. On the market demand side, on the other hand, market research can be carried out. However, clever people within the company who are responsible for sales, for example, and are therefore close to the customer, can often also provide information. They can also provide answers to questions that may be quantitative, but are certainly qualitative.
Intelligent algorithms
In the past, people would have said that the results are only as good as what I have programmed. Nowadays, however, there are self-learning algorithms. This gives you a lot more options and these algorithms can generate scenarios independently if they are really ideally formulated. This may lead to completely different solutions than initially thought. For example, Google has managed to beat the best Go player in the world with Go - using their simulation. Of course, you have to consider the extent to which this is really transferable to normal companies. But a lot is possible in this direction - either programmed with apps, artificial intelligence or just on a qualitative level.
In practice, this is mainly used today by companies that make heavy 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 keep track of the entire diversity and recognize patterns at a glance. Automated processes fed with intelligent algorithms, on the other hand, are perfectly capable of doing this. However, a little caution must be exercised here, because ultimately it should be known for strategy development whether it is a matter of symptoms or consequences that have causes. In order to change something, an attempt must first be made to establish a cause-effect relationship. With big data, as used 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 were also bought by other customers with similar interests. These are correlation analyses. Which work absolutely brilliantly. But if a strategy is to be developed and implemented for the company, it must be 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. The topic of simulation can also be used excellently in teaching. After all, you only get better if you apply and practise things independently. It's the same with decision-making. When you practise making decisions, you also become more aware of where you may be making mistakes. This is where topics such as cognitive biases or bounded rationality come into play. All of this can be trained in a simulation in a protected environment, which could be compared to the Lufthansa flight simulator. There the pilots have to train for all possible situations, even a crash, and at the same time do not put themselves in any danger.
Insights that emerge from such simulations in companies are often already familiar scenarios. For example, understanding how interdependent the various 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 connections have been recognized too late and that one's own goals may have been missed, strengthens awareness of this. The important thing about simulations is to be able to make even the stupidest decisions in a protected environment and to check them again afterwards. This also gives you the opportunity to test the "what if". This in particular can often really help. When decisions are made with good results, you tend to be satisfied, but the crucial question should be whether even better results could have been achieved. In addition, whether the results may only have been good because others made decisions that were beneficial to your own company and the success is therefore not due to your own strategy or tactical measures. At this point, a simulation offers the opportunity to clearly recognize correlations and train to perceive as many things as possible at the same time.
Raising awareness through scenarios
Experience shows that teams in companies often work very interdisciplinary and on their own silo topics. This means that everyone thinks for themselves, often only for their own organizational unit, but in the context of the simulation, when it comes to making decisions under time pressure, the exciting realization often comes 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. It is not possible to think about decisions for as long as you like and make further improvements. At some point, decisions have to be made and they have consequences. If these are positive as expected - wonderful. However, there are often also negative consequences and then the causes have to be found. Some managers think they can make decisions intuitively based on their extensive experience, but there is a danger here 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 to go beyond one's own convictions, review the decision once again and play through a scenario for the future that may look completely different from what is expected.
Simulations as preparation for the future
In these volatile times, time horizons are getting shorter and shorter. Nobody can foresee changes, disruptions and factors such as the coronavirus crisis or the war in Ukraine. It is therefore all the more important to be prepared for things that are not necessarily expected in the future. Thinking ahead and possibly writing down and outlining the various scenarios can really help here. After all, this is how simulations in the corporate environment came about. Shell was the first company to introduce this in the 1960s. An entire unit was specialized in thinking ahead and researching possible scenarios. At the end of the 1960s, there was one scenario, the so-called oil price shock, which actually happened at the beginning of the 1970s. So Shell was already mentally prepared for it. This is exactly what is meant by the use of simulations. Regardless of whether they are qualitative or quantitative, driven by artificial intelligence or not. The aim is 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, tested.
Learning and thinking beyond your own limitsYou can learn how to react in unexpected situations. This learning never stops. To briefly refer to the book "Hope is not a strategy", where the topic is taken a little further: To continue learning from the simulation - 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 has arisen at that point and also to simulate it in a very small way. However, this also requires a certain amount of thought and possibly also resources. Strategy simulations do not always have to be large-scale. Many simulations are also used in the field of logistics and operations, where those responsible want to explore the consequences of, for example, realigning or replacing a machine. As already mentioned, it is very important to move away from "silo thinking" and think outside the box. This will move 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 way and can specifically point out the meanings and repercussions for other areas.
Tips for implementation Finally, there 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 existing data is with Excel, where you can enter the data and try it out, change parameters and analyze how the results turn out. 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 need to be made. If you want to go further and shed light on a specific problem, there are problem solvers. For example, the software developed independently by Jürgen Weigand, which can be used for this purpose. It just has to be clear that this simulation or such software only works well if the data entered is the data that is really needed. For example, if decisions are to be made in pricing, data on the cost side and the market, as well as a price idea, must be available. Scenarios can then be tested and simulations can be made as complex as required. However, the following applies here: The more complex, the more varied the results can be. Hence Jürgen's recommendation at this point: keep it short and simple. The result is a prediction, a recommendation, which can then possibly be reviewed internally in a business wargaming session. The truth is on the field.contactFor all those who are interested in conducting their own simulation with his team, there are various simulation software solutions from Jürgen Weigand. You can find all the important information in the show notes. 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 UnderwoodProf.JürgenWeigandandhttps://www.juergenweigand.comUnderwoodGmbHHopeis not astrategyWHUSimulations
The book Hoffnung ist keine Strategie jetzthiervorbestellen.