Trade-offs as a challenge
Making decisions in the event of conflicting objectives using mathematical optimization
A trade-off refers to the weighing up of two objectives that influence each other and are in conflict with each other. This means that only one goal can be improved at a time - at the expense of the other.
In most cases, we think of this as an economic trade-off. But we often encounter trade-offs in our everyday lives and we make a decision more or less consciously. And even plants have to face this problem: In order to ensure their survival in the best possible way, they make compromises between competing characteristics such as defense mechanisms on the one hand and growth on the other. A higher investment in their own defense system in the form of thorns, spines or chemical substances results in a lower investment in growth and vice versa.
In this blog post, however, we are of course not focusing on the topic of plant ecology, but on the economic aspect of trade-offs for companies. Using examples, we would like to provide an overview of possible economic trade-offs and show how the use of mathematical optimization can fundamentally change the way we deal with trade-offs.
Where there are goals, conflicts are not far away
Companies are often faced with the dilemma of pursuing different goals. They strive for efficiency and innovation. They want and need to be socially, ecologically and economically successful. And preferably all at the same time. The various objectives often compete for limited resources. Overall, conflicting goals and trade-offs are an everyday reality for companies and a challenge that needs to be overcome.
Conflicting goals in companies - examples
Short-term profit vs. long-term growth
A classic example of a trade-off in companies is the conflict between short-term profit and long-term growth. A company could, for example, achieve higher profits in the short term by cutting costs or holding back investments. However, this approach can lead to a loss of competitiveness or customer confidence in the long term, which jeopardizes the company's long-term success.
Cost vs. quality
Another typical example is the decision between cost and quality. If a company wants to offer its products or services more cheaply, the product result may suffer. On the other hand, costs increase if a company strives to improve its products or services. A trade-off between cost and quality must therefore be found here.
Costs vs. supplier diversification
A common trade-off in companies is between cost efficiency and supplier diversity. When companies consolidate their suppliers, they can reduce costs but run the risk of being more susceptible to delivery failures or quality problems. Therefore, when optimizing the supply chain, it is crucial to find a balance between cost efficiency and risk minimization.
Stock levels vs. delivery times
There is a fundamental conflict of objectives between minimizing stock levels and ensuring short delivery times. In order to keep storage costs low, companies often want to reduce stocks. However, this can lead to longer delivery times, which can have a negative impact on customer satisfaction.
Ecology vs. economy
The conflicting goals of economy and ecology challenge companies to reconcile economic success with environmental protection. The balance between profit maximization and sustainability is crucial. Environmentally friendly measures should not drastically increase costs. Companies must reconcile economic success and environmental protection in order to operate sustainably in the long term.
The examples mentioned are just a few examples of the complex interactions between companies. In fact, there are many other dilemmas at and between different corporate levels.
Goal: A good balance
Unresolved conflicts of objectives are forcing companies to rethink their decision-making processes and find ways of reconciling efficiency, social and environmental responsibility and economic success.
As already mentioned, companies have to deal with trade-offs and prioritize goals in order to achieve them. However, this also means that not all objectives can be fulfilled equally well. In some cases, decisions are made where an advantage can be achieved, but at the expense of another objective.
However, those who weigh things up carefully can get closer to an optimum that intelligently balances all interests. This requires a great deal of knowledge about the interrelationships of complex company processes and, as a result, well-founded recommendations for action.
Conflict resolution with the help of mathematical optimization
Once the conflicting objectives have been identified, the right measures need to be taken to eliminate them. In doing so, companies often have to weigh up which approach is the best with regard to the company's objectives.
The use of analytical methods such as the mathematical optimization. Mathematical models can be used to find the optimum balance - always taking into account all objectives, resources, variables and restrictions. Special solvers can then be used to generate optimal solutions for the conflicting objectives.
Further interesting content
Discover the optimization potential with OPTANO
The more objectives are formulated and the more they contradict each other, the more complex your company's planning becomes. However, this complexity should not prevent you from resolving your company's conflicting objectives. After all, the more complex the planning, the greater the potential for optimization. Find out below how you can exploit this potential with the help of OPTANO.
Planning software such as OPTANO creates the necessary transparency, offers well-founded recommendations for action and enables them to be compared in order to support data-driven decisions.
Creating transparency with OPTANO
In order to be able to prioritize competing goals, transparency is required first of all. The interdependencies between the individual goals must be recognized and understood. For prioritization, it is therefore advisable to define the objectives using KPIs (Key Performance Indicators) and weight them against each other.
As optimization software, OPTANO enables the analysis and representation of data as a model. By using mathematical optimization methods, a large number of different objectives can be taken into account and the trade-off of conflicting objectives can be made visible. In addition, interactions and inefficiencies are identified better and faster.
Well-founded options for action with OPTANO
OPTANO helps you identify the right measures to achieve the desired goals - analyzed on the basis of all the data to be taken into account. Ultimately, our optimization model takes over the planning of your business goals. Our powerful algorithms always calculate the best possible result from millions and millions of options.
And you can also cope with the growing complexity of your planning because, unlike manual planning, the model is so flexible that a large number of boundary conditions can be taken into account. There are therefore virtually no limits to the planning possibilities. No matter how the parameters change, you can always rely on OPTANO to make the right decision.
Compare alternative courses of action with what-if scenarios
With the help of prescriptive analytics, OPTANO not only formulates concrete options for action, but also enables the simulation of decisions and interventions in company processes through the use of what-if scenarios. For example, it is possible to investigate how changes in stock levels affect delivery times. Or what influence a consolidation of suppliers has on the resilience of the supply chain.
OPTANO thus ensures the necessary transparency and optimum planning throughout the company at all times.
And then there's the box tree moth...
To come back to our trad-off example from plant ecology: Unfortunately, plants often need a lot of time to adapt to new conditions. The current case of the box tree moth shows that a large population of introduced pests can lead to the destruction of plants in a very short time.
It's a good thing that companies can make adjustments much faster with the help of software.