Written by Frederike Peffer, Customer Success Manager at aifora
We all make countless decisions every day. Some of them we make deliberately, others we make subconsciously. Some are easy for us, and others we debate over and over again in our head until we come to a conclusion. But at the end of the day, every decision is a risk-taking judgment.
In day-to-day business, there is hardly any time to assess all impacts and consequences thoroughly. However, impact assessments are the basis for all decisions, whether they are personal, social or work-related. Executives often believe that they have to choose between a “right” and a “wrong” compromise. But are these decisions really effective?
The Right Decision
Decisions must be made quickly and in the face of uncertainty –especially now as we’re still fighting the COVID-19 pandemic, which has made the future more unpredictable than ever. Many retailers are facing bankruptcy as they have struggled to quickly make the right decision regarding disrupted supply chains and demand fluctuations while also dealing with other issues like employee absence and employee safety as the virus continued to spread. Others were “luckier” due to their ability to quickly adapt and willingness to embrace technological advancements to support the decision-making process.
Jean-Christophe Babin, CEO at Bulgari, said in an interview about the current crisis:
But how do we make the right decision? Well, one thing is clear – relying solely on your gut is definitely not the right way to go.
A Systematic Process
The Nobel prize-winning psychologist and economist, Daniel Kahneman, discovered that most business decisions are not based on facts. The lengthy process of rational consideration and the inclusion of facts is usually too cumbersome and exhausting. Rather, decisions are guided by emotions and often made intuitively.
In his book “Thinking, fast and slow”, Kahneman defines two different systems for decision-making, where ‘System 1’ describes the non-consciously working and intuitive system, while ‘System 2’ refers to the consciously working problem-solving system.
System 1
- decides intuitively
- quickly
- unconsciously
- controlled by emotions
- essential for survival
x prone to error
System 2
- logical
- calculated
- unconsciously
- rational thinking
- less errors
Nevertheless, facts should be the basis for well-founded decisions, at least in business. A report by Forrester shows that 74 percent of companies would like to work data-driven, but only 29 percent have sufficient skills.
A positive development is the vast amount of data that is archived in most companies nowadays, but the problem remains that for most it is not possible to retrieve the necessary data at the push of a button.
Evaluating complex scenarios is already a challenge with regard to the amount of internal data collected over many years. In addition, there is external data that needs to be included, such as competition or weather data.
An attempt of a reality representation
A model allows users to simulate processes “on a small scale”, that would not be possible or useful in reality due to their effort or risk. Data modelling in Excel therefore only creates a simplified image of a partial reality. There is a risk that certain connections are overlooked or that certain effects have not been taken into account. Neglecting important factors brings unforeseen consequences and is often the reason why objectives are not met, projects fail, problems grow, and new problems arise.
Strategic decisions should be well-founded, transparent and take all consequences into account. Only when all possible consequences are known, can businesses firmly determine whether an objective can be achieved with what measures, and what undesirable side effects are to be expected. As a rule, the Controlling department is commissioned to prepare data ad hoc and to obtain information from the specialist departments in order to quickly create a business case. So how is it possible to provide data in such a way that companies can use it as a quick basis for decision-making without constantly falling back on System 1?
Decision Analysis with Simulations & Dashboards
The word “simulation” has its origins in the Latin “simulatio”, which can be translated into “adjustment”. Colloquially, a simulator is “someone who pretends to be”. In scientific terms, a simulation is the carrying out of a “what if” analysis. It is therefore about understanding what can happen in a given situation. This approach makes it possible to assess the consequences of a specific action or decision and to “try out” the future.
Therefore, simulations are scenarios that can be run using a model. For example, the best case, the worst case or the most likely case can be simulated. By including complex data sets, different scenarios can be mapped. These can be shaped to different degrees by applying different business rules or by implementing a different strategy.
Assessing the consequences of these scenarios is the prerequisite for reflected, well-founded and forward-looking decisions. A dashboard then visualizes and interprets data from complex simulations and presents the results clearly so that they are easier for the human eye to grasp.
Dashboards help users get to the point and quickly identify trends. Currently, dashboards can help to apply the Corona effect in models and test different scenarios with the help of simulations. This enables decision makers to make well-founded, for example regarding pricing and inventory management.
Different strategies or actions can also be compared in a dashboard. In this way different questions can be answered with the help of data:
- How will consumer demand develop under different conditions?
- Which strategy fits best to our business model?
- How will customer behavior change?
- How can we achieve our planned sales ratio?
Dashboards are therefore important for strategic decisions and serve management in making decisions through aggregated data, mostly in the form of KPIs. Moreover, they can also contain operational data, which facilitate daily decisions for different departments.
How a Simulation Approach can Help Retailers Make Better Decisions
While even the best simulation may not always be 100% right, data-driven decision-making is always more objective and more effective than any other approach. Retailers who still use spreadsheets for inventory and pricing decisions will soon be left behind in the retail race. With aifora, retailers can take advantage of their data and accurately forecast sales performance, profits and margins – while mitigating risks and eliminating nasty surprises.
