Optimizing decision-making: Efficient information filtering in shop floor management

In a business world characterized by a flood of data and time pressure, management is often faced with the challenge of filtering out the most important topics from a variety of topics. It is important to find the signal in all the noise, i.e. to identify from the constant stream of information that is really relevant for decisions and processes. This ability to separate important from unimportant is crucial in order to be able to act effectively and purposefully. In this context, both structured information processing for humans and advanced algorithms from a technological perspective play a role. They make it possible to set priorities clearly and ensure that management focuses its attention on the issues that have the biggest impact on company performance. The following shows how oee.ai helps to identify the most important information and optimize management decision-making through the use of visualizations and algorithms.

Pyramid principle: Structuring for clarity and efficiency through cause-and-effect relationships

The pyramid principle developed by Barbara Minto During her time at McKinsey, is a method of structuring information that aims to reduce complexity and create clarity in communication. The core of the principle is to arrange information hierarchically, with the most important and overarching points being presented first. This approach follows a pyramid structure: At the top is the core message or the main message, followed by supporting arguments or data with increasing levels of detail. This type of information preparation is particularly effective in management, as it enables executives to quickly grasp the essence of a topic without getting lost in details. By applying the pyramid principle, complex information can be brought into a clear, logical and easy-to-understand form, which significantly facilitates and speeds up decision-making.

Algorithms: Straight to the target based on data

The opposite approach is known as a scientific funnel, in which all details are communicated and presented until the key message is reached. What may be appropriate for scientific work is not practicable for people in the daily practice of operational management — look at all the details first before making a decision. However, you can rely largely on algorithms to help you prioritize activities. Visually, they start the analysis at the lowest data level and gradually consolidate the knowledge gained upwards. This type of analytics can be fully automated with oee.ai. The algorithm can make the consolidation steps transparent, but it doesn't have to.

Prioritization methods for managing production

The pyramid principle can be described as a “1:3:10” approach. Decision-making is structured in time: In one second, the process status is recorded, trends are identified in three seconds and, with ten seconds of attention, causes are visualized in order to then start analyzing problems and identifying activities. This procedure was exemplified on linkedin presented. In oee.ai, the corresponding widgets are configured so that the information is presented in the required order.

Alternatively, algorithmic prioritization can be used in oee.ai. Using specialized algorithms, oee.ai identifies the most significant losses or anomalies from the extensive data stream of the systems and actively notifies the need for action. In this case, the prioritization, which is carried out in the “1:3:10” approach with visual guidance by humans, is carried out by an algorithm and can be communicated independently of shop floor management. The algorithm can also make the decision process transparent, but it doesn't have to.

Focus on prioritized topics in shop floor management

The prioritized topics discussed as part of shop floor management are of decisive importance for a company's operational efficiency. By prioritizing topics, whether through visual dashboard configuration or algorithmic analysis, shop floor management can focus on the most important and urgent matters.

In practice, this means that shop floor meetings are more focused and goal-oriented. Instead of spending time reviewing less relevant data, participants can focus on the most critical points that have the biggest impact on production output and quality. This enables management and teams to react quickly to changes or challenges, develop effective solution strategies and thus continuously improve operational performance.

The use of prioritized information in shop floor management leads to improved decision-making, optimized processes and ultimately to an increase in the overall efficiency of the company.

conclusion

In a data-driven business world, the ability to efficiently filter and prioritize relevant information is critical. Two methods of prioritization — visual dashboard configuration and algorithmic analysis — optimize information preparation, prioritization, and finally decision making. The application of this prioritized information in shop floor management improves operational efficiency, makes it easier to respond quickly to operational challenges and thus promotes the overall performance of the company.

Both methods strive to get the signal in data noise and enable management to focus on the key issues.

Have we sparked your interest? Then feel free to contact us at info@oee.ai.

Author: Linus Steinbeck