Dive deep into your business processes and identify weaknesses and optimization potential. With Motion-Mining® you use advanced technology to make manual work processes more efficient and ergonomic.
Process analysis is the targeted examination of processes and the breakdown into their individual components with the aim of understanding the process and identifying weak points and optimization potential.
Process analysis distinguishes between different types of processes, including business processes and technical processes.
Process analysis forms the basis of process optimization in the company. In commercially oriented companies, process optimization helps to continuously improve the efficiency and effectiveness of existing work, business, production and development processes with the help of process analyses and to utilize the resources required for these purposes.
Affected organizations include public administrations, social institutions and other companies. Process analyses and subsequent process optimization serve to ensure the achievement of objectives.
In the past, process optimization was regarded as a task of quality management, but it is now seen as part of a comprehensive integrated process management of companies and institutions.
Process analyses and the optimization of processes as a prerequisite for an effective basic business orientation are an integral part of any modern company management if it is to be able to operate successfully in national and international competition.
A structured approach to all operational processes is the cornerstone of any process analysis, leading to process optimization. For process optimization, it is of great importance to establish interdepartmental process chains. In the first step towards process optimization, the existing processes are surveyed and classified in the course of the process analysis, e.g. with the help of process modeling. For this purpose, suitable key performance indicators (KPIs) are introduced to evaluate the quality and performance of the processes to be described. As part of the process analysis, a process map of the company is created based on the process description obtained, which can be used as a reference basis for further process optimization. This process optimization can have effects on all areas of the company. Such a process analysis, evaluation and classification is preferably carried out in connection with a holistic concept for the operational processes as well as the human and material resources. Continuous process optimization, which is carried out on the basis of such an evaluation, pursues the primary goal of continuous process improvement, while not impairing its operation.
Process optimization and control in operations is now inconceivable without appropriate tools (software). Companies can choose from a wide range of packages that can be individually adapted to the corresponding operational requirements. In the context of process optimization, this means that primarily the defined processes and their key figures are examined, with a classification being made with regard to the added value for operational value creation. The information resulting from the process analysis forms the basis for the use of these tools. These are used to focus operational resources on the core processes and thus define the corresponding key performance indicators. The results obtained are then examined for their effectiveness in the course of simulations.
New process-oriented approaches are essential in the context of the global complexity of modern business processes in today's world. Companies and institutions that have achieved at least approximate integration in this respect are still a rarity. With the help of process analysis, manufacturing, sales, and logistics processes are now being optimized primarily in terms of costs and throughput times. However, areas with softer Key Performance Indicators (KPI), in which the human factor is directly involved, are still hardly mapped in a process-oriented manner and are only rarely the subject of process optimization.
This can be attributed not least to the fact that, due to their specific characteristics, such process analysis with regard to value creation processes often cannot be carried out adequately with the software tools available today, and thus cannot be fully investigated and optimized.
In the model and analysis phase of process analysis, the soft factors mentioned above are difficult to determine in static models. In contrast to the standardization of activities, which is often not very promising because corresponding processes are usually rarely repeated, procedures that improve employee self-management appear more promising. A process environment is created in which those involved in the process instinctively act correctly (nudge management).
Where people work and work steps are performed manually, it is difficult to perform process optimization and recording in detail. Input and output are often known, the operations within a process have to be uncovered by process analysis. To close the information gap, process analysis is currently performed by a process engineer. During process analysis, the process is observed, recorded and analyzed. The process during process analysis, in which employees record times with a clipboard, pencil and stopwatch, for example, involves considerable manual effort and is therefore carried out far too infrequently in practice. As a result, rationalization, optimization, but also ergonomic potentials in industrial work processes often remain unused.
Our Motion-Mining® technology can help with process optimization and process analysis. For process analysis, this technology uses mobile sensors (wearables) and miniature radio transmitters (beacons) to record processes as they run. By equipping employees with wearables and the environment with beacons, process data is obtained during process analysis, based on which process optimization can take place. Meanwhile, we are able to distinguish between about 60 different movements during process analysis. In addition to walking and running, the movements include overhead handling, unhealthy bending, sitting for long periods, bending from the back, carrying, lifting, and holding. Based on the potential identified during the process analysis, we work with customers to develop individual measures for process optimization, thus pointing the way to more efficient and ergonomic work processes. In detail, the individual work steps are automatically reconstructed from the process data determined in the process analysis with the help of a self-developed pattern recognition solution based on Deep Learning and made accessible for further analysis. For this purpose, the movements, body postures, and also the work situation are detected and assigned to the activities in the work process. Compared to manual analysis methods, a 40 to 80 times larger database can be accessed for process optimization, which is generated without physical observation of the employees. Likewise, the scope of application of the GDPR is not open due to a comprehensive anonymization of the data and various organizational measures. Process managers are enabled by our motion mining technology to carry out process analyses and process optimizations more frequently, over a longer period of time, and with several employees at the same time.
Motion-Mining® Process analyses are currently primarily carried out in the production and logistics sectors. In the healthcare sector, we have also taken the first steps with pilot projects with regard to process optimization. The process analysis is carried out with regard to the recording of internal material flows, care activities, and their documentation.
Seamlessly integrate our Motion Mining® hardware into your work processes to collect activity and movement data from your employees and vehicles. Visually evaluate them with our AI-supported MPI software.
Record the movements of your employees and vehicles anonymously with our convenient wearables.
Visualize the measured data with our MotionMiners PROCESS INTELLIGENCE software (MPI for short).
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