Process performance
| Process performance |
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| See also |
Process performance or process capability is the degree to which the process meets the quality requirements. If we take into account the tolerance of the tested property, we can determine the potential and real capacity of the process to meet the quality requirements. Thanks to this, it is possible to determine how many products are within the defined specifications. To assess the process's capacity, you should directly refer to its spread (usually estimated based on the range or standard deviation) to the width of the assumed tolerance field[1].
Regarding to the process, there are three different perspective distinguished in literature[2]:
- process targets – referring to external and internal users and coming from their requirements
- process design – setting up the appropriate structure and creating the logical way of running the process to achieve its goals
- process management – including management of targets, performance, resources and process interface through supporting each process stage
Properly management of process performance enforces controlling of implementation process and execution during its lifecycle[3].
The model of modern control (BPM) includes six complex aspects[4]:
- process modeling
- process implementation
- performance planning
- process monitoring
- performance measurement
- performance enhancement
Process Performance Indicators
Measuring progress in process lifecycle is the key element in process-oriented enterprises and it is possible by deploying of indicators - Process Performance Indicators (PPIs) – that have specified target values to achieve in a certain period. Set PPIs need to be understandable for all stakeholders and verifiable by automated analysis (there is a recommendation to set them by applying the SMART model). The main issue in measuring the progress nowadays is that the indicators are created during the implementation of process (they should be prepared before starting the lifecycle) and they are too formally to understand by non-technical stakeholders or management. To avoid the misunderstanding and further issues, there should be prepared the PPI specification that will contain the process name, set goals, definition and target of indicator, scope, source and responsible person for the process[5].
Integrating Process Performance Indicators into BPM (Business Performance Management) lifecycle created a need to establish PPI phases[6].
There are four stages[7]:
- evaluation – identifying PPI correlations with business and predicting the future behavior
- design – defining PPIs and connect them with BP, preparing time analysis
- instrumentation – implementing of measurement points
- computation – calculating and monitoring PPIs
Analysis of different organization showed using of indicators which can be group as below (model PPINOT)[8]:
- base measures (time measure, count measure, condition measure and data measure) – they directly comes from the process and do not require further calculations
- derived measure – they are calculated by using aggregation function (e.g. average, minimum)
- aggregated measure – they represent the function of other measurements
Examples of Process performance
- The performance of a manufacturing process can be assessed by looking at how consistent the products produced are in terms of size, shape, weight, and other characteristics. For example, if the production process is designed to produce widgets with a certain size range, the process performance can be measured by the proportion of widgets that fall within that range.
- The performance of a service process can be measured by the amount of time it takes to complete tasks, the accuracy of the output, or customer satisfaction with the experience. For example, a restaurant may measure the performance of its order-taking process by the average time it takes to take an order, the average accuracy of orders placed, or customer feedback surveys.
- The performance of a quality control process can be assessed by looking at the number of defects in the final product or the number of defects detected by the quality control process. For example, a manufacturing plant may measure the performance of its quality control process by the percentage of products that are within tolerance or the number of defects caught before the product is shipped.
Advantages of Process performance
Process performance is a useful tool to measure the potential and current capacity of a process to meet quality requirements. Some of the advantages of process performance include:
- Improved productivity: Process performance is a great way to identify and eliminate inefficiencies in a process. By understanding where a process is under-performing, it can be improved to increase overall productivity.
- Increased customer satisfaction: With improved process performance, the product or service quality provided is improved, leading to increased customer satisfaction.
- Reduced costs: By identifying and eliminating inefficiencies, process performance can reduce costs associated with production and servicing.
- Improved product or service quality: Through process performance, the quality of products or services can be improved. This leads to higher customer satisfaction and greater loyalty.
- Better decision making: By understanding the process performance, managers and executives can make better informed decisions about how to improve the process.
Limitations of Process performance
- Process performance is limited by the quality requirements set for the process. If the process does not meet the quality requirements, then it can not be considered to be performing to its potential.
- Process performance is also limited by the variability of the process. If the process is too variable, then it can not consistently meet the quality requirements.
- Process performance is also limited by the equipment and materials used. If the equipment and materials used are of poor quality, then the process will not perform to its potential.
- Process performance is also limited by the human factor. If the people involved in the process do not have the necessary skills or do not follow the process correctly, then the process performance will be compromised.
Process performance or process capability can be determined by using a variety of approaches. These include:
- Statistical process control (SPC) – this is a method of monitoring and controlling a process over time to ensure it is producing products or services that meet the quality expectations. It involves analyzing data collected from the process to detect any sources of variation and then taking corrective action to ensure that the process stays within acceptable limits.
- Design of Experiments (DOE) – this is a methodology that helps to identify the cause and effect of different variables on a process. Through DOE, it is possible to determine the most important factors that affect the process performance, and then optimize the process to ensure that it is running at its best.
- Process Mapping – this is a technique used to visualize the flow of a process and identify areas for improvement. It can help to understand the process performance and identify potential opportunities for improvement.
- Process Simulation – this is a computer-based technique used to model the behavior of a process under different conditions. It can be used to predict the output of a process under different conditions and determine the most efficient way of running it.
In conclusion, process performance or process capability can be determined by a variety of approaches including statistical process control, design of experiments, process mapping and process simulation. Each of these approaches can provide valuable insights into the performance of a process and help to identify areas for improvement.
References
- Balaban N., Belić K., Gudelj M., (2011), Business Process Performance Management: Theoretical and Methodological Approach and Implementation, Management Information Systems, (2011), 4, 3-4.
- Kueng, P. (2000). Process performance measurement system: a tool to support process-based organizations. Total quality management, 11(1), 67-85.
- Río Ortega A., Resinas M., Durán A., Ruiz–Cortés A., (2010), Defining Process Performance Indicators by Using Templates and Patterns, Universidad de Sevilla, 1-3.
- Río Ortega A., (2012), On The Definition and Analysis of Process Performance Indicators, Universidad de Sevilla, 62, 25-26.
Footnotes
Author: Justyna Kurnik
