Statistical Engineering

Statistical Engineering as a Tool for Practice Improvement

The objective of applying statistical thinking applications in practice management is to improve results. To do so, we must improve the business processes (e.g. patient flow) that produce the results. Improving processes typically requires us to improve the average and also reduce variation. Improving dynamic business processes is not easy! Success often requires a sequential approach combining existing subject matter knowledge with new information gained through collecting and analyzing process data. Our knowledge guides our data collection, and the subsequent data analysis improves our understanding of the process. Several iterations of this process are typically required to achieve improvement objectives.

All activities in your practice are performed through a system of processes, although these processes are not always obvious to the casual observer. Therefore, a key preliminary step toward improvement is to map the process in question via the SIPOC model. This analysis will often identify non-value-added activities, such as the “hidden plant,” which could be eliminated through appropriate process improvements. Part of our analysis view the process from the larger context of the system in which it operates. This ensures that efforts will improve the overall business system, rather than push the problem from one area of the practice to another. The process of creating data—the measurement process—is critically important and should not be overlooked.

Experience shows that in some cases, your business process might be “broken,” and that means that some aspect of the process may need to be fixed to return it to its typical performance level. In such cases, the basic problem-solving framework provides one overall approach that integrates various tools in a logical sequence to solve the problem. In other cases, however, the process may be performing consistently, but at an unsatisfactory level. There is nothing broken to fix; instead we just need to fundamentally change the process to improve its overall performance. For these cases, the process improvement frameworks provide different sequences of steps and tools. Generally, we employ run and control charts as key tools to diagnose whether the process is stable. This information helps us to determine the most appropriate improvement approach unique to your practice environment.

We utilize various types of tools in the improvement frameworks as we work to eliminate existing frictions in your organization processes. Data collection tools help us to obtain the data needed for improvement. Sampling tools ensure that we have the right quality and quantity of data. Data analysis tools extract information from numerical data. Knowledge-based tools analyze qualitative data—that is, ideas. These tools are even more dependent on participation from the people with the most appropriate knowledge of the process – your staff and the software they utilize. Best results are obtained when these various types of tools are used in conjunction with each other in a logical sequence.

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