Process Discovery, sometimes referred to as Business Process Discovery, delves into how businesses complete tasks, analyze that information and develop process maps and process models. The models created through Process Discovery can help a business improve operations, save money, explore automation opportunities, and increase audit compliance.
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While some people use the term Process Discovery, others call this set of techniques Business Process Development. To add to the confusion, some researchers define Process Discovery in terms of the start-to-finish operation—extracting data from event logs, developing performance metrics, generating process maps from the event log data, using the maps to create process models, and describing variations from existing "as-is" real-world business processes. Other researchers include only the first step, obtaining data from event logs, in their definition of Process Discovery. The remaining steps are classified separately. Thus, any discussion of Process Discovery/Business Process Discovery should begin with a definition of terms, so all participants understand what, exactly, is under discussion.
Process Discovery can reveal issues with current business processes, such as poor documentation, gaps in performance, lack of uniformity, and operational uncertainties.
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Analyzing event logs and mapping the resulting data can also identify ways for businesses to document, improve, and automate their processes. Process Discovery can also improve employee satisfaction. This is accomplished by increasing visibility and employee ownership of tasks while reducing risks. Businesses can realize savings through Process Discovery, too. Automating tasks, improving employee morale, and closing performance gaps are all proven ways that businesses can save money. Process Discovery can assist in all these areas.
In the past, Process Discovery was conducted manually through interviews and analysis of business documentation. This approach is still in use today. However, sophisticated algorithms can also be used to rapidly analyze numerous event logs and create process maps and models to help managers and analysts visualize processes and address inconsistencies. These algorithms use a variety of search techniques to create process models. The process models, in turn, can vary in appearance because several different visualization types are available, including Business Process Model Notation, Petri nets, and Directly-Follows Graphs.
Analysts are finding more and more ways to use Process Discovery in healthcare. For example, Process Discovery can assist with the analysis of decision points in clinical pathways. Process Discovery can also be used to generate process models from healthcare event logs which can be used in simulations that allow researchers to further refine existing clinical pathways. These simulations can then be used to analyze care management scenarios. Process Discovery identifies tasks that can potentially be automated. One automated task that can help healthcare providers keep protected health information (PHI) secure is the transcription of incoming voicemail attachments.
Paubox Email Suite, which enables covered entities to send HIPAA compliant email, can do just that. We leverage email artificial intelligence (email AI) with Natural Language Processing (NLP) to transcribe incoming voicemail attachments. This allows healthcare providers to read the transcriptions instead of listening to the original audio, keeping PHI from being overheard and maintaining HIPAA compliance.