Business process management activities can be arbitrarily grouped into categories such as design, modeling, execution, monitoring, and optimization.
Design Process design encompasses both the identification of existing processes and the design of "to-be" processes. Areas of focus include representation of the process flow, the factors within it, alerts and notifications, escalations, standard operating procedures, service level agreements, and task hand-over mechanisms. Whether or not existing processes are considered, the aim of this step is to ensure a correct and efficient new design. The proposed improvement could be in human-to-human, human-to-system or system-to-system workflows, and might target regulatory, market, or competitive challenges faced by the businesses. Existing processes and design of a new process for various applications must synchronize and not cause a major outage or process interruption.
Modeling Modeling takes the theoretical design and introduces combinations of variables (e.g., changes in rent or materials costs, which determine how the process might operate under different circumstances). It may also involve running "what-if analysis"(Conditions-when, if, else) on the processes:
"What if I have 75% of resources to do the same task?" "What if I want to do the same job for 80% of the current cost?".
Execution Business process execution is broadly about enacting a discovered and modeled
business process.
Business process Enacting a business process is done manually or automatically or with a combination of manual and automated business tasks. Manual business processes are human-driven. Automated business processes are software-driven. Business process automation encompasses methods and software deployed for automating business processes.
Business process automation Business process automation is performed and orchestrated at the business process layer or the consumer presentation layer of SOA Reference Architecture. BPM software suites such as BPMS or iBPMS or low-code platforms are positioned at the business process layer. While the emerging
robotic process automation software performs business process automation at the presentation layer, therefore is considered non-invasive to and de-coupled from existing application systems. One of the ways to automate processes is to develop or purchase an
application that executes the required steps of the process; however, in practice, these applications rarely execute all the steps of the process accurately or completely. Another approach is to use a combination of software and human intervention; however this approach is more complex, making the documentation process difficult. In response to these problems, companies have developed software that defines the full business process (as developed in the process design activity) in a
computer language that a computer can directly execute. Process models can be run through execution engines that automate the processes directly from the model (e.g., calculating a repayment plan for a loan) or, when a step is too complex to automate,
Business Process Modeling Notation (BPMN) provides front-end capability for human input. Compared to either of the previous approaches, directly executing a process definition can be more straightforward and therefore easier to improve. However, automating a process definition requires flexible and comprehensive infrastructure, which typically rules out implementing these systems in a legacy IT environment.
Business rules Business rules have been used by systems to provide definitions for governing behavior, and a business rule engine can be used to drive process execution and resolution.
Monitoring Monitoring encompasses the tracking of individual processes, so that information on their state can be easily seen, and statistics on the performance of one or more processes can be provided. An example of this tracking is being able to determine the state of a customer order
(e.g. order arrived, awaiting delivery, invoice paid) so that problems in its operation can be identified and corrected. In addition, this information can be used to work with customers and suppliers to improve their connected processes. Examples are the generation of measures on how quickly a customer order is processed or how many orders were processed in the last month. These measures tend to fit into three categories: cycle time, defect rate and productivity.
Business activity monitoring (BAM) The degree of monitoring depends on what information the business wants to evaluate and analyze and how the business wants it monitored, in real-time, near real-time or ad hoc. Here,
business activity monitoring (BAM) extends and expands the monitoring tools generally provided by BPMS.
Process mining Process mining is a collection of methods and tools related to process monitoring. The aim of process mining is to analyze event logs extracted through process monitoring and to compare them with an ''
process model. Process mining allows process analysts to detect discrepancies between the actual process execution and the a priori'' model as well as to analyze bottlenecks.
Predictive business process monitoring Predictive business process monitoring concerns the application of data mining, machine learning, and other forecasting techniques to predict what is going to happen with running instances of a business process, allowing to make forecasts of future cycle time, compliance issues, etc. Techniques for predictive business process monitoring include Support Vector Machines, Deep Learning approaches, and Random Forest.
Optimization Process optimization includes retrieving process performance information from modeling or monitoring phase; identifying the potential or actual
bottlenecks and the potential opportunities for cost savings or other improvements; and then, applying those enhancements in the design of the process. Process mining tools are able to discover critical activities and bottlenecks, creating greater business value.
Re-engineering ==Suites==