Process Mining 101
Process mining is about extracting knowledge from the event logs recorded by an information system. Until recently, the information stored in event logs was rarely used to analyse underlying processes. Process mining aims at improving the control over business processes by providing techniques and tools for discovering performance, organizational and social related information from event logs.
There are three classes of process mining techniques. This classification is based on whether there is a prior model and, if so, how the prior model is used during process mining.
- Discovery: Previous models do not exist. A new model is constructed or discovered from an event log based on low-level events.
- Conformance checking: There is an a priori model. The existing model is compared with the process event logs and potential discrepancies between the log and the model are analysed.
- Enhancement: There is an a priori model. The model is extended with a new aspect or perspective, so that the goal is not to check conformance, but rather to improve the existing model.
Process Mining for IT Service Management
“IT service management (ITSM) refers to the entirety of activities – directed by policies, organized and structured in processes and supporting procedures – that are performed by an organization to design, plan, deliver, operate and control information technology (IT) services offered to customers. It is thus concerned with the implementation of IT services that meet customers’ needs, and it is performed by the IT service provider through an appropriate mix of people, process and information technology” Source: Wikipedia
So, processes are at the core of ITSM. Enterprise Service Management platforms such as ServiceNow, Cherwell and Remedy capture audit logs that can be readily transformed into event logs for process mining. This allows for a powerful platform to Drive cost reduction and increase service delivery performance through;
- Reducing and eliminating inefficient and costly variants to standard processes
- Measuring and improving performance of workgroups and assignees
- Proactively adapt processes in alignment with SLAs and customer expectations
- Ensuring compliance with best practice service management processes
- Tracking process metrics to guide continual service improvement
Examples:
Change Management Process Explorer
- Visualise the most common process variants related to change and release management processes.
- Analyse the volume of changes associated process steps and which steps have a high standard of deviation, representing an unstable process
- Explore processes containing loops to determine the root cause and what mediation steps are required
Process Variant Metrics
- Variants represent a set of steps associated used to perform a certain process.
- Processes often have hundreds of non-compliant variants.
- Metrics can be used to determine non compliant and inefficent variants within a given process
User Process Metrics
- Analyse the length of time users are taking to perform steps within variants of a process
- Provides valuable information on training and knowledge related issues, SLA Resolution and workforce/resource problems
Process Metric Trend Analysis
- Drive continual process improvement by tracking the performance of process and service delivery metrics over time
- Advanced visualisation techniques provide for correlation analysis between metrics to determine cause and effect
- Machine learning algorithms can be applied to predict metrics performance