Process Mining for Service Management


Process Mining for Service Management

 Service Management Overview

Service Management was originally specific to IT and defined as follows:

Information technology service management (ITSM) comprise the activities that are performed by an organization to design, build, deliver, operate and control information technology (IT) services offered to customers.  IT service management is characterized by adopting a process approach towards management, focusing on customer needs and IT services for customers rather than IT systems, and stressing continual improvement

Perhaps the key word in the definition above is ‘process’.  Service Management is all about processes that guide the lifecycle of a task, each task representing a specific instance of a service delivered to a customer. This ‘process approach’ is formalised by the existing of multiple IT Service frameworks, such as ITIL, COBIT and TOGAF.

As IT Service Management matured, enterprise IT Service Management providers such as ServiceNow extended service management practices across the whole organization.   So, the concept of service management and related processes is now also seen in organizational areas such as HR, Finance and Sales.   And for an increasing number of organisations, service management is a key component of digital automation initiatives

Measuring Service Management

When it comes to measurement and analytics for Service Management, typically, process metrics focus on the result of a task process. For example, did the task meet SLA, how long did it take resolve, what assignment group closed the task, etc. Result orientated metrics are adequate to measure the high-level performance of a process but provide little insight into the reason behind process performance issues.

Furthermore, if we look at the Service Management Process Analytics overview below, performance related metrics only covers aspects of ‘Increase Efficiency’ and ‘Improve Performance’. So, something more is needed to uncover what’s actually happening in a process and to help explain why.   This is where process mining for service management comes steps in

Service Management Process Analytics


 Service Management Process Models

Process mining enables visualisation of the lifecycle of your processes, providing a level of insight into your processes not available through traditional service management performance metrics. An event log is generated from activities associated with a task – audit events and workflows, journal entries, approvals, SLA data and task timestamps. Process Mining algorithms then transform the event log is then transformed into process variants, activities, and steps, along with a vast array of metrics available for analysis. The end result is a service management process model, seen below;

Process Model for ServiceNow Incidents by State

Examples of process models include;

·   Incidents by State:   Show’s the various state changes that occur during the resolution of an incident.  This can be used to identify:

  • Steps that can potentially be automated.  These are indicated by highlighted steps where the duration and std deviation are minimal
  • Variants, or combinations of steps, representing incidents not meeting SLA and/or taking excessive time to resolve.   Automated insights are then available to identify which resources and assignment groups are involved and what the types of incidents are
  • The % of incidents that are resolved in alignment with defined workflows i.e., are compliance with specified processes

·   Incidents by Assignment Group:   Show’s the various combinations of assignment groups that are involved in the resolution of incidents.   This can be used to identify:

  •      Loops or re-work in a process where an incident goes back to a previous workgroup
  •      Inefficiency in incident resolution based on the which workgroup assignments take longer than others.   This can further be analysed by the types of incidents and resources involved

Compliance Management

In addition to more detailed performance metrics, leveraging advanced process mining tools like the Metricus Process Miner facilitates the measurement and management of compliance and simulation of cost savings. Variants, activities, and steps in a process can be flagged as compliant or non-compliant, and workflows can be imported from service management tools like ServiceNow to automatically flag compliance.   Metrics such as % Process Compliance, % Tasks Compliance and % Variants Compliant can then be viewed and analysed across various groups and resources assigned to tasks.  To see how this works in action, just watch the Metricus Tutorial on Compliance Management, a quick 5-minute overview of compliance management using process mining

Process Model for Non-Compliance – ServiceNow Stories