Service Management involves providing accessible information technology to customers, and its high volume of daily requests makes it ideal for process mining. This article outlines the benefits and three practical ways to optimise Service Management processes using process mining.
Assessing your Service Management process
Maintaining a positive company image and ensuring customer loyalty depends on well-executed Service Management. It serves as a critical factor for customers when deciding to continue using a company’s services. The Service Manager may proudly declare, “We provide excellent service value to our customers!” However, tracking ongoing service requests becomes challenging due to the sheer volume.
Key questions arise:
– Which service requests should have been resolved by now?
– What are the common reasons for SLA breaches?
– How can the overall Service Management process be improved?
– What is the variation in service quality across different sub-units of the organization?
These challenges make Service Management an ideal candidate for process mining. Process mining provides visibility into the entire end-to-end process, helping identify root causes for problems in process execution.
Steps included in a Service Management process
In a Service Ticket, process steps can generally be categorised as follows:
SLA starts:
A service provider receives a request to look into an issue with the product/service by a customer or another stakeholder who needs the issue to be looked at.
A task is opened/created:
A ticket is created internally, which is then assigned to a member of the customer service team or a technical expert.
An expert works on the ticket:
This may either be a straightforward and quick answer to satisfy the original inquiry. However, sometimes you might need to get more information from other stakeholders – such as the customer themselves, vendors, specialists, etc.
The ticket is resolved:
The expert has solved the reported issue! Hooray!
SLA ends:
The service has been fulfilled (hopefully before the agreed resolution deadline within the SLA).
The ticket is closed:
The service request is closed with no expectations to be further investigated unless the service request is reopened.
In an ideal scenario, all service requests would be straightforward. However, in reality, most are not. There may be repeated back-and-forth conversations, tickets not handled by the right people, and records not recorded correctly. These factors can lead to longer resolution times and breached SLAs.
How it all works: Process Mining for Service Management
Various event types, like “SLA Start” or “State [Awaiting],” are recorded in the service management system database with timestamps. From the process start to “State [Resolved]” and beyond “SLA End,” each event is documented. Using this data, a process mining model is created to visualise your service management process.
QPR ProcessAnalyzer, QPR’s Process Mining software, extracts data directly from your information systems, such as ServiceNow, using built-in connectors. It then visualises and identifies symptoms of inefficient processes, like bottlenecks, reassignments, and SLA or conformance violations.
3 practical ways for optimizing your Service Management process
Optimise your Service Management process with QPR ProcessAnalyzer in three steps:
1. Explore your current processes: Evaluate end-to-end process duration and internal benchmarks.
2. Utilise Root Cause Analysis: Identify and understand issues like extended lead times.
3. Continuous improvement: Monitor and enhance using built-in KPIs for Process Compliance and service request resolution times.
1. Discover and benchmark as-is process steps in different parts of your organization
Process Mining generates computer-generated process flowcharts from traces in your data management systems (e.g., ServiceNow). These flowcharts reveal undesirable behavior, skipped steps, and delays in your Service Management process. Utilising Process Discovery tools, like duration analysis and case attribute profiling, helps identify issues (e.g., prolonged resolution times), pinpoint their occurrence, and initiate compliance checks and process enhancements.
2. Understand where and why issues are happening in your Service Management processes
Root Cause Analysis reveals cases prone to reassignments or rework, identifies event chains leading to later issues, and pinpoints sources of SLA violations. Ranking root causes by their impact on business outcomes guides focus on areas for enhancing customer satisfaction and reducing resolution times. Beyond this, it helps identify “role models” with fewer issues, enabling internal benchmarking across the organisation. Following root cause analysis, you can develop a plan of action for further investigations and process improvement initiatives. Leverage various visualisation methods, including ad-hoc analysis and long-term process monitoring via Dashboards.
3. Improve continuously with ready-made applications for a variety of Service Management use cases
Process mining stands out from traditional BI reports due to its user-friendly nature. Unlike traditional approaches, you don’t require a data scientist to interpret or analyse findings, thanks to the inclusion of AI-based advanced analyses and customisable dashboards.
QPR takes this convenience to the next level with its pre-built Service Management dashboards, streamlining the process significantly. This means that everything is already set up, making process mining with QPR faster and more straightforward than ever before.
Upon opening a dashboard, you instantly gain insights into critical aspects, such as identifying the occurrence and impact of SLA breaches, along with their root causes. The QPR Service Management Application currently offers dashboards for various analysis and overview angles, including Operations Overview, SLA Breach, Service Request Reassignment Analysis, Leadtime (SLA Start to SLA End), and Process Conformance/Compliance.
These dashboards are not just randomly created; they result from collaboration with both internal and external process experts. The goal is to provide the most insightful information to address the crucial questions for Service Management professionals. These dashboards are versatile, allowing continuous monitoring of operations, deep dives into KPIs (such as SLA compliance percentage, service request resolution times, and reassignment counts), and the identification of sources of delays or opportunities for process improvement.
To sum it up: What are the benefits of using Process Mining for Service Management?
Process mining provides precise insights into the operations of your Service Management processes. It allows you to understand specific details, such as the time taken from a new incoming service request to issue resolution, the frequency and locations of SLA breaches, and the level of compliance with the designed Service Management process model.
Identifying development areas within your processes enables targeted improvement efforts for maximum value. Armed with objective insights, you can confidently make changes, such as streamlining service request escalation procedures, learning from challenging service requests to document best practices for training, and refining Service Management processes to enhance service value delivery to customers and stakeholders.
With process mining, you gain a comprehensive understanding of how, why, and where your Service Management performs well and where improvements are needed. Importantly, these improvement ideas are grounded in facts and data rather than opinions or gut feelings. This ensures that decisions and improvement initiatives are confidently based on a solid foundation, guiding your path towards optimizing Service Management.