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Improve Your Problem Management

Your 6-step guide to optimizing Problem Management.
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Improve Your Problem Management
Challenges (8) Goals (8) 6 Steps Preview Outcomes Data FAQs (4)

Master Problem Management with Process Mining

ProcessMind helps you uncover hidden inefficiencies in your Problem Management process. Easily identify bottlenecks, repetitive tasks, and prolonged resolution times that impact service quality. Our platform provides clear insights into process deviations and areas for improvement, enabling data-driven optimization. Gain a comprehensive understanding of your problem resolution lifecycle, from identification to closure, regardless of your source system.

Download our pre-configured data template and address common challenges to reach your efficiency goals. Follow our six-step improvement plan and consult the Data Template Guide to transform your operations.

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Mastering Problem Management is crucial for maintaining operational stability and delivering exceptional service. Process mining for Problem Management offers an unparalleled, complete, and end-to-end view of how problems are truly identified, investigated, and resolved within your organization. It allows you to move beyond anecdotal evidence and discover the actual pathways your problem records take, from initial detection through to final resolution and verification. This deep analytical capability reveals critical insights into bottlenecks that delay resolution, uncovers non-compliant process deviations, and highlights significant opportunities for automation across your entire workflow. Regardless of your underlying ERP, ITSM, or any other source system, ProcessMind extracts the event data to reconstruct the reality of your operations, providing an objective, data-driven understanding that is system-agnostic and universally applicable to your unique Problem Management process.

The Problem Management process often grapples with several common challenges, regardless of the system used. These include prolonged root cause analysis, frequent reoccurrence of known problems, inefficient handoffs between teams, and a general lack of visibility into the true cycle time of problem resolution. Organizations struggle with understanding why certain problems take longer to resolve, where resources are being misallocated, or if established standard operating procedures are actually being followed in practice. ProcessMind directly addresses these pain points by providing detailed process maps and performance metrics derived directly from your operational data. You can precisely identify where delays occur, pinpoint the exact steps that add no value, and expose variations that lead to suboptimal outcomes. This clarity empowers you to streamline operations, reduce Mean Time To Resolution (MTTR), improve resource utilization, and ensure that your Problem Management process actively contributes to service stability, not just reacting to incidents.

Analyzing your Problem Management process with ProcessMind delivers tangible benefits that translate into improved efficiency, reduced costs, and enhanced service quality. By gaining an empirical understanding of your process, you can make informed decisions to optimize workflows, eliminate redundant steps, and prioritize automation initiatives that will have the greatest impact. This leads to a significant reduction in recurring problems, fewer service disruptions, and ultimately, higher customer satisfaction. Furthermore, identifying and addressing compliance gaps proactively minimizes risk and ensures adherence to internal policies and external regulations. To begin uncovering these powerful insights, our platform is designed for seamless integration with your existing data landscape. You can start by leveraging our comprehensive data template, which guides you through extracting the necessary event logs from your system, ensuring a smooth and rapid onboarding experience. ProcessMind is committed to helping you transform your Problem Management from a reactive necessity into a proactive, optimized, and highly efficient operation.

Problem Management Process Mining Service Management ITSM Root Cause Analysis Process Optimization Efficiency Compliance

Common Problems & Challenges

Identify which challenges are impacting you

Problem records often linger in the investigation phase for weeks without clear progress, leading to a mounting backlog and unresolved underlying issues. This delay prevents teams from addressing the source of recurring incidents, which increases the burden on the service desk and degrades overall service reliability.

ProcessMind tracks the duration of the investigation phase, highlighting exactly where the process halts. We surface records that have exceeded typical resolution times, enabling problem coordinators to intervene and reallocate resources before the investigation becomes obsolete.

When a problem record is bounced between multiple technical teams, context is often lost and the resolution timeline expands significantly. This lack of clear ownership results in wasted effort, frustrated technical staff, and a failure to meet service level targets for critical infrastructure stability.

Our analytics engine maps the sequence of assignment activities to reveal these ping-pong patterns. You can see which support groups are frequently redirecting records, allowing for better training or clearer definition of group responsibilities to stop the cycle of avoidance.

Failing to publish a workaround quickly means that incident agents continue to struggle with repetitive issues, increasing the mean time to resolution for end users. When the gap between identifying a problem and publishing a workaround is too wide, the business suffers from unnecessary downtime despite a known temporary fix existing.

ProcessMind measures the lag between identifying a workaround and the workaround published activity. This visibility ensures that temporary solutions are disseminated rapidly, minimizing the impact of ongoing problems while technical teams focus on the final root cause resolution.

Even after a root cause is identified, the path to a permanent fix often stalls before a change request is initiated. This disconnect between problem and change management workflows leads to persistent known errors that could have been resolved, leaving the IT environment vulnerable to recurring service disruptions.

We analyze the time elapsed between the root cause identified activity and the change request initiated event. This exposes friction points in the transition from problem management to change management, ensuring that permanent fixes move forward without unnecessary administrative delays.

When the problem management lifecycle is too slow, the same incidents continue to flood the service desk, consuming valuable resources on repetitive tasks. This cycle drains efficiency, distracts teams from strategic projects, and erodes user confidence in IT's ability to maintain a stable environment.

ProcessMind correlates the related incident count with the duration of the investigation and fix phases. By showing how slow problem resolution directly inflates incident volumes, we help you build a business case for accelerating permanent fixes to reduce the overall service desk burden.

Teams frequently bypass the post-implementation review phase to quickly close records and reduce backlogs. Without this crucial step, organizations fail to verify that the fix worked as intended or capture lessons learned, leading to potential future failures of a similar nature and hindering long-term service improvement.

ProcessMind tracks the compliance of the post-implementation review activity for every closed problem record. We highlight deviations from the standard process, ensuring that all resolution steps are followed for long-term service improvement and compliance requirements.

Critical problems often fail to meet their service level targets because of hidden inefficiencies in the investigation and fix stages. Missing these deadlines compromises IT service stability and can lead to a loss of business trust when critical infrastructure remains unstable for longer than agreed.

By correlating SLA due dates with actual process timestamps from your source system, ProcessMind identifies the specific activities causing breaches. This allows you to monitor service level targets in real time and adjust priorities or workflows before deadlines are missed.

When technicians fail to accurately categorize the root cause of a problem, it becomes impossible to identify long-term trends or systemic infrastructure weaknesses. This lack of data prevents management from making informed decisions about infrastructure investments or process changes needed to improve stability.

ProcessMind identifies records where the root cause category attribute is missing or set to generic values. By highlighting these data quality gaps, we help organizations improve data integrity and gain better insights into the actual drivers of IT instability.

Typical Goals

Define what success looks like

Faster root cause analysis prevents recurring incidents and minimizes infrastructure downtime. By accelerating the investigation phase, technical teams can move away from repetitive firefighting and focus on implementing permanent fixes that improve overall service reliability and reduce the time that critical vulnerabilities remain unaddressed.

Process mining visualizes the entire investigation flow within your system to identify precisely where teams stall. By pinpointing bottlenecks in specific support groups or technical domains, the platform provides actionable insights to reduce investigation time, allowing you to monitor the path from problem identification to root cause determination to ensure every investigation stays on track.

Every handoff between support groups increases total resolution time and creates administrative overhead. Reducing these hops ensures the right experts handle the issue immediately, preventing the common ping-pong effect that occurs when problem ownership is poorly defined, which leads to a more streamlined process and higher accountability.

Our platform tracks the history of assignment fields for every problem record in your source system. By identifying patterns where records are incorrectly routed or frequently bounced between teams, you can optimize group routing rules and cut unnecessary reassignments, ensuring that the investigation moves forward without losing momentum during handoffs.

Providing a workaround quickly reduces the impact of an active problem on end users and the service desk. It allows support staff to resolve incidents even before a permanent fix is ready, significantly decreasing the volume of open tickets and improving user satisfaction while a permanent solution is being developed.

Process mining analyzes the time elapsed between problem identification and the publication of a workaround in the known error database. This insight helps you standardize this critical step, ensuring that documentation for known errors is available faster. This visibility allows you to hold teams accountable for the rapid communication of interim solutions.

The ultimate measure of success for any problem management team is the reduction of recurring incidents. By identifying and fixing root causes, you lower the total cost of ownership for IT services and reduce the daily burden on the service desk, demonstrating the tangible value of the process to the wider business.

Our platform correlates incident volume with specific problem records to evaluate the long-term effectiveness of your permanent fixes. This enables you to verify that solutions eliminate the root cause as intended, rather than just treating symptoms. You can track the success rate of implemented changes to ensure they are delivering the expected reduction in incident volume.

A smooth transition from a problem record to a change request is essential for implementing permanent fixes in a controlled manner. Delays in this transition mean that identified vulnerabilities remain in the production environment for longer than necessary, increasing risk and undermining the investigation effort.

By mapping the digital footprint between the problem and change processes in your system, process mining identifies friction in the approval and handoff lifecycle. This helps you bridge the gap between root cause identification and the initiation of a fix, reducing the time that proposed solutions get stuck in administrative limbo or approval queues.

Meeting service level agreements for high-priority problems is critical for maintaining business continuity and operational stability. Consistent compliance builds trust with business stakeholders and guarantees that the most impactful issues receive the urgent attention they require, reducing the total duration of critical service outages.

Process mining monitors your actual performance against SLA targets by analyzing timestamps throughout the record lifecycle. By identifying the specific process stages or support groups where SLA breaches are most likely to occur, we provide early warnings, enabling your teams to maintain compliance across all priority levels and intervene before a breach happens.

Learning from past problems is essential for continuous service improvement and preventing future mistakes. Completing reviews for every major problem ensures that lessons are documented and shared, preventing the recurrence of similar issues and improving the maturity of the IT organization over time.

Our platform monitors the presence of post-implementation review activities before a record is allowed to close. By identifying where this step is frequently skipped or delayed, you can enforce compliance with your defined process and ensure that valuable knowledge is captured and shared across the service desk for every major problem.

Accurate data is the foundation of effective problem management and long-term trend analysis. Improving the quality of root cause categories allows for better strategic decisions and more targeted investments in technology or training to address systemic issues within the IT infrastructure, leading to long-term stability.

Process mining analyzes root cause and category fields across thousands of records to identify inconsistencies, re-categorizations, or the overuse of generic 'other' categories. This insight enables managers to refine data entry standards and improve the reliability of reporting, making it easier to spot emerging technology trends from your source system data.

The 6-Step Improvement Guide for Problem Management

1

Connect & Discover Data
2

Map Problem Mgmt Process
3

Identify Process Bottlenecks
4

Analyze Root Causes
5

Design Process Improvements
6

Monitor & Iterate
1

Connect & Discover Data

What to do

Connect your data source, such as your ERP or service management system, to extract relevant Problem Record activity logs. Ensure all necessary event data, including timestamps and case IDs, are imported for analysis.

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Why it matters

This foundational step ensures you have a complete and accurate dataset, providing the basis for understanding the actual flow and performance of your Problem Management process.

Expected outcome

A comprehensive and accurate dataset of Problem Management activities is ready for analysis.

WHAT YOU WILL GET

Uncover Hidden Truths in Your Processes Today

ProcessMind illuminates the actual flow of your operations, providing an objective, data-driven view. It pinpoints inefficiencies and compliance gaps you never knew existed.
  • Visualize your end-to-end process flow
  • Pinpoint hidden inefficiencies and bottlenecks
  • Ensure compliance with process rules
  • Optimize resource allocation effectively
Discover your actual process flow
Discover your actual process flow
Identify bottlenecks and delays
Identify bottlenecks and delays
Analyze process variants
Analyze process variants
Design your optimized process
Design your optimized process

TYPICAL OUTCOMES

Realizing Value with Problem Management Process Mining

These outcomes illustrate the tangible improvements organizations realize by applying process mining to their Problem Management workflows. By gaining data-driven insights, teams can identify bottlenecks, streamline resolution processes, and prevent recurring issues more effectively.

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Faster Root Cause Discovery

Average reduction in investigation time

Streamlining the path from investigation start to root cause identification allows technical teams to focus on permanent fixes rather than prolonged diagnosis, reducing critical service interruptions.
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Minimized Handoff Rework

Reduction in problem record reassignments

Identifying bottlenecks in initial routing ensures that problem records reach the correct experts immediately, preventing wasted effort and delays across multiple support groups.
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Improved SLA Adherence

Better compliance for critical problems

Real-time visibility into stalled problem records helps management intervene before service level agreement targets are missed, ensuring consistent service delivery to the business.
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Reduced Resolution Rework

Lower problem reopen rates

Validating resolutions before closure ensures that underlying issues are truly fixed, preventing the costly cycle of investigations restarting after a supposed fix and improving overall stability.
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Accelerated Workaround Delivery

Faster publication of temporary solutions

Accelerating the publication of temporary workarounds significantly reduces the impact of ongoing incidents on end users, minimizing business disruption while the long-term solution is developed.
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Fewer Recurring Incidents

Reduction in related service desk tickets

Efficiently identifying and resolving root causes, and publishing permanent fixes, helps prevent new incidents from clogging the service desk and reduces the total cost of support.

Results vary based on process complexity, data quality, and the specific implementation strategy. These figures represent typical improvements observed across various Problem Management implementations.

FAQs

Frequently asked questions

Process mining visualizes the actual path of every problem record, revealing deviations from standard workflows and identifying hidden bottlenecks. It provides a data-driven view of your process, helping teams optimize efficiency and improve resolution times.

You typically need an event log containing a unique case identifier, a timestamp for each activity, and a description of the activity. Key attributes like status changes, assigned groups, priority, and category provide richer context for deeper analysis.

Initial insights can often be generated within a few days to a few weeks, once data extraction from your source system is established. The first phase focuses on connecting to the system and mapping primary process changes to create a baseline model.

Process mining highlights specific stages where investigations stall by quantifying the duration of each transition. It pinpoints resource gaps or missing information that prolong the investigative phase. This data-driven approach replaces anecdotal evidence with factual evidence of where delays occur.

By mapping every transition, process mining identifies records that bounce repeatedly between support groups without resolution. This helps managers recognize unclear group ownership or situations where specific teams lack the resources to handle certain problem types. Such insights enable process redesign and better resource allocation.

Process mining identifies the root causes of SLA breaches by showing the exact path of records that failed to meet targets. You can compare compliant versus non-compliant records to see if specific support groups or problem types are more prone to delays. This enables targeted interventions to ensure priority problems are handled within required timeframes.

By analyzing the linkage between incident and problem records, process mining identifies patterns where issues are repeatedly addressed with workarounds rather than permanent fixes. This visibility helps prioritize high-impact solutions that eliminate entire clusters of recurring support tickets.

Standard reports provide snapshots and aggregated metrics, but they often miss the actual journey of a problem record. Process mining reveals the specific transitions, loops, and deviations that occur between those metrics. It shows exactly where and why a process is stalling, complementing standard reporting with a deeper, longitudinal view for true optimization.

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