RPA Incident Management: 5 IT Metrics RPA Can Improve in ’23

Infographic showing SLA compliance tracking by RPA bots.

Incident management is a pivotal process for IT organizations. But often, it is riddled with inefficiency. Teams struggle with slow identification, long resolutions, lack of context, and repetitive grunt work. This results in poor system availability and mounting business costs.

According to Forrester, the average hourly cost of an infrastructure failure is a whopping $100,000. Downtime during peak periods can send costs spiraling even higher.

But what if we told you technology exists to completely transform this process?

Enter RPA.

Robotic process automation offers immense potential to overhaul IT service management in 2024. Intelligent software bots can amplify the productivity of IT teams multifold when it comes to critical processes like incident management.

In this comprehensive guide, we will explore 5 key metrics RPA can substantially improve for streamlining incident management:

1. Slashing Mean Time to Acknowledge (MTTA)

MTTA refers to the average time taken for IT staff to acknowledge an incident from the moment it’s detected. The 2022 State of IT Service Management report by ServiceNow found that MTTA can average up to 43 minutes currently.

Infographic showing current MTTA is 43 minutes on average.

Why is lengthy MTTA detrimental?

It allows incidents to persist, often escalating into major outages with widespread impact. Those extra minutes of unchecked disturbance disrupt workflows and processes organization-wide.

This is why minimizing MTTA is critical.

With RPA, intelligent bots can be programmed to continuously monitor infrastructure and business-critical applications. These bots have an eagle-eyed view across thousands of data points spanning servers, networks, services, CRM platforms, ERP systems and more.

At the first sign of anomaly, like a spike in transaction errors or elevated CPU loads, RPA bots autonomously trigger alerts and create incident tickets. IT staff are notified instantly on mobile devices via push notifications or SMS.

This real-time monitoring and alerting capability offered by solutions like MoogSoft AIOps helps slash MTTA down to the minute or even second level.

According to MoogSoft’s own client data, using their platform reduced MTTA by 90% on average.

Teams like Colorado’s Department of Revenue were able to decrease MTTA from a staggering 2 hours to just 30 seconds. This allowed IT technicians to respond to and remediate incidents almost instantly.

By rapidly shortening the time taken to trigger alerts, RPA enables IT teams to dramatically optimize MTTA KPIs. Quicker acknowledgement minimizes business disruption when issues do occur.

2. Accelerating Mean Time to Repair (MTTR)

MTTR refers to the average time required to fully repair and restore a failed system or service to normal function.

According to 2022 ServiceNow metrics, MTTR currently averages 4 hours and 36 minutes for most enterprises.

Just imagine an e-commerce website powering over $2 million in sales daily experiencing multiple hours of downtime. Or servers crashing in the middle of peak trading hours for an investment bank.

These examples underscore why lengthy MTTR and prolonged downtimes can rapidly spiral into substantial revenue losses.

This is where RPA comes into play to create a paradigm shift.

Bots excel at automatically gathering rich contextual data about system failures and incidents. They can pull relevant logs, system events, performance metrics, topology info, and recent changes made from across the IT stack.

Infographic showing RPA bots gathering contextual data across IT stack.

All this data is aggregated into dynamic incident dashboards and tickets. Now IT technicians have full visibility and key insights at their fingertips to start troubleshooting quickly.

Some RPA platforms like BigPanda even auto-generate hypotheses on the root cause based on past incident patterns. This allows technicians to quickly validate or rule out the most probable reasons for the outage.

By turbocharging the diagnostic process in this manner, RPA-enabled AIOps solutions dramatically shorten MTTR.

According to research by ESG, using an AIOps solution like BigPanda improved MTTR by 62% on average.

With accelerated identification and remediation, IT teams can significantly optimize MTTR KPIs with RPA.

3. Boosting First Contact Resolution (FCR) Rates

The FCR rate refers to the percentage of incoming tickets resolved by IT support staff on very first contact. Avoiding ticket escalations and repetitions is key.

Per 2022 benchmarks from HappyFox, the average FCR rate still lingers at a modest 75%. This indicates that 1 in 4 users have to repeatedly follow up before their issues get fully resolved.

Such repetitive contacts strain IT teams and frustrate end-users. RPA helps turn this equation around.


By using natural language processing to analyze incoming tickets. The context and intent behind the user‘s description of the problem is understood.

Bots can then accurately match tickets to the appropriate IT teams and subject matter experts. This precision routing avoids situations where tickets bounce endlessly between departments. It gets issues in front of the right agents right away.

Some RPA platforms even auto-recommend relevant knowledge base articles that can potentially solve the user‘s problem immediately.

By enabling context-aware routing and self-service recommendations, RPA empowers IT teams to resolve a higher percentage of tickets on first contact itself.

Real world results validate this. Mohawk College saw self-service options delivered through AI increase FCR rates by 15%.

Higher FCR creates smoother user experiences while also reducing ticket volumes entering the IT workflow. This is a win-win for both customers and IT staff.

4. Maintaining 100% SLA Compliance

SLAs or service-level agreements are critical governance documents. They specify standards of system and service performance that IT must maintain.

Infographic showing SLA compliance tracking by RPA bots.

Some common SLA clauses include:

  • Minimum uptime percentage (99.99%)
  • Maximum latency for transactions (2 seconds)
  • Minimum network availability (99.9%)
  • Maximum response time for support tickets (24 hrs)

Manual tracking of such metrics is incredibly tedious, not to mention prone to human error. Employees can easily miscalculate uptime or apply inconsistent logic.

RPA eliminates this margin of error. Bots can be programmed to automatically track SLA compliance across all critical systems with consistent logic.

For instance, bots continuously monitor application uptime across data centers. Any duration of downtime is precisely logged to check against the SLA threshold.

Network availability is sampled frequently and exactly per the SLA. Response times for ticket updates are tracked down to the last millisecond without fail.

Bots compile this performance data into visual dashboards and detailed reports updated in real-time. No more chasing excel sheets or paperwork during audits.

Such automation enables IT leaders to proactively identify potential underperformance before SLA violations occur. Bots provide the tools to uphold compliance rigorously.

According to McKinsey, RPA improves compliance with SLAs by over 80%. This reduces financial and reputational risks while also providing documented proof of quality IT service.

5. Eliminating Mundane IT Workflow Chores

IT service desks spend countless hours on repetitive chores vs focusing on high-value work. Tedious activities like:

  • Copy-pasting info across multiple ticketing and documentation systems
  • Resetting passwords, adding/offboarding users, updating permissions
  • Moving huge logs and files from system to system
  • Filling out forms with repetitive data

According to Forbes, such mundane tasks consume 60% of a typical IT worker‘s time. This is where RPA can step in to relieve staff of these burdens.

Bots can take over repetitive workflows end to end. For instance, when an employee joins, the HR system triggers a bot. The bot will automatically create user accounts across all necessary apps. It updates Active Directory, ensures the right access levels, and sends onboarding paperwork.

These bots perform such repetitive tasks with far greater speed and accuracy than human clerks. Forbes notes that RPA reduces manual work in IT service desks by ~65% on average.

With RPA implementing best practices around the clock, IT teams can better focus on innovation and enhancing user experiences.

Getting Started With RPA for Incident Management

Based on client successes, here are 5 proven steps to maximize value from RPA in IT service management:

  1. Build a unified integration framework allowing bots easy access to ticketing systems, monitoring tools, CMDBs etc. APIs enable this seamless connectivity.

  2. Start with simple, rules-based workflows before pursuing advanced self-learning automations. Walk before you run.

  3. Standardize processes first, eliminating redundancies. Straightforward procedures are easiest to automate.

  4. Involve IT staff during solution design to foster user acceptance. Technicians offer insights on pain points.

  5. Focus on augmenting rather than replacing staff. Bots handle repetitive tasks while staff focus on high-value activities.

The Bottom Line

RPA is a game-changing technology for optimizing IT service management in the digital era. Bots act as a virtual assistant for IT teams, taking on the repetitive and mundane.

This allows staff to focus on innovation and customer-centric initiatives that create real business value. It also unshackles them from constantly firefighting failures and outages.

With RPA, IT leaders can maximize system and service availability while delivering exceptionally delightful user experiences.

To assess if your organization is ready for RPA in enhancing ITSM, take our 1 minute assessment:

[Link to RPA for ITSM readiness assessment]