Optimizing RPA Robot Performance through Digital Experience Monitoring

The strategic importance for the RPA Monitoring 

In an economic environment where operational efficiency determines competitive advantage, RPA robots have become essential assets. However, as revealed by the Deloitte 2024 Automation Study, 62% of companies report frequent interruptions in their automated processes, resulting in significant financial losses and decreased confidence in these technologies.

Digital Experience Monitoring (DEM) now represents the preferred solution to ensure the reliability and performance of RPA robots. This approach goes beyond traditional monitoring by offering complete visibility across the entire automation chain.

Analysis of the current RPA Monitoring Landscape 

Current State and Challenges 

According to the Forrester “The State of RPA 2025” report, the main issues encountered by companies are:

• Lack of visibility into robot performance (76%)

• Difficulties in identifying the source of failures (68%)

• Excessive incident resolution time (average MTTR of 4.2 hours)

• Absence of relevant business metrics (57%)

Essential Key Performance Indicators (KPIs)

For effective supervision of your RPA robots, experts recommend prioritizing:

• Operational availability rate (target: >99.8%)

• Processing time per transaction (sector benchmark available)

• Automation success rate (target: >99.5%)

• Mean Time to Resolve incidents (MTTR)

• Business impact of interruptions (in monetary value)

The five pillars of an effective DEM strategy for RPA

1. Advanced Synthetic Monitoring

Synthetic monitoring allows continuous simulation and monitoring of critical paths for your RPA robots. This proactive approach detects anomalies before they impact business processes.

Csa study : Société Générale implemented synthetic test scenarios for its 320 mortgage processing robots. Result: early problem detection in 92% of cases and a 78% reduction in incidents.

Recommended configuration:

• Test frequency: every 3-5 minutes for critical processes

• Response time verification for each process step

• Output data validation (data quality)

2. Real-time performance analysis

Real-time analysis allows immediate identification of performance anomalies and determination of their cause.

Essential metrics to monitor:

• Response times of applications used by robots

• Error rate per process step

• System resource consumption

• Availability of external services

3. Underlying Application Monitoring

RPA robots interact with multiple applications and systems. Monitoring these components is crucial to ensure the proper functioning of your automations.

Recommended monitoring architecture:
RPA Robot → Applications → Infrastructure → External Services → User Experience

Case study : AXA reduced incidents related to underlying applications by 65% by implementing a comprehensive DEM solution integrating RPA robot and critical application monitoring.

4. Intelligent alert system and proactive resolution

An effective alert system should be configured to identify anomalies before they impact the business and trigger appropriate corrective actions.

Alert prioritization matrix:

5. Impact analysis and continuous optimization

Impact analysis allows quantifying the effect of RPA performance issues on your business objectives and guiding optimization efforts.

Recommended decision-making dashboard:

• Performance trends over 30/60/90 days

• Dependency mapping and failure points

• Financial impact of incidents

• Optimization opportunities ranked by potential ROI

Integrate DEM into your automation strategy

Methodological approach in 4 steps

1. Evaluation: Audit of existing RPA environment

2. Design: Definition of KPIs and monitoring configuration

3. Implementation: Progressive deployment by order of criticality

4. Optimization: Continuous analysis and adjustments

Demonstrated ROI of DEM for RPA

According to the EY “Automation Excellence 2024” study, companies that implemented a DEM solution for their RPA robots observed:

• 73% reduction in service interruptions

• 62% decrease in MTTR

• 28% increase in RPA team productivity

• Average ROI of 315% over 18 months

Expert resources and references

• Gartner: “Market Guide for Digital Experience Monitoring 2025”

• Forrester Wave™: “RPA Monitoring Solutions, Q1 2025”

• McKinsey: “The Future of Intelligent Automation 2024”

• IDC: “Digital Experience Management for Enterprise Automation 2024”

Recommended tools and technologies

• Ekara (IP-Label): Leading DEM solution with advanced RPA capabilities

• Dynatrace: Full-stack monitoring with AI for causal analysis

• Datadog: Comprehensive monitoring with native integration of RPA platforms

• AppDynamics: End-to-end visibility of RPA applications and processes

Conclusion and Action Plan

Integrating Digital Experience Monitoring into your RPA strategy is no longer an option but a necessity to ensure the reliability, performance, and ROI of your automation investments.

To get started, we recommend:

1. Assessing the maturity of your current RPA monitoring

2. Identifying your critical automated processes

3. Defining your priority KPIs

4. Selecting the DEM solution adapted to your environment