QPR

Analyzes event logs from business systems to automatically discover and visualize actual process flows, revealing hidden inefficiencies, bottlenecks, and deviations from expected workflows. Transforms raw event data into visual process maps that expose operational reality.

Creates interactive dashboards that display live operational metrics, KPIs, and process performance indicators updated in real-time. Provides operations teams with immediate visibility into process health and performance across the organization.

Automatically discovers process flows from event logs and creates visual representations of how work actually flows through the organization. Generates process models that can be explored, filtered, and analyzed interactively.

Calculates process costs by combining event logs with cost data (labor rates, system usage, etc.) to understand the true cost of each process variant and activity. Identifies cost drivers and opportunities for cost reduction.

Allows users to define custom metrics and KPIs based on event log data to track organization-specific performance indicators. Enables creation of business-relevant measures beyond standard process mining metrics.

Analyzes and compares performance across multiple processes simultaneously to identify which processes offer the greatest improvement opportunities. Enables portfolio-level optimization decisions and resource prioritization.

Uses historical process data and machine learning to forecast future process outcomes, identify risks, and predict bottlenecks before they occur. Enables proactive decision-making based on data-driven predictions rather than reactive responses.

Integrates with RPA tools to automate repetitive, rule-based tasks across legacy and modern systems. Orchestrates bot execution at scale to eliminate manual work and reduce human error in high-volume processes.

Compares actual process execution against defined compliance rules, policies, or best practices. Identifies deviations, violations, and non-conformances that could indicate fraud, inefficiency, or regulatory breaches.

Identifies and analyzes different execution paths and variations within the same process. Quantifies the frequency and impact of each variant, helping teams understand process diversity and its business implications.

Measures and analyzes process cycle times, throughput rates, and wait times to identify where processes spend time. Breaks down delays into waiting, processing, and rework components to guide optimization efforts.

Analyzes how resources (people, systems, equipment) are allocated and utilized across processes. Identifies over-utilized bottlenecks and under-utilized resources to optimize resource allocation and capacity planning.

Creates digital simulations of processes based on discovered process models to test potential improvements before implementation. Enables what-if scenario analysis to predict the impact of changes on cycle time, cost, and resource requirements.

Extracts event data from various enterprise systems and transforms it into standardized event logs suitable for process mining analysis. Handles data cleaning, deduplication, and enrichment to prepare high-quality input for mining algorithms.