Process Mining Market by Offering (Software (Process Discovery Tools, Conformance Checking Tools), Services), Mining Algorithm (Deep Learning, Sequence Analysis), Data Source (ERP Systems, CRM Systems), Vertical and Region - Global Forecast to 2028
Updated on : Feb 01, 2024
The process mining market is anticipated to grow rapidly, reaching a value of USD 12.1 billion by 2028 from USD 1.8 billion in 2023. Over the course of the projected period at a CAGR of 45.6%. The rapid expansion of the process mining market can be attributed to several key drivers, as organizations navigate through intricate processes, there's a heightened necessity for tools that can adeptly dissect and optimize these complexities, the pervasive wave of digital transformation has evolved into a tidal force, with businesses across sectors increasingly integrating advanced technologies and process mining serves as the compass, illuminating the intricate pathways of operations, fostering transparency, and empowering organizations with the control needed to navigate through the intricacies of modern business environments.
Technology Roadmap of Process mining till 2030
The process mining market report covers the technology roadmap till 2030, with insights into the short-term, mid-term and long-term developments.
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Short-term (2023–2025):
- Improved data collection from various sources including databases, IoT devices, and external APIs.
- Real-time data integration for more accurate process monitoring.
- More sophisticated data analysis techniques, including statistical analysis and machine learning algorithms.
- Predictive analytics to forecast process issues and bottlenecks.
- User interfaces that are more intuitive and require less technical expertise.
- Enhanced data visualization for easy process analysis.
- Improved scalability to handle larger datasets and complex processes.
- Cloud-based solutions for flexible and cost-effective scaling.
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Mid-term (2026–2028):
- Extensive use of artificial intelligence for process automation and optimization.
- Intelligent process mining tools capable of making autonomous decisions.
- Enhanced integration capabilities with other enterprise systems, such as ERP and CRM.
- Seamless data flow between various business applications.
- Widespread adoption of blockchain for secure and transparent process data recording.
- Integration with smart contracts for automated process execution.
- Quantum computing will be used for complex data processing and analysis.
- Faster and more accurate process discovery and monitoring.
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Long-term (2029–2030):
- Comprehensive process mining suites offering end-to-end process management.
- Integration with a wide range of business systems and applications.
- AI-driven process improvement recommendations integrated into everyday business operations.
- Proactive decision support for process optimization.
- Process mining becomes an integral part of core business operations.
- Real-time process monitoring and optimization for competitive advantage.
- Process mining embedded in DevOps and Continuous Integration/Continuous Deployment (CI/CD) pipelines.
- Real-time monitoring and optimization of software development and deployment processes.
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Market Dynamics
Driver: Increasing complexity of business processes
With businesses engaging in diverse and interdependent operations globally, the intricate network of workflows is further compounded by the integration of technologies such as ERP systems, CRMs, and RPA. Stringent regulatory compliance requirements, coupled with the imperative to meet customer expectations for personalized experiences, contribute to the multifaceted nature of these processes. Process mining emerges as a vital tool, providing real-time visibility, actionable insights, and historical perspectives to unravel the complexities, optimize operations, and drive informed decision-making in the ever-evolving landscape of modern business.
Restraint: Data security and privacy concerns
In this modern era, where organizations increasingly rely on process mining solutions to optimize their operations, the sensitivity and confidentiality of data cannot be overstated. As businesses delve into the intricate details of their processes through mining, there is a growing apprehension about the security of the data being analyzed. Companies handle vast amounts of proprietary information, including customer data, financial records, and internal operations data, making them susceptible to breaches. The reluctance to adopt process mining tools often stems from the fear that exposing such granular insights may inadvertently lead to data leaks or unauthorized access. Compliance with data protection regulations, such as GDPR, adds an additional layer of complexity, necessitating stringent measures to ensure adherence. This concern is particularly pronounced in industries dealing with highly regulated information, such as finance and healthcare, where the repercussions of a security breach can be severe, including legal actions, financial penalties, and reputational damage.
Opportunity: Artificial intelligence and machine learning integration
As organizations across various sectors strive for operational excellence and efficiency, the synergy between AI, ML, and Process Mining emerges as a powerful solution. AI and ML technologies enhance Process Mining capabilities by enabling advanced data analysis and predictive insights. Process Mining involves the extraction of knowledge from event logs to discover, monitor, and improve business processes. When integrated with AI and ML, it transcends mere retrospective analysis, offering proactive and real-time decision-making support. One key aspect is the ability of AI and ML algorithms to handle large and complex datasets, allowing for more comprehensive process mapping and analysis. This, in turn, facilitates the identification of inefficiencies, bottlenecks, and opportunities for optimization within business processes. The predictive analytics offered by ML algorithms further empower organizations to forecast potential process deviations, enabling preemptive corrective actions.
Challenge:Interpreting complex insights
Process Mining tools are adept at extracting and analyzing vast amounts of data to provide valuable insights into business processes. However, the sheer volume and intricacy of the generated data often pose a usability challenge for end-users. The complexity arises from the diverse sources of data, intricate process interdependencies, and the nuanced nature of business workflows. Organizations may struggle to derive actionable insights from the wealth of information presented by Process Mining tools, hindering effective decision-making. The challenge of interpreting complex insights translates into a potential bottleneck for deriving meaningful and strategic conclusions. This complexity can overwhelm users, leading to difficulties in identifying key patterns, bottlenecks, or areas for improvement in their processes.
Process Mining Market Ecosystem
By offering, continuous monitoring & analytics tools software segment to account for a larger market size during forecast period
The software segment of the process mining market includes various software solutions that cater to the needs of several industries. Continuous analytics allow organizations to continuously optimize their processes based on real-time data. This iterative improvement cycle ensures that businesses are always operating at peak performance, meeting customer expectations, and adapting to changing market dynamics effectively. These tools enable proactive issue identification and resolution. By constantly analyzing processes, they can detect anomalies or inefficiencies before they escalate. This proactive approach aligns with the modern business ethos of preventing problems rather than reacting to them, contributing to smoother operations.
By mining algorithm, discovery algorithms segment to hold the largest market share during the forecast period
In an era marked by increasingly complex business operations, discovery algorithms showcase a remarkable adaptability. They excel in handling intricate process structures and variations, making them indispensable for industries with multifaceted workflows. This adaptability positions them as the go-to solution for businesses navigating intricate operational scenarios. The iterative nature of discovery algorithms allows for continuous monitoring of processes. As businesses evolve and adapt to changing market dynamics, these algorithms facilitate real-time insights into ongoing operations.
By data source, financial systems data segment to register the fastest growth rate during the forecast period
Financial systems form the backbone of any organization, serving as the nerve center for monetary transactions, budgeting, and financial planning. As businesses increasingly recognize the pivotal role of finance in overall operational health, the demand for process mining within financial systems intensifies. Financial processes are inherently complex, involving numerous steps and stakeholders. Process mining excels in unraveling intricate workflows, identifying bottlenecks, and optimizing processes for efficiency. The financial systems data segment benefits significantly from the ability of process mining to streamline these intricate financial workflows.
By region, Europe to hold the largest market size during the forecast period
Process mining's versatility makes it applicable across a wide range of industries, from manufacturing to finance. Europe, with its diverse economic landscape, sees widespread adoption of process mining solutions across various sectors, contributing to the region's overall market share. Supportive government initiatives and funding for digital transformation projects further propel the adoption of process mining in Europe. This creates an environment conducive to innovation and technological advancement, fostering the growth of the process mining market in the region.
Europe has a well-established regulatory framework that emphasizes transparency and compliance in business operations. The need to adhere to stringent regulations, such as GDPR (General Data Protection Regulation), propels the adoption of process mining solutions as organizations seek tools to ensure compliance and maintain a clear audit trail. European businesses have a strong focus on achieving operational excellence to remain competitive on the global stage. Process mining plays a pivotal role in streamlining processes, identifying bottlenecks, and optimizing workflows, aligning perfectly with the strategic objectives of businesses in the region.
Key Market Players
The process mining solution and service providers have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgrades, partnerships, and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. Some major players in the process mining market include UiPath (US), ABBYY (US), Celonis (US), IBM (US) and Software AG (Germany) along with start-ups such as Apromore (Australia), Inverbis Analytics (Spain), Mindzie (US), and Workfellow (Finland).
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Report Metrics |
Details |
Market size available for years |
2018–2028 |
Base year considered |
2022 |
Forecast period |
2023–2028 |
Forecast units |
USD (Billion) |
Segments covered |
Offering, Mining Algorithms, Data Source, Vertical, and Region |
Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
Companies covered |
IBM (US), ABBYY (US), Celonis (US), UiPath (US), Software AG (Germany), SAP Signavio (Germany), QPR Software (Finland), Microsoft (US), Appian (US), Pegasystems (US), Mehrwerk (Germany), Kofax (US), Soroco (US), iGrafx (US), Nintex (US), Automation Anywhere (US), Hyland Software (US), Fluxicon (Netherlands), Datapolis (Poland), Apromore (Australia), BusinessOptix (US), StereoLOGIC (Canada), Worksoft (US), Inverbis Analytics (Spain), Skan.ai (US), Mindzie (US), Cyclone Robotics (China), Upflux (Brazil), Puzzledata Inc. (South Korea), Kyp.ai (Germany), Workfellow (Finland). |
This research report categorizes the process mining market based on offering, mining algorithms, data source, vertical, and region
By Offering:
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Software
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Process Discovery Tools
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Event Log-Based Discovery
- Automated Discovery
- Interactive Discovery
- Log Filtering & Preprocessing
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Process Map-Based Discovery
- Flowchart Generation
- Process Map Visualization
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Event Log-Based Discovery
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Conformance Checking Tools
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Model-Checking Conformance
- Direct Model Comparison
- Statistical Model Checking
- Automated Rule-Based Conformance
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Log-Based Conformance
- Deviation Detection
- Anomaly Detection
- Root Cause Analysis
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Model-Checking Conformance
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Process Enhancement & Simulation Tools
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Simulation & Optimization
- Process Simulation
- What-If Analysis
- Optimization Algorithms
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Process Enhancement & Automation
- Recommendation Engine
- Automation Integration
- Process Redesign Tools
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Simulation & Optimization
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Performance Analysis Tools
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Performance Metrics
- Key Performance Indicator (KPI) Tracking
- Process Efficiency Analysis
- Bottleneck Identification
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Performance Visualization
- Real-Time Performance Dashboards
- Historical Performance Trends
- Performance Benchmarking
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Performance Metrics
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Visualization Tools
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Process Visualization
- Interactive Process Maps
- Process Flowcharts
- Heatmaps & Sankey Diagrams
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Data Visualization
- Data Dashboards
- Custom Data Visualizations
- Data Exploration Tools
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Process Visualization
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Continuous Monitoring & Analytics tools
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Real-Time Monitoring
- Continuous Event Stream Analysis
- Real-Time Process Tracking
- Alerting & Notification
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Historical Analytics
- Trend Analysis
- Root Cause Analysis
- Historical Process Performance Reports
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Predictive Analytics
- Machine Learning Models
- Predictive KPI Forecasting
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Advanced Prediction Models
- Complex Event Processing
- Time Series Forecasting
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Real-Time Monitoring
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Integration & Collaboration tools
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Data Integration
- Data Source Integration
- API & Data Connector Support
- Data Transformation & Mapping
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Collaboration Tools
- Workflow Collaboration
- Team Collaboration
- Process Documentation & Sharing
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Data Integration
- Other Software
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Process Discovery Tools
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Services
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Professional Services
- System Integration & Implementation Services
- Support & Maintenance Services
- Training & Consulting Services
- Managed Services
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Professional Services
By Mining Algorithms:
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Discovery Algorithms
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Heuristic Mining
- Directly-Follows Graph Discovery
- Dependency Graph Discovery
- Alpha Algorithm
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Alpha Miner
- Enhanced Heuristic Mining
- Noise Filtering
- Loop Handling
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Inductive Miner
- Directly-Follows Graph Induction
- Log-Petri Net Conversion
- Noise Tolerance
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Heuristic Mining
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Conformance Checking Algorithms
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Token-Based Replay
- Fitness Assessment
- Alignments
- Precision & Generalization
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Log-Based Conformance Checking
- Deviation Detection
- Conformance Metrics
- Root Cause Analysis
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Model-Based Conformance Checking
- Process Model Alignment
- Fitness Analysis
- Precision & Generalization
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Token-Based Replay
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Enhancement & Extension Algorithms
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Process Simulation
- Monte Carlo Simulation
- Process Variability Analysis
- What-If Analysis
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Recommendation Algorithms
- Process Optimization Suggestions
- Resource Allocation Recommendations
- Compliance Improvement Guidance
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Predictive Analytics Algorithms
- Machine Learning for Process Predictions
- Predictive KPI Monitoring
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Process Simulation
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Clustering & Classification Algorithms
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Process Instance Clustering
- Similarity Measures
- Hierarchical Clustering
- K-Means Clustering
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Process Variant Classification
- Decision Tree Classification
- Naive Bayes Classification
- Support Vector Machines (SVM)
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Anomaly Detection
- Statistical Anomaly Detection
- Isolation Forest
- Autoencoders for Sequence Anomalies
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Process Instance Clustering
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Sequence Analysis Algorithms
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Sequential Pattern Mining
- Frequent Sequential Pattern Discovery
- Parallel Sequence Mining
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Sequence Alignment
- Event Log Sequence Alignment
- Sequence Edit Distance Metrics
- Sequence Clustering
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Process Path Analysis
- Path Frequency Analysis
- Abstraction of Process Paths
- Critical Path Identification
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Sequential Pattern Mining
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Deep Learning Algorithms
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Recurrent Neural Networks (RNN)
- LSTM-Based Process Analysis
- GRU-Based Sequence Modeling
- Event Sequence Prediction
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Transformer Models
- Attention-Based Process Analysis
- Transformer-XL for Long Sequences
- Process Text Mining
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Graph Neural Networks (GNN)
- Graph-Based Process Analysis
- Graph Attention Networks (GAT)
- GNNs for Process Prediction
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Recurrent Neural Networks (RNN)
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Temporal Process Mining Algorithms
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Temporal Pattern Discovery
- Time Interval-Based Patterns
- Temporal Rules & Constraints
- Duration Analysis
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Time Series Analysis
- Event Log Time Series Analysis
- Process Event Forecasting
- Time-Related Process Insights
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Temporal Pattern Discovery
- Other Mining Algorithms
By Data Source:
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Enterprise Resource Planning (ERP) Systems
- Financial ERP Data
- Inventory ERP Data
- Procurement ERP Data
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Customer Relationship Management (CRM) Systems
- Sales CRM Data
- Marketing CRM Data
- Customer Support CRM Data
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IoT Devices & Sensors
- Sensor Data Analytics
- IoT Device Performance Data
- Predictive Maintenance Data
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Custom Applications & Databases
- Custom Database Tables
- Legacy Application Data
- Web Application Logs
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Workflow & BPM Systems
- Workflow Process Data
- Business Process Model & Notation (BPMN) Model Execution
- Process Workflow Metrics
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Document Management Systems
- Document Workflow Data
- Content Management Data
- Digital Signature Workflows
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Supply Chain & Logistics Data
- Transportation & Shipping Data
- Supplier & Vendor Interactions
- cold-chain monitoring Data
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Financial Systems Data
- Accounting & Financial Transactions
- Expense Management Data
- Audit & Compliance Records
- Other Data Sources
By Vertical:
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BFSI
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Loan Origination & Underwriting
- Credit Risk Assessment
- Mortgage Approval Process
- Loan Document Verification
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Fraud Detection & Prevention
- Transaction Fraud Analysis
- Identity Theft Detection
- Anti-Money Laundering (AML)
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Customer Onboarding & KYC
- Customer Due Diligence
- KYC Process Efficiency
- Compliance Monitoring
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Claims Processing
- Insurance Claims Verification
- Claims Settlement Efficiency
- Fraudulent Claims Detection
- Others
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Loan Origination & Underwriting
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Manufacturing
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Production Optimization
- Production Line Efficiency
- Workforce Productivity
- Equipment Utilization
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Quality Control & Assurance
- Defect Detection & Prevention
- Compliance Monitoring
- Root Cause Analysis
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Supply Chain Management
- Inventory Optimization
- Supplier Performance Analysis
- Demand Forecasting & Planning
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Maintenance & Reliability
- Predictive Maintenance
- Asset Utilization Analysis
- Downtime Reduction
- Others
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Production Optimization
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IT & ITeS
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Software Development Lifecycle (SDLC) Analysis
- Code Review & Optimization
- Bug & Issue Tracking
- Release Cycle Efficiency
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IT Help Desk & Support
- Ticket Resolution Time Analysis
- Incident Trends & Patterns
- Service Level Agreement (SLA) Compliance
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IT Infrastructure Management
- Network Performance Monitoring
- Server Resource Utilization
- IT Asset Inventory
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Cybersecurity & Threat Detection
- Intrusion Detection & Response
- Security Incident Analysis
- Compliance with Security Policies
- Others
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Software Development Lifecycle (SDLC) Analysis
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Healthcare & Life Sciences
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Patient Care & Hospital Management
- Patient Journey Analysis
- Resource Allocation Optimization
- Billing & Claims Processing
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Clinical Trials Optimization
- Trial Enrollment Efficiency
- Adverse Event Analysis
- Drug Development Timelines
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Electronic Health Records (EHR) Analysis
- EHR Data Accuracy
- Regulatory Compliance
- Patient Outcome Improvement
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Supply Chain & Pharmaceutical Manufacturing
- Pharmaceutical Production Optimization
- Drug Traceability
- Inventory Management
- Others
-
Patient Care & Hospital Management
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Retail & E-Commerce
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Customer Experience Enhancement
- Customer Journey Mapping
- Personalization & Recommendations
- Cart Abandonment Analysis
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Inventory & Stock Management
- Stock-Level Optimization
- stock Demand Forecasting
- Shelf Space Optimization
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Order Fulfillment & Logistics
- Order Processing Efficiency
- Delivery Time Optimization
- Returns Management
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Pricing & Promotion Strategy
- Dynamic Pricing Analysis
- Promotion Effectiveness
- Profit Margin Optimization
- Others
-
Customer Experience Enhancement
-
Energy & Utilities
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Energy Consumption Analysis
- Energy Efficiency Improvement
- energy Demand Forecasting
- Renewable Energy Integration
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Asset Management & Predictive Maintenance
- Equipment Reliability Analysis
- Asset Performance Optimization
- Grid Resilience Enhancement
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Grid & Distribution Optimization
- Grid Performance Analysis
- Distribution Network Efficiency
- Smart Grid Implementation
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Environmental Compliance
- Emissions Monitoring & Reporting
- Regulatory Compliance
- Sustainability Initiatives
- Others
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Energy Consumption Analysis
-
Transportation & Logistics
-
Route Optimization
- Transportation Route Efficiency
- Delivery Time Monitoring
- Fleet Management
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Inventory & Warehouse Management
- Inventory Turnover Optimization
- Warehouse Efficiency
- Demand Forecasting
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Logistics Visibility & Tracking
- Supply Chain Visibility
- Carrier Performance Analysis
- Last-Mile Delivery Optimization
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Safety & Compliance
- Driver Safety Monitoring
- Regulatory Compliance
- Incident & Accident Analysis
- Others
-
Route Optimization
-
Government & Defense
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Citizen Services Improvement
- Government Service Efficiency
- Citizen Experience Enhancement
- Compliance Monitoring
-
Public Health & Safety
- Emergency Response Optimization
- Disease Surveillance
- Traffic Management
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Regulatory Compliance & Auditing
- Audit Trail Analysis
- Data Privacy Compliance
- Regulatory Reporting
- Others
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Citizen Services Improvement
-
Education
-
Student Lifecycle Management
- Enrollment Process Optimization
- Academic Performance Analysis
- Student Support Services
-
Curriculum & Course Optimization
- Curriculum Design Efficiency
- Course Enrollment Analysis
- Learning Outcome Improvement
-
Resource Allocation
- Faculty Workload Balancing
- Infrastructure Utilization
- Budget Allocation Efficiency
- Others
-
Student Lifecycle Management
- Other Verticals
By Region:
-
North America
- US
- Canada
-
Europe
- UK
- Germany
- France
- Italy
- Spain
- Netherlands
- Rest of Europe
-
Asia Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Australia & New Zealand (ANZ)
- Rest of Asia Pacific
-
Middle East and Africa
- Saudi Arabia
- UAE
- South Africa
- Turkey
- Rest of Middle East & Africa
-
Latin America
- Brazil
- Mexico
- Argentina
- Rest of Latin America
Recent Developments:
- In July 2023, Microsoft announced the launch of Power Automate Process Mining, infused with next-generation AI which enables organizations to easily understand what is happening across their business, maximize process insights, use out-of-box recommendations to reduce the complexity of processes, transform operations, and drive continuous process improvement with automation and low-code apps.
- In May 2023, Pegasystems announced the launch of Pega Process Mining, which will make it easier for Pega users of all skill levels to find and fix process inefficiencies hindering their business operations.
- In May 2023, QPR Software announced a brand-new partnership with Paris-based Solution BI, known for their customer-centric end-to-end business intelligence solutions.
- In March 2023, UiPath launched a new process mining tool called Communications Mining which brings new capabilities to understand and automate business communications. It uses state-of-the-art AI models to turn business messages—from emails to tickets—into actionable data.
- In January 2023, Appian announced a strategic alliance with EY to support clients on digital transformation initiatives using the next wave of intelligent automation and process mining.
Frequently Asked Questions (FAQ):
What is process mining?
Process mining is a method of applying specialized algorithms to discover, validate and improve workflows. By combining data mining and process analytics, organizations can mine log data from their information systems to understand the performance of their processes, revealing bottlenecks and other areas of improvement. Process mining leverages a data-driven approach to process optimization, allowing managers to remain objective in their decision-making around resource allocation for existing processes.
What is the total CAGR expected to be recorded for the process mining market during 2023-2028?
The market is expected to record a CAGR of 45.6% from 2023-2028.
Which are the major growth enablers catalyzing the process mining market?
The process mining market is being majorly driven by factors such as increasing complexity of business processes, rising adoption of digital transformation and growing need for process visibility and control.
Which are the top three process mining tools prevailing in the process mining market?
Continuous monitoring and analytics tools, process discovery tools, and conformance checking tools are among the top-3 process mining tools in terms of adoption because they offer organizations the ability to gain real-time insights into their business processes, identify bottlenecks and inefficiencies, ensure compliance with desired process models, and make data-driven decisions.
Who are the key vendors in the process mining market?
Some major players in the process mining market include IBM (US), ABBYY (US), Celonis (US), UiPath (US), Software AG (Germany), SAP Signavio (Germany), QPR Software (Finland), Microsoft (US), Appian (US), Pegasystems (US), Mehrwerk (Germany), Kofax (US), Soroco (US), iGrafx (US), Nintex (US), Automation Anywhere (US), Hyland Software (US), Fluxicon (Netherlands), Datapolis (Poland), Apromore (Australia), BusinessOptix (US), StereoLOGIC (Canada), Worksoft (US), Inverbis Analytics (Spain), Skan.ai (US), Mindzie (US), Cyclone Robotics (China), Upflux (Brazil), Puzzledata Inc. (South Korea), Kyp.ai (Germany), Workfellow (Finland).
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The process mining market research study involved extensive secondary sources, directories, journals, and paid databases. Primary sources were mainly Interviews with experts from the core and related industries, preferred process mining providers, third-party service providers, consulting service providers, end-users, and other commercial enterprises. In-depth interviews were conducted with various primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information and assess the market’s prospects.
Secondary Research
In the secondary research process, various sources were referred to for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendors’ websites. Additionally, Process mining spending of various countries was extracted from the respective sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on solutions, services, market classification, and segmentation according to offerings of major players, industry trends related to solutions, services, deployment modes, business functions, applications, verticals, and regions, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various Interviews with Experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and process mining expertise; related key executives from process mining software vendors, SIs, professional service providers, and industry associations; and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using Process mining solutions, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of Process mining solutions and services, which would impact the overall process mining market.
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COMPANY NAME |
DESIGNATION |
IBM |
Business Process Consultant |
Celonis |
Vice President India COE |
Microsoft |
Principal Program Manager |
UiPath |
VP of Engineering - Process Mining |
SAP Signavio |
Customer Solution Director |
Pegasystems |
Global Head of Insurance |
Market Size Estimation
In the bottom-up approach, the adoption rate of process mining solutions and services among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of Process mining solutions and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the Process mining market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major Process mining providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall Process mining market size and segments’ size were determined and confirmed using the study.
Global Process mining Market Size: Bottom-Up and Top-Down Approach:
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Data Triangulation
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the process mining market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major process mining providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall Process mining market size and segments’ size were determined and confirmed using the study.
Market Definition
IBM defines process mining as the utilization of specialized algorithms to uncover, validate, and enhance workflows. This approach amalgamates data mining and process analytics, enabling enterprises to extract valuable insights from log data derived from their information systems. This valuable data helps organizations comprehend the efficiency of their processes, unveiling impediments and potential areas for enhancement. Process mining relies on a data-centric strategy for optimizing processes, enabling managers to maintain objectivity in their decisions concerning the allocation of resources to existing processes.
Stakeholders
- Process mining software vendors
- Process mining service vendors
- Managed service providers
- Support and maintenance service providers
- System Integrators (SIs)/migration service providers
- Value-Added Resellers (VARs) and distributors
- Distributors and Value-added Resellers (VARs)
- Independent Software Vendors (ISV)
- Third-party providers
- Technology providers
Report Objectives
- To define, describe, and predict the process mining market by offering (software and services), mining algorithm, data source, vertical, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
- To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the process mining market
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies.
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the process mining market
- To analyze the impact of recession across all the regions across the process mining market
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per your company’s specific needs. The following customization options are available for the report:
Product Analysis
- Product quadrant, which gives a detailed comparison of the product portfolio of each company.
Geographic Analysis
- Further breakup of the North American Process mining market
- Further breakup of the European market
- Further breakup of the Asia Pacific market
- Further breakup of the Middle Eastern & African market
- Further breakup of the Latin America Process mining market
Company Information
- Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in Process Mining Market