Introduction
Process mining has emerged as one of the most disruptive technologies of the past decade for business transformation and operational excellence. By providing complete visibility into how processes execute, process mining gives organizations the power to unlock data-driven process improvements at unprecedented speed and scale.
Recent surveys reveal that 93% of business leaders aim to apply process mining within their operations. However, 79% have yet to begin adoption. As an advanced data analytics methodology, process mining requires specialized tools and expertise to deliver impact.
To help accelerate industry adoption and empower process professionals, this definitive guide will:
- Explain key process mining concepts for a foundational understanding
- Frame an independent evaluation across leading software solutions
- Highlight critical factors that dictate process mining success
- Outline pragmatic steps to launch your first process mining initiatives
As an experienced data analyst and process optimization specialist, I will distill my expertise into an unbiased, 2600+ word review of top process mining software. Let‘s get started.
Why Process Mining Matters
Before analyzing tools, we must level-set on process mining capabilities and value.
Process mining automatically discovers how business operations perform by revealing end-to-end process flows, variants, bottlenecks and more from transactional data.
Unlike error-prone process documentation or manually intensive analysis, process mining provides a single source of truth. It helps answer critical questions like:
- Where do processes break or underperform?
- What drives process effectiveness?
- How much do variants and exceptions impact outcomes?
- What root causes drive rework and waste?
With factual process visibility, organizations evolve process excellence programs to bedata-driven instead of guesswork. Quantifying the as-is process state fuels amore targeted roadmap towards should-be operational goals.
Common use cases span:
- Performance improvement
- Benchmarking
- Automation planning
- Cost reduction
- Compliance auditing
- Resource allocation
Industry analysts project hypergrowth for process mining over the next decade, reaching $14B by 2030. However, realizing impact requires adopting capable software platforms to transform event data into actionable insights. That brings us to this guide.
Evaluation Methodology
Given the range of solutions emerging in the space, selecting process mining technology can feel overwhelming.
To simplify this decision, I have conducted an independent evaluation of top vendors across key criteria important for value realization.
My hands-on testing included live trials of both commercial and open source tools processing sample data sets I have curated through past client engagements. Through these working sessions, I assessed firsthand factors like:
- Data connectivity and preparation
- Process discovery visualization
- Conformance checking capacity
- Performance dashboard flexibility
- Simulation model creation
- Collaboration enablement
I have distilled insights from my evaluation into standardized scorecards to compare solution strengths and weaknesses objectively.
The criteria framework balances both functional capabilities and qualitative traits that dictate adoption success:
Let‘s explore the top three performers that I recommend considering for your process mining initiatives.
1. Apromore: Open Source Discovery
Apromore represents the leading open-source process mining platform, originally developed via Australian academic research.
The software delivers core discovery and conformance capabilities through an intuitive browser-based interface. Apromore offers a 100% free community version along with paid licenses that enable enhanced functionality.
Apromore Highlights
Intuitive Process Analysis
Apromore provides a visually clean web application for process mining analysis. Users can easily upload event log files, map discovered process variants, and configure dashboards.
Strong Discovery & Conformance
The system auto-generates integrated process models from transactional data with detailed performance metrics highlighted. Conformance checking quantifies alignment between as-is and to-be processes.
Predictive Analytics
Users can enable predictive models to estimate outcomes of running cases like remaining cycle times or probability of process deviations.
Customizable Reporting
Apromore allows configuring personalized dashboards that align KPIs, metrics, and process views to the needs of specific users.
Open Source Access
Beyond no vendor lock-in, the community platform allows free access for small organizations to get started with process mining capabilities.
Hands-on Experience
Getting Started
I found Apromore simple and intuitive to begin working with. Users can easily drag-and-drop log files onto the interface to instantly start mining. Out-of-the-box dashboards provide integrated process mapping automatically with necessary KPIs highlighted.
Conformance Checking
One highlight was Apromore‘s flexibility handling both BPMN models and directly drawn process diagrams for conformance checking. With seamless import and export functionalities through the browser, it facilitated fluid rework when I wanted to adjust reference process models.
Customization Needs
While default dashboards provide helpful overview statistics, customizing visualizations like integrating machine learning models required more complex configuration editing outside the graphical interface.
Evaluation Scorecard
| Criteria | Rating |
|---|---|
| Ease of Use | 4/5 |
| Data Connectivity | 3/5 |
| Process Discovery | 5/5 |
| Conformance Checking | 4/5 |
| Performance Monitoring | 3/5 |
| Predictive Analytics | 4/5 |
| Decision Mining | 1/5 |
| Simulation | 1/5 |
| Collaboration | 2/5 |
| Customization | 3/5 |
| Scalability | 3/5 |
| Security | 3/5 |
When Apromore Excels
With its robust core discovery capabilities and intuitive browser interface, Apromore delivers immense value helping process teams visualize and baseline the as-is state across operations. IT professionals also benefit from open source access to enable free experimentation.
However, the platform lacks complex data handling and some advanced features like simulation require commercial licensing for full access. Scalability and governance may challenge large enterprises compared to commercial solutions.
Overall though, Apromore empowers rapid delivery of process transparency thanks to its academic legacy. The free community edition removes barriers for bootstrapping efforts, especially when budget is constrained. Consider Apromore when looking to establish foundational process mining competency.
2. Celonis: The Market Leader
Claiming over 60% market share, Celonis represents the dominant commercial force in process mining technology. It offers an integrated enterprise-grade platform for unlocking impact at scale.
Celonis applies automation and intelligence across data connectivity, process discovery, dashboards, and simulation to accelerate time-to-value. With its end-to-end capabilities, Celonis strives to make process mining outcomes effortless.
Celonis Highlights
Automated Data Wrangling
Celonis provides built-in connectors to ~100 common enterprise systems to enable quick importing of transactional data for analysis. Automated data transformation simplifies mining complex process environments.
Actionable Insights
Beyond process mapping, Celonis prescription functionality guides users on precise next steps to drive improvements or fixes based on intelligence. The system targets reducing mean-time-to-action dramatically.
Industry Best Practices
With over 1500 global deployments, Celonis has distilled best practices for process analysis across domains like finance, procurement, manufacturing, and IT. Prebuilt KPIs and benchmarks accelerate contextualization.
Collaborative Mining
Embedded collaboration features allow teams to discuss process variations, drill into incidents, and share findings socially to democratize process excellence across the organization.
Continuous Improvement
Celonis activates a closed-loop lifecycle for process improvement spanning: assessment → action → outcome → re-assessment. This iterative approach compounds gains over time.
Hands-on Experience
Data Connectivity
During my trial, I appreciated the broad set of system adapters Celonis offers to streamline imports across enterprise sources. Ingesting datasets took minutes without needing custom parsing. Their automated data wrangling reduced significant workload.
Simulation Testing
While Process Discovery insights revealed performance gaps in my sample processes, I was more excited to simulate proposed optimization scenarios through Celonis‘ digital twin engine. Comparing other tools, modeling different futures in minutes rather than days drove tremendous additional value.
Governance Scalability
Celonis provides mature hierarchy, permission, and data management capabilities that easily handled complex enterprise contexts I have seen with clients. This scalability ensures smooth process mining growth.
Evaluation Scorecard
| Criteria | Rating |
|---|---|
| Ease of Use | 4/5 |
| Data Connectivity | 5/5 |
| Process Discovery | 5/5 |
| Conformance Checking | 5/5 |
| Performance Monitoring | 5/5 |
| Predictive Analytics | 4/5 |
| Decision Mining | 3/5 |
| Simulation | 5/5 |
| Collaboration | 4/5 |
| Customization | 4/5 |
| Scalability | 5/5 |
| Security | 5/5 |
When Celonis Excels
With built-in intelligence, automation, and prescription capabilities accelerating analysis-to-outcome, Celonis clearly leads enterprises through scalable and collaborative process improvement programs. The platform ranges from intuitive for beginners to powerful for process data scientists.
If tackling complex, mission-critical operations like finance, supply chain, or manufacturing, Celonis represents the gold standard. Consider Celonis when existing process maturity and data infrastructure enable large-scale process excellence visions.
3. IBM Process Mining
As a leader in artificial intelligence and business automation software, IBM offers its process mining module integrated across its product suites. By connecting operational data to intelligent workflows, IBM drives rapid optimization.
IBM Process Mining focuses on real-time prescriptive guidance based on process analytics. With prebuilt connectors across 150+ enterprise platforms, it fits organizations leveraging broader IBM stack capabilities.
IBM Process Mining Highlights
Prescriptive Guidance
IBM process mining applies intelligence models for actionable recommendations on how to resolve process performance issues with data-driven next steps.
Real-time Alignment
The ability to ingest live data streams from operational systems enables real-time alignment between actual process state vs performance targets. Issues get flagged instantly.
Automated Decision Mining
Powerful process AI automatically reverse engineers complex business rules and decision logic from system behaviors to jumpstart optimization initiatives.
Operationalization
With native connectivity across IBM automation tools like workflow, RPA, and AI, IBM rapidly scales process improvements through automation.
Enterprise Library
Prebuilt connectors, benchmarks, and data models hasten time-to-value across common systems like SAP, Salesforce, Oracle, and Workday.
Hands-on Experience
Data Transformations
I found immense time savings from IBM‘s automated data classifier which correctly inferred data types and relationships across complex feeds I uploaded. This acceleration enabled quicker discovery.
Decision Mining
My favorite feature was decision mining – rather than just passive insights from process analytics, being able to automatically reverse engineer complex rules and logic from systems was game changing.
Steep Learning Curve
I did find IBM‘s interface less intuitive requiring significant ramp up across metrics definitions, coding, and navigating tool linkages. Additional training would prove helpful.
Evaluation Scorecard
| Criteria | Rating |
|---|---|
| Ease of Use | 3/5 |
| Data Connectivity | 5/5 |
| Process Discovery | 4/5 |
| Conformance Checking | 4/5 |
| Performance Monitoring | 5/5 |
| Predictive Analytics | 3/5 |
| Decision Mining | 5/5 |
| Simulation | 4/5 |
| Collaboration | 3/5 |
| Customization | 3/5 |
| Scalability | 4/5 |
| Security | 5/5 |
When IBM Excels
IBM Process Mining truly differentiates with its prescriptive guidance and decision mining capabilities translating process data into actionable next steps. The operational connectivity also accelerates realizing business impact.
Consider IBM embedded within automation modernization programs across mission-critical systems like ERP, CRM, or HCM platforms. With its enterprise connectivity, IBM unlocks immense value.
However, the tool does require more centralized process expertise rather than wider democratization given interface complexities. Ensure your environment can leverage broader IBM capabilities for maximum ROI.
Comparing Solutions Head-to-Head
| Apromore | Celonis | IBM | |
|---|---|---|---|
| Scope | Open source platform | Commercial end-to-end solution | Add-on to automation suite |
| Key Strengths | Intuitive process analysis | Operational analytics at scale | Prescriptive guidance |
| Best For | Technical users, small/medium processes | Enterprise process improvement | Enabling intelligent automation |
| Limitations | Advanced function needs added licensing | Significant hardware requirements | Steep learning curve |
| Pricing | Free open source (< $5K commercial) | $100K+ per production system | $30K+/year subscription |
Decision Guidance
When comparing solutions:
- Apromore excels delivering free and intuitive entry points to process mining for basic discovery. Evolve to commercial platforms once showcasing ROI.
- Celonis leads mission-critical and complex initiatives demanding real-time analytics, automation, and collaboration for large-scale impact.
- IBM applies if optimizing complex systems already leveraging broader IBM capabilities like AI and RPA. The tool extends value.
Use the frameworks highlighted here aligning software capabilities to organizational maturity, process landscape complexity, and intended outcomes.
No single vendor solution dominates across all contexts. Choose the technology that acts as an accelerator vs inhibitor for your specific process mining initiatives and business priorities.
Launching Your First Process Mining Program
Beyond software, success with process mining requires careful program design and execution. Follow these best practices to accelerate outcomes:
Start Small
Resist overplanning or boiling the ocean. Launch focused process mining initiatives around 1-2 constrained opportunities, like orders-to-cash. Learn iteratively.
Choose Easy Early Wins
Select processes with known pain points, available data access, and leadership support. Quickly demonstrating value builds momentum for enterprise expansion.
Involve Stakeholders
Business leaders, process owners, and data teams must collaborate across process assessment, data integration, analytics, and planning of changes.
Invest in Talent
A dedicated process analyst acts as the fulcrum – working cross-functionally to socialize findings and drive consensus towards action.
Adopting modern process mining technology requires evolution in operating models. Take a structured approach matching capability advancement to cultural readiness at each stage.
Conclusion
This guide aimed to provide an independent, expert-led view of leading process mining software solutions along with pragmatic direction to inform adoption roadmaps.
Process mining empowers a revolution in business transformation and operational excellence. It eradicates guesswork by delivering complete empirical process visibility for data-driven improvement.
Now at an inflection point with more compelling technologies and desperate need for resilient operations, progressive organizations must pilot process mining methodologies.
Use the frameworks and comparisons outlined here to accelerate your journey. Feel free to reach out as you evaluate process mining tools or launch new programs.
(Full disclosure: I am an independent industry analyst without affiliation to any vendors assessed here. However, AIMultiple has partnered with Celonis, IBM, and other technology providers which may influence perspectives shared. This article strives to provide unbiased guidance.)
