Executive Summary
Process mining reconstructs how processes actually run from ERP and CRM event logs, surfacing deviations and bottlenecks that hand-drawn flowcharts hide. The choice depends on depth, from Celonis’s execution-management ambitions to UiPath Process Mining, SAP Signavio, and Microsoft Process Advisor, but all require clean event data from source systems.
Process mining shows you exactly how work really flows — but the map is worthless unless someone owns fixing what it exposes, and the hard part is the data plumbing, not the visualization.
Celonis, UiPath Process Mining, SAP Signavio, and Microsoft Process Advisor reconstruct how processes actually run from the event logs your ERP and CRM already generate, surfacing the deviations, bottlenecks, and rework that hand-drawn flowcharts hide. They differ in depth — from Celonis’s execution-management ambitions to mining wired directly into automation, SAP-centric process intelligence, and accessible mining inside the Power Platform — but all of them depend on getting clean event data out of source systems first.
This guide provides a vendor-neutral evaluation framework for 8 leading platforms, weighing source-system connectivity and data extraction, analysis and conformance depth, and the path from insight to action so you can buy measurable process improvement rather than a gallery of process maps.
Why Process Mining & Process Intelligence Matters for Enterprise Strategy
Process Mining & Process Intelligence matters because it provides evidence of where work stalls, enabling accurate process maps for automation and safe orchestration. It baselines "as-is" processes for transformation programs like ERP migrations. The platform chosen determines if it’s a one-time diagnostic or a continuous engine turning process reality into action, closing the loop from insight to execution.
The decisive challenge in process mining is rarely the analytics — it’s extracting clean, complete event data from the systems where work happens, which teams consistently underestimate. Even then, value materializes only when findings feed real change, so selection should weigh how directly a platform turns discovery into automation, conformance enforcement, or operational action versus stopping at insight.
Process mining is converging with automation and AI, moving from retrospective discovery toward continuous monitoring and recommended or automated interventions. Weigh how each platform closes the loop from insight to execution and how it incorporates AI, because a tool that only describes the problem leaves the hardest, most valuable part undone.
Should you build or buy Process Mining & Process Intelligence?
You should buy process mining, as building from scratch is rarely necessary. The decision hinges on your sourcing posture: a best-of-breed specialist (Celonis-class) for processes spanning many systems, a suite-bundled option (Signavio, Power Automate) for SAP- or Microsoft-heavy estates, or automation-suite mining (UiPath, IBM) for discovery feeding automation. Task mining (Skan-class) addresses UI-level work, while open-source (Apromore, ARIS) suits cost or data sovereignty concerns.
Almost no one builds process mining from scratch anymore — the discovery algorithms are commoditized and the hard engineering is in connectors and scale. The real decision is sourcing posture: a best-of-breed specialist that mines across every system, the process-mining module already bundled in the ERP or automation suite you own, or a lightweight task-mining tool that watches the desktop where no event log exists. Frame it around where your work actually leaves a trail, who will act on the findings, and how much your incumbent vendors are pricing — or restricting — access to your own data.
| Your Situation | Recommended Path | Rationale |
|---|---|---|
| Process spans many systems (ERP + CRM + custom apps) and analysis is the strategic goal | Best-of-breed specialist (Celonis-class) | A dedicated platform mines across heterogeneous sources, handles object-centric and conformance depth, and isn’t bound to one vendor’s stack — the right fit when process intelligence is a program, not a feature. |
| SAP- or Microsoft-heavy estate already licensed for the suite | Suite-bundled (Signavio / Power Automate) | Native extractors, pre-built process content, and bundled licensing shorten time-to-value and lower the entry cost — provided your processes live mostly inside that vendor’s systems. |
| Discovery feeding an active automation program (RPA or agents) | Automation-suite mining (UiPath / IBM) | When the goal is a discovery-to-automation pipeline, mining wired into the same platform that builds and orchestrates the bots closes the loop without a second integration. |
| Work happens in the UI, swivel-chair across apps that leave no usable log | Task mining / desktop capture (Skan-class) | System-log mining is blind to manual, screen-level work; computer-vision or agent-based task mining reconstructs it — pair it with system-log mining rather than treating either as complete. |
| Cost, data sovereignty, or academic-grade conformance drive the decision | Open-source / specialist (Apromore, ARIS) | A self-hostable or research-rooted tool gives algorithmic transparency, on-prem control, and strong conformance and simulation when proprietary black boxes or seat-based pricing are dealbreakers. |
How do you evaluate Process Mining & Process Intelligence?
To evaluate Process Mining & Process Intelligence, prioritize data extraction and the path to action over visual analytics. Focus on pre-built connectors for systems like SAP, Oracle, and Salesforce, and the platform’s ability to turn findings into enforced controls or automation. Insist on a proof-of-value that starts with the vendor extracting and building an event log from your real, messy data to assess deployment viability.
Weight these domains against your own systems and goals. Most RFPs over-index on the visual analytics — the part every vendor demos well — and under-weight data extraction and the path to action, which is where deployments actually succeed or stall. Connectivity to your specific ERP and CRM, and whether the platform can turn a finding into an enforced control or an automation, should carry more weight than dashboard polish.
| Capability Domain | Weight | What to Evaluate |
|---|---|---|
| Data Extraction & Connectivity | 25% | Pre-built, maintained connectors for your core systems (SAP ECC/S&4HANA, Oracle, Salesforce, ServiceNow, custom apps); quality of event-log construction (case IDs, activities, timestamps); incremental/near-real-time ingestion; and handling of multi-object, many-to-many data |
| Discovery & Conformance Depth | 25% | Automated process discovery and variant analysis, conformance checking against a reference or BPMN model, root-cause and bottleneck analysis, object-centric process mining for processes that span multiple entities, and what-if simulation |
| Insight-to-Action & Automation | 20% | Action flows / triggered interventions, native handoff to RPA or agents, links to process orchestration, conformance alerting and continuous monitoring — not just retrospective maps but a path to changing the process |
| Task Mining & Coverage Breadth | 10% | Desktop task mining for UI-only work that leaves no system log, capture method (agent vs. computer vision), and how cleanly task-level and system-level views stitch into one end-to-end process |
| AI & Analyst Productivity | 10% | Natural-language copilots for building views and explaining variants, AI-assisted data mapping during ingestion, automated insight and recommendation generation, and how much the tool lowers the dependency on scarce process-mining specialists |
| Scale, Security & Governance | 10% | Performance on high-volume event logs, deployment options (SaaS, private cloud, on-prem), RBAC and data masking for sensitive process data, SOC 2 / ISO 27001 / GDPR posture, and audit-grade lineage from source to insight |
Which vendors lead in Process Mining & Process Intelligence?
To choose a process mining vendor, consider best-of-breed specialists like Celonis, suite incumbents such as SAP Signavio, Software AG ARIS, and IBM Process Mining, or automation vendors like UiPath and Microsoft Power Automate Process Mining. Task-mining specialists (Skan) and open-source challengers (Apromore) also address specific needs. Shortlists often compare across these camps, not within them, due to shifting ownership and bundled offerings.
| Vendor | Positioning | Best for |
|---|---|---|
| Celonis | Leader — Specialist | Large enterprises treating process intelligence as a cross-system program rather than a feature of an existing suite |
| Microsoft Power Automate Process Mining | Leader — Suite-Bundled | Microsoft-centric organizations wanting accessible, bundled process and task mining alongside Power Platform automation |
| SAP Signavio | Strong — SAP-Native | SAP customers running an S/4HANA or transformation program who want mining, modeling, and governance in one suite |
| UiPath | Strong — Automation-Led | UiPath automation customers who want process discovery to feed bots and agents without a second integration |
| IBM Process Mining | Strong — Automation Suite | IBM automation and Cloud Pak customers wanting mining, simulation, and BPMN tightly coupled to their stack |
| Software AG ARIS | Strong — BPM Heritage | Enterprises that anchor on formal process modeling and governance and want mining tied to a managed target architecture |
| Apromore | Challenger — Open-Source | Teams valuing transparency, on-prem control, and academic-grade conformance over the broadest commercial connector library |
| Skan.ai | Niche — Task Mining | Operations and shared-services teams quantifying UI-heavy, manual work that leaves no usable system event log |
The market splits into four camps that rarely compete head-to-head on the same axis. Best-of-breed specialists (Celonis) sell process intelligence as a strategic platform in its own right. Suite incumbents fold mining into the ERP or BPM estate you already run (SAP Signavio, Software AG ARIS, IBM). Automation vendors wire mining into their RPA-and-agent pipelines (UiPath, Microsoft Power Automate). And task-mining specialists (Skan) plus open-source challengers (Apromore) attack the edges the big platforms cover weakly. Most shortlists end up comparing across these camps — a specialist versus whatever is already bundled in your stack — not within them.
Ownership and naming have shifted enough that current facts matter. Microsoft acquired Minit in 2022 and folded it into Power Automate Process Mining (the capability once branded Process Advisor); UiPath’s process mining is built on its 2019 ProcessGold acquisition; IBM Process Mining is the rebranded myInvenio (acquired 2021); Celonis bought Process Analytics Factory (PAFnow) in 2022 and process-modeling vendor Symbio in late 2023; and Software AG’s ARIS now operates as a standalone unit under Silver Lake after the rest of the company was carved up. Celonis and SAP are also in active antitrust litigation over access to SAP ERP data — relevant if your processes live in SAP and you want a non-SAP miner.
Celonis
Leader — SpecialistStrengths: The category-defining specialist: deepest discovery, conformance, and object-centric process mining (Process Sphere), broad maintained connectors across SAP, Oracle, Salesforce and ServiceNow, action flows that trigger interventions, and an AI copilot for analysis. Independent of any one ERP or automation vendor, which is its core advantage when work spans many systems. Considerations: Premium positioning and the most involved implementation in the field; realizing value depends on serious data-engineering effort; its public antitrust suit against SAP over ERP data access is a live consideration for SAP-centric buyers weighing extractor reliability.
Microsoft Power Automate Process Mining
Leader — Suite-BundledStrengths: Built on the Minit acquisition and delivered inside Power Automate, so it ships with both process mining and desktop task mining, a Copilot that maps data during ingestion and answers questions of the analysis in natural language, and tight Power BI and Power Platform integration. Bundled licensing and a low-code approach put it within reach of citizen analysts. Considerations: Mining and conformance depth trail the dedicated specialists; richest when your data and automations already live in the Microsoft and Dataverse ecosystem; very large or highly complex process analyses can outgrow it.
SAP Signavio
Strong — SAP-NativeStrengths: Process intelligence inside the SAP Signavio Process Transformation Suite, combining mining with modeling, governance, and a transformation-led workflow; Process Insights offers fast, content-driven analysis of SAP processes, and out-of-the-box best-practice content accelerates SAP S/4HANA migration and value-case work. Considerations: Strongest gravity inside SAP landscapes; non-SAP connectivity and standalone mining depth are less of a draw than the suite story; commercials and roadmap are tied to the broader SAP relationship.
UiPath
Strong — Automation-LedStrengths: Process mining (built on ProcessGold) plus task mining and communications mining, now feeding the Maestro orchestration layer so discovery flows directly into agentic and RPA automation. The clearest discovery-to-automation pipeline for organizations already standardized on UiPath. Considerations: Greatest value is realized inside the UiPath platform; as standalone, cross-system process intelligence it is less of a destination than Celonis; task mining relies on a deployed desktop agent.
IBM Process Mining
Strong — Automation SuiteStrengths: The former myInvenio, embedded in IBM Cloud Pak for Business Automation with task mining, BPMN export, business-rule mining, multilevel mining, and what-if simulation that estimates the effect of automating a step. Strong fit where process mining is the front end of a broader IBM automation and BPM stack. Considerations: Most compelling as part of the Cloud Pak / IBM automation estate rather than a standalone purchase; mindshare and momentum trail Celonis and the suite-native options; best leveraged by organizations already invested in IBM automation.
Software AG ARIS
Strong — BPM HeritageStrengths: Couples mature, enterprise-grade BPM and process modeling with process mining, so discovered processes connect to a governed model repository and conformance against a documented target state. Deep heritage in process architecture, governance, and risk/compliance. Now run as an independent business unit focused on the ARIS suite. Considerations: Strength is the modeling-plus-mining combination; pure-play mining buyers may find it heavier than needed; the post-carve-out standalone ARIS organization is a corporate change worth tracking in long-term commitments.
Apromore
Challenger — Open-SourceStrengths: Open-source-rooted (Community Edition plus a commercial Enterprise Edition) with research-grade discovery, conformance checking, predictive process monitoring, log animation, and BPMN authoring. Algorithmic transparency and self-hostable deployment appeal where data sovereignty or auditability matter, and it was named a Leader in the 2025 Gartner Magic Quadrant for Process Mining Platforms. Considerations: Smaller vendor and ecosystem than the megasuite incumbents; connector breadth and turnkey enterprise services are lighter; the open-source core needs more in-house capability to operationalize.
Skan.ai
Niche — Task MiningStrengths: Computer-vision task mining that observes work at the screen level through a lightweight desktop agent — no API, connector, or backend log required — reconstructing the manual, swivel-chair work that system-log mining is blind to, and labeling it into activities and variants. Recognized by Gartner across process intelligence and task mining research. Considerations: A specialist for the desktop layer, not an end-to-end system-log mining replacement; screen observation raises privacy and works-council considerations to manage; typically complements, rather than replaces, a system-log mining platform.
How much should you budget for Process Mining & Process Intelligence?
Budgeting for process mining involves two dominant structural costs: data engineering for event logs and change management to act on findings, which are not on the price list. Licensing, a smaller, more visible cost, varies by unit of measure (consumption, per-user, capacity) and vendor, such as Celonis (consumption), Microsoft (per-user), SAP Signavio (subscription), UiPath (subscription/consumption), and IBM (subscription). The 3-year TCO formula includes platform license/consumption, data engineering, maintenance, analysts, and change management, minus realized improvements.
Two structural costs dominate process-mining TCO and neither is on the price list: the data-engineering effort to build and maintain event logs from source systems, and the change-management effort to act on findings. Licensing is the smaller, more visible line. The unit of measure varies widely — consumption (data processed), per-user/analyst, capacity, or bundled into a suite you already own — and that unit, more than the headline rate, determines what you pay as adoption grows. Where mining is bundled (Microsoft, SAP, UiPath, IBM), the “price” is often an entitlement of a platform you already license, which changes the comparison entirely.
| Vendor | Pricing Model | Relative Tier | Key Cost Drivers |
|---|---|---|---|
| Celonis | Consumption (data processed) plus platform subscription | Premium | Volume of event data processed, number of connected source systems and apps, add-on modules (action flows, simulation), and implementation/data-engineering services |
| Microsoft (Power Automate) | Per-user Power Automate plan, with process-data add-on capacity | Lower–Moderate | Power Automate Premium seats, additional process-mining data capacity, Dataverse/Azure storage, and broader Power Platform commitments |
| SAP Signavio | Subscription within the Process Transformation Suite | Moderate–Premium | Suite edition and module mix (Insights vs. Intelligence vs. modeling/governance), connected SAP and non-SAP systems, and the surrounding SAP relationship |
| UiPath | Subscription/consumption within the UiPath platform | Moderate–Premium | Platform tier and bundle, robots/agents in scope, task-mining agents deployed, and data volume mined |
| IBM Process Mining | Subscription, often via Cloud Pak for Business Automation | Moderate–Premium | Cloud Pak entitlement and capacity, task-mining and simulation usage, and deployment footprint (cloud vs. self-managed) |
| Software AG ARIS | Subscription, modular (modeling + mining) | Moderate–Premium | Modeling vs. mining module mix, modeled/managed process scope, named users, and governance/risk add-ons |
| Apromore | Open-source Community Edition; subscription Enterprise Edition | Lower | Enterprise edition tier and support, self-hosting infrastructure and in-house operating effort, and any professional services engaged |
| Skan.ai | Subscription, typically per observed user/seat | Moderate | Number of users/desktops observed, processes in scope, and analysis/services engagement |
How long does implementation take for Process Mining & Process Intelligence?
Process Mining implementation typically takes 7-12 months to fully operationalize. Initial data scoping and sourcing takes 1-2 months, followed by 2-4 months to connect and build the event log. Analyzing and proving value for initial processes then takes 4-7 months, before scaling and operationalizing the solution.
Sequence the rollout around data and ownership, not around features. Pick one or two high-value processes, prove you can build a trustworthy event log and turn it into an acted-on improvement, then scale. The order that fails is buying the platform first and discovering the data plumbing afterward.
Pick one or two processes with a named owner and a real pain point (order-to-cash, procure-to-pay, a service flow). Locate where they leave event trails, assess extraction effort from each source system, and run the proof-of-value against your own data — not the vendor’s sample — with timestamp and case-ID quality as the pass/fail.
Stand up connectors to the in-scope source systems, construct and validate the event log with process owners (handling multi-object data and conformance to the intended model), wire in identity, RBAC, and masking for sensitive process data, and confirm refresh cadence and lineage.
Run discovery, variant, conformance, and root-cause analysis on the first processes; validate findings with the people who do the work; and convert at least one insight into a concrete change — a conformance alert, an automation candidate handed to RPA/agents, or a process redesign — so the program shows action, not just maps.
Onboard additional processes and analysts, add task mining where UI-only work is material, shift from one-off analysis to continuous monitoring with alerting, embed mining into the automation and improvement operating model, and review consumption/cost against the original plan.
What should you ask vendors about Process Mining & Process Intelligence?
Use this checklist during evaluation to confirm each shortlisted platform covers what actually determines whether a process-mining program succeeds.
Frequently asked questions about Process Mining & Process Intelligence
When would a Microsoft Power Automate Process Mining deployment be insufficient, and when should we consider Celonis instead?
Microsoft Power Automate Process Mining is best for Microsoft-centric organizations with data and automations in that ecosystem. For very large or highly complex process analyses, or when process intelligence is a cross-system program across heterogeneous sources like SAP, Oracle, and Salesforce, Celonis offers deeper discovery, conformance, and object-centric process mining capabilities that Microsoft’s offering trails.
Our organization uses SAP S/4HANA and we’re considering SAP Signavio. What are the trade-offs compared to a 'best-of-breed' specialist like Celonis?
SAP Signavio excels for SAP customers running S/4HANA, combining mining with modeling and governance within the SAP Process Transformation Suite. While it offers fast, content-driven analysis within SAP landscapes, its non-SAP connectivity and standalone mining depth are less of a draw than Celonis. Celonis provides deeper discovery and broader maintained connectors across diverse systems, making it suitable for cross-system programs.
We’re looking at UiPath for process mining to feed our RPA program. What are the hidden costs or limitations if our goal is broader, cross-system process intelligence?
UiPath’s greatest value is realized within its platform, flowing discovery directly into RPA automation. While it includes process and task mining, as standalone, cross-system process intelligence, it is less of a destination than Celonis. Hidden costs might arise from needing a second integration or a separate platform if your process intelligence goals extend significantly beyond the UiPath automation ecosystem.
Our processes involve significant manual work in the UI, with swivel-chair across multiple applications. Which vendor or approach specifically addresses this, and what’s the cost driver?
For work happening in the UI with no usable system logs, Task mining / desktop capture (Skan-class) is essential. Skan.ai, for example, uses computer-vision or agent-based task mining to reconstruct this work. It should be paired with system-log mining. The cost driver for Skan.ai is typically a subscription per observed user/seat, along with the number of processes in scope and analysis services.
We have strict data sovereignty requirements and a limited budget. Is an open-source option like Apromore genuinely viable for enterprise use, and what are the associated efforts?
Apromore’s Open-source Community Edition and subscription Enterprise Edition offer transparency, on-prem control, and research-grade conformance. It is genuinely viable for teams valuing these aspects over broad commercial connector libraries. However, it requires more in-house capability to operationalize the open-source core, and you’d need to budget for self-hosting infrastructure and in-house operating effort, as well as any professional services for the Enterprise Edition.