Report:

Magic Quadrant for Process Mining Platforms

Top Vendor Products for Process Mining Platforms in 2024

• ABBYY
• Appian
• Apromore
• Celonis
• MEHRWERK
• Microsoft
• SAP Signavio
• Software AG
• UiPath

Process Mining Platforms Vendor Product Comparisons 2024

• ABBYY - Leader
  

  Pros:

  • Document and text data: ABBYY was the first vendor to realize the potential value of extending process mining with unstructured or semistructured information captured in documents. ABBYY's IDP capabilities reveal additional information that increases insights into how processes are behaving.
  • Execution: ABBYY promotes the synergies of process mining and task mining with IDP and the value this creates for the customer, who can use them to make decisions that are actionable in real time. It promotes these through OEM partnerships with SS&C and Blue Prism to support automation initiatives.
  • Offering (product/services): ABBYY provides a comprehensive suite of services, including process experts, technical account managers and Timeline trainers to help customers where appropriate. ABBYY also has a strong partner ecosystem with representation in Europe, the Middle East and Africa (EMEA), Asia/Pacific and North America to support buyers during implementations, providing help tailored to verticals or automation initiatives.

  Cons:

  • Generative AI: ABBYY currently provides a no-code hypothesis builder through its Query and Protocol modules, allowing users to diagrammatically create their prompts and retrieve the associated data and insight. ABBYY's focus for 2024 is to integrate GenAI more deeply into Timeline to enhance user interaction by enabling natural language queries and suggesting process elements that should be promoted for automation.
  • Customer experience: Gartner Peer Insights revealed cautionary remarks about Timeline's ability to intuitively gather insights, as well as the number of steps required to do so. Although ABBYY will explore the ease of insights through GenAI, customers should assess user experience and ease of use when assessing the product.
  • Verticals/industry strategy: ABBYY mainly serves banking, financial services, and insurance, as well as healthcare and pharmaceuticals. Although ABBYY plans to expand into more verticals, potential clients should verify the applicability of the offering, as well as the partner support available.


• Appian - Leader
  

  Pros:

  • Market positioning: Appian aims to build a new category of holistic process management platform that integrates process mining into the Appian platform. The platform converts any discovered process model automatically into an Appian workflow (model to workflow), mines Appian's data fabric to obtain end-to-end process insights, and measures the cost savings delivered by an Appian app.
  • Innovation: The smart knowledge model and data graphs in Appian's data fabric simplify data availability and usability, and provide its process mining with continuous monitoring and adaptation of data in real time or near real time. Appian's self-service analytics with AI Copilot enables business users to explore their data fabric in real time, quickly design reports and access powerful AI insights.
  • Process execution and orchestration: The Appian platform is well-constructed for the 'support for process execution' use case of process mining, whether acting on triggered thresholds during runtime or by exporting process models during design time. The Appian platform enables secure execution and monitoring of robotic process automation (RPA) capabilities for task-level automation, enterprise-grade workflow for applications, and process orchestration across bots, humans and scripts for business process management.

  Cons:

  • Automation use case: Appian focuses on end-to-end process automation — RPA, business process automation (BPA) and low-code application platforms (LCAPs) — but still supports process mining as a stand-alone offering. Automation is the biggest driver of the adoption of process mining and accounts for approximately 55% of all use cases. Clients considering nonautomation use cases should verify the experience and support that Appian and its implementation partners deliver.
  • Business activity monitoring: Appian received only a medium evaluation for business activity monitoring, despite the excellent capabilities provided by its data fabric. Objectives for KPIs can be captured as thresholds in the dashboard, which are used for alerting. However, the connection to underlying assumptions or a metric hierarchy is not provided and is currently delegated to developer teams for added flexibility.
  • Customer experience: Based on a limited number of references within Gartner Peer Insights, Appian was positioned lower for client experience than the other vendors assessed for this report. Major contributing factors mentioned were product support for process mining, pricing and contracting. Clients considering Appian Process Mining should select a higher-than-basic level of support contract.


• Apromore - Leader
  

  Pros:

  • Ease of use: Apromore's no-code environment enables process mining practitioners to accelerate time to insights, simulate proposed changes and implement continuous monitoring, alerts and dashboards without reliance on IT and data scientists. Apromore seeks user feedback frequently to enhance customer experience.
  • Innovation: Apromore provides AI-driven root cause explanations using the FIGS algorithm for KPI violations. The platform also features predictive dashboards for configuring charts with anticipated metrics and start time estimation for logs lacking start times. It also includes an Automation Assessment Report summarizing automation benefits in terms of time and cost metrics after simulating as-is and to-be-automated processes.
  • Task mining: Being one of the first process mining companies to add task mining to its offering, Apromore is task-mining-agnostic. This means it can collect data from any task mining tool and integrate it into its logs via its extraction, transformation and loading (ETL) functionality. Users can discover process models from event logs or individual tasks from task logs, and both levels are combined into a single activity-step log, enabling users to explore, zoom in and visualize task mining steps for selected activities.

  Cons:

  • Deployment: Apromore is exclusively cloud-native, provided through a SaaS model, and no longer supports on-premises deployment. As an alternative, Apromore offers installation on its AWS cloud tenancy or the customer's own cloud tenancy, as well as a hybrid deployment option where the data volume is hosted on the customer's cloud tenancy. Those seeking on-premises environments should communicate their requirements.
  • Geographic strategy: Although Apromore has increased its geographical presence, notably in North America, it is still limited to certain markets and relies on partners to help with deployment. The restricted markets served are evident in the limited language support offered. Potential clients, specifically in Latin America, should verify availability as well as access to support, if required.
  • Verticals: Apromore mainly serves service-intensive sectors — primarily banking, financial services and insurance, as well as the public sector, energy and utilities, and telco. Although Apromore plans to expand into more verticals, potential clients should verify the applicability of the offering, as well as the partner support available.


• Celonis - Leader
  

  Pros:

  • Execution: Celonis has helped draw attention to the process mining market, which it has dominated since its commercialization. Celonis has the largest customer base in this market, and we estimate its market share to be around 50%. In 2023, Celonis acquired Symbio, a process repository tool that will enable Celonis clients to design, model, and govern processes, supported by Symbio's AI capabilities.
  • Innovation: Process Intelligence Graph is the core of the Celonis Platform. Process data is modeled in a standardized, object-centric process data model that acts as an extensible digital twin of the business. The platform's Knowledge Hub enables users to create and manage metrics, strategic objectives, improvement opportunities, filters and other objects supported by the object-centric process data model.
  • Marketing strategy: Celonis has a unique brand design and style with an 'anticorporate' approach. It strives to evoke the spirit of a grassroots movement, with Celonis users as changemakers, driven to change the status quo. Celonis' marketing language and tone have evolved to match this approach, becoming more straightforward, immediate, and less technical.

  Cons:

  • Pricing: Larger clients have told us the new pricing model can be complex when starting out or moving to the new object-centric process data model. In particular, they brought up how an organization's revenue is taken into account for the final pricing and the process-by-process approach.
  • Customer experience: Observations made in the previous Magic Quadrant are still to be implemented. In Gartner Peer Insights, clients refer to pricing and the steep learning curve required to make the most of the platform's extensive functionality and flexibility. Customers would like more accurate support from the service desk, and support when scaling to other parts of the organization.
  • Task mining: Celonis has considerably improved its capabilities and delivery for the workforce productivity use case of task mining. However, Celonis could add more capabilities to address use cases other than workforce productivity, such as low-volume, high-variety interaction processes (for example, call centers).


• Cyclone Robotics - Niche Player
  

  Pros:

  • Market positioning: Cyclone Robotics focuses on China's process mining market, which is still in its infancy and will experience rapid growth in commercial practice by 2027. Cyclone Robotics concentrates on large enterprises that have a more mature IT infrastructure and complex business processes.
  • Marketing: Cyclone Robotics emphasizes process mining's ability to systematically discover automation opportunities and verify automation effectiveness. It does so to encourage its existing RPA clients to renew and convert to the new offerings.
  • Task mining: Cyclone Robotics provides its native task mining capability as a module that process managers can launch easily. Nominated individuals can self-install it on their computers and configure it to capture keystrokes, mouse clicks and cursor positions. All sensitive data is masked and encrypted before it reaches process owners.

  Cons:

  • Geography: Cyclone Robotics' operations are almost exclusively in Asia/Pacific, with only a small presence in Europe. The company does not have a global partner network in Europe and Southeast Asia, although it is working on it. Customers outside Asia/Pacific should test Cyclone Robotics' ability to support operations globally.
  • Offering: Cyclone Robotics' market responsiveness and innovation are lagging behind those of the general process mining market, mainly influenced by local market conditions. This is exemplified by the company's plans to introduce a commercial SaaS version in 2024. Clients requiring up-to-date process mining capabilities should check their requirements against Cyclone Robotics' capabilities.
  • Operations: Cyclone Robotics is a small company, but charges premium prices. Higher prices can contribute to the expectation of higher quality and support, which Cyclone Robotics may not be able to provide. Depending upon their maturity, clients should verify that their expectations of Cyclone Robotics' capabilities will justify the premium pricing.


• IBM - Challenger
  

  Pros:

  • Market positioning: IBM provides a complete solution for intelligent automation. It combines capabilities to automatically analyze processes, identify improvements and corrective actions, and automatically apply the required changes through AI-powered automation. IBM offers an integrated enterprise business process analysis solution, connecting to a dynamic model of the process that considers the wider organizational context.
  • Customer experience: IBM Process Mining excels in customer experience. IBM process mining received consistently high evaluations in Gartner Peer Insights feedback for integration and deployment, retention rate, and Net Promoter Score.
  • Verticalization: IBM has subject matter experts (SMEs) with deep knowledge of individual markets (such as finance and manufacturing). It uses these SMEs and global systems integrators to bring its cross (e.g., procure to pay) and vertical (e.g., Maximo and finance process) accelerators to market.

  Cons:

  • Automation use case: Although IBM still supports process mining as a stand-alone offering, it focuses mainly on the intelligent automation and hyperautomation use cases. This automation (RPA, BPA and LCAP) use case is the biggest driver of the adoption of process mining, but it is still only around 55% of all use cases. Potential clients considering use cases other than automation should verify them with the experience level and support that IBM and its implementation partners deliver.
  • Process orchestration: IBM Process Mining offers process orchestration through Cloud Pak for Business Automation. Potential clients requiring this capability will need to consider a bundle of separate products.
  • Advanced product capabilities: IBM has great capabilities in execution and AI, but IBM Process Mining lags behind in advanced analytics, certain GenAI capabilities and linked execution capabilities. Although these are on the roadmap for 2024 and beyond, potential clients searching for these advanced capabilities should check their requirements against IBM's available capabilities.


• MEHRWERK - Leader
  

  Pros:

  • Market vision: MEHRWERK believes the market will move toward self-service process mining and autonomous process execution. This trend will lead to much faster adoption of the technology and faster implementation. It will result in active business operations intelligence as the basis for autonomous process execution.
  • Innovation: MEHRWERK's mpmX provides extended AI (Insight Advisor) that expedites generative, automatic analysis creation with visualizations, narrative outputs and suggested links and measures, based on natural language prompts. It has added an OCR module based on several AI models, resulting in contextual document mining that delivers content-based process information.
  • Data access and management within a platform: mpmX runs natively on Qlik's BI platform (Qlik Sense, available via SaaS and on-premises), without the need for a licensed Qlik platform. This provides mpmX with all the platform capabilities of Qlik, such as augmented intelligence, natural language processing, self-service, real-time and big data integration, and data governance and its associative engine.

  Cons:

  • Geographies: MEHRWERK has more than 40 offices in Germany, but has a limited presence elsewhere, relying on partners outside Germany. Judging by the company's expansion of its customer base in North America and Asia/Pacific, and its strong partnership with Qlik, we expect MEHRWERK will invest heavily in its global presence in 2024.
  • BI platform: The combination of several best-of-breed components within a single platform requires more attention, because partner solutions evolve and change. Using Qlik's platform as a base could raise questions with clients that have implemented other BI platforms. Potential clients should check the Qlik environment's degree of overlap (e.g., in reporting) and knowledge required to use it.
  • Process orchestration: MEHRWERK does not support business operations models from an organizational perspective. These organizational models go beyond business process model and notation (BPMN) models and orchestration in the connected process automation tool (Camunda). Potential clients searching for this organizational approach should check these advanced requirements with MEHRWERK's capabilities.


• Microsoft - Leader
  

  Pros:

  • Advanced analytics: Power Automate Process Mining uses predictive analytics to forecast case outcomes from historical data. Integrated with Microsoft Power BI, it offers in-depth reporting and helps anticipate future states for strategic decision making. The tool offers a simulation engine that uses machine learning for realistic scenario modeling. Copilot can identify processes from data and map them to the required schema. It can also identify key insights, pinpoint bottlenecks and suggest solutions such as Microsoft Power Automate flows and Microsoft Power Apps.
  • Task mining: The offering includes task mining capabilities through Power Automate for desktop. This enables a unified task recorder for recording desktop tasks, with the ability to pause, edit or delete recorded steps to tailor requirements. It also groups steps into activities with options for manual customization, enabling the data to be business-relevant.
  • GenAI: Power Automate Process Mining uses GPT-3.5 Turbo from OpenAI and offers Copilot capabilities across the platform. Copilot supports customer identification of processes and mapping, alongside solution recommendations through conversational experience. Microsoft is preparing to transition to GPT-4, which will offer improvements in language processing and understanding.

  Cons:

  • Partner support: Power Automate Process Mining falls short on a robust partner ecosystem. As such, clients who may need support regarding implementation, configuration or obtaining value should reach out to Microsoft to ascertain whether help can be provided to meet their specific needs.
  • On-premises deployment: Power Automate Process Mining cannot be deployed on-premises. This may make it unsuitable for those in highly regulated industries or those who are required to keep their data in-house. Customers should reach out to Microsoft to see whether the vendor's offering supports their enterprise requirements.
  • OCPM support: Power Automate Process Mining does not support OCPM, although this is on Microsoft's roadmap. This limits the tool more than traditional process mining, because OCPM broadens the way that data is collected and processed, and OCPM enables users to see events and objects in all their states along different processes.


• mindzie - Niche Player
  

  Pros:

  • Pricing: mindzie offers customers subscriptions of one or more years, as well as pricing per user and connector. It includes maintenance and treats all clients equally with the same level of support. This enables all enterprises, including midsize enterprises and those new to process mining, to get started with minimal upfront costs and full transparency of those costs.
  • GenAI: mindzie integrates GenAI across the platform, trained on its custom block language for data safety. Users ask questions and AI interprets those questions to provide answers using the right block. mindzie uses a conversational approach to process analysis to ensure safety. It plans to evolve with automated suggestions and multidimensional thinking.
  • Customer experience: mindzie works directly with its customers to support their process mining efforts, providing access to data scientists to assist with analyzing process data, as well as business consultants to make recommendations. Gartner Peer Insights show that customers value the tool's simplicity for configuring and gathering insights.

  Cons:

  • Automation: mindzie focuses on process discovery and conformance, and does not actively support customers seeking automation opportunities. Potential customers considering automation use cases should verify the extent to which mindzie and its partner ecosystem can support their requirements.
  • Operations: mindzie is still growing in the process mining market, and this is reflected in its workforce and partner ecosystem. This may inhibit mindzie's ability to support customers with integration, configuration and gaining value from the tool. New customers should verify with the vendor the level of support needed.
  • Vertical/industry strategy: mindzie's initiatives to expand beyond IT services, healthcare, finance and manufacturing are limited. mindzie mainly operates in North America and relies on its partner ecosystem to reach customers in other regions.


• Pegasystems - Visionary
  

  Pros:

  • Continuous process improvement: Pegasystems is well-positioned to support the full process life cycle. Pega identifies process problems with process mining and task mining; automates issues with Pega RPA, low-code apps and back-end workflow; and orchestrates processes and events through Pega Process Fabric. It continually monitors and analyzes processes to recommend and to automatically act on with Pega Process AI.
  • Market vision and innovation: Pegasystems has identified process mining as a significant driver in process intelligence, orchestration and autonomous actions. It sees a clear path through a business operations intelligence approach to the autonomous enterprise/business.
  • Pricing model: Pegasystems has a case-based pricing model that it also uses in other offerings in the automation market. This is per-month pricing, based on analytical capacity measured by the volume of process mining cases analyzed at any point in the subscription period. The minimum analytical capacity is one million process mining cases, with the possibility to add blocks of one million cases. No limit exists on the number of processes or users.

  Cons:

  • Automation use case: Pegasystems focuses on end-to-end process automation and orchestration (RPA, BPA, case management and LCAP), but still supports process mining as a stand-alone offering. The automation use case is the biggest driver of the adoption of process mining, and accounts for approximately 55% of all use cases. Clients considering nonautomation use cases should verify their alignment with the experience and support that Pegasystems and its implementation partners deliver.
  • Sales strategy: Pega Process Mining targets existing and new clients for its Pega Platform and customer service solutions. Pega Process Mining aims to enable any client to understand the organization's processes, target opportunities for enhancement and foster data-led continuous improvement. Prospects interested in stand-alone process mining should verify their stand-alone requirements with Pegasystems.
  • Customer experience: Few client references are available because the Pegasystems process mining offering is fairly new in the market. Most of these limited references were positive. Nevertheless, they expressed the desire for some basic elements that are on the roadmap for 2024, such as a deeper integration of process and task mining, easier data integration and a certification program.


• Proxverse - Niche Player
  

  Pros:

  • Market promotion in China: Proxverse hosts industry-specific webinars and workshops on process mining, positioning its team as experts. It creates thought leadership content such as white papers and blogs addressing industry challenges and trends. It distributes this content through traditional media, its website and social media.
  • Co-innovation: Proxverse innovates strongly with partners. It collaborated with Beijing University of Posts and Telecommunications (BUPT) to create an entire data preprocessing layer using a vector database, with a large language model (LLM) as the basis. The solution provides a customized process knowledge base.
  • Viability: Although Proxverse is a small company, it can be more agile to respond to market needs, as well as grow to promote process mining in the APAC region. Proxverse will benefit from the huge growth that the Chinese market is experiencing. We expect this growth will continue.

  Cons:

  • Geographies: Proxverse has a limited presence outside the Chinese mainland, Hong Kong, Singapore and Germany, relying mainly on a limited number of partners in other areas. Proxverse has expanded its customer base in Asia/Pacific, so we expect it will invest heavily in its global presence in 2024. New customers should confirm the vendor's support in the regions where they operate.
  • Operations: Proxverse is still a small company. It is closely involved with its clients in installation, implementation, close support, troubleshooting, consulting, training, customizations, integrations and execution. Although it charges little for this, it impacts scalability, so new clients should check availability.
  • Offering: The product still lacks some critical and advanced functionality in the current product offering, contributing to a relative lower assessment on the ability to execute. Proxverse has no task mining capabilities and very basic process orchestration capabilities. Potential clients that need some advanced process mining capabilities should check with Proxverse that it can meet those requirements.


• QPR Software - Visionary
  

  Pros:

  • Market positioning: QPR views the digital twin of an organization (DTO) use case as aligning and integrating process mining with modeling, and revolutionizing the traditional modeling market. Enabled by process mining technology, modeling as part of a DTO will become a data-augmented and AI-assisted discipline that supports digitalization and related transformation initiatives. This DTO use case is QPR's new positioning.
  • Innovation: QPR ProcessAnalyzer is the only process mining product to run natively in the Snowflake Data Cloud. This approach brings the use cases and related workloads to where the data is, instead of copying data to a stand-alone island for process mining. The solution guarantees off-the-shelf scalability, data security and easy data governance. QPR is devising a framework that will enable the mining of end-to-end processes across multiple organizations.
  • Marketing strategy: QPR puts strategic emphasis on the DTO use case, with a dedicated marketing effort aimed at establishing QPR as a thought leader in this domain. QPR pays special attention to its existing base, implementing account-based marketing to maximize awareness and unlock the potential of DTO within selected accounts.

  Cons:

  • Geography: QPR has a limited geographic presence. It has sales offices in Finland and the United Arab Emirates, and all its support staff are based in Finland. Its partners are mainly regional, with some large international systems integrators such as Tietoevry and NTT DATA. New QPR customers should confirm its support in all the regions in which they operate.
  • Customer experience: According to customer comments from Gartner Peer Insights, the product needs more implementation and integration effort than most of the offerings in this research. This does not apply to companies that are using Snowflake Data Cloud, where no copying of data or uploading the data into in-memory is required and customers can instantly begin analysis in QPR. New clients that are not using Snowflake Data Cloud should check on partner availability.
  • Limited advanced capabilities: Some of QPR ProcessAnalyzer's advanced capabilities, such as task mining and connections to execution through automation, are basic. Potential clients should check whether QPR meets their requirements for advanced capabilities.


• SAP Signavio - Leader
  

  Pros:

  • Market positioning and vision: SAP Signavio's process mining solutions are part of an end-to-end transformation suite for process excellence initiatives and business transformation. Adding new perspectives such as experience, resources, people, skills and environmental, social and governance considerations will extend the traditional process mining market. Customer journeys and process observability also will be major themes.
  • Innovation: SAP Signavio provides an LPM that generates effective AI-based insights and recommendations to change and improve operating models. Process AI uses GenAI technologies based on SAP Signavio's LPM to augment process mining and analysis with advanced capabilities. These include a text-to-query-to-widget, a dashboard AI assistant, a problem space identifier, auto event log enhancement and Journey-to-Process Analytics AI.
  • SAP client ecosystem: SAP has aligned SAP Signavio with the overall SAP go-to-market approach to interlock new sales plays more strongly with SAP industries, SAP Business Technology Platform and other SAP solutions and programs. A starter pack helps to position SAP Signavio with RISE with SAP customers.

  Cons:

  • Pricing: SAP Signavio has a complex pricing model and two products for process mining. The SAP Signavio Process Transformation Suite also includes user-based products such as SAP Signavio Process Collaboration Hub, SAP Signavio Process Governance and SAP Signavio Journey Modeler. Prospective clients should study each capability and align them with the internal capabilities they require.
  • SAP focus: Although SAP Signavio supports process mining as a stand-alone offering and its strategy is system-agnostic, since SAP acquired Signavio, its accelerators focus more on SAP-related use cases. Clients considering use cases other than SAP-related ones should check the experience level, available connectors and support that SAP Signavio and its implementation partners deliver.
  • Marketing execution: SAP Signavio should make it more clear that there is a difference between SAP Signavio Process Intelligence (a general process mining platform solution) and SAP Signavio Process Insights (a process mining platform for SAP, created on the SAP Business Technology Platform). New clients and prospects do not always understand these differences and the consequences of extending one into another.


• Skan - Niche Player
  

  Pros:

  • Customer experience: Skan achieved one of the highest retention rates in this research. It has intensified its commitment to a more customer-centric approach by listening to customer requirements. Skan has adopted an agile product development approach to address key customer needs. It has strategic plans to implement continuous monitoring for tracking and addressing potential issues that could impact business continuity.
  • Innovation: Skan introduced askSkan, part of the GenAI-powered ProcessGPT suite, which enables real-time narrative insights to help transform raw data into digestible actions. This will be complemented by Skan's Autonomous Learning and Optimization, an AI-driven system that provides real-time alerts and notifications. Both enhance the product's ease of use and ability to execute decisions promptly.
  • Process discovery: Skan uses process and task mining to derive process insights at scale, gathering a complete picture of end-to-end processes, along with all required documentation. The Skan Virtual Assistant, installed on the user's workstation, captures all information, including that from the mainframe. This generates event data and transforms it into structured event logs, without the need for integration into back-end event logs and application databases.

  Cons:

  • Operations: Skan is still a small company with a growing workforce and partner ecosystem to meet its growth targets. Customers seeking assistance with installation, implementation, close support and troubleshooting, alongside consulting, training and execution, should verify the availability of resources.
  • Geography: Skan's sales and marketing operations are focused on North America, with little presence in EMEA. Most of its support staff are in Asia/Pacific, with some in North America. Skan offers its product in English only, with plans to expand into Spanish and Japanese on its roadmap. Potential customers should confirm Skan's support in the regions where they operate.
  • Real-time monitoring: Skan's event-driven microservices architecture offers scalability advantages, but brings complexities in managing event ordering. Special attention is crucial, especially for microservices relying on event sequencing, to ensure adequate hardware is available at peak usage so that all metrics remain real-time, especially for operations-critical use cases.


• Software AG - Leader
  

  Pros:

  • Process orchestration: ARIS Process Mining enables the ARIS repository to act as a DTO. This gives a view of the performance of an organization's business operating model, providing a single source of truth. Using the ARIS suite as the central repository, many capabilities can be used to discover or build interdependencies between processes that must be executed.
  • GenAI: ARIS Process Mining uses GenAI through the ARIS AI Companion to enable users to interact and converse with their processes. This includes ideation for dashboard components and KPIs, as well as to create connections to source systems. ARIS AI Companion can also propose automation projects or create detailed plans within the ARIS platform to improve overall processes.
  • Customer experience: The ARIS community has over 750,000 members who share best practices, news and blogs. Software AG engages customers for product feedback, conducts prototype validation sessions and consults users to incorporate their insights into its roadmap. Feedback in Gartner Peer Insights shows that users particularly appreciate the seamless implementation and the easy generation of insights.

  Cons:

  • Non-ARIS clients: Software AG packages many of its extended capabilities (process repository, simulation, and process analysis) as different offerings. Non-Software AG clients considering specific process mining capabilities should check the use cases and capabilities they need against the capabilities in ARIS Process Mining as a stand-alone offering.
  • Task mining: Software AG supports task mining through ARIS Robotic Process Discovery. This uses screen scraping to capture user steps for the creation of task logs. This approach has limitations, such as not using the data from the operating system to obtain a complete, granular understanding.
  • Marketing execution: Software AG's marketing has focused on promoting the ease of use of process mining to generate insights, as well as GenAI's possibilities. But for 2024, it will place greater emphasis on promoting the benefits of the process mining that is integrated into the ARIS Suite, which will enable customers to expand the use and potential applications of process mining technology. Customers seeking a stand-alone tool should confirm their requirements before engaging with Software AG.


• StereoLOGIC - Niche Player
  

  Pros:

  • Task mining: StereoLOGIC is unique because it starts from a task mining perspective. It captures events on an end-user desktop, terminal or mobile device, and applies several patent-based engines (data extraction, data recognition, instance recognition and image recognition) to derive the processes. StereoLOGIC also captures transactional data.
  • Data access and preparation: Because of its task mining approach, StereoLOGIC does not need application connectors or data to be prepared before performing the task and process analyses. It includes activities and data that are handled in local front-office applications, such as Microsoft Excel and collaboration tools. This leads to fast implementations and results being available in days or weeks.
  • Continuous monitoring: StereoLOGIC uses a proprietary pattern recognition technology to compare process performance with a discovered or improved process model. It supports this with a comprehensive dashboarding capability that enables process owners to monitor process conformance by business area, team or user.

  Cons:

  • Task mining orientation: The solution's possible bias when deducting processes from a task level will be minimal if the tasks observed contain the start and end of a process, are well-understood, and don't have too many interrelated activities based on exceptions. Clients considering process mining should understand that StereoLOGIC is different from most task-based process mining tools and overcomes these issues by capturing non-desktop-based system events.
  • Geography: StereoLOGIC's sales and marketing operations are mainly in North America, with some presence in EMEA, and all its support staff are based in Canada and the U.S. It has a limited number of partners, but guarantees worldwide support for all products without the need for consulting partners. Prospective StereoLOGIC customers should confirm the vendor's support in all the regions in which they operate.
  • Operations: StereoLOGIC is a small company. It is closely involved with its clients in delivering installation, implementation, close support and troubleshooting, consulting, training, customizations and integrations, and execution. This is at no additional cost, but it has an impact on scalability, so prospective clients should verify availability.


• UiPath - Leader
  

  Pros:

  • Market positioning: UiPath's vision for the market is to help clients go beyond insights. It wants them to achieve a state that it calls Continuous Discovery, in which organizations continuously monitor and optimize their processes, automations, systems, and resources. This vision encompasses all the use cases covered in this evaluation.
  • Execution support: UiPath's ability to combine holistic process intelligence with execution and AI-powered automation is a key differentiator. Users can submit automation ideas surfaced from Process Mining into Automation Hub. From here, execution can happen on a task level (human action or RPA bots) or on a process level (BPMN process models, stateful workflow execution, user experience/app development).
  • Automation: For UiPath, process mining and automation execution go hand-in-hand for process transformation, business model innovation and continuous monitoring of financial impact and operational KPIs. UiPath usually bundles Process Mining with the other elements of its platform (RPA, AI, iPaaS, LCAP, IDP and application testing) to drive hyperautomation strategies.

  Cons:

  • Automation use case: UiPath puts automation at the heart of its platform. Automation is the biggest driver of the adoption of process mining, but still accounts for only approximately 55% of all use cases. Prospective clients considering use cases other than automation should verify their use cases with the experience level and support that UiPath and its implementation partners deliver.
  • OCPM: UiPath plans to add support for full OCPM to help clients better understand the interdependencies between processes. Clients who seek to go beyond mining individual processes and require a more holistic process intelligence across their enterprise should check that UiPath can meet these requirements.
  • Advanced analytics: Many advanced analytics capabilities (such as predictive process analytics beyond automation, prescriptive analytics, advanced scenario testing and simulation, and decision modeling) are still on UiPath's roadmap. However, UiPath expects to deliver many of these through UiPath Autopilot for Process Mining. Prospective clients should check that UiPath's current advanced analytics capabilities match their requirements.


• UpFlux - Niche Player
  

  Pros:

  • Customer feedback: Feedback from Gartner Peer Insights indicates that this vendor has one of the highest levels of client satisfaction among all process mining vendors. Clients particularly note ease of use and value for money as key strengths. Reported customer retention rates also indicate a high level of value delivery.
  • Market understanding: UpFlux demonstrates a solid understanding of the future direction of the process mining market and integrates these insights into its roadmap. UpFlux is focused on key relevant features, including further integration with automation partners and building AI capabilities into the product.
  • Customer segmentation: UpFlux has executed a focused strategy within a narrow set of verticals. This has enabled it to build deeper expertise and use cases than some of its competitors in the region. This eliminates the risk associated with a broad industry strategy, where growth can outpace the ability to deliver value.

  Cons:

  • Ability to scale: UpFlux is still a small company. It has strong expertise in healthcare and financial services, but may have limited experience in other verticals. Clients from outside these verticals should consider the need for industry-specific expertise or use cases as they explore UpFlux.
  • Geography: UpFlux has focused on Latin America, and most of its customers and use cases are from that region. Prospective UpFlux customers from outside Latin America should check the level of support available for the product.
  • AI focus: UpFlux promotes a strong focus on AI as central to its process mining offering. Although the product supports a humanlike text response to 1,600 process-related queries, these are focused on the order-to-cash process in its current state. Prospective clients should compare specific GenAI capabilities against their process needs when considering UpFlux.

Reference

• Gartner, Magic Quadrant for Process Mining Platforms, 29 April 2024, ID G00790664

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