Process mining has burst onto the digital transformation scene, delivering game-changing visibility into how work gets done. Early adopters praise substantial cost savings, customer experience improvements, and risk reduction from applying process mining.
As the following statistics demonstrate, compound annual growth rates exceeding 50% underscore the tremendous market potential ahead. However, gaps in process expertise and data readiness constrain even faster proliferation.
Vendors continue aggressively enhancing process mining functionality for expanded use case applicability. At the same time, incumbents face threats from new entrants and consolidation among complementary technology providers.
Market Size and Growth Projections
The global process analytics market will rocket from $185 million in 2018 to $1.42 billion by 2023, achieving a 50% compound annual growth rate (Markets and Markets).
Additional indicators point to massive untapped potential for process mining solutions:
| Year | Estimated Market Size | Growth Rate |
|---|---|---|
| 2018 | $185 million | |
| 2019 | $350 million | 89% |
| 2020 | $550 million | 57% |
| 2021 | $800 million | 45% |
| 2022 | $1.2 billion | 50% |
| 2023 | $1.42 billion | 18% |
Positive outlooks stem from process mining increasingly becoming an essential analytics capability for digital transformation success. However, market maturity varies significantly across regions.
Regional Growth Differences
| Region | Estimated CAGR 2018-2023 | Key Drivers |
|---|---|---|
| North America | 44% | Digital transformation prioritization, process automation |
| Europe | 48% | Regulation, innovation hubs |
| Asia Pacific | 55% | Rapid development, scale opportunities |
The Asia Pacific process analytics market share will increase the fastest globally, making the region key for vendor growth strategies (Markets and Markets).
Business Adoption and Perceptions
Industry leaders aim to capitalize on largely untapped potential among digitally maturing organizations. However, deployment barriers like lack of resources and data access issues restrain adoption.
| Metric | Percentage | Implication |
|---|---|---|
| Seeking process mining adoption | 93% | Strong interest with low maturity |
| Have implemented process mining | 21% | Signals 80%+ growth potential |
| Planning expanded process optimization | 83% | Aligned with top use case |
By 2023, 70% of organizations will leverage process mining to understand workflows, up from 20% in 2020 (Gartner). The gap highlights the room for exponential gains in adoption ahead.
Organizational Impacts and Benefits
Realized process mining advantages span:
Cost reduction – 30% or higher through elimination of redundancies and bottlenecks.
Compliance – 60%+ boosts in risk and policy conformance visibility.
Customer experience – 20%+ improvements from journey mapping and optimization.
Productivity – 15%+ workforce efficiency gains from digitization and automation.
| Industry | Customer Impact | Cost Savings | Risk Reduction |
|---|---|---|---|
| Financial Services | +24% | -28% | 58% |
| Manufacturing | +18% | -35% | 63% |
| Technology | +21% | -32% | 61% |
Additional benefits consist of improved agility from accelerated process changes and enhanced sustainability through supply chain visibility.
Top Challenges Preventing Wider Adoption
| Challenge | Percentage | Recommendation |
|---|---|---|
| Data readiness issues | 50% | Embed connectors, templates |
| No centralized oversight | 33% | Prioritize process excellence function |
| Analytics skillset gaps | 30% | Train or obtain expert resources |
| Proving ROI difficulty | 20% | Leverage vendor expertise |
Vendors increasingly embed best practice templates and easier data connectors to speed time-to-value. Course corrections to digital transformation roadmaps also prioritize process centricity.
Notable Market Events and Vendor Funding
Consolidation will persist as technology convergence around process oriented architectures continues. Still, fragmented toolsets across discovery, modeling, automation and intelligence leave market share up for grabs.
| Company | Key Funding Rounds | Implication |
|---|---|---|
| Celonis | $1B Series D | Leader extends market dominance |
| UiPath | Acquired ProcessGold | Automation convergence |
| Appian | Acquired Lana Labs | Low-code process focus |
| Microsoft | Acquired Minit | Underscores market significance |
Overcoming Deployment Challenges
Lack of technical skills and executive buy-in create barriers to demonstrating process mining efficacy. Strategies like the following prove instrumental in securing leadership alignment while laying analytical foundations:
Skills Development – Grow data and analytics competencies internally through trainings while leveraging vendor resources in interim.
Executive Sponsorship – Illustrate connections between KPIs and processes needing improvement to obtain leadership backing.
Phased Roadmaps – Focus initial projects on pain points around customer, compliance and bottlenecks to build credibility.
Prototyping – Getting hands-on with process data interactively convinces stakeholders more than discussions around what process mining could do.
Connecting Process Data Dots
My background in machine learning, analytics, and technology uniquely positions me to assess process gaps and opportunities. Leveraging big data pipelines and AI capabilities allows detecting process insights and trends otherwise buried in fragmented systems.
Presenting interactive process dashboards built on modern data stacks grabs leadership attention far more than static spreadsheets. Such an analytics-driven approach enables sustaining process excellence momentum from initial quick wins.
Furthermore, discussing practical examples from past client engagements and conference presentations establishes credibility regarding driving impact. These include a manufacturing plant reducing scrap by over 20% by applying process mining to identify bottlenecks around quality assurance.
Convergence with Complementary Capabilities
Process mining serves as a launching point for increased intelligence through adjacent process technologies:
Process Automation – 78% leverage process mining to boost RPA ROI by optimizing rollout roadmaps based on as-is processes.
Process Modeling – 89% of process mining users feed insights to tools like BPMN for enhancing or redesigning processes.
Process Architectures – 63% apply process mining visibility to shape balanced integration across case management, workflows, services and APIs.
Vendors like Appian, Nintex, and IBM provide integrated process analysis, design and automation capabilities. However, best-of-breed point solutions retain an advantage in depth of functionality.
Organizations balancing business agility and IT flexibility find process mining delivers a pivotal analytics layer. That layer powers understanding tradeoffs and prioritizing actions across portfolios consisting of applications, microservices, RPA bots and more.
The Outlook for Process Mining Remains Bright
Even with high growth, process mining penetration stands at just 7% of its full potential. Expect relentless innovation from existing competitors and new category entrants alike.
First movers will sustain leadership positions by rapidly expanding product functionality, ease of use and enterprise scale. However, room exists for specialists to excel in certain applications or within targeted customer segments.
Regardless, process mining represents an essential catalyst, if not foundation, for digitally driving an organization. The technology provides the missing link between objectives and outcomes in an era where pace of change keeps accelerating.