AI-POWERED PROCESS OPTIMIZATION
Process Improvement Copilot: Bridging Inefficiencies to Ideas
Business process improvement (BPI) is a crucial value-adding stage of business process management, as it introduces process changes to eliminate flaws and enhance performance. However, the inherent demands of BPI on domain knowledge, process expertise, time, and creativity in conjunction with a scarcity of adequate computational support, hinder organizations from fully leveraging BPI. Recognizing this gap, recent research calls for all types of contributions to process improvement and innovation systems (PIISs), from design knowledge to software artifacts. Leveraging the latest developments in generative artificial intelligence, increased availability of process execution data, and extensive collections of BPI knowledge, we propose a new technical approach to supporting the generation of process improvement ideas in BPI initiatives. To this end, we develop the Process Improvement Copilot – a retrieval-augmented generation (RAG)-enhanced PIIS that generates context-specific process improvement ideas and provides related justification, thereby facilitating their further evaluation and implementation. This research contributes a novel technical approach to automated BPI by exploring a RAG-based use case, designing a corresponding system architecture, developing a software prototype to demonstrate its technical feasibility, and evaluating the Process Improvement Copilot's usefulness in a naturalistic workshop setting.
Key Impacts of the Process Improvement Copilot
Our evaluation highlights the significant benefits of the Process Improvement Copilot in transforming BPI initiatives within organizations.
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System Architecture Understandability
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Software Prototype Usefulness
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Time Reduction for Idea Generation
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Leveraging Accumulated BPI Knowledge (DO1)
The Process Improvement Copilot leverages a substantial body of accumulated BPI knowledge, including existing BPI patterns, case studies, and allows for the integration of proprietary organizational knowledge. This structured approach ensures that ideation phases are well-informed, preventing unnecessary reinvention and promoting the reuse of proven solutions. The RAG-enhanced architecture directly supports this by providing a comprehensive knowledge base for relevant information retrieval.
Generating Context-Relevant Process Improvement Ideas (DO2)
Our system excels at generating highly relevant process improvement ideas by considering the specific context of each BPI initiative. It utilizes process execution data from event logs and comprehensive user-provided context (covering goal, process, organization, and environment dimensions). This contextual awareness enhances the quality and applicability of the generated ideas, making them actionable for real-world scenarios.
Reducing Time and BPI Expertise Required (DO3)
By automating the idea generation process, the Process Improvement Copilot significantly reduces the time and specialized BPI expertise traditionally required for this stage. This computational support increases human resource utilization and streamlines BPI initiatives, making them more efficient and accessible to a broader range of users without extensive prior experience.
Handling Complex BPI Initiatives (DO4)
The Copilot is designed to address complex BPI scenarios, capable of dealing with multiple process inefficiencies simultaneously. It considers various performance dimensions and multi-objective BPI requirements, utilizing the Idea Combinator component to consolidate initial ideas into a unified improvement plan. This ensures a coordinated approach to comprehensive process optimization.
Facilitating Human-on-the-Loop Follow-up Actions (DO5)
Recognizing the importance of human oversight, the system operates in a human-on-the-loop mode. It provides justifications and traces the origin of generated ideas back to relevant knowledge chunks, enhancing transparency and trustworthiness. Prompt engineering and LLM configuration minimize hallucinations, ensuring predictable and reliable output that supports informed human decision-making and further evaluation.
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of experts agreed that the time needed to generate process improvement ideas and justifications is significantly reduced.
Enterprise Process Flow
Ingest Event Log
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Identify Inefficiencies
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Provide Context
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Retrieve BPI Knowledge
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Generate Ideas
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Consolidate Ideas
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User Review
| Feature | Process Improvement Copilot | Afflerbach et al. (2017) |
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| Leverages BPI Knowledge |
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| Context-Relevant Ideas |
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| Reduces Time & Expertise |
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| Handles Complex Initiatives |
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| Human-on-the-Loop Support |
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Case Study: Purchase-to-Pay Process Optimization
An analysis of a purchase-to-pay event log revealed a critical inefficiency: the 'Change Quantity' activity was executed multiple times in 8.0% of cases, with 5.0% occurring in direct succession. This repetitive rework significantly impacted process throughput time. The Process Improvement Copilot, leveraging its RAG-enhanced architecture and BPI knowledge, rapidly identified this bottleneck.
The Copilot suggested several targeted process improvement ideas. Notably, it recommended **batch processing** for similar 'Change Quantity' requests, justifying this by its potential to reduce the frequency of the activity and significantly minimize process throughput time through optimized resource utilization. Other ideas included introducing **conditional compensations** to streamline variations and **reducing touchpoints** to lessen time-consuming interactions with external parties. These suggestions were directly informed by relevant BPI patterns, offering actionable steps to enhance efficiency and optimize the process flow.
Impact: Experts found the generated ideas relevant, with 20% considered actionable without further investigation, and 40% of proposed follow-up actions assessed as actionable, demonstrating the Copilot's practical value in real-world BPI initiatives.
Quantify Your Potential AI-Driven ROI
Estimate the impact of implementing AI process improvement with our interactive ROI calculator. Adjust the parameters to see your potential annual savings and reclaimed hours.
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Your AI Implementation Roadmap
Implementing cutting-edge AI requires a structured approach. Here's a suggested roadmap for integrating the Process Improvement Copilot into your enterprise.
Phase 01: Initial Integration & Inefficiency Identification
Integrate the Copilot with existing process execution data (e.g., Celonis). Focus on automatically identifying core process inefficiencies and establishing the foundational knowledge base, including internal BPI best practices.
Phase 02: Contextual Idea Generation & Validation
Utilize the Copilot to generate context-specific process improvement ideas for identified inefficiencies. Implement human-on-the-loop validation of generated ideas, refining prompts and knowledge retrieval based on expert feedback.
Phase 03: Expanding BPI Scope & Knowledge
Extend the Copilot's capabilities to support additional BPI stages, such as idea evaluation and simulation. Broaden the knowledge base with quantified impact studies and detailed business rules to enhance idea quality and relevance.
Phase 04: Advanced AI Integration & Feedback Loops
Explore multi-technology PIISs, combining GenAI with other AI techniques. Implement reinforcement learning mechanisms and feedback loops to continuously improve system performance and adapt to evolving organizational needs.
Phase 05: Scalability & Continuous Optimization
Conduct comprehensive technical benchmarking of the RAG architecture in real-world scenarios. Focus on optimizing the system for scalability, reliability, and long-term performance, ensuring the Copilot remains a valuable asset for ongoing process innovation.
Ready to transform your processes?
The Process Improvement Copilot offers a novel approach to automate and enhance your BPI initiatives. Connect with our experts to discover how AI can drive efficiency and innovation in your organization.
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