珠峰集团+UiPath+持续发现和智能自动化手册——拥抱人工智能的时代-英-151页_4mb

Continuous Discovery and Intelligent Automation Playbook Summary

Introduction

This report outlines the necessity for digital transformation via innovation and the role of continuous discovery and intelligent automation (CDIA) in driving business outcomes. Enterprises are moving toward a digital-first model to address challenges like evolving stakeholder expectations, competition, and supply chain disruptions. CDIA provides a value-based approach to innovate, optimize processes, and achieve targeted process and business KPIs.

Key Stakeholders and Their Priorities

• Automation Leads: Focus on improving operational efficiency, generating cost savings, and achieving high ROI from automation initiatives. Challenges include change management, limited technology awareness, and process understanding.
• Process Owners: Prioritize process efficiency, cost savings, and employee experience. Key challenges are lack of process visibility, stakeholder buy-in, and siloed approaches.
• CXOs: Aim to maximize revenue, achieve operational excellence, and drive continuous innovation. Obstacles include identifying transformation opportunities and talent shortages.

Role of CDIA

CDIA helps tackle challenges by offering accurate process visibility, real-time insights, and data-driven actions for optimization. It supports building organizational resilience and innovation through a lifecycle of discovery, evaluation, prioritization, implementation, and continuous monitoring.

Technologies Enabling CDIA

Core technologies include process mining, task mining, and communications mining for discovery, combined with rule-based automation (e.g., RPA), API automation, intelligent document processing (IDP), and conversational AI for actions. Benefits span cost savings, operational efficiency, governance improvement, and enhanced customer experience.

Benefits and Adoption

• Key Benefits: Enterprises achieve process optimization, improved governance, cost savings, and automation ROI. AI-based tools like generative AI enhance capabilities.
• Market Characteristics: Process mining and task mining markets are growing rapidly, with high adoption by North American enterprises in BFSI and manufacturing. Factors include cost savings and operational needs.
• Geographic/Industry Trends: North America leads adoption, with BFSI, telecom, and retail as key industries.

Best Practices for Implementation

• Secure executive sponsorship and develop effective change management programs.
• Foster collaboration between process excellence and automation CoEs.
• Leverage best practice frameworks for identifying and prioritizing process areas, selecting enterprise-grade solutions, and scaling initiatives.
• Start with low-hanging fruit projects and use structured prioritization based on improvement and impact potential.

Case Studies

• EY: Improved auditing efficiency through process mining.
• İşbank: Enhanced process efficiency and customer satisfaction.
• Stoneridge: Accelerated automation with task mining and RPA.

Capability Maturity Model (CMM)

Assesses enterprise capabilities across vision, technology, talent, and implementation. Levels range from Basic to Leader, guiding organizations to enhance their CDIA journeys based on environmental factors like risk appetite and technology savviness.

Conclusion

CDIA is pivotal for digital transformation, offering enterprises a pathway to innovation, efficiency, and competitive advantage when implemented with strong governance and change management.