Unlocking Digital Transformation through Business Process Mining
Business Process Mining can play a pivotal role in driving digital transformation by streamlining operations and enhancing efficiency. This webinar will delve into various aspects of process discovery, analysis and monitoring, and offer practical knowledge for initiating your digital transformation journey.
View this on-demand webinar to learn:
- The impact Process Mining can have on achieving a successful digital transformation
- The different stages involved in the discovery, digitization, and analysis of processes and tasks
- How Process Mining can help companies optimize processes, improve visibility, and achieve informed decision-making
- How to get started with Process Mining in your organization
We’ll also share a demonstration of iGrafx Process Mining technology.
iGrafx, Account Manager
Shervin is an accomplished Account Manager specializing in process management. With a background as a process management consultant, Shervin excels in analyzing and automating processes to enhance key performance indicators (KPIs). As the Account Manager for iGrafx in Germany, Austria, and Switzerland, Shervin is dedicated to driving client growth and success through tailored process optimization strategies. His deep understanding of process management principles and commitment to continuous improvement make him a trusted advisor for organizations seeking to streamline operations.
Armen has over 15 years of experience in business process optimization, orchestration, and automation. Together with his team, he has successfully led numerous complex digital transformation projects that involved intricate technological and organizational solutions. Recently, his company has been primarily dedicated to enabling companies to enhance, implement changes, and monitor complex end-to-end processes through data utilization, leveraging process, task, and conversation mining. They have gained a reputation for their unwavering focus on achieving business outcomes and tackling challenging data issues.