In June, Skan hosted a fireside chat on “The recent rise of AI driven Process Intelligence and its impact on Enterprise Transformation”, featuring a star-studded panel of senior leaders and executives with decades of experience across digital transformation, automation, artificial intelligence, and process excellence:
- Vinaykumar Mummigatti, Chief Automation Officer, LexisNexis
- Rob Strub, Managing Director and Head of North America Operations, Citi
- Preetha Sekharan, VP, Digital Strategy & Transformations, Unum
- Ted Shelton, Expert Partner, Automation and Digital Innovation, Bain & Company
- Douglas Kim, Sr Fellow, MIT Media Lab Connection Science Institute
- Avinash Misra, CEO and Co-Founder, Skan
The panel had a deep discussion about how leaders across industries are grappling with the pressures of meeting promised operational savings, the compliance challenges of far-flung teams, and how to consistently meet the committed SLAs promised to customers when associate churn is higher than ever and our systems aren't keeping up. The discussion then dove into how modern executives are approaching these challenges by deploying emerging technologies including automated process discovery, process mining, process intelligence, and AI.
Below are Skan's top four insights from this energizing discussion
Analytical speed is critical. Executives need to be able to take action on process insights before those insights become outdated.
Manual process discovery can take months or even years, but processes and work are constantly changing. As a result, by the time the insights are gathered and organized, they are often outdated. This can result in misinformed or counterproductive actions or decisions based on those insights, leading to many of the challenges being experienced today with implementing automation tools and workflows. Successful leaders are looking towards faster and continuous methods for understanding processes and work, powered by data and technology.
Digital Transformation is changing the way companies are organizing their operations.
Historically, organizational coordination has been one of the highest cost of doing business, leading many companies to organize their operations in silos. However, the companies that are seeing the most success with digital transformation are organizing around processes and outcomes. This requires a complex view of how work is being done end-to-end across the organization.
Don't chase “shiny objects”. First understand the end-to-end view of processes, then decide on the right technology based on your goals.
Many executives jump towards the newest and most exciting automation or artificial intelligence tool without first understanding the end-to-end view of the processes. This results in applying automation and process optimization towards specific tasks, without understanding the true bottlenecks. Improving processes starts with understanding processes and seeing the big picture.
Look for the “triple plays”. Don’t settle for ‘trade offs’ across competing operational objectives.
Historically, companies have had to make trade-offs between process efficiency, risk/control, and customer experience. However, the demands on the modern enterprises are to meet and improve all of these objectives simultaneously: improve efficiency while also optimizing client experience and simplifying processes. This challenge is being met by a new class of technologies in process discovery and decision tools leveraging machine learning and artificial intelligence.