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1334: Infor - 3 Pillars of a Winning Hyper-Automation Strategy

1334: Infor - 3 Pillars of a Winning Hyper-Automation Strategy

FromThe Tech Talks Daily Podcast


1334: Infor - 3 Pillars of a Winning Hyper-Automation Strategy

FromThe Tech Talks Daily Podcast

ratings:
Length:
24 minutes
Released:
Sep 11, 2020
Format:
Podcast episode

Description

Infor is a global leader in business cloud software specialized by industry. With 17,300 employees and over 68,000 customers in more than 170 countries, Infor software is designed for progress. Hyper-automation is set to be one of the largest tech trends emerging in the wake of COVID-19. With a renewed focus on driving organizational efficiencies, businesses should shift to a hyper-automation mindset to streamline day-to-day operations, improve customer and employee satisfaction, and protect the bottom line. To remain competitive in the post-COVID landscape, businesses must develop robust cloud strategies that can combine data across AI, ML, NLP, process mining, and other technologies needed for hyper-automation. Rick Rider, Vice President, Product Management at Infor, believes the scope of automation will evolve from discrete tasks and transactions based on static rules to automating knowledge work. This will require moving beyond RPA to developing a hyper-automation strategy that focuses on optimizing digital processes from IT infrastructure to customer-facing applications. Rick discusses the 3 pillars of a winning hyper-automation strategy: Clear roadmap: Work with business leaders and trusted partners to define a clear roadmap to achieve specific business goals. Augment with AI and ML: Determine how AI/ML functions will perform in conjunction with other components of your business and augment human capabilities to achieve end-to-end process automation. Maximize impact with cloud technology: Establish a clear view of all data sources, then leverage cloud technology to deliver that data to applications for intelligent process automation.  
Released:
Sep 11, 2020
Format:
Podcast episode

Titles in the series (100)

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