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Virtual Event: Driving Efficiency Through Hyperautomation

Harnessing Interoperable Technologies to Facilitate End-To-End Automation

Thursday, March 11, 2021
(Start: 12.00pm ET / 9.00am PT)

Agenda Overview:

Inefficient enterprise architecture can be a devastating hindrance on the productivity of an organization. If automation processes are unable to be scaled to strategic goals and priorities, organizations face a range of obstacles in achieving end-to-end automation. In recent years, the public sector has leveraged Robotic Process Automation (RPA) in automating internal functions. But what if RPA were combined with other existing technologies to offset its downfalls? This is where hyperautomation can help.

Hyperautomation refers to complementary systems of interoperable technologies that can automate business processes. There are several key technologies utilized in hyperautomation, including RPA (Robotic Process Automation), iPaaS (Integration Platform as a Service), AI (Artificial Intelligence) and Intelligent Business Process Management Suites (iBPMSs), among others. Through integration, the individual limitations of each of these technologies are overcome and agile automation at scale is enabled. By designing IT ecosystems that combine a range of existing tools, governments are presented with opportunities to develop individual technologies while maximizing departmental efficiency.

Public Sector Network’s Driving Efficiency through Hyperautomation Virtual Event will help government departments and agencies leverage multiple technologies, including RPA, AI and machine learning, to deliver more efficient processes with fewer mistakes, workforce optimization, data-driven decision-making and ultimately, better outcomes for citizens.

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Key Takeaways:

Realize the benefits of hyperautomation in facilitating end-to-end automation to drive efficiency in your government context

Invest in the development of existing technologies to build strong and sustainable enterprise architecture

Upskill and redistribute an enabled workforce to complete higher value work instead of processing tasks that could be performed by various existing technologies

Create flexible IT ecosystems that can easily support and integrate emerging technologies that may assist in driving efficiency in the future

Event Speakers:

Dr. Joel Martin

Acting Director General at the Digital Technologies Research Centre
National Research Council Canada

Sevgui Erman

Dr. Sevgui Erman

Director - Data Science Division, Chief Data Scientist
Statistics Canada

Ranjan Banerjee

Ranjan Banerjee

Manager, Program Office
Communications Security Establishment

Chris Moore

Community Advisor, Canada
Public Sector Network

Dennis Batacan

Executive Director, Digital Transformation
Manitoba Government Central Services

Irina Krasteleva

Director, Solutions Centre
Transport Canada

Erik Balodis

Erik Balodis

Program Director - Enterprise Data and Analytics Strategy
Bank of Canada

Event Partners:



Interested in sponsoring? Contact Andrew Cowan by phone (1-647-459-8904) or email (

Become a Partner

Agenda Highlights:

12:00pm ET / 9:00am PT
Chair Opening: What is Hyperautomation and How Will it Impact the Public Sector?
12:20pm ET / 9:20am PT
Keynote Session: Beyond Task-Based Transformation – Simplifying Business Process through Continuous Integration of Automation
12:35pm ET / 9:35am PT
Partner Session: Exploring the Latest Innovations in Hyperautomation
12:50pm ET / 9:50am PT
Government Case Study: Identifying and Packaging the Right AI Tools for Your Organization – and Applying them Effectively
1:05 pm ET / 10:05am PT
Government Case Study: AI at Work – Improving Efficiency, Speed and Flexibility
1:20 pm ET / 10:20am PT
Virtual Refreshment Break
1:25pm ET / 10:25am PT
Partner Session: Unlocking the Potential of Hyperautomation
1:40pm ET / 10:40am PT
Panel Session: Preparing your Organization for RPA Implementation
2:10pm ET / 11:10am PT
Closing Remarks from the Conference Chair & Virtual Event Adjourns


Complimentary to attend

For public sector only

Online event