It’s the nature of the beast when it comes to technology adoption: new tech goes through multiple stages of acceptance, from doubt and cautious consideration to eventually moving to widespread acceptance. While not everyone accepts change at the same pace, some industries lag behind others. The world of higher education, for example, has rarely been the first to implement new technologies. Yet with major disruptions facing educational institutions, they can no longer afford to avoid embracing new technologies and processes that can have a significant impact on the way they operate. Hyperautomation — the disciplined approach to automating processes using smart technologies like AI and machine learning — is one such field that can help educational institutions from facing obsolescence. 

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Why Is Hyperautomation Needed in Education?

The field of higher education, while generally slow to adopt new tech, stands to benefit by replacing legacy systems to process information more quickly, lower costs, and respond to change more adeptly. In particular, they can improve operations in areas ranging from admissions and administration to records and security. While hyperautomation and its associated technologies have many potential applications within higher education to improve modernization strategies, organizations that implement hyperautomation in education will see immediate returns when used on some of the most common pressure points, including:

  • Budget constraints within administration financial plans
  • Departmental silos across campuses
  • An aging workforce and ability to capture process acceptance issues
  • The need to attract new staff and retain existing talent
  • Supporting existing and new technology systems that may have minimal cross-platform communication
  • Data protection and cybersecurity for staff and students alike

Tools for Hyperautomation in Education

The implementation of the technologies associated with hyperautomation is not meant to be a minor modification of an existing strategy or process. Leaders must look for every opportunity to integrate these tools across their campus operations. There are three critical tools for hyperautomation in education that can be implemented:

  1. Intelligent Document Processing (IDP) - IDP software can be used to analyze unstructured content such as an email to gather data and populate usable formats and templates. It can be used to automate processes related to reviewing transcripts; verifying academic standards for athletes; evaluating admissions documents; and assisting with administrative tasks.
  2. Robotic Process Automation (RPA) - Unlike IDP, RPA is focused on structured data points that can be collected from applications, financial aid documents, course loads, and graduation applications. This software can greatly improve university efficiency in processing required documents.
  3. Business Process Management - BPM workflow automation can be used by faculty and administration to move time consuming physical paperwork to digital documents that can be easily tracked through the approval process. By automating paperwork for financial aid, class registration, and even marketing, faculty and administration have more time to focus on making the educational experience better for students.

Implementing Hyperautomation in Education With Agile Practices 

The pandemic created a need for typically slow organizations to respond and pivot in faster ways than ever before. Hyperautomation, when implemented with Agile practices, can help educational institutions transform and scale their digital modernization. By combining the tenets of agile, such as breaking projects into multiple smaller phases and enhancing collaboration of stakeholders, hyperautomation efforts can more quickly generate value by replacing tedious manual tasks that administrators find themselves mired in every day.  University technology leaders can introduce tools such as AI and RPA to optimize the analysis of information to eventually increase efficiencies exponentially, creating a much-needed multiplier effect. 

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An Example From Alumni Engagement

Private colleges and universities support much of their operations from donations raised through extensive fundraising. One Director of Alumni Engagement at a prestigious university needed to implement a new campaign to support the work of the Business School without adding to his current staff. One of the hyperautomation tools put to the task was the use of bots (automated software applications) to analyze alumni emails and online response forms to gather and process requests and funnel the results to the proper individuals or channels. 

This type of smart automation allows the director to save valuable time for the staff and administrators to focus on critical work that cannot be handled by software. Moreover, bots can use natural language processing (NLP) to understand and track details and nuances that may lead to additional donors and funding. The end result is increased funding for the university to further fulfill its long-term educational mission.

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Conclusion: Learn Key Hyperautomation Tools

As universities continue to look for opportunities to implement hyperautomation and its associated tools, there will be an increasing need for employees trained in skills like AI and Machine Learning as well as Robotic Process Automation. Industry recognized certifications from partners like Purdue and IBM will provide credibility for those looking to optimize their value in the workplace.

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