by Shashi Bhargava, on Dec 9, 2024 5:14:04 PM
Key takeaways from the blog
- High-pressure document-intensive scenarios demand automation.
- IDP and RPA are complementary technologies for improving speed and accuracy.
- AI and Copilot augmentation enable out-of-the-box automation scenarios.
Admission processes occur throughout the year for different academic streams. Thousands of students apply every season along with their duly filled-in application forms and supporting documents. Reading each student’s application and supporting documents and then shortlisting the candidature according to the University’s criteria is a mammoth task. The admissions personnel distribute the load among their trusted hands and sometimes faculty members double up as admin officers to manage the load. Putting in extra hours pushes the human personnel to the edge, which gets reflected in the incorrect data capture and rework. Such high-pressure and document-intensive scenarios demand intelligent document processing (IDP) and robotic process automation (RPA) to improve processing speed, productivity, and efficiency.
Pain-points during University Admissions
Typically, some of the major hurdles during university admissions include –
- High data volumes: Managing high volumes of student applications through manual operations with some trusted hands has very low scalability. Onboarding interns for the process during workload peaks results in lower speed and poor data quality.
- Error-prone data entry: Manual operations under looming deadlines result in inaccurate data capture and rework. Human error under pressure with growing student application volume is natural and leads to inaccurate data capture and repeated rework.
- Backlogs and workloads: The admissions procedure has stringent criteria and looming deadlines. As a result, it is impossible to select the right candidates in the given admissions cycle. It results in backlogs. Brilliant students get dropped off and they reach out to other universities for fear of losing their academic year.
- High turn-down ratio: Losing brilliant students to other universities due to slower student application processing influences the University’s gradation.
- Time-consuming validations: Application evaluators have to validate the student data within the same student application docket across different documents. It is a time-consuming process that results in further backlogs.
- Multiple data entries: The extracted data needs to be keyed into different systems, resulting in swivel chair operations, slower speed, and low turnaround time.
- Lack of transparency: Universities key in data from student applications one by one while handling huge volumes of data. It results in low time-to-insights and a lack of transparency.
Accelerate University Document Processing with IDP
IDP supports document and process-intensive scenarios, such as University admissions, in a significant manner –
- Highly accurate data extraction: IDP has high data capture accuracy or confidence levels while extracting data from free-flowing or unstructured documents. It also seamlessly integrates the extracted data in a structured format into downstream systems, such as University CRMs and ERPs.
- Hand-written data extraction: IDP also accurately extracts data from hand-written documents and accurately captures the matter from hand-written forms.
- Improved data quality: High accuracy in data extraction results in improved data quality for faster time-to-insights.
- High transparency: Faster time-to-insights results in high visibility and transparency across the academic admissions process. It helps tap the influx of prospective students, gain quick insights about their quality and caliber, and eliminate the intelligence loss to other universities.
- Plug-and-play document automation: IDP starts delivering from day one without downtime during installation, ensuring a quick return-on-investment.
- Faster turnaround time: IDP extracts data within a fraction of the manual data processing time. It eliminates backlogs and streamlines operations.
Synchronize University Databases using RPA and much more
RPA solutions help automate process-intensive environments that involve tedious and repetitive processes. Further, AI and Copilot augmentation enable out-of-the-box automation. Some of the typical automation scenarios at Universities are –
- Segregate, classify, and forward email: Auto-segregate email received from different students and other work-related entities and route them to the proper departments or personnel for faster processing. Acknowledge receiving the emails at the first instance, generate an inwarding number, and classify the email as per the subject and content.
- Read and extract data from documents and email: Auto-download document attachments in specified folders, auto-extract data from the attachments and email, and integrate it with downstream systems.
- Schedule appointments: Create an appointment schedule offline in a spreadsheet and set the automation solution to use the spreadsheet details to schedule appointments in Outlook, Skype, or any other meeting scheduler.
- Manage payroll: Autonomously track teaching staff attendance, extract details from the attendance management system, and integrate the details with the payroll system to generate pay cheques/credit the salary account.
- Onboard students/staff/partners: Track the status of entities to be onboarded, auto-check the status of their documents received/pending, seamlessly auto-send reminders related to pending documents, and monitor the end-to-end onboarding process till completion.
- Manage inventories: Autonomously track and fulfill inventories of academic books, sports and gym items, pantry stock, etc.
Key benefits of IDP and RPA for process-intensive scenarios
IDP and RPA complement each other. This technology convergence brings to the table the desired business outcome of –
- High Accuracy: It improves overall data quality for faster time-to-insight and decision-making.
- Speed: It significantly improves student application processing speed and onboarding.
- Increased Productivity: It improves staff productivity and supports the recurring admissions cycles.
Simply put
Automating document processing and academic tasks performed manually is crucial as student intake increases year-on-year and student application volume increases correspondingly. Relying on sub-par document processing solutions is detrimental in such scenarios. Adopting state-of-the-art technologies, such as IDP and RPA, improves the accuracy, productivity, and efficiency of the admissions process. Further, the AI and Copilot aspects support out-of-the-box automation scenarios, taking productivity and efficiency to an entirely new level.
