case study
IIM Calcutta

Transforming India's Largest Placement Drive

Table of Contents
5 min read

Overview

IIM Calcutta faced challenges in creating effective timetables each academic term. The manual process of scheduling classes, taking into account demand for courses, avoiding scheduling conflicts, and considering faculty preferences, had become time-consuming and error-prone. The school sought to streamline this process through automation, using data-driven methods to improve efficiency and accuracy. This case study outlines how the school implemented an automated timetable scheduling system based on demand estimation data, a course clash matrix, and faculty preferences, significantly improving the process.

The Problem

Before automation, the school’s scheduling team manually assigned courses to available time slots, trying to balance several variables:

  1. Demand Estimation Data: Predicting student enrolment for various courses.
  2. Course Clash Matrix: Avoiding scheduling conflicts between courses often taken by the same students.
  3. Faculty Preferences: Accommodating instructors' preferred teaching times and avoiding overbooking them.

This process involved back-and-forth communication between faculty, the administration, and students. As the number of courses and faculty increased, the scheduling process became more complex, often resulting in inefficiencies, scheduling conflicts, and under-utilization of classrooms. There was also a growing dissatisfaction among students who could not enrol in their preferred classes due to poor time slot allocation.

Objectives

The primary goals of the automation initiative were:

  • Increased efficiency: Automating the scheduling process to save time.
  • Better demand matching: Using enrolment data to ensure popular courses were scheduled in larger venues and at optimal times.
  • Conflict resolution: Preventing course clashes and double bookings for both students and faculty.
  • Faculty satisfaction: Incorporating faculty preferences without manual intervention.
  • Flexibility: Allowing quick adjustments in response to changes in student enrolment or faculty availability.

Solution: An Automated Timetable Scheduling System

The business school implemented a timetable scheduling system built around three key data sources: demand estimation data, a course clash matrix, and faculty preferences. The system also leveraged optimization algorithms to create conflict-free schedules.

1. Demand Estimation Data

The school had historical data on student enrolment patterns and trends for each course, which was fed into a demand estimation model. This model predicted the number of students likely to enroll in each course, enabling the system to assign appropriate time slots and classroom sizes. Popular courses were given priority for larger venues and time slots with high student availability.

2. Course Clash Matrix

A matrix was developed that mapped out common course pairings that students often take together. The matrix identified potential clashes if two or more courses were scheduled simultaneously. The automated system used this data to ensure that no two courses likely to be taken by the same students were scheduled at the same time.

3. Faculty Preferences

Faculty members were asked to submit their preferences for teaching times (e.g., mornings, afternoons) and any constraints (e.g., research commitments, personal scheduling conflicts). These preferences were then incorporated into the scheduling system. The system aimed to accommodate as many preferences as possible while still ensuring a balanced and efficient schedule.

4. Optimization Algorithm

The system used a constraint-based optimization algorithm, designed to find the best possible schedule based on the available data. The algorithm balanced several competing priorities:

  • Minimizing course clashes for students.
  • Assigning courses to suitable classrooms based on demand predictions.
  • Accommodating faculty preferences.
  • Ensuring balanced use of classrooms and time slots to avoid overloading any one period.

Implementation

The implementation process involved several phases:

  1. Data Collection and Integration: Historical enrolment data, course relationship data (clash matrix), and faculty preferences were gathered and standardized for integration into the new system.
  2. System Development: The timetable scheduling software was customized for the school’s needs, with functionalities added to input, process, and output schedules based on the three key data sets.
  3. Testing and Validation: A series of test schedules were generated and validated against historical outcomes. Faculty and administrative staff reviewed the test schedules to ensure the system was meeting their needs.
  4. Training and Rollout: Training sessions were held for administrative staff on how to input data, review schedules, and make minor manual adjustments when needed.

Results

The new system led to several immediate improvements:

  • Increased Efficiency: The time spent creating timetables was reduced by more than 70%. What used to take weeks was now done in a matter of days.
  • Fewer Scheduling Conflicts: There was a marked reduction in student complaints about course clashes, with the system resolving over 95% of potential conflicts identified by the course clash matrix.
  • Optimized Classroom Use: Classrooms were better utilized, with larger classes assigned to appropriately sized rooms based on demand estimation.
  • Faculty Satisfaction: Over 85% of faculty preferences were successfully incorporated into the final schedule, improving satisfaction among instructors.
  • Improved Flexibility: The system allowed for quick re-scheduling in response to changes in student enrolment or unexpected faculty absences, without needing to start from scratch.

Challenges and Lessons Learned

While the automated scheduling system proved successful, several challenges were encountered:

  • Data Quality: The system’s effectiveness depended heavily on accurate demand estimation and up-to-date faculty preferences. Initial data inconsistencies required additional cleaning and verification.
  • Faculty Buy-In: Some faculty members were initially skeptical of the new system, fearing it would reduce their flexibility. Clear communication and the system’s ability to accommodate most preferences helped ease concerns.
  • Customization: The business school required a custom solution to fit its specific needs, which increased initial development time and costs. However, the long-term benefits of efficiency gains outweighed these initial hurdles.

Conclusion

By implementing an automated timetable scheduling system that leveraged demand estimation data, a course clash matrix, and faculty preferences, the business school significantly improved its scheduling process. The system not only saved time and reduced errors but also improved faculty and student satisfaction by creating more balanced, conflict-free timetables. This case demonstrates the value of data-driven decision-making and automation in addressing complex administrative challenges in higher education.

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Team EDTEX successfully automated the Day Placement Process at XLRI, which includes efficient scheduling and real-time student tracking. This automation has streamlined our placement activities, making the process more organized and manageable for all involved parties.

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All stakeholders involved in the placements process, including students, the Placement Committee, Institute Administration, and participating companies, have expressed their satisfaction with Skynet. The platform has proven to be an invaluable asset in facilitating virtual placements, ensuring a seamless and efficient experience for everyone.

Conclusion

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This innovation has reduced manual effort by more than 97% for both the Programme Offices and students and allowed implementing programme specific credit policies

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Comprehensive Support Systems from EDTEX

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Customized Placement Process Automation

Recognizing the unique needs of ISB Hyderabad & Mohali placement process, the Skynet platform was customized to fit the specific requirements of the institute. The platform automates various aspects of the placement process, from managing

1. Student Master profile creation

2. Student profile data validation,

3.  Student e-profile book

4.  Automatic CV generation in the institute format

5.  PPT event Management with Notifications

6.  PPT Attendance tracking

7.   Applications Management

8.   Shortlisting Management

9.   Offer Management (dream offer workflows)

10.  Scheduling interviews

11.  Students

12.  50 plus Custom Reports and Analytics Dashboards

13.  Custom User Access (functional control management)

14.  Dedicated single tenet EDTEX cloud for optimal performance

15.  Recruiter Registration Portal

16.  Invoicing Workflows

17.  Query management system

Key Features of the Skynet Platform

  1. Comprehensive Student  Profile Management: Skynet enables students to create detailed  profiles, including academic records, extracurricular achievements, and work experiences. This information is easily accessible to recruiters,  allowing them to shortlist candidates efficiently.
  2. Automated Application  Tracking: The platform automates the tracking of student applications for different job roles. Students can apply for positions through a centralized system, which keeps track of all their applications and updates them on the status in real-time.
  3. Interview Scheduling: Skynet facilitates the scheduling of interviews by coordinating between students  and recruiters. The system ensures that interview slots are allocated     fairly and that there are no conflicts, providing a smooth scheduling     experience.
  4. Recruiter Management: Skynet platform includes robust tools for managing recruiter information and  communication. Recruiters can access the system to post job openings, view  student profiles, and manage their recruitment schedules.
  5. Data Analytics and  Reporting: Skynet provides powerful analytics and reporting  features, allowing the placement office to generate detailed reports on  placement activities. These insights help in evaluating the success of the placement process and identifying areas for improvement.

Benefits of the Skynet Platform

  • Increased Efficiency: By automating routine tasks, the Skynet platform reduces the workload on the placement office staff, allowing them to focus on more strategic     activities.
  • Enhanced Accuracy: Automation minimizes the risk of errors in data handling and scheduling, ensuring a more reliable and accurate placement process.
  • Improved Transparency: The platform offers real-time updates and transparent processes, fostering trust among students and recruiters.
  • User-Friendly Interface: Both students and recruiters benefit from an intuitive interface that simplifies the placement process and enhances user experience.

Exceptional Support from EDTEX

Throughout the implementation and operational phases, the EDTEX team provided exceptional support to ISB Hyderabad. Their expertise in developing tailored software solutions ensured that the Skynet platform was perfectly aligned with the institute's specific needs. The team's responsiveness and commitment to addressing any issues promptly played a crucial role in the successful deployment of the system.

Conclusion

The implementation of the Skynet Placement Process Automation system at ISB Hyderabad represents a significant advancement in the institute's placement activities. By customizing the platform to meet their unique requirements, ISB Hyderabad has enhanced the efficiency, accuracy, and transparency of their placement process. The collaboration with EDTEX has proven to be highly beneficial, providing a robust and user-friendly solution that meets the high standards of the institution.

This tailored automation system not only streamlines the placement process but also ensures a seamless experience for all stakeholders involved, positioning ISB Hyderabad as a leader in innovative educational solutions.