Weill Cornell Graduate School of Medical Sciences

The School Faculty (Academic Staff) leave scheduling required process reengineering to optimize management intelligence for granting approvals and maintaining optimal staff and employee utilization.

Background

Weill Medical College of Cornell University’s biomedical research unit and medical school is based in New York City. The school conducts its research operations in collaboration with Columbia University at New York Presbyterian Hospital. Academic staff and employees across multiple departments encountered challenges in effectively managing research project timelines due to suboptimal vacation scheduling. This inefficiency led to difficulties in maintaining continuity and productivity in research activities.

Challenges

The primary challenge was to overhaul the leave scheduling process to make it more efficient and intelligent. The school needed a system that could manage work schedules, attendance, absence data, vacation quotas, and leave requests and approvals seamlessly, ensuring minimal disruption to research activities.

Solution

As a Senior Consultant, we played a pivotal role in directing the development and implementation of key enhancements to the leave scheduling process, which included:


01
Service-oriented Architecture

Service-oriented Architecture

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02
Role-based Applications

Role-based Applications

Developing role-based web/mobile applications, these applications collected work schedule rules, attendance/absence data, vacation quota accrual rules, and leave requests and approvals.

03
SAP HANA ECC

SAP HANA ECC

Using SAP HANA ECC system, The business logic was implemented using the SAP HANA ECC system, which integrated with the User Interface via OData RESTful API.

04
SAP Flori

SAP Flori

Developing the User Interface with SAP Fiori Framework, This framework provided an intuitive and user-friendly interface for managing leave schedules.

Outcome

The implementation of this solution drastically improved the efficiency and intelligence of the leave scheduling process. By automating many of the previously manual tasks, we were able to reduce errors and ensure that leave requests and approvals could be managed seamlessly. The use of service-oriented architecture allowed for the handling of large volumes of data quickly and accurately, further enhancing the overall performance of the system.

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