Course Name: Modelling and Analytics for Supply Chain Management

Course abstract

This course focuses on the application of analytical techniques for determining effective solutions to problems associated with supply networks considering the constraints of demand and supply. The objectives of the course are to understand the nature of supply networks, goal of supply networks and explain the impact of analytics based supply chain decisions on the success of a firm. The coverage includes key metrics that track the performance of the supply network in terms of each driver, identification of the key factors to be considered when designing a distribution network and use of analytical techniques for developing a framework for network design. Emphasis is laid on the use of optimization techniques for facility location, capacity allocation and evaluation of supply chain design decisions under uncertainty. Along with these objectives, this course is also aimed at understanding the concepts of multi-criterion decision making in supplier selection and rating, inventory management techniques under uncertain demand and supply environment, mathematical models for design of transportation networks, and the role of soft computing techniques for matching supply with demand.


Course Instructor

Media Object

Prof. Kunal Kanti Ghosh

Prof. Kunal Kanti Ghosh has over three decades of experience at various levels in the automobile industry. He was the "Corporate Initiatives Head" of Tata Technologies Ltd and was adjudged the "Best Young Materials Manager" by the Indian Institute of Materials Management in 1986. He also received the "Best young Manager's Award" from All India Management Association in 1990. He was the prime architect of "Parts Supply Management System" for Nissan Plant in Australia, Melbourne.
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Media Object

Prof Anupam Ghosh

Prof Anupam Ghosh obtained Masters Degrees with specializations in Supply Chain Management, Accounting, and Commerce. His PhD is on Information Visibility in Supply Chain. He has about 13 years of teaching experience in Supply Chain Management, Supply Chain Analytics, and International Marketing. He was a Visiting Scholar to Bentley University, Waltham, MA, USA during 2004-05. He has worked on projects on Healthcare Information Systems in USA, Fixing Transportation Fares for Public Transportation Systems in India, and has conducted various Management Development Programs on Supply Chain Management and Materials Management.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jan-Apr 2021

  View Course

 Syllabus

 Enrollment : 18-Nov-2020 to 25-Jan-2021

 Exam registration : 15-Jan-2021 to 12-Mar-2021

 Exam Date : 25-Apr-2021

Enrolled

1478

Registered

149

Certificate Eligible

91

Certified Category Count

Gold

0

Silver

20

Elite

41

Successfully completed

30

Participation

8

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Note:
We have taken best assignment score from both Jan 2020 and Jan2021 course
Modelling and Analytics for Supply Chain Management - Toppers list

PIYUSH 88%

PDIL

SHANTESH BASAVARAJ METI 85%

DR. VISHWANATH KARAD MIT WORLD PEACE UNIVERSITY, PUNE

RAMAA ANANTHAMURTHY 82%

R V COLLEGE OF ENGINEERING

PRABIR KUMAR MUKHERJEE 82%

MANDAR SHASHIKANT ACHARYA 80%

Kirtane & Pandit LLP

FINCE ANNA PHILIP 80%

Beroe

DEBJIT MODAK 80%

DRDO

SMIT HIREN PAREKH 80%

VEERMATA JIJABAI TECHNOLOGICAL INSTITUTE

AMBUJ KUMAR 80%

KAMLA NEHRU INSTITUTE OF TECHNOLOGY

Enrollment Statistics

Total Enrollment: 1478

Registration Statistics

Total Registration : 150

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.