Advanced SCM and Analytics

Credits / 1.5 (10 sessions of 90 minutes each)
Faculty Name / Prof Arun Kumar Paul(Extn: 727) [
Program / MBA–BM 2016-18
Academic Year and Term / 2017-18, Term- VI

PREREQUISITE:

  • Should have quantitative and analytical bend of mind;
  • 6.00 qpi cutoff including (OR and OM-I)
  1. CourseDescription and Objective:In today’s globalized world, efficient and effective management of complex supply network plays an important role in determining the long term success of any business. Traditional way of decision making in a supply chain, with variety of local and global parameters to take care, is becoming increasingly difficult and wasteful. Thus comes the role of ‘Analytics’, as the supply chain would provide tremendous opportunity to collect on-line real time data and then the use analytic tools to look into the data for improvement opportunities, taking intelligent decisions that will have positive impact on the cost structure and service delivery.

This elective builds on the concepts and knowledge of core OM course and SCM elective. Objective of this course is to make students appreciate as to how supply chain modeling and analytics is still an untapped opportunity for many organizations (even with ERP platforms or otherwise), since they have data at their disposal but lack either the tools or the knowledge to exploit it in terms diagnostic or predictive analysis. This course will deal with some advanced concepts of SCM and on issues of using analytics on various aspects of a supply chain to improve forecasts, demand planning, sourcing, production and distribution.

  1. Learning Outcomes: Upon successful completion of this course, the student should be able to:

Course Objectives / Program Objectives
Demonstrate understanding of elements in certain advanced SCM concepts and analytics. / 1.4
Understand, formulate and quantitatively solve real world problems in the supply chain of manufacturing or service sector. / 2.1
  1. Suggested readings

Books

  • Supply chain management by Sunil Chopra, and Peter Meindl, Pearson
  • Modeling the Supply Chain by Jeremy F. Shapiro. Duxbury Thomson Learning
  • Designing and Managing the Supply Chain concepts, Strategies and Case studies,by D. Simchi-Levi, P. Kaminsky, E. Simchi-Levi, and Ravi Shankar, Tata McGraw Hill, New Delhi.
  • Business Logistics / Supply Chain Management by Ballou and Srivastava, Pearson.
  • Big Data Driven Supply Chain Management by Nada R. Sanders, Pearson Inc., USA.

Journals

  • Supply Chain Management: An International Journal (Available on
  • Supply Chain Management Review
  • Purchasing World
  • International Journal of Purchasing and Materials Management
  • International Journal of Physical Distribution & Logistics Management
  1. Tentative Session Plan:

Session No. / Topics / Remarks / Pre-readings
1 / Introduction; Role and importance of supply chain analyticsin descriptive to prescriptive domain
2 / Concepts and decision domains of supply chain analytics including multi-objective decision making / R1
3,4 / Advanced methods of demand forecasting (Time series analysis & projection – Box-Jenkins; Causal method – Life cycle analysis) / R2
5,6 / Inventory management with repairs items and returns products / components / R3
7,8 / Network design and optimisation with integrative modelling of forward and reverse logistics / R4
9 / Multi-objective planning for supply chain with Analytics software / C1
10 / Group work presentation

R1 –Supply chain analytics – G C Souza, KSB

R2 – Competing on analytics with external processes – SRM & CRM

R3 - An advanced heuristic for multiple-option spare parts procurement after end-of-production; Inderfurth, K., and Kleber, R. (2013); Production and Operations Management.

R4- An Integrated Forward/Reverse Logistics Network Optimization Model for Multi-Stage Capacitated Supply Chain, Scientific Research iBusiness.

C1 – GT Nexus Leader in cloud computing supply chain management

Group Work

Practical / Application oriented: Applying or evaluating the concepts and tools learnt in the course to a real-life situation in production and operations management area of a company, and then reporting your findings to the class.
  1. Evaluation: (Total of 100%)
  1. Quiz1(Individual, online): 20 %
  2. Class participation and attendance : 15 %
  3. GroupWork: 25 %
  4. Final exam (hard copy) (All inclusive) : 40 %
  1. Other remarks
  1. Come to class on time.
  1. Cell phones should remain switched off during the entire duration of the class and should be kept inside your bag and not on the table. Any student found keeping mobile phone on the table will be marked absent for the day.
  1. No request will be entertained to change the class project, once finalized by the group, and intimated to the instructor.
  1. Absence fromany on-line quiz is strongly discouraged.
  1. Academic Integrity: Utmost care is taken as to maintain class decorum, follow the exact evaluation norms, conduct fair examinations, fair and transparent evaluation of examination papers so as to maintain the highest academic integrity.

Secretary: ……..Saliyamma Xavier; Extn: 899

Prof. Arun Paul/OSCA/Jan 2017Page 1