Course TOD512 Decision Semester Winter Semester 2025
Science
Faculty Name(s) Subhankar Saha Contact subhankar.saha@ahduni.edu.in
School AMSOM Credits 1.5
GER Category: Not Applicable Teaching Pedagogy P/NP Course: Can not be taken as
Enable:NO P/NP
Schedule
Section 1 11:00 am to 12:30 pm Wed 06-01-25 to 28-02-25
11:00 am to 12:30 pm Mon 06-01-25 to 28-02-25
Section 2 11:00 am to 12:30 pm Tue 06-01-25 to 28-02-25
11:00 am to 12:30 pm Thu 06-01-25 to 28-02-25
Prerequisite TOD501 Introductory Statistics/TOD501 Descriptive and Inferential Statistics
Antirequisite TOD212 Decision Sciences
Corequisite Not Applicable
Course Description Everyone makes decisions but very few think of building a method to their decision making.
The course is designed to help students understand how to make better decisions. The
course brings in the concepts of management science with the intention of helping
students achieve better clarity in their decision making by understanding available
information and the choices therein.
The course aims to help students understand data better and apply logical and solid
methodologies to arrive at the best possible decision given the information available.
Course Objectives i. To introduce the students to mathematical and statistical methods to analyzing data and
making better decisions.
ii. To inculcate in students a data driven approach to decision making
iii. To build conXdence & comfort in students to work with data and appreciate the value of
using data to make better decisions.
Learning Outcomes At the end of this course, students will be able to:
• Students will be able to make better decisions with limited information
• Students will be proXcient with techniques such as optimisation, forecasting, simulations
to model business data and make decisions based on those models.
• Students will be able to use MS Excel and its data analysis add-ins to analyse data & make
better business decisions.
Pedagogy • All sessions will be hands-on - students (in groups of max 4 members) working along with
the faculty in solving business problems.
• Sessions will be based around a particular exercise or case as mentioned in the session
plan.
• Each session will be based around solving the business problem as mentioned in the
session plan; theories, tools & techniques used to solve the problem will be elaborated as
part of solving the problem at hand.
Expectation From • Attend all the classes and do the assignments
Students • Carry their laptop with all requisite software installed to every session.
• Display curiosity, a willingness to work hard and a commitment to learn & improve
• Students are expected to have installed MS Excel version 2013 or above on their
computers.
• Students will be guided to install other open source software required for the course.
Assessment/Evaluation Mid-Semester Examination:
Assignments - 30%
End Semester Examination:
Written - 30%
Other Components:
Case Analysis - 20%
Quiz - 10%
Class participation (Including attendance) - 10%
Attendance Policy As per Ahmedabad University Policy.
• Students are expected to be present for all sessions barring extraordinary circumstances;
• Students can be marked absent for a session if unprepared for the session
Project / Assignment • Class Participation (10%)
Details • Case Analysis (20%)
• Assignments (30%)
• Quiz (10%)
• End-Semester (30%)
1. Exercises at the end of every Topic
2. Assignment to be submitted at the end of every topic
3. Simulation Exercise/Quizzes Conducted in-class
Course Material Text Book(s)
An Introduction to Management Science – Quantitative Approaches to Decision
Making, Anderson Sweeney, Williams, Martin, Thirteenth edition Edition, Cengage
Learning,
Business Analytics, James Evans, Third edition Edition, Pearson Education,
Reference Book
Operations Research, Hamdy Taha, Ninth edition Edition, Pearson,
Introduction to Management Science – A Modeling and Case Studies Approach with
spreadsheets, Fredrick Hillier, Mark Hillier, Third Edition Edition, McGraw Hill
Companies,
Managerial Decision Modelling with Spreadsheets, Balakrishnan, Render, Stair, Third
Edition Edition, Pearson,
Additional Information 1. Course Pack with all exercises, cases & connected datasets mentioned in the session
plan will be shared with students.
Reference Books:
1. Business Analytics, 2nd Edition, James Evans, Pearson
2. Introduction to Operations Research, 10th Edition(SIE), Hiller, Lieberman, Nag & Basu,
Mcgraw Hill
Session Plan
N TOPIC TITLE TOPIC & SUBTOPIC DETAILS READINGS,CASES,ET ACTIVITIES IMPORT
O. C. ANT
DATES
1 Knowing the Forecasting with Time series & Exercise: Sales Case Discussion &
future Regressions; Moving averages & Forecast/ Case: Problem Solving
Exponential smoothing Happy Cow Ice
Cream
2 Knowing the Forecasting with Time series & Exercise: Sales Case Discussion &
future Regressions; Moving averages & Forecast/ Case: Problem Solving
Exponential smoothing Happy Cow Ice
Cream
3 Building Single Time period decisions; Exercise: Pricing Case Discussion &
Spreadsheets Multiple Time Period; decisions/ Staing Problem Solving
for Business Decisions
Decisions
4 Building What If Analysis; Scenario Exercise: Financial Case Discussion &
Spreadsheets Analysis; Goal Seek Statement Problem Solving
for Business Forecasting/ Case:
Decisions Toy world Inc.
5 Simulating the Monte Carlo Simulation Case: Netscape: Case Discussion &
Future Simulating Company Problem Solving
Valuation
6 Simulating the Simulation & risk analysis Exercise: Overbook Case Discussion &
Future model/ Cash Budget Problem Solving
model/ New Product
sales
7 Optimize your Linear Optimization & Sensitivity Case: Merton Truck Case Discussion &
decision Analysis Co Problem Solving
8 Optimize your Linear Optimization & Sensitivity Case: DHL Supply Case Discussion &
decision Analysis Chain & Swiss Milk Problem Solving
9 Optimize your Linear Optimization & Sensitivity Exercise: Assest Case Discussion &
decision Analysis allocation/ Problem Solving
Production
Planning/ Product
Mix
10 Analyse your Decision Tree & Decision Exercise: Goferbroke Case Discussion &
decision Strategy Problem Solving
11 Analyse your Value of Information Case: Express Bike Case Discussion &
decision works Problem Solving
12 Analyse your Bayesian Decision Analysis Case: Ratnagiri Case Discussion &
decision Alphonso Orchard Problem Solving
13 Trial Your Overview Data Analytics Online simulation
knowledge Simulation Exercise
14 Review
15 End Term
Exam
