Wednesday, April 02, 2025
Date: 2nd April 2025 to 12th April 2025
Time: 10 am to 5 pm
Venue: Classroom
Resource Person: Mr. Vishal Thelkar
Participants: PGDM Students
Faculty Coordinator: Mr. Ganesh Pathak
Organizer: Center for Learning and Development, DYPBS
Objectives:
1. To introduce students to the fundamental concepts of Decision Science and its relevance in managerial decision-making.
2. To enable participants to apply quantitative techniques to analyse complex business problems.
3. To enhance problem-solving abilities using tools like Excel Solver, Decision Trees, and Linear Programming.
4. To provide practical exposure to decision-making models through case studies and simulations.
5. To develop critical thinking and data-driven decision-making skills for real-world business scenarios.
A comprehensive session on Decision Science was organized from 2nd April to 12th April 2025, aimed at equipping PGDM students with analytical tools and decision-making frameworks essential in today’s data-centric business environment. Conducted by Mr. Vishal Thelkar, the session was structured to bridge the gap between theoretical knowledge and practical application.
Workshop Highlights:
Week 1: Foundations of Decision Science
The first week laid the theoretical groundwork by exploring decision-making processes in business environments. Mr. Thelkar introduced various decision-making models including rational, bounded rationality, and intuitive models. Emphasis was placed on the role of data in improving decision quality. Students explored basic statistical tools and their use in interpreting business data.
Week 2: Quantitative Tools and Practical Applications
During the second week, students were trained in quantitative decision-making techniques such as Linear Programming, Sensitivity Analysis, and Decision Trees. The sessions included hands-on exercises using Microsoft Excel and Solver to model and solve real-life business problems. Case-based learning and simulations helped students understand how to apply decision science in practical scenarios.
Key Takeaways
Understanding the role of data and logic in structured decision-making
Gaining hands-on experience with decision analysis tools and Excel functions
Applying quantitative methods to real-world business challenges
Developing a logical and evidence-based approach to management problems
Building skills in interpreting data and drawing actionable insights