Data Optimization

Overview

Data Optimization: Linear programming, sensitivity analysis, and decision-making introduce learners to practical optimization techniques that help businesses make smarter, data-driven decisions.

The course covers linear programming, sensitivity analysis, transportation, assignment problems, and decision theory. Learners will understand how to optimize resources, production, costs, and distribution, and evaluate ‘what-if’ scenarios as business conditions change.

Using practical business situations, the course helps learners move from identifying a problem → building an optimization model → finding the best solution → analysing changes → making informed decisions.

By the end of the course, learners will have a structured framework for approaching complex business problems analytically and using optimization techniques to support better decision-making.

Key highlights

• Operations research: Build data-driven decision-making skills.
• Linear programming: Optimize resources, costs, and profits.
• Sensitivity analysis: Assess the impact of changing business conditions.
• Excel Solver: Interpret key optimization and sensitivity results.
• Transportation and assignment: Solve logistics and resource allocation problems.
• Decision theory: Make informed decisions under uncertainty.
• Practical applications: Learn through real-world business scenarios.

Objectives

By the end of the course, learners will be able to:

• Understand operations research and optimization for business decisions.
• Formulate and solve linear programming problems (LPP).
• Apply sensitivity analysis and Excel Solver to evaluate changing conditions.
• Solve transportation, transhipment, and assignment problems.
• Apply decision theory, decision trees, and expected monetary value (EMV) for uncertain situations.
• Interpret optimization results and make data-driven business decisions.

USPs

• From data to decisions: Turn data into actionable business decisions.
• Practical and industry-relevant: Learn through real-world business scenarios.
• What-if analysis: Understand the impact of changing business conditions.
• End-to-end learning: From problem formulation to optimization and decision-making.
• Excel Solver focus: Gain practical exposure to Solver and sensitivity reports.
• Multiple applications: Linear programming, sensitivity analysis, transportation, assignment, and decision theory.
• Managerial focus: Connect analytical results with practical business decisions.
• Cross-functional skills: Applicable across operations, supply chain, finance, analytics, and management.

Who can attend

MBA and management students, business/data analysts, operations and supply chain professionals, managers, consultants, entrepreneurs, and anyone interested in optimization and data-driven decision-making.

Application process

• Register on the course platform.
• Receive confirmation and login details by email.
• Start learning on the learning management system (LMS) and complete the weekly activities.

Certificate

Receive a digital certificate of completion once you meet the course completion requirements, such as completing quizzes and assignments, and any required participation.

Fees

Enrol in the first module for free. You will need to pay to move to Module 2.