Module: Operational Analytics

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Operational Analytics
Module Code	MNA1178
Faculty	DCU Business School	School	DCU Business School
NFQ level	9	Credit Rating	5

Description

This module introduces students to Management Science and mathematical modelling in the context of operations management, including familiarise students with decision making and problem solving using appropriate techniques and methods. There is a focus on transforming operational data into better decision making through the use of optimisation techniques, predicting outcomes and choosing the best course of action in the face of risk.

Learning Outcomes

1. Determine which quantitative analysis technique is appropriate for solving a specific problem
2. Use the appropriate quantitative method in a technically correct way to solve a business problem
3. Analyze quantitative output and arrive at a conclusion
4. Identify situations where mathematical models can help managers make better decisions
5. Describe and interpret a mathematical model, clarifying the underlying assumptions and the model’s limitations
6. Evaluate the application of a mathematical model, checking its correctness and its adequacy for the decision making problem to tackle

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	22	No Description
Assignment Completion	57	No Description
Independent Study	46	No Description
Total Workload: 125

Section Breakdown
CRN	21412	Part of Term	Semester 2
Coursework	0%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	Y
Resit Category	RC1	Best Mark	N
Module Co-ordinator		Module Teacher

Type	Description	% of total	Assessment Date
Assessment Breakdown
Assignment	Hands on mathematical modelling problem solving and decision making	30%	n/a
Report(s)	Individual report on a key topic in the area of management science	70%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Introduction to Management Science for Operations

Linear Programming Concepts

Linear Programming Formulation and Applications

Modelling with Spreadsheets

What-if Analysis

Indicative Reading List

Books:

Frederick S. Hillier, Mark S. Hillier: 2019, Introduction to Management Science: A Modelling and Case Studies Approach with Spreadsheets, 6th Edition, McGraw Hill, 1259918920
Frederick S. Hillier, Mark S. Hillier: 2023, Introduction to Management Science and Business Analytics, McGraw Hill, 1260716295

Articles:
None

Other Resources

None