MANAGEMENT ANALYTICS
BACKGROUND INFORMATION
Introduction to Management Analytics
• Welcome and introduction
• Brief overview of management analytics
• Importance of analytics in business management
Module’s AIMS:
To provide students with major concepts, models, tools, and metrics used in management analytics
This module will facilitate better understanding of data. It also equips you with concrete skills you can apply in your organization’s decision-making.
Beginning with basic descriptive statistics and progressing to regression analysis, you’ll explore analytics through real-world examples in various managerial dimensions.
The role of Management Analytics
• Management analytics refers to the use of data analysis techniques to gain insights into business performance and inform. decision-making.
• It involves collecting and processing large volumes of data from various sources, such as customer transactions, website activity, and social media interactions.
• Management analytics can help organizations identify patterns and trends, uncover opportunities for growth, and mitigate risks.
• It requires a combination of technical skills in data analysis and management, as well as a strong understanding of business strategy and objectives.
• In the context of international business, management analytics can provide valuable insights into global market trends, consumer behavior, and competitive dynamics.
SYLLABUS
✓ Relationships Among Variables
✓ Probability and Distributions
✓ Hypothesis testing
✓ Regression Modelling
Learning Outcomes
Knowledge
1. the role played by management analytics in contemporary organisations;
2. how management analytics are conducted;
3. appropriate use of standards, methodologies and technologies employed in management analytics;
4. how the results from management analytics are used.
Skills
1. apply analytics techniques to decision problems that arise in management;
2. interpret and critically analyse data and information to solve problems and make informed decisions in management
Course Structure
▪ Lectures PLUS workshops ;
Workshops
Provide students with a structured opportunity to practice problems associated with materials discussed in the lecture.
Assessment Scheme
Assessment 1
First online quiz (15%): in Learning Week 6.
This assesses student’s understanding of descriptive analytics .
Assessment 2
Second online quiz (15%): Learning Week 12.
This assesses student’s understanding of regression modelling techniques.
Assessment 3
Groupwork-based assignment (3000 words , 70%): The assessment requires students to work in group to analyse practical management decisions, that discusses the modelling issues, the results, their implications and makes recommendations for improvement.
o The final grade for the module will be based on these three components.
o The passing grade is 16 (40%), taking three components together.