• This module will teach methods for collecting data, how to conduct quantitative analysis and translate the outcomes into actionable insights that might inform business decision making, resource allocation and investment choices.
• You’ll consider a range of data from market, financial and customer analysis to operational performance factors, and learn how to present information in accessible formats for different audiences.

Class aims

This class introduces students to business intelligence and business/data analytics from the perspective of a general manager, as tools that can be used by managers/leaders to drive evidence-based operational and strategic decision-making in a modern workplace. Analytics as a business concept resonates with the organisational management theme of Digitalisation & Technology. Additionally, analytics is a key management tool to drive effective strategies in Innovation, Adaptability, Resilience and Sustainability. Analytics is also a key management technique pertinent to effective and efficient day-to-day management and strategic change.

Learning outcomes

a. subject specific knowledge and skills

• Critique the potential value and practical challenges to managers regarding data and analytics, including around increasing volumes of data, increasing availability of related technology, and increasing expectations from both internal and external customers/end users
• Identify and appraise analytical approaches to support evidence-based decision making in a variety of organisational situations
• Use and critique visualisations of analysis to deliver business intelligence insights
• Create business intelligence insights via a transparent and reliable application of analytical methods for decisions facing uncertainty
• Create business intelligence insights via a transparent and reliable application of analytical methods for decisions facing trade-offs

b. cognitive abilities and non-subject specific skills

• To read and appraise articles and reports which contain numerical results and analysis
• To write about modelling and data/statistical analysis in a coherent manner
• To think critically, especially in the presence of numerical information
• To improve team-working skills through group work
• To reflect upon the role of analytical methods within the context of professional practice