Skip to main content

Predictive and Prescriptive Decision-Making


  • Credit value: 15 credits at Level 7
  • Convenor and tutor: to be confirmed
  • Assessment: a 4000-word report (100%)

Module description

Organisations have access to large amounts of data, for example on customer behaviour. The translation of this data into evidence-based decisions to shape organisational strategy and policy is therefore critical. This requires managers to be able to understand and interpret data. This module builds on the principle concepts and techniques of data analytics that will be taught on the Data Analytics using R module to provide you with tools and techniques that can be used to make decisions.

Indicative module syllabus

  • Data-driven decision-making
  • Behavioural aspects of decision-making
  • Decision models and probability
  • Predictive modelling
  • Bayesian decision models
  • Simulations, e.g. Monte Carlo
  • Collaborative human and machine decision-making
  • Automated machine learning (AML) - DataRobot or H2O
  • AI (intro only)
  • Time series/forecasting

Learning objectives

By the end of this module, you will have:

  • in-depth knowledge and understanding of the role of business analytics in solving complex organisational problems and supporting strategic decision-making
  • acquired, organised, synthesised and analysed large data sets to generate insight that supports organisational decision-making
  • the knowledge and skills to evaluate the relevance, reliability and validity of large datasets
  • an understanding of the application of data analytics, statistics and forecasting techniques and tools to support decision-making.