UCL School of Management

Module Fact Sheet

MSIN0116: Decision Making and Analytics

Masters, level 7
MBA students only
Delivery method
For full-time students 8 x 3 hour sessions over two weeks. Part-time students 8 x 3 hour sessions over two weekends.
In-class test (3 hours)  30%
Group coursework 1 (case study) 20%
Group coursework 2 20%
Individual coursework 30%
Previous Module Code

Course overview

Since the building of explicit models for analysing decisions is an important task for every manager, the first part of the module will focus on different techniques used for this decision-making process. Sessions are devoted to modelling concepts that are applicable to a variety of different management situations. Modelling can be seen as a kind of art in which one needs to use one’s creativity, imagination and business understanding, the modeller also needs to have strong technical knowledge. The first part of the course brings a mix of the two and will focus on the different techniques that can be used in modelling.

The second part of the module investigates how leading companies are using data and analytics to improve their strategy processes as well as fundamental tenets of data and analytics. The second part of the module also exposes students to aspects of strategy that are tied to data and analytics.

Learning outcomes

After this module, the student should:

·         Understand the main concepts of deterministic modelling (linear and integer programming);

·         Be able to formulate a deterministic model in MS Excel and understand and interpret solution reports;

·         Comprehend the importance of (big) data and analytical skills for decision-making;

·         Be able to demonstrate the use of mathematical programming by means of some real-life problems;

·         Be able to link the modelling approach with the investigation of the managerial situation;

·         Be able to deal with uncertainty in the decision-making process;

·         Understand the importance of scenario analyses for making decisions (decision tree analysis and simulation); and

·         Understand the (often conflicting) relation between quantitative modelling and human behavior.

As well, upon successful completion of the module, students will be able to:

·         Understand how organisations create, deliver and capture value.

·         Understand the nine building blocks of a business model: Customer Segments; Value Propositions; Channels; Customer Relationships; Revenue Streams; Key Resources; Key Activities; Key Partnerships; and Cost Structure. 

·         Use the Business Model Canvas to describe the design of organisations and their business models.

·         Understand the range of business issues that organisations are addressing using business analytics.

·         Understand new business models enabled by data and analytics and how companies are using the “3P’s” —proprietary, public and purchased data—to create entirely new business models.

·         Understand the different types of decisions involved in business strategy development and execution, and their characteristics. 

·         Understand how organisations are using data and analytics to improve strategy decisions.

·         Understand how organisations are using analytics platforms and tools in their strategy process.

Assessment summary

In-class test (3 hours)  30% Group coursework 1 (case study) 20% Group coursework 2 20% Individual coursework 30%

Current students should refer to Moodle for specific details of the current year’s assessment.

Past versions of this module

MSIN0116 18/19

MSINGC01 17/18

Last updated Wednesday, 26 June 2019