Current 2016/17 Module Catalogue

Module Details

Module Code:
MANM302
Module Provider:
Surrey Business School
Level:
M
Number of Credits:
15
Module Title:
INFORMATION FOR DECISION MAKING
Module Co-ordinator:
FAKHIMI M Dr (SBS)
 
 
ECTS Credits
7.5

Module Availability

Semester 2

Assessment Pattern

Assessment TypeUnit of AssessmentWeighting %
CourseworkSmall Group Project (3000 Words)60
Examination2 Hour Examination (Closed Book)40

Module Overview

The module introduces the foundations of knowledge management, epistemology and semantic analyses as sources of business value. The module covers topics and problems associated with the role and responsibilities of knowledge workers in the age of ‘Big data’. It deals the use of data sources to identify, capture, create, and distribute organizational knowledge. It seeks to develop students’ abilities to identify the existing epistemological foundations (semantic relationships) and build additional understanding from the data sources available to a company. It also teaches the use of decision making tools and skills to formulated ideas and knowledge structures in order to propose initiatives which facilitate future value creation. The module emphasizes the building and evaluation of emergent models as an alternative decision-making approach to the established and widely used traditional key performance metrics from econometric and financial analyses.

Prerequisites/Co-requisites

None

Module Aims

The module is structured in three broad segments. The first segment provides an introduction to the topic space related to knowledge management and its role in supporting value creation for the company. The second segment introduces methodologies for exploring diverse data content, developing knowledge ontologies. In this segment students are introduced to several software packages that are used to classify, explore and develop understanding of inherent (non-obvious) relationships in data blocks/stores. The third segment of the module looks at approaches and methods that support the evaluation and refinement of the initiatives identified by the analyses.

Learning Outcomes

On successful completion of this module, students will be able to:

  • High quality evaluation of the literature dealing with the role of knowledge in creating business value (inherent in the module concepts) (C&K)
  • Ability to apply the concepts in the module towards the analysis of the specific functions and activities related to the building of knowledge and management of knowledge assets in the business organization (understand the knowledge function), (K&P)
  • Demonstrate the ability to work with sources of data in order to successfully Identify, analyse, apply viable mechanisms for knowledge building for the company (develop knowledge projects), (T&P)
  • Show proof of critical understanding of the benefits and recognize the inherent shortcomings of ICT use in knowledge projects (pros/cons in use of ICT tools),(K&P)
  • Formulate business development initiatives from knowledge projects (actionable plans), (C,K,T&P) (requires all of the previous outcomes)

Key: C-Cognitive/Analytical; K-Subject Knowledge; T-Transferable Skills; P- Professional/ Practical skills

Module Content

Indicative content includes:

  • Knowledge, knowledge work the business organization
  • Analysing knowledge needs and using advanced ICT for managing organizational knowledge
  • The knowledge-based view of the firm and long-term building of business value
  •  Intellectual Structures of the Analytics Solution
  • Using Semantic analysis for the development of knowledge ontologies
  • Applying Ontologies in the study of large semi-structured data repositories
  • Simulation and modelling for Decision Making

Methods of Teaching/Learning

The learning and teaching strategy is designed to:

Total student learning time 150 hours. 

The module will be made up of regular weekly lectures, which will introduce the topics, concepts, and relevant issues and problems. Students will be expected to have read the papers assigned for the specific week's lecture in order facilitate their understanding of the lecture and the overall mastering of the material.

In the second part of the semester the lectures will also include demonstration of ICT tools and how they are used in the development of organizational knowledge. Students are expected to use those tools outside of the class sessions in order to improve their ability to work with them (specifically in light of the completion of the project assessment work)

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate

  1. Individual/Small group Project:

Student teams will be given a case study that they will use in order to explore and develop a report using the analytics concepts and tools taught in the lectures. (maximum word count 3,000 words)

       2.  Written Exam:

The written examination will be in two parts. The first part will evaluate students’ understanding of the concepts, terms and topics taught in the module. The second part of the exam will provide a short case study text which the students should use to answer problem solving questions related to the text and information provided

The assessments are designed to evaluate students capabilities and knowledge in three domains:

  •  First the understanding of the material and ability to meaningfully apply the concepts and terms in the module content. This is practically exercised in the project work and then evaluated in the written exam.
  • Second, is the ability to work with analytical software in order to develop insights and understanding into the provided data. In their project work students will have to successfully use analytical software in the creation of the project deliverable. Students will also be asked software specific questions in the written exam to ensure they can demonstrate understanding.
  • The third and final aspect is the ability to explain the implications of the results that were generated. A required part of the project write up will include the interpretation of the results in order to recognize the role of reification and black-boxing in modern day knowledge-based work and avoid garbage-in, garbage-out thinking.

Thus, the summative assessment for this module consists of:

  • Group project which formulates the decision space for an analytics problem. Demonstrates students’ ability to work with the material in the module and produce analytical outputs.
  • Written exam which evaluates basic knowledge and understanding of the module terminology.

Formative assessment and feedback

  • Ongoing participation in the class discussion of academic papers. Lectures in this module are not transmission based, but operate on a Learning Space model (see Kolb 1984) which is possible due to relatively small class size.
  • One week of teaching time in the module will be set aside to discuss the development of the group project.
  • Students will receive written comments in the submitted projects.
  • Students will receive written comments on their exam papers.
  • Continous open door policy – meeting with module convenor to discuss module material and project development.

Module Hours

Lecture Hours:24

Lab Hours:9

Reading List

MANM302: INFORMATION FOR DECISION MAKING

Last Updated

11 July 2016 by LIONS S Miss (Student Serv)