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Throughout the 2021-22 academic year, we will be prioritising face to face teaching as part of a blended learning approach that builds on the lessons learned over the course of the Coronavirus pandemic. Teaching will vary between online and on-campus delivery through the year, and you should read guidance from the academic department for details of how this will work for a particular module. You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.

WM9A5-15 Digital & Data Science Consultancy

Department
WMG
Level
Taught Postgraduate Level
Module leader
Liping Zheng
Credit value
15
Module duration
2 weeks
Assessment
Multiple
Study locations
  • University of Warwick main campus, Coventry Primary
  • Distance or Online Delivery
Introductory description

Digital and Data Science technologies have grown significantly in the last decade in terms of both organisational adoption and their importance to operational practices. Equally, however, such technologies have grown in complexity and sophistication. As a consequence, many organisations can struggle to identify the opportunities available to them through digitalisation and machine learning, and to effectively implement and optimise these solutions.

In such a climate, there is an increasing demand for eBusiness professionals who have both a thorough technical understanding of digital/data technology, and the ability to effectively communicate with key stakeholders to build comprehensive requirements and design successful implementations. These professionals can be external to the organisation (e.g. management consultancy firms), but there is also similar demand for staff to act as internal-consultants.

Module aims

The principal aim of the module is to give participants exposure to the varied workload and challenges associated with delivering digital and data science projects in the real world. Alongside the taught curricula, participants will engage in a hands-on simulation of a consultancy project to incorporate all of the key elements and milestones - from client requirements and requirements illication, through to data exploration and initially analyses, before delivering a final, full project plan and timeline.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

What is Digital & Data Science Consultancy?

  • Business Analysis and Requirements a. Business Analysis b. Systems Thinking c. Requirements Gathering and Elicitation

Project Scoping and Engagement Management

  • Project Scoping and Design
  • Project Management for Consultancy Projects
  • Digital Solutions for Consultancy Projects

Solution Design and Implementation

  • Determining the Problem/Solution Space
  • Decision Science & Multi-Criteria Decision Analysis
  • Data analysis and solution matching
  • Solution Implementation
  • Change Management

Capstone Project a. Industry Case Study b. Digital Consultancy Simulation c. Client Presentations

Learning outcomes

By the end of the module, students should be able to:

  • Demonstrate a comprehensive understanding of digital and data science consultancy concepts
  • Interpret and evaluate complex organisational problems and requirements
  • Critically analyse advanced data technologies and evaluate their suitability to specific use cases
  • Demonstrate a sound conceptual understanding of the forefront of digital & data science consultancy practice and their application in real-world scenarios
  • Critically evaluate the systematic and operational risks associated with digital transformations and develop comprehensive mitigation strategies
Indicative reading list

View reading list on Talis Aspire

Interdisciplinary

A mixture of technology/computing topics, statistics, and business topics

International

Topics are of high international demand

Subject specific skills

Digital transformation, multi-criteria decision analysis, soft systems and decision analysis, consultancy practice, project planning

Transferable skills

Consultancy skills, project management, communication skills, teamwork

Study time

Type Required
Lectures 14 sessions of 1 hour 30 minutes (14%)
Seminars 10 sessions of 1 hour 30 minutes (10%)
Practical classes 6 sessions of 1 hour 30 minutes (6%)
Assessment 105 hours (70%)
Total 150 hours
Private study description

No private study requirements defined for this module.

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Assessment group A
Weighting Study time
Retrospective 20% 30 hours

A presentation/demonstration of the achieved work and a reflection on the project plan and how it can be improved

Post Module Assingment 60% 45 hours

A business-style report discussing core topics in digital & data science and consultancy

Creation of online project tools 20% 30 hours

Development of online tools such as Kanban boards, wikis and similar to support the project plan

Assessment group R
Weighting Study time
Post Module Assingment 100%

A business-style report discussing core topics in digital & data science and consultancy

Feedback on assessment

Verbal feedback for in-module element. Written feedback and annotated scripts for post-module element

There is currently no information about the courses for which this module is core or optional.