BUSINESS ANALYTICS IN SERVICES - 2022/3

Module Overview

Corporations, governments, entrepreneurs, and various organisations around the world are using data to extract patterns and generate insights to support strategic decision making and create innovative solutions to business problems. This module will equip students with the fundamental concepts and tools needed to understand the emerging role of business analytics in service organisations and shows students how to apply business analytics tools and to communicate with industry professionals to effectively use and interpret analytic models and results for making better business decisions. Emphasis is placed on applications, concepts, and interpretation of results, rather than theory and calculations. Students will use a computer software package for data analysis and presentation.

Module provider

Hospitality & Tourism Management

Module Leader

PEREIRA DOEL Pablo (Hosp & Tour)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

Indicative content:

• Overview of data-driven decision making and business analytics


• Introduction to Excel and Tableau


• Managing different types of data: data sources, data classification, data quality, and dealing with missing data


• Fundamentals of descriptive analytics and applications of managerial statistical tools


• Fundamentals of predictive analytics and applications of forecasting and extrapolation


• Fundamental of prescriptive analytics and applications of simulation


• Data visualisation and interpreting insights from graphs, charts, tables, etc.


• Creating business intelligence dashboard using Tableau

Assessment pattern

Alternative Assessment

The group assignment will be replaced with a Business Intelligence Dashboard with Tableau (individual)

Assessment Strategy

The assessment strategy is designed to enable Students to demonstrate their ability to gather and analyse data for business insights to support organisational decision making in the services sector. Students will be required to show that they have both the relevant analytical and diagnostic tools and appropriate methodologies to manage data and suggest recommendations and solutions. In addition, the assessment strategy will enable students to recognise that they are building up their knowledge and understanding about trends and developments in the industry and demonstrate how a manager can respond to these developments by making sense of patterns extracted from big data. 

Thus, the summative assessment for this module consists of: 

• Students will form a group to work on a dataset to identify business insights to solve specific business problems for a service organisation(s). Each group  may use the datasets provided in the module or self source the datasets from other secondary sources. The Students will need to identify variables from the datasets to analyse using Tableau. The group will use appropriate data analysis and visualisation techniques and must include both descriptive and predictive analytics in the project. Each group will produce a business intelligence dashboard (digital, on Tableau platform) to inform strategic decision making for the organisation(s). Each Student will submit a 5-slide deck to summarise their own understanding on the key findings from the business intelligence dashboard and propose recommendations for the organisation(s) and/or the industry. The slide deck will be designed for posting online on a website or professional networking sites (such as LinkedIn) and thus informative and easy to understand. Individual learning e-portfolio (Individual)


• Strategic Business Intelligence Summary, 5 slides (Individual)


• Students will be required to critically reflect on and evaluate their own learning throughout the semester project (business intelligence dashboard) and how this informs their professional practice and/or their enterprising, leadership, social responsibility, and global outlook. Students will be required to produce a critical reflection of their own learning through the submission and delivery of a podcast or a video lasting no more than 10 minutes or less. Formative assessment Students will be required to contribute to moderated discussion forums and seminars to demonstrate the development of their knowledge and mastery of the academic research as well as demonstrate awareness of current industry trends.

• During the first tutorial, the assignments and the feedback process is explained;  


• Feedback is also provided during and after in-class discussions/guided activities; 


• As the tutorials and activities are built around topic-specific exercises in a group setting, students do not only benefit from lecturer feedback but also receive peer evaluations;


• A pre-assignment feedback session where students will be given feedback on the progress of their project; Once marking is completed, students are provided with feedback, which contains detailed generic feedback as well as a breakdown of marks. This enables students to assess their own performance compared to their peers.

Module aims

• This module aims to introduce business analytics process, including the framing of business and analytics problems, working with different types of data, methodological selection, and business intelligence reporting, in the context of organisational decision making and problem solving within the services sector, including hospitality, tourism, transport, and events.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to provide students with an overview of business intelligence and data analytics, covering the key areas of data-driven decisions, business process improvement, and business problem solving. The foundations of business analytics will be supplemented with practical projects using an analytical software package to input and analyse data and generate and interpret insights for managerial decision making. The module will focus on providing students with a combination of the necessary conceptual knowledge and practical skills to make critical and strategic business decisions in a global context, with an emphasis on business sustainability in the services sector, including hospitality, tourism, transport, and events. 

The learning and teaching methods include: 

• Foundational lectures with supporting materials on big data, business analytics, business intelligence, and decision making in the context of services, including hospitality, tourism, transport, and events


• In-class exercises, practical examples and case studies, and tutorials in a computer lab to apply knowledge and analytical skills to real-world issues and datasets


• A project in which students extract patterns from big data and interpret the results to generate business solutions through a business intelligence dashboard


• Data analytics coaching sessions


• Supporting guest lecture sessions


• Formative feedback sessions


• Independent learning through reading, practicing with the software, collaborative activities, and research associated with the assessments

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MANM516

Other information

This module adopts the University curriculum framework, which aims to develop learners with strong capabilities in Digital Capabilities, Employability, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. 

This module contributes to the development of the following capabilities: 

• Digital Capabilities: This module focuses on developing students capabilities in analysing data and capturing business insights for managerial decision making. Students will develop their skills in using descriptive, predictive, and prescriptive analytics and data visualisation. They will learn how to use a software to create business analytics dashboard. Students will use the virtual learning environment (VLE), SurreyLearn, video conferencing platforms such as Zoom and Microsoft Teams, and data analytics software to facilitate learning. These include accessing teaching and learning materials and engaging with their instructors and peers. Module assessments require students to work collaboratively with peers to analyse datasets using a software, Tableau, and to create a dashboard to present insights from the datasets. 
• Employability: The assessments in this module require students to extract business insights from big datasets and to create a dashboard, using Tableau, to present the managerial implications of these insights. These business analytics and data-driven decision making skills will prepare students to be successful managers in the digital age. 
• Global and Cultural Capabilities: Students will learn how to interpret results of business analytics and their implications to service business in a global context by extracting, comparing, and contrasting individual and group behaviours, as well as sectoral, national, and regional differences captured from big datasets. Sustainability: Students will learn how to reflect on how to interpret business intelligence to support sustainability in the services industry. Resourcefulness and Resilience: Students will be required to use a range of sources to identify relevant datasets, conduct independent research, network with relevant companies/organisations, and work collaboratively with peers to extract patterns and critical insights from datasets. Finding solutions through unstructured problems is the key learning aspect of this module that will develop students resourcefulness and resilience.

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.