Introduction:

Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. An important approach to enhancing competitiveness is recruiting skilful social capital i.e. staff who have good knowledge about the business and can work with data. Organisations need employees who can carry out data analysis and present and interpret the results in line with business needs. On the other hand, Higher Education Institutions strive to equip students and graduates with employability skills required for the new jobs in the age of data and analytics. To address this need, I have designed the following research programme to cater for 24 URSS projects.

Benefit for students:

• Gaining insights for the jobs of the future and planning for future readiness.
• Hands-on experience in working with data and an analytics project of interest in a supported way.
• Receiving comprehensive feedback and customized advice on Hard and Soft analytics skills in relation to employability.

This research programme aims:

• To establish students’ initial level of employability readiness and data orientation.
• To support students in carrying out Business Analytics projects using the CRISP-DP approach.
• To assess students’ areas of strength and weaknesses.
• To provide comprehensive written feedback on Hard Skills.
• To co-create approaches for Soft Skills improvement in a face-to-face meeting.
• To inform future research on employability skills development and curriculum based on the insights and feedback gathered in this research programme.

The research programme has 6 themes:

1. Visualisation Analytics
2. Operations Analytics
3. Marketing Analytics
4. Environmental Analytics
5. HR/People Analytics
6. Financial Analytics

Each theme has 4 defined research projects for interested students to select and carry out under my supervision. Questions and the Datasets for each student’s research project will be provided. Students should have a good Maths/Stats background and programming skills with Python. Familiarity with free Gen-AI tools and some machine-learning approaches would be beneficial. These projects are suitable for UG year 3 students.

Process:

The ethical procedure will be followed to adhere to the University of Warwick research regulations.

Stage 1: Diagnosis

In a meeting with each student I will establish students’ initial level of employability readiness and data orientation.

Stage 2: Planning

In a meeting with each student, I will provide research questions and the datasets and orient students to use the CRIPS-DM approach.

Stage 3: Implementation

In regular supervision meetings, I will guide the students to use available resources to study and carry out the Business analytics research projects.

Stage 4: Evaluation

Students' projects and results will be assessed to establish areas of strength and weaknesses. Comprehensive written feedback on Hard and Soft Skills will be provided, followed by a meeting to reflect, discuss and co-create approaches for skills improvement and connecting the dots.

Stage 5: Reflection and learning

The outcome of students’ achievements, will inform future research in terms of future projects as well as new curriculum development.

Contact

Please contact Dr Salimeh Pour Mohammad for further details.