MBA Project and Consultancy Module Introductory Notes

Module Overview and Objectives

• Context and Significance: The MBA Project and Consultancy module serves as the cornerstone project of the entire MBA journey. It represents a 30-credit weighted component, meaning it has a significant impact on final degree classification.

• Primary Objective: The purpose is to provide hands-on experience in managing consultancy and real-world projects. Students act as consultants to solve a specific problem or issue facing a real organization.

• Student Agency: Students are given the autonomy to write their own assignment questions and briefs. The expectation is that if a student can define the question, they can generate plausible solutions.

• Management Context Requirements: Regardless of the industry (e.g., geology, clinical work), the project must be framed within a management context. This includes themes such as:

  • Strategy

  • Leadership

  • Logistics and operations management

  • Change management

Key Deadlines and Administrative Milestones

• Data Capture Form Submission ($June\,4$): This form identifies the general topic and preferred methodology (quantitative, qualitative, or mixed). It is used to pair the student with a supervisor based on industry and methodological expertise.

• Proposal and Ethics Form ($July\,9$): Students work with their assigned supervisor to refine their project goals. High approval rates are common, though some may receive a "pass and proceed" with minor revisions required for aims and objectives.

• Final Assessment Deadline ($September\,10$): This is the hard deadline for the final report or presentation recording. It is recommended to leave at least 3 weeks for writing and formatting prior to this date.

Selecting and Scoping a Research Topic

• Access to Organizations: Students must secure written permission from an organization. This is crucial for primary data collection (interviews, surveys).

• Ideal Topic Characteristics:

  • Exploratory and Open-Ended: Avoid topics that can be answered with a simple "yes" or "no."

  • Engaging and Relevant: The speaker recommends topics like AI (Artificial Intelligence) and its operationalization in the workplace, as these are trending/cutting-edge.

  • Feasible Scope: A project that is too broad cannot be finished by the deadline; a project that is too narrow will not meet the learning competencies.

• Project Refinement: It can take several weeks to refine an idea from a vague interest into a practical research question. Students should use mind-mapping and brainstorming techniques during this phase.

Assessment Options and Requirements

Students must choose one of the following two formats for their final assessment:

• Option 1: Written Project Report:

  • Length: $8,000$ to $10,000\,\text{words}$.

  • Style: Follows a traditional dissertation or thesis format.

• Option 2: Recorded Consultancy Presentation:

  • Duration: $30\,\text{minutes}$.

  • Format: A recorded video (e.g., via Microsoft Teams) where the student presents slides as if speaking to a client board of directors.

  • Advantages: The presenter notes that students often score higher on video presentations because they demonstrate active consultancy skills and specific communication techniques that written reports allow students to repeat unnecessarily.

Quantitative versus Qualitative Methodologies

• Quantitative Data:

  • Nature: Objective, measurable, and factual.

  • Example: Analyzing birth rates in Hull using secondary data from councils or sending out anonymous surveys using QR codes to younger demographics.

  • Tools: Often used by scientists or economists to make statistical decisions.

• Qualitative Data:

  • Nature: Subjective, open-ended, and narrative-based.

  • Example: Conducting focus groups with mixed genders to discuss challenges related to population shifts. The researcher pulls themes from the resulting narrative.

  • The Researcher's Voice: In qualitative research, the researcher provides an "authentic voice" because they are central to the problem-solving process.

The Supervision Process and Relationship

• Role of the Supervisor: Experts are assigned to provide one-to-one guidance. They have approximately $6\,\text{hours}$ of time dedicated to each student.

• Student Responsibility: Students must proactively manage the relationship. This involves:

  • Discussing availability and holiday commitments.

  • Establishing expectations for meetings (e.g., submitting word counts or sections of work before the meeting).

  • Seeking motivation and guidance on data analysis.

• Engagement Warning: Students are cautioned against ignoring their supervisor until the week before submission; supervisors generally refuse to review an entire document at the last minute.

Practical Consultancy Framework

• Consultancy Stages:

  1. Diagnosis: Asking many questions to clarify the problem (the "Doctor" metaphor).

  2. Analysis: Using tools and frameworks to analyze the situation.

  3. Choice Identification: Providing options for the client.

  4. Recommendations: Directing the client toward a specific path forward.

• Scoping Implementation: Consultancy usually involves diagnosis and recommendation. Implementation plans should be minimalistic or phased out separately to ensure the project is achievable by $September\,10$ and to avoid giving away too much free work.

• Case Study Example: Pace Farm Mill (Australia):

  • Project Title: Optimization of Supply Chain Resilience in the Milling Industry of Australia.

  • Objectives:

    1. Identify risks and vulnerabilities in the current supply chain via literature review and stakeholder data.

    2. Analyze current resilience strategies and compare them to industry benchmarks.

    3. Evaluate performance under disruptive scenarios.

    4. Recommend practical, cost-effective strategies for implementation.

Questions & Discussion

• Confidentiality (Duane): Duane asked if confidentiality agreements (NDAs) are possible for sensitive energy sector data. The speaker confirmed that standard NDAs with the university are available, but highly classified data (e.g., state secrets) should be avoided in favor of a different topic.

• Industrial Supervisors (Duane): Duane inquired if a company-side supervisor can be involved. The speaker agreed this is allowed to ensure the project meets company perspectives.

• External Stakeholders (Richard): Richard discussed a digital transformation strategy for a shareholder. The speaker advised focusing on designing the strategy/change management rather than implementation. She suggested interviewing CEOs, department heads, and even end-customers, and mentioned that LinkedIn is a viable tool for finding contacts for benchmarking.

• Final Presentation to Company (Charlotte): Charlotte asked if presenting to the real company is required. The speaker noted it is not required for the module, but is highly encouraged for personal career development and traction within the organization.

• Anonymous Data and Fictionalization (Scott): Scott expressed concern that his company might be nervous about their name appearing even with an NDA. The speaker clarified that students can fictionalize the company name (e.g., "Company X") as long as the primary data collected is real.

• Methodological Distinctions (Shouta): Shouta asked about the difference between Change Management and Decision Making in the topic form. The speaker explained that Decision Making focuses on systems-based models, while Change Management focuses on process, resistance, and levers of change.

Common Pitfalls and Success Factors

• Self-Plagiarism: Using significant portions of previous MBA assignments is considered a plagiarism offense.

• Descriptive vs. Evaluative Writing: Students at the MBA level must move beyond describing what they did; they must critically evaluate tools, acknowledge their shortcomings, and synthesize data.

• Referencing: All charts, graphs, and external sources must be meticulously referenced throughout the project.

• The "Lens" of the Researcher: The speaker used a metaphor about a bus traveling right or left (based on door location) and a story about her mother using coconut branches to ward off evil to illustrate that researchers bring cultural and experiential biases to their data analysis. Students must justify their perspective and be aware of how their "lens" affects their solutions.

• AI Integration: Students are encouraged to use AI tools like Copilot for refining aims, objectives, and literature themes, but must maintain clear boundaries to ensure the AI does not write the actual assessment.