Group assignment briefing microsite

Modernize one HRM practice at Orion Solidified Apparel Limited.

You are acting as Orion’s HRM department. Your task is to select one strategic HRM pain point, use the provided n8n automation package, evaluate the AI-assisted output, and present a practical recommendation to the board.

Choose your HRM scenario See what your group must do
Your main responsibility: HRM judgement, not technical coding.
Use only: Synthetic case data supplied for the assignment.
Remember: AI output is a draft, not a final HR decision.

The case company

Orion Solidified Apparel Limited

Orion Solidified Apparel Limited is a hypothetical apparel manufacturer operating in the Southern Province of Sri Lanka. It has a main factory near Galle/Koggala and a smaller production unit near Matara.

The company has grown quickly, but many HR practices remain manual. HR relies heavily on Google Sheets, paper records, supervisor messages, and informal follow-ups. Buyers are asking for stronger delivery reliability, better quality, and clearer social-compliance evidence.

The board has asked HR to modernize one HRM practice through a focused 90-day pilot using low-cost digital tools, AI-assisted analysis, and evidence-based HRM thinking.

Current pressure points

  • Rising production pressure and delivery deadlines
  • Absenteeism and retention concerns
  • Incomplete training and skills records
  • Unstructured employee complaints and voice channels
  • Questions about fairness in incentives and performance management

Choose one route

Five HRM modernization scenarios

Each group selects one scenario. The provided n8n workflow will use the scenario you choose to generate a first-draft HRM analysis and recommendation.

Scenario 1

Recruitment and workforce planning

The company struggles to recruit enough sewing machine operators and junior supervisors before peak production cycles.

Pain point

Recruitment is reactive, vacancy approval is late, and new employees often leave within the first few months.

Strategic HRM question

How can Orion build a more reliable workforce planning and recruitment process?

Workflow will generate

    Your group should decide

    Whether Orion should prioritize external recruitment, internal promotion, realistic job previews, school partnerships, or employee referrals.

    The technology support

    How the plug-and-play workflow helps your group

    You are not expected to design the workflow. You will use the provided automation as an HR decision-support tool, then apply your own judgement.

    1Google Form or Sheet intake
    2n8n scenario analyzer
    3Tavily evidence search
    4OpenRouter GPT-5.4-mini analysis
    5Google Docs draft report

    Google Drive, Sheets and Docs

    Stores the case inputs, group intake details, generated report, and evidence appendix links.

    n8n

    Connects the assignment data, selected scenario, AI analysis, search evidence, and output document.

    Tavily

    Finds a small number of external sources to support HRM benchmarking and evidence-based recommendations.

    OpenRouter GPT-5.4-mini

    Generates the initial HRM diagnosis, risks, intervention options, KPIs, and draft implementation plan.

    Student process

    What your group must do

    Use this checklist to stay on track. Your browser will remember the items you tick on this device.

    0% complete

    Ten-person group structure

    Suggested group roles

    Each role has a narrow responsibility so that everyone contributes without turning the assignment into a technical project.

    01

    HR Director / Coordinator

    Coordinates the group and leads the board-style presentation.

    02

    HR Strategy Lead

    Connects the chosen issue to strategic HRM theory.

    03

    Case Data Analyst

    Reviews the synthetic HR data and identifies patterns.

    04

    Workflow Operator

    Runs the provided workflow and captures evidence screenshots.

    05

    AI Output Reviewer

    Challenges weak, generic, or unsupported AI suggestions.

    06

    Employee Voice Lead

    Checks fairness, worker experience, and communication quality.

    07

    Compliance and Ethics Lead

    Reviews privacy, bias, human oversight, and responsible AI use.

    08

    Implementation Planner

    Builds the practical 90-day pilot plan.

    09

    KPI and Finance Lead

    Defines success measures and resource implications.

    10

    Report Editor / Presenter

    Improves the memo structure and supports presentation delivery.

    Final submission

    Deliverables

    Your generated Google Doc is a starting point. The final submission must show your group’s judgement, not a copy of the AI output.

    1. Group HRM modernization memo

    1,200–1,500 words. Diagnose the problem, use case evidence, critique the AI output, and present your improved recommendation.

    2. Workflow evidence appendix

    3–5 screenshots showing the intake row, workflow success, results sheet, generated Google Doc link, and external evidence list.

    3. Group presentation

    5 minutes, followed by Q&A. Present the HRM problem, workflow insight, your recommendation, risks, and KPIs.

    4. Individual reflection

    500–700 words explaining your role, contribution, HRM learning, and what you learned about using AI responsibly in HRM.

    Assessment weighting

    How the assignment is weighted

    The group component rewards HRM diagnosis, evidence use, AI critique, and realistic implementation. The individual component rewards personal contribution and reflection.

    75%

    Group activity

    • 13% HRM problem diagnosis
    • 13% Use of case data and workflow output
    • 17% Strategic HRM recommendation
    • 12% Implementation plan and KPIs
    • 10% Critical evaluation of AI output
    • 7% Ethics, fairness, privacy, and human oversight
    • 3% Presentation and Q&A
    25%

    Individual reflection

    • 7% Role and contribution
    • 7% HRM learning
    • 7% AI and n8n usefulness and limitations
    • 4% Honesty, specificity, and clarity of writing

    Responsible AI in HRM

    Rules for ethical use

    HRM decisions affect people. Treat the workflow as a support tool, not an authority. Your recommendation must protect fairness, privacy, worker voice, and human judgement.

    Use synthetic data only.Do not upload real employee records, real grievances, real CVs, NIC numbers, phone numbers, or medical details.
    Do not automate employment decisions.No hiring, rejection, dismissal, discipline, pay, or promotion decision should be based only on AI output.
    Challenge the AI output.Identify unsupported assumptions, missing worker perspectives, bias risks, and unrealistic suggestions.
    Keep human review central.Your final recommendation must include HR review, supervisor consultation, and employee voice where relevant.

    Questions students usually ask

    FAQ

    Do we need to build the n8n workflow?

    No. The workflow is provided. Your group uses it as a plug-and-play HRM analysis tool.

    Can we simply submit the AI-generated Google Doc?

    No. The generated document is a draft. Your final memo must evaluate, correct, and improve the AI output using HRM theory, case evidence, and your group’s judgement.

    Can we choose more than one scenario?

    No. Choose one scenario and analyze it properly. A focused recommendation is better than a broad but shallow answer.

    Can we use real company data?

    No. Use only the synthetic data supplied for the assignment. This protects privacy and keeps the activity fair for all groups.

    What should our presentation sound like?

    Speak as Orion’s HRM department presenting to senior management: concise, evidence-based, practical, and ethically careful.

    Ready to begin?

    Start by reading the case, choosing one HRM scenario, assigning roles, and preparing your group intake row.