Apex Delivery Fleet Scenario
Updated: Sep 9
This project is a fully interactive branching scenario built in Articulate Storyline 360. It simulates a real‑world decision environment where a late‑shift operator must evaluate technical evidence, stakeholder input, and schedule pressure before authorizing a drone activation in unsafe cold‑weather conditions. The scenario is designed to assess decision‑making, evidence interpretation, and risk mitigation under stress.
Context and Learning Goal
Organizations often face decisions where technical warnings conflict with commercial pressure. The scenario trains learners to interpret technical evidence, prioritize mitigations, and avoid deferring responsibility without transferring situational awareness.
What I delivered
Realistic evidence artifacts (seal spec, test log, waiver).
Stakeholder selection, mitigation checklist, and decision capture.
JavaScript risk scoring and six outcome layers.
Reflection and takeaway slides tying decisions to real‑world lessons.
Design Approach
Learner persona: late‑shift operator with limited time and competing priorities.
Evidence design: actionable artifacts that provide information needed to make a safe decision.
Role‑based perspectives: simulate Engineer, CTO, and Safety Officer viewpoints to expose organizational constraints and trade‑offs.
Decision mechanics: single decision with a short rationale, three potential mitigations, and a computed risk score driving six outcome layers.
Learning Outcomes and Assessment
Measures whether learners act on evidence, apply mitigations, and communicate risk.
Outcomes map to real consequences: catastrophic failure, near miss, safe proceed, delay for testing, and escalation failure.
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