Impact Analysis

Correct Answer: Analyze historical data patterns of similar supply chain events

When analyzing a sudden supply chain disruption, starting with historical data patterns of similar events is the most reliable approach because: 1. It provides real-world evidence of what has actually happened in similar situations 2. Historical patterns reveal both successful and failed mitigation strategies 3. Past data helps quantify the likely scope and duration of impacts 4. It offers concrete examples of recovery timelines and resource requirements The other options are less reliable starting points: Listing alternative suppliers is reactive and may not address root causes or broader implications. Financial calculations are premature before understanding the full scope of the disruption through historical analysis. Stakeholder feedback about schedule changes is too subjective and narrow in focus to serve as an initial analysis point for understanding the full range of potential impacts.

Correct Answer: Risk probability matrix with prioritized impact levels

A risk probability matrix with prioritized impact levels is the most valuable output for this situation because: 1. It helps quantify and visualize the potential consequences of the design flaw 2. It enables the team to assess both the likelihood and severity of the impact 3. It provides a structured approach to prioritize response actions 4. It facilitates decision-making regarding whether design changes are necessary Why other options are less suitable: Detailed documentation of manufacturing processes would be premature since the design flaw needs to be assessed first before determining process changes. Stakeholder engagement assessment would be a secondary concern after understanding the technical impact of the flaw. Resource allocation spreadsheets would only become relevant after determining the necessary corrective actions based on the risk assessment.

Correct Answer: Changes in process cycle time and throughput capacity

Changes in process cycle time and throughput capacity is the best metric because it measures actual operational performance and business impact. This metric provides quantifiable data about how the new system affects core business operations, showing real productivity changes and potential bottlenecks. Process cycle time and throughput directly relate to business efficiency and service delivery capabilities. Other options are less reliable indicators: The number of departments involved doesn't necessarily correlate with operational disruption - a change could affect few departments severely or many departments minimally. Financial cost variations mainly focus on implementation expenses rather than operational impact. Documentation updates are an administrative consideration but don't measure actual operational disruption to the business processes.