Introduction
The recent 20% increase in Otis's Gen2 elevator installation time over the last quarter is a significant concern that requires immediate attention. This issue not only impacts operational efficiency but also has potential ripple effects on customer satisfaction, project timelines, and overall company performance. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Seasonal changes could impact construction schedules and workforce availability. Expected answer: No significant correlation with seasons. Impact on approach: If seasonal, we'd focus on adaptive strategies; if not, we'd look deeper into internal factors.
Why it matters: Helps determine if this is a systemic issue or localized to certain regions or project types. Expected answer: Varied impact across regions, with some showing more significant delays. Impact on approach: If localized, we'd focus on region-specific factors; if global, we'd investigate company-wide changes.
Why it matters: Recent changes could directly impact installation times. Expected answer: Minor updates to safety protocols were implemented. Impact on approach: If changes occurred, we'd scrutinize their impact; if not, we'd look at other factors like training or supply chain.
Why it matters: Changes in personnel could affect efficiency and expertise levels. Expected answer: Some natural turnover, but no major shifts. Impact on approach: High turnover would lead us to focus on training and retention; stability would point us towards other factors.
Why it matters: Ensures we're comparing apples to apples and not dealing with a data anomaly. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd need to reassess the data; if consistent, we'd proceed with our analysis of actual installation times.
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