Introduction
Festive season is the most important period of the year for Bajaj Finance's consumer durable business. Diwali week alone can account for a large share of the quarter's TV, refrigerator, and smartphone loans. So when a dashboard shows that consumer durable loans disbursed at partner stores in Maharashtra are down 15% week-over-week during Diwali week, while the rest of India is flat, it gets leadership's attention fast.
The question: diagnose the drop. I'll clarify the metric, rule out external factors, map the journey, break down the metric, prioritise data, form hypotheses, find the root cause, validate it, and propose a fix.
Clarify, rule out the obvious, understand the journey, break the metric into a funnel, then test hypotheses from most to least likely.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Each points to a different part of the system. Expected answer: Disbursals are down 15%. Applications are down only 3%. Impact on approach: The problem sits between application and disbursal.
Why it matters: Diwali timing shifts each year. Expected answer: Both. Versus the same festive week last year, Maharashtra is down 12% while other states are up 8%. Impact on approach: Seasonality alone cannot explain it.
Expected answer: It's concentrated in large-format chains and in smartphones and TVs; small stores are less affected. Impact on approach: Look at what differs between chains and small stores.
Expected answer: A new version of the representative's sales app went live in Maharashtra and Gujarat ten days ago. A risk policy update on new-to-credit customers went national two weeks ago. Impact on approach: Two strong candidates, one regional and one national.
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