Identify the Scope and Timing:

Was this increase gradual or did it occur suddenly? Is the problem only occurring in Gurugram, or are there other regions experiencing similar increases?

Examine Internal Factors:

1. Operational issues: Check if there are any recent changes or issues in our warehousing, inventory management, or delivery personnel in Gurugram.
2. Technical issues: Analyze if there have been any bugs or system glitches in our order management system or delivery routing algorithm that could be causing delays.
3. Changes in policies or procedures: Assess if there have been any recent changes to the delivery or operational policies that might have inadvertently affected the delivery times.

Review External Factors:

1. Regulations and Policies: Check for any new local regulations, roadworks, or policies in Gurugram that may be impacting delivery times.
2. Market dynamics: Consider market-level dynamics, like strikes, festivals, local events, or even competitor actions that could be influencing our delivery times.

Analyze relational KPIs:

Look into related metrics like number of orders, customer complaints about delivery, return rates, etc. This could provide additional insights into the problem.

Engage cross-functional teams:

Engage with teams that could provide relevant insights - the ground operations team could provide details on what they're seeing on the ground, while the tech team could check for any system issues.

Develop hypotheses and validate:

Based on the information gathered, develop hypotheses about potential root causes of the problem and devise ways to validate these. This might involve data analysis, field visits, discussions with delivery personnel, etc.

Plan and act:

Once the root cause(s) is identified, work on devising a plan to mitigate it. This could involve fixing technical issues, training delivery personnel, adjusting operational procedures, communicating with customers, or working with local authorities.

Monitor and Iterate:

Once the changes are implemented, continue to monitor the metric and iterate on the solutions as necessary until the delivery times come back to normal.

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