How to analyze delivery delays and find where operations break down

From the field · Logistics coordinator

Find the cause of late deliveries after a carrier change

On-time delivery falls after one region switches carriers. Warehouse dispatch is also delayed on Mondays, and several shipments have attempted-delivery events before completion.

Columns used in the example

shipment_id · service · route · carrier · promised_at · ready_at · dispatched_at · attempted_at · delivered_at · exception_code

Follow it with your own file

1. make consistent timestamps and apply service-level cutoff and business-day rules.
2. Construct ordered event timelines and flag missing or impossible sequences.
3. Measure ready-to-dispatch, transit-to-attempt, and attempt-to-delivery separately.
4. Compare carrier and route patterns while controlling for Monday dispatch and service mix.

Check: Shipment counts must reconcile to orders, open/cancelled populations must remain separate, and stage durations must use valid ordered events. Unattributed delay should remain visible.

What needs resolving first

A late final delivery can originate from warehouse dispatch, carrier transit, customs, address quality, weather, or an unsuccessful attempt. One final status cannot establish where the process failed.

Build the result step by step

1. Build event timelines: Order promised, ready, dispatched, hub, attempt, exception, and delivery timestamps by shipment.
2. Define eligible service: Document order cutoff, business days, service type, cancellation, and open-shipment treatment.
3. Calculate stage duration: Measure delay contribution only where adjacent timestamps and status evidence exist.
4. Prioritize routes and causes: Use shipment counts, severity, recurrence, carrier, route, product, and customer impact.

What changes the answer

• Order promised, ready, dispatched, hub, attempt, exception, and delivery timestamps by shipment.
• Document order cutoff, business days, service type, cancellation, and open-shipment treatment.
• Measure delay contribution only where adjacent timestamps and status evidence exist.
• Use shipment counts, severity, recurrence, carrier, route, product, and customer impact.

The final delay is the sum of operational stages

Breaking elapsed time into stages connects evidence to the owner who can act. It also prevents a carrier comparison from absorbing warehouse, customs, customer, or data-quality differences.

Where this usually goes wrong

Exception codes are not always independent evidence; they can be late, generic, or entered inconsistently. Validate with timestamps and source process before assigning blame.

Choose the approach that matches the evidence and repetition

Warning signs in the file

• Promised dates and timestamps use different zones or cutoff rules.
• Customer-not-home attempts count as carrier transit delay.
• Open shipments are treated as late deliveries before their due date.

Doing these steps in Prepyr

Prepyr accepts CSV files only. Export the worksheet or table you need as a UTF-8 CSV first; workbook formulas, formatting, macros, charts, and other sheets will not be included. Describe the result you need: Analyze logistics delivery delays and identify the responsible process stage. Check the columns selected, preview any proposed changes, and compare the output with the source before applying or exporting it.

Prepyr steps used here: Text analysis · Charts · Reports · Sensitive Column protection

Make the output easy to check

• Time zones and cutoffs aligned
• Shipment population defined
• Event order validated
• Stage durations reconciled
• Unattributed delay disclosed

Questions readers usually ask next

What denominator should on-time delivery use?

Use eligible completed or due shipments under the documented service promise, with open, cancelled, and excluded shipments shown separately.

Does an exception code prove the cause of delay?

Not alone. Check timing, event sequence, source quality, and operational evidence before attributing cause.