Delivery Delay Histogram

This histogram groups late parcel deliveries by the number of hours past their promised arrival time. Most late parcels fall in the first two hours, and the frequency drops as delays become longer. That pattern helps an operations team separate a common small delay from a smaller group of severe exceptions. Use the same promise-time definition across all records and exclude canceled deliveries unless they are part of the question. The chart does not explain why parcels were late, so pair it with route, carrier, weather, and warehouse data when diagnosing causes. Keep the bins consistent when comparing different weeks or service regions.

類型 長條圖引擎 echarts-bar更新時間 2026/9/24

需求

“Create a histogram of 100 late parcels using 2-hour delay bins from 0 to 12 hours with frequencies 41, 28, 16, 9, 4, and 2.”

接著試試Add a bin for parcels delivered early.Change the 6–8 hour bin to 12 parcels.

這張圖裡有什麼

看懂背後的決策。

01Definition

Measure delay against the promised arrival time.

02Bins

Use equal two-hour intervals.

03Priority

Investigate the parcels delayed more than six hours.

Use this histogram to understand the spread of late-delivery exceptions across a delivery operation.

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常見問題

What is a delivery-delay histogram?

It groups deliveries by how late they arrived so the distribution of delays is visible.

Why not use only average delay?

An average can hide whether most delays are small or whether a few severe cases are pulling it upward.

Can I compare two delivery regions?

Yes, if both use the same delay definition, period, and bin ranges.