Measuring on-time delivery performance is crucial for shippers, and doing it right is essential. As Peter Drucker famously said, “If you can’t measure it, you can’t improve it.” Unfortunately, many shippers either lack the necessary data to assess their delivery performance or are unsure how to proceed. What’s more, even when they measure on-time performance, they doubt the results due to poor data quality. Worse, even if they do measure on-time delivery accurately, many shippers struggle with conducting root cause analysis to take corrective actions.

In this article, we’ll look at the common pitfalls in measuring on-time delivery (OTD) performance. While it may seem straightforward, there are numerous traps that can lead to inaccurate measurements and misleading results. Join me as I detail the five best data analytics practices to accurately measure on-time delivery. More importantly, I’ll show you how to use this data to identify the root causes of delivery failures and implement effective corrective actions.

Common Mistakes When Measuring eCommerce On Time Delivery.

First, the best way to measure on-time delivery is to use key performance indicators (KPI). Indeed, on-time delivery KPIs are crucial metrics for measuring and evaluating the efficiency and effectiveness of a company’s ecommerce delivery process. For a detailed explanation of different types of On-Time Delivery KPIs, see my article, Click here.

Moreover, measuring on-time delivery performance is not easy. This is because of many factors to include determining what to measure and getting access to the data you need. As a result, it is easy to make mistakes. Below is a list of common mistakes when measuring on-time delivery.

Common Mistakes When Measuring On-Time Delivery

Measuring On-Time Delivery: 9 Mistakes You Want To Avoid For More Reliable Delivery Results

• a. Relying On Shipment Status That Is Inaccurate Or Lacks Detail Scans.
• b. Relying On Incomplete Tracking Data.
• c. Measuring On-Time Delivery Against The Wrong Promised Date.
• d. Incorrectly Measuring On-Time Delivery.
• e. Neglecting To Consider The Time To Process, Pick, & Pack An Order.
• f. Not Balancing Costs And Setting Too High Of An On-Time Delivery Standard.
• g. Skew Measurements To Make The Operations Look Good.
• h. Too Focused On Collecting Carrier Service Refunds Versus Improving Performance.
• i. Blindly Measuring Performance Because the Boss Told You To Do It.

For a detailed discussion of these mistakes, see my article, Measuring On-Time Delivery: 9 Mistakes You Want To Avoid For More Reliable Delivery Results.

Four Major Benefits Of Measuring Ecommerce On-Time Delivery Performance.

“If you can’t measure it, you can’t improve it”

Peter Drucker

Measuring ecommerce on-time delivery performance is crucial for businesses. In fact, improving your ecommerce delivery operation is the number one reason to measure OTD performance. This Key Performance Indicator (KPI) enables you to identify the root cause of delivery exceptions and to take corrective action. As a result of continuous operations improvement, the following benefits will occur.

Benefits Of Measuring And Optimizing Ecommerce On Time Delivery. 

1. Delight The Customer. When customers receive their orders on time, they are more likely to be pleased with their shopping experience and become repeat customers.
2. Brand Reputation. Late deliveries will damage a business’s reputation and lead to negative reviews and unfavorable word-of-mouth publicity.
3. Cost Savings. By improving on-time delivery performance, businesses avoid additional costs such as express shipping fees or refunds for dissatisfied customers.
4. Competitive Advantage. Lastly, in today’s competitive ecommerce landscape, businesses that offer fast, reliable delivery are more likely to attract and retain customers.

Five Data Analytics Practices for Best Measuring Ecommerce On Time Delivery.

Diagnostic Analytics For Agile Decision-Making: The Best Way For Businesses To Quickly Research Why Things Happened

Again, businesses can make a lot of mistakes when measuring on-time performance. The primary way to avoid mistakes in measuring OTD is through effective data analytics. First, you need to collect the right data that is both complete and accurate. Next, you need to measure the right data to both measure OTD performance and identify the root cause of a delivery failure. This is called diagnostic analytics where you find out the “why” behind the delivery failure. For more discussion, see my article, Diagnostic Analytics For Agile Decision-Making: The Best Way For Businesses To Quickly Research Why Things Happened.

When measuring OTD, the crucial data elements are dates: shipped, delivered, and promised. Below are some data analytics tips for measuring on time delivery performance and diagnosing the root cause of a delivery exception.

“When measuring OTD, the crucial data elements are dates: shipped, delivered, and promised. “

1. Date Shipped: Accurately Measuring It for On-Time Delivery.

90% of the time it is easy to determine the date shipped. The carrier provides a “hard” ship date – i.e. the date and time they picked up and took possession of the shipment. The other 10% of the time the date and time shipped are ambiguous.

For the other 10% of shipments, either the carrier or your shipping operation will provide bad ship date information. Specifically, the ship date will be missing or it will not be a “hard” ship date. To work around this for measuring On-Time Delivery (OTD), shippers can use an approximate ship date such as the Bill Of Lading (BOL) date or the electronic manifest date (when the shipping label was created). While these “soft” ship dates are better than nothing, they can skew OTD measurements. To ensure accuracy, it’s crucial to work with your logistics partners to obtain a “hard” ship date – the exact date and time the carrier took possession of the shipment. Without this, your OTD measurements are suspect.

“… work with your carrier and shipping operation to obtain a “hard” ship date – the exact date and time the carrier took possession of the shipment.”

2. Date Delivered: Need To Capture In Order to Measure On-Time Delivery.

This is usually fairly easy as most carriers provide a “hard” delivery date and time.The reason why most carriers’ delivery date data is reliable is because delivery drivers scan the shipment barcode at the point of delivery or they get a delivery signature, or a picture of the package as the proof of delivery (POD). Again, if you are not getting good delivery data, you need to invest the time and work with your delivery carriers to get this information.

3. Promised Delivery Date: This is Provided by the Shipper, Not the Carrier.

Determining the promised data can be tricky for many operations. If you have a mature ecommerce operation, normally the order fulfillment system generates the promised date and that date is provided to the end-customer. If you have a well run operation, this promised date in your order fulfillment system will match what the delivery carrier’s estimated delivery date is. Of note, the promised date can change if there is some type of order fulfillment or delivery exception.

Remember, the carrier’s promised date is not necessarily your company’s promised date. Hence, it is the ecommerce operation that is responsible for determining the promised date. Indeed, it is the shipper who can best determine the promised date balancing it against customer desires, cost efficiency, the competition, and what is achievable.

“… the carrier’s promised date is not necessarily your company’s promised date.”

4. Delivery Exceptions: Key to Capture These Events for Analysis to Identify Root Cause and Corrective Action.

Ecommerce Delivery Exception Mistakes To Avoid And How To Handle

Sometimes delivery or shipment exceptions are hard to measure. If either the shipper or the carrier has immature IT systems, these exceptions may either not get recorded, nor communicated to key stakeholders.

Also, delivery exceptions are often blamed on carriers, but surprisingly, they’re only responsible for about 50% of these issues. The remaining exceptions can be attributed to various factors, including business closures and weather conditions. Worse, the shipper may be the source of the delivery exceptions such as incorrect addresses or poorly prepared shipping labels. Without a doubt, understanding the root causes of delivery exceptions is crucial to mitigate their impact and improve overall shipping efficiency. For a detailed discussion on delivery exceptions, see my article, eCommerce Delivery Exception Mistakes To Avoid And How To Handle.

5. Order Fulfillment Click-To-Ship Analysis: Identify All Delivery Exceptions, Not Just Caused By the Carrier.

Shippers often blame carriers for delivery exceptions, but this isn’t always accurate. In fact as previously discussed, over half of these issues can be unrelated to the carrier such as your order fulfillment operations. Hence, to get a clear picture of delivery performance, it’s crucial to obtain comprehensive data from your order fulfillment system. For instance, this can include the initial delivery date promised to customers, order fulfillment duration, returned shipments, and other order defects like damages or incorrect picks. Without a doubt, you need to have information from your order fulfillment operations, to measure OTD effectively and take action to improve overall delivery performance and customer satisfaction.

More Resources for Measuring On-Time Performance.

For more information and viewpoints on measuring on time delivery performance, see these articles:

• Samir Saci’s article Logistic Performance Management Using Data Analytics
• Descartes’ Analytics For Improving Carrier and Supplier Performance
• VisualSouth’s How to Measure the On-Time Delivery KPI
• Stacey Barr’s How To Meaningfully Measure On Time Delivery Of Anything
• Also, for Measuring On-Time, In-Full, see this article, Establishing An OTIF Metric for Supply Chains: Practical Advice You Need To Know
• Lastly, for more information on OTD KPIs, see SC Tech Insights’ article, The Best On-Time Delivery KPIs To Make Your Customers Delighted.

The Best On-Time Delivery KPIs To Make Your Customers Delighted

Need help with an innovative solution to make your supply chain analytics actionable? I’m Randy McClure, and I’ve spent many years solving data analytics and visibility problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. If you’re ready to supercharge your analytics or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.

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