Studies consistently show that delivering on time is important. It’s important to your customers, who will vote with their dollars if they don’t get the right order at the right time for them—and it’s important operationally: if your drivers are always running behind, sticking to a plan becomes impossible and endless rework ensues.
And yet, a meaningful percentage of deliveries still manage to arrive late. Sure, there are plenty of cases where there's nothing you as the delivery organization can do about it: unexpected traffic jams, freak weather events, truck breakdowns. But sometimes you’re in a position to make sure that the delivery arrives on time and operational factors hold you back.
In this article, we’ll go over what some of those factors might be and how to deal with them with the right techniques, tools, and technology.
How to Calculate Your On-Time Delivery Rate
You can’t optimize what you can’t measure. That’s why step one to boosting your on-time delivery (OTD) rate is to calculate what it actually is.
The formula for this is pretty simple:
- The total number of deliveries that arrived on time
- Divided by the total number of deliveries carried out
Once you’ve got this number for a particular period, you can establish a baseline and track your improvement over time. If you’re having trouble getting this data, then you’ve potentially got another issue that needs to be solved before you can address: last mile visibility.
You can check out our recent article for a guide on how to achieve a level of strategic visibility in the last mile that will enable you to set the right KPIs, establish benchmarks, and track your progress over time.
What Causes Late Deliveries?
Reasonable expectations for on-time deliveries are going to differ somewhat depending on your industry and your business. But for use cases where you’re scheduling a specific time that your customer can expect you, you really want your OTD numbers to be in the 90s if possible.
If you’re not in that range, there are a handful of reasons that might be the case:
- Unrealistic route expectations: You might feel like your fleet should be able to complete a certain number of stops per route—but if your drivers are always running late, you may not be setting them up for success by providing routes that are actually doable. This may be a matter of having unrealistic expectations for how many stops a driver can complete in a day, or it could be a matter of not providing the most efficient sequences of stops from the perspective of drive time and distance.
- Not factoring in differences in service time: If your teams are doing different kinds of jobs over the course of their routes (e.g. a mix of over-the-threshold deliveries and installations), the amount of time they spend on site will be extremely variable from stop to stop. If you’re not accounting for those differences in service time when you establish ETAs for your routes, you run the risk that someone expecting a delivery right after a complex installation process gets their order much later than expected. Obviously this can have cascade effects impacting the rest of the route as well.
- Not factoring in drive time differences between vehicle types: The most frequent culprit here is not factoring in the differences in speed between cars and trucks—this is the sort of thing that crops up if you’re using Google Maps or another light route planner that is designed for last mile deliveries. An experienced route planner might be able to eyeball the difference to some extent and make adjustments accordingly, but on some level you need to factor this in if you don’t want to make unreasonable demands on your drivers.
- Not factoring in differences in drive time between drivers: Not all drivers will be able to complete their routes at the same speed. This means that there’s a risk that you give your slower drivers more stops on a given route than they can actually complete, and they get progressively later as the day goes on. This is the sort of thing that you can do more effectively if you track driver performance over time.
- Not effectively predicting traffic conditions: There’s nothing you can do about freak traffic incidents—if there’s a highway pileup that’s backed up traffic for miles, the only thing you can do is send a communications blast to all your impacted customers. But there are instances where traffic shouldn’t be a surprise. If you’re trying to get from Manhattan to Long Island around rush hour, you should expect the drive time to be double what it usually would and factor that time into your ETAs accordingly.
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How Do You Ensure Consistent On-Time Delivery Performance?
None of the causes that we listed out above for poor on-time delivery rates are insurmountable. In fact, they often have the same root cause: lackluster route optimization.
If you’re planning routes by hand, finding the most efficient sequence of stops can be a significant challenge. From there, predicting ETAs (at least a scale larger than a couple of routes) can be a matter of guesswork. The result is often late deliveries and unhappy customers.
Even many legacy technology solutions fall down at these hurdles. You may not be able to configure the service time differences between different types of stops, or you may not be able to accurately deal with traffic and weather.
This flips on its head when you have the right solution. Route optimization software can help you ensure consistent on-time deliveries by giving you the flexibility to plan routes according to your needs while still enabling accurate delivery ETAs. Here’s the best routing solutions make that happen:
- Configurable service times: No one knows your operation better than your team. That’s why your routing solution should enable you to configure your service time expectations—both across delivery types and across delivery personnel—as needed.
- Continuous learning: The most impactful solutions on the market right now are leveraging AI and machine learning to improve delivery ETAs over time. They can turn your accumulated delivery data into increased accuracy and smarter performance, so that your delivery ETAs become much more precise and accurate than a human planner (or even most legacy solutions!) could hope to achieve.
- Integration with delivery execution: One of the biggest areas that can contribute to a low OTD rate is disconnect between what you expect of drivers and what they can actually perform. Even the smartest route planning solution is going to struggle to match expectations to reality if it’s not actually connected to your delivery route execution process. But when you have route planning and route execution within a single solution, you can create a feedback loop that improves performance over time.
Your ability to deliver on time is critical for winning and keeping business. It has a huge impact on customer satisfaction and on repeat buying, and it can even help you cut costs (i.e. through a reduction in unplanned returns and redelivery attempts). In that sense, it’s worth investing in getting it right. If you’re struggling to achieve the OTD numbers that you’re striving for, your first investment should probably be a smart delivery route optimization solution.