Matias Honorato (left), supply chain and logistics data analyst at Beetrack, a provider of package tracking software based in Chile, presents the company’s findings on research conducted into the trends of failed deliveries in South America
Failed deliveries have an impact on several areas of the supply chain, namely customer satisfaction, delivery cost and delivery performance. Beetrack has always placed a special emphasis on customer satisfaction, as we strongly believe that, within the transportation industry, drivers are the new brand ambassadors in customer-facing situations. But while the customer satisfaction impact of a failed delivery can be estimated at best, determining the financial value of a failed delivery within the operational area is straightforward.
Each failed delivery attempt adds extra costs to the total delivery chain. These additional costs include added transport costs, re-delivery time, and additional handling at the warehouse or storage area in the event of failed second delivery. If the package fails permanently, further costs are incurred by returning it to the sender. Customer support services also add further costs.
Blackbay, a provider of mobility enabled solutions for the transport and logistics sector, estimated that failed first-time delivery attempts in the UK during 2013 cost US$1.1bn, while, at the same time, the online retail market in the country reached roughly US$119bn in sales. Looking beyond the UK alone, worldwide internet retail sales for 2016 are forecast to reach more than US$2tn. Going on theses figures, the cost of failed deliveries worldwide may very well be in the range of tens of billions.
What we have learned from our data
We analyzed failed delivery records from our database to understand when they occur, and what patterns can be seen. Our information is mainly from the South American market, which should be taken into account when comparing with the USA, Europe or Asia. Nevertheless, the correlations we identified validate worldwide trends and give us some insights into where optimizations can be made.
The analysis focused on e-commerce deliveries across three separate months that vary widely in terms of consumer behavior: we selected December, a high shopping season, February, a holiday season, and April, a regular activity month.
We analyzed more than half a million deliveries made in South America across the three selected months, with twice as many deliveries made in December and April when compared with February.
Next, we looked at the relevancy and consistency of the data. Before drawing any conclusions, we wanted to check the percentage of deliveries made every hour is similar across each month.
In terms of the percentage of deliveries, we found the only notable difference was between the hours of 9:00am and 10:00am in December and February. Apart from that exception, the majority of deliveries remain consistent in terms of distribution across the period.
We then found that, regardless of the increase or decrease in total volume, there is little change in the monthly patterns for failed deliveries across the three months. The percentage of failed deliveries across the day remains consistent, and variations between different months are minimum. Looking at this data, we can draw a few conclusions with regard to failed delivery behavior and best delivery times.
What do the failed delivery KPIs show?
Failed deliveries can occur for several reasons, such as a wrong address; the driver not knowing the geographical area and street distribution; maps not being updated; or the end customer not waiting for a delayed delivery.
Building KPIs and tracking the different failure reasons separately can provide insights into how to improve the delivery process. Data validation, for example, is a major problem for US businesses, costing an estimated US$611bn every year in postage, printing and staff overheads. We do not have enough data for Latin America regarding data validation but hopefully, as more companies start managing their KPIs and deliveries, we will be able to calculate the cost of incorrect data.
Having said this, the results of the failed delivery KPIs reveal the following:
• Delivering before 10:00am can significantly improve delivery rates.
• Deliveries made between 10:00am and 7:00pm show a similar rate of delivery failure.
• Delivering after 7:00pm doubles the risk of a failed delivery compared with working hours and is five times more likely to fail when compared with early mornings.
The results showed that there is a higher potential to successfully deliver during morning times meaning that, unless we are dealing with a same-day delivery scenario, having a flexible delivery fleet focused on morning schedules, especially during high shopping seasons, can help carriers to control costs.
To read more on Beetrack’s white paper on understanding failed deliveries click here.
Images courtesy of Beetrack.
August 3, 2016