The latest Eye on the Last Mile report shows how the merging of previously separate concerns requires a more integrated response across our operations.
Written by Henrik Batallones
The last few years has seen massive shifts within last mile logistics in the Asia Pacific region. A deeper understanding of customer preferences and needs has led to new approaches to streamline costs and improve performance. The emergence of new technologies—and, importantly, the lower cost of entry for them—has made those approaches easier to implement, at least for the most part.
And, at least in the Philippines, the last mile does not just cover direct-to-customer deliveries typical of e-commerce. In our urban settings, with an explosion of new, smaller retail formats necessitating more frequent trips with smaller drop sizes, the impetus to ensure costs are optimal while keeping service levels high remains.
We had the privilege to witness the unveiling of the latest Eye on the Last Mile report, put together by solutions provider FarEye, during their Last Mile Leaders event in Bangkok, Thailand last May 21-22. The report—which is supported by the Supply Chain Management Association of the Philippines—illustrates the convergence of previously separate considerations in the last mile, and how artificial intelligence is being used to address these issues head-on without inflating costs.
While individual conditions among countries in the Asia-Pacific region are different, it’s worth noting that there are common concerns among the last mile players surveyed for the report: the complexity of physical supply chains, the fragmented nature of logistics ecosystems, and the enthusiastic adoption of AI in the quest for solutions to logistical bottlenecks.
The report was put together by surveying over 500 last mile providers in Southeast Asia, Australia and New Zealand, as well as adjacent markets. The full report is now available at lastmileleaders.com.
Cost complexities
The report finds that our cost-to-serve is rising—an average of 18.9% annually—but most don’t see where they are coming from, at least outside of obvious culprits such as fuel, labor and fleet maintenance, which remain key cost drivers.
The report asserts that a significant amount of costs come from operational inefficiencies that are not necessarily captured numbers-wise. Failed deliveries, rescheduled and re-attempted deliveries, invoice reconciliation and even inquiries from customers asking about their orders add up, and pricing models have not kept up with evolving complexities on the ground.
75% of those surveyed consider inefficient routing as a major bottleneck, even higher than driver availability and real-time visibility. This changes the question from a matter of capacity and availability to a matter of whether there is enough flexibility within the system to better optimize operations across the last mile network.
Predictability over speed
Perhaps surprisingly, speed is no longer the top thing customers ask of last mile providers, according to the report—but predictability. 38% of respondents seek predictable delivery times, while just 24% seek low-cost deliveries, and 22% seek fastest possible deliveries. Also interestingly, 60% of surveyed operators say their customers are willing to pay extra for predictable delivery—for example, paying for delivery to be made within a particular date and time window.
This shifts the onus even further to last mile providers, especially those seeking to differentiate themselves in an increasingly competitive market. Can they build and manage systems that allow customers to specify their preferred delivery windows and provide visibility (preferably in real time) every step of the way? Can these systems devise routes that hit those delivery windows considering external factors like weather, traffic and driver availability? Perhaps, can the customer then reschedule the delivery to a later date, and the system adapt to it with as little internal disruption as possible?
Striking a balance
Despite the seeming shift towards behind-the-scenes technologies, the transport fleet remains an important component in realizing these changes in the last mile. Even here, operators have talked about a shift in how they manage their fleet. The traditional thinking—of owning your entire fleet for greater control, or outsourcing your entire fleet for flexibility—is giving way to a hybrid model of sorts.
The report states 62% of operators are primarily running on outsourced transport networks, with 27% running their own fleets, and just 7% relying on gig fleets. The direction of travel is firmly on outsourcing, with 48% of operators planning to expand their fleets in this way in the next five years. Perhaps more critically, half of those surveyed plan to deepen their relationships with their carriers.
These closer relationships would help address the greater demand for flexibility and predictability from customers, potentially improving operator visibility—the most-cited operational bottleneck, according to the report—as well as audit and reconciliation and carrier performance.
AI in the equation
For last mile providers in the Asia Pacific region, artificial intelligence has long been part of the equation, with 78% of surveyed firms saying it now plays a role in routing, dispatching, carrier selection and ETA prediction. 43% of them are in the early stages of implementation, while 20% are still exploring, and 22% have yet to start on their AI journey.
Interestingly, lack of trust barely figures as a barrier to AI adoption, according to the report. (98.3% of respondents have said they trust AI to make the right decision.) Most concerns lie in whether the organization is prepared to make the transition, with 27% citing complexity of the integration process; 20% citing lack of internal expertise, and 18% citing poor quality of data.
In addition, whether companies have worked with AI the longest or have yet to get going, most have expressed an intention to invest in delivery technology in the next year.
Where should we go next?
With these insights at hand, the question is: what’s our travel of direction? Obviously, towards satisfying our end customers, which means further leveraging available technologies and partnerships to get there. But here, the implementation may differ, depending on many factors, some of which are outside of our control: limitations on infrastructure; inaccuracies in address data; increasing fuel and transport costs, especially with the current geopolitical picture; and the overall maturity of the organization to take the next step in transforming their last mile networks.
The report concludes with a Delivery Maturity Index, which can help gauge an organization’s preparedness to leap further into deeper integration of technology.. Two factors are at play: whether the right data is visible across the operation, and who (or what) makes the decisions across the network.
In an ideal world, the report sees an adaptive last mile network, where AI drives real-time orchestration (and, in some cases, executes autonomously) dependent on real-time demand and capacity. Teams would be tasked with defining the perimeters in which the system makes decisions, rather than running it directly.
Could this work in the Philippines? Overall, our ecosystem may not be there yet. One last mile provider may be ready, but other elements—government regulators, for instance, who determine whether travel is allowed through certain avenues in certain circumstances—may not be plugged in, and may not be willing to plug in. In addition, the workforce’s current orientation towards tasks may signify an unpreparedness towards a new AI-led paradigm.
If anything, the shifting nature of customer demands—and the availability of more tools at hand to meet them more efficiently—means it’s up to us to work even closer with our partners to find the right solutions that fit our customers’ needs, as well as our bottom line’s.