Think You Know the Best Way to Load a Truck or Container? Let’s Put Your Theory to the Test.

The new Zebra SmartPack™ “system of intelligence” uses machine learning and prescriptive analytics to eliminate blind spots in your loading operations and help increase shipping capacity, even when resources are scarce.

Two workers look at their rugged tablet screen as they stand outside dock doors
by S. David Silk
February 23, 2021

Historically, it has proven difficult to routinely load a trailer or container to maximum utilization given the quick turnaround time. Even unloading within an allotted amount of time can be a challenge if you don’t know how pallets or packages were loaded – and how many items are actually in there – until you open the door.  

Staff are often given a clipboard (or, if they’re lucky, a mobile computer) with instructions on what to do and when and then left to figure out how best to either make all the freight fit in the space or clear it all out within the allotted amount of time.

Loading operations, in particular, are kind of like playing a game of Tetris. Except, in this case, “points” are earned by stacking as many pallets and packages as possible into a trailer or container and ensuring there’s minimal space remaining when the timer buzzes. (No one wants to leave space underutilized.) And though supervisors may be nearby (also with a clipboard) to help coach the team along, even they are limited in their ability to influence the strategy employed come game time. Their understanding of what is happening inside the trailer or container is limited to what they can see or the information conveyed by the load teams. As a result, it can be difficult to influence the fill rate and wall height to meet fullness goals before the door closes.

When it comes to unloading a trailer, the supervisor might feel as though one person can handle an incoming shipment. But, once the truck pulls up, it could become clear that it is a full load and more resources are needed to turn that unit around on schedule. The problem is that, unless the supervisor actually sees that variance between planned and actual needs, that unloader might have to fly solo – and that could start a chain reaction of delays or force the next loading team to move even faster than planned.

That’s why Zebra first developed SmartPack™ a few years back. We wanted to eliminate those blind spots and give multiple stakeholders within transportation and logistics (T&L) organizations a way to gain complete, real-time situational awareness. You’ll be surprised at how much you can learn about your load operations, and how much you can improve them, when you have a clear view of every movement taken, every second and in every corner.

However, expanding one’s operational visibility is just the first step to improving workflow execution.

As I mentioned in my last blog post, you need empirical data to make informed decisions about your load operations, and you need it in real time. That’s why SmartPack has evolved into much more than just a video feed aggregator since its inception.

The Core Value of SmartPack: Driving T&L Beyond “Digitalization”

It’s important to create a digital “system of record” that can log loading actions in real time and serve as a single source of truth about what is or isn’t occurring across your operations. But it’s even more important to stand up a “system of engagement”.

Although knowledge is power, you won’t be able to drive meaningful improvements unless you understand why something is happening and exactly what they must do to address it. Moreover, you must be able to close the loop in order to benefit from these insights and maximize your return on investment (ROI). If you recognize that something is going awry during load workflows, or you see an opportunity to improve fill rate efficiency, utilization, or adherence to critical times, then you must be able to tell someone “on the inside” the next best step to take to either mitigate that issue or maximize the opportunity.

That’s why the second generation (and current state) of SmartPack is providing so much more value for action-driven supply chain organizations right now. In addition to capturing load operations from every vantage point, this system of engagement is also providing the metrics needed to optimize future operations.

Even though supervisors are still monitoring load operations from the sidelines, they’re finally in a position to act on what they’re seeing thanks to a host of machine and computer vision technologies that are now aggregating data about work in motion every 15 seconds and conducting some additional post-processing telemetry. They just have to login to the SmartPack dashboard to see “what happened” and determine “why it happened”. So, instead of simply choreographing workflows, supervisors and logistics managers can better assess how trends are unfolding without having to conduct a deep – or manual – analysis. This gives them an opportunity to revise strategies to achieve better outcomes in future workflows, which is the core value of SmartPack.

Incredible, right?! With demands on capacity continuing to grow, and showing no signs of slowing, any technology tool that can help supply chain organizations optimize their fill strategies, improve resource utilization and ship more goods with fewer trips are going to pay off.

However, even those who employ SmartPack as a system of engagement in the way I just described may find that they eventually hit a wall in value gains (no pun intended). That’s because a system of engagement is still heavily reliant on a human’s ability to spot an issue or opportunity and then make the right decision about how and when to address it. The problem is that no one person can keep an eye on all trailer loading stations or air cargo container unit load devices (ULD) within his or her purview, much less across an entire facility or region – even with the help of machine and computer vision systems and mobile devices. Could you simultaneously watch 12 video streams and not miss something?

That’s why we spent most of 2020 further developing SmartPack’s capabilities and refining new “premium value” for the SmartPack solution as a “system of intelligence”.

How We’re Leveraging Machine Learning and Prescriptive Analytics to Lighten the Load on Supervisors and Logistics Managers

We recognized that for T&L organizations to meet all of their goals, they would need a full-scale “system of intelligence” that automates much of the “coaching” role. So, we incorporated machine learning algorithms that automatically sense, analyze and act on both sudden and subtle issues in the load process that can impact fulfillment and compliance, such as fill rate inefficiencies or underutilization of trailers and containers. These algorithms are governed by a set of dynamic rules that use prescriptive analytics software to propose and support the execution actions to enhance outcomes.

Think of the loading and unloading workflows as a timeline of work activity that can be segmented into four contiguous durations, each with a critical time and/or work rate goal assigned to it.

If SmartPack recognizes that goals aren’t being met, then it will prompt immediate action by sending a real-time alert to the supervisor and or team via their mobile computers. The message will share what is exactly wrong – maybe the work activity is moving too slowly or walls of parcels are not being erected in a way that will allow target fullness by a specific time deadline to be achieved. Corrective action will also be communicated to get the work activities back on track.  If the corrective action repeatedly gets ignored by the team and/or supervisor, then the supervisor’s manager will be notified in an escalation alert to get the work activity back on track. The images show some of the visual alerts that loaders and supervisors may receive to help them actively coach their teams.

A side-by-side look at what supervisors and loading teams will receive from the SmartPack visual alerts

Look at How Dynamic Your Load Operations Can Become – and How Much Premium Value You Can Extract from SmartPack – When You Employ Dynamic Rules

With real-time performance insights and resolution recommendations now generated automatically in SmartPack – without any human mediation needed – the burden is no longer on supervisors to figure out what’s happening inside each trailer or container or why a load wasn’t in compliance with a service-level agreement (SLA). And the risk of someone making a “wrong decision” or delaying action is significantly reduced. The system of intelligence delivers decision support to the worker in order for that worker to make the best next action in the workflow.

In fact, two primary dynamic rules have been explicitly developed to help customers understand “what could happen” in any given situation and “what optimization actions must be taken” before, during and after a load to change or improve outcomes:

- The Load Predictor Dynamic Rule uses a combination of historical data, goal objectives and current resources to help you improve labor availability and refine your load strategy. For example, its common practice to build tall walls to maximize utilization within a trailer or container, yet higher walls do not automatically equal the desired utilization. Plus, this load method is more time and labor intensive and there is always a tipping point where returns will diminish. So, if COVID-19 social distancing mandates and reduced workforce levels only allow for one loader to be assigned to each dock, SmartPack may recommend that the loader build shorter walls to increase load fullness given the short turnaround period and limited labor capacity since building taller walls takes more time and, therefore, fewer walls would be erected. This is something that a dock supervisor may not have recognized without aggregate access to operational data and the ability to conduct a strategy analysis at a macro level.

- The Load Activity Dynamic Rule continuously tracks load progress and completion rates against critical workflow milestones to ensure activity starts and ends on time during each duration. If your load team is running behind schedule, it will let them know so that they can make adjustments and meet goals ahead of a deadline. If the team continues to fall behind, additional warnings will be sent, and alerts will be escalated to supervisors and their managers as needed. And though this rule is primarily focused on improving load teams’ immediate performance, it has the potential to inform future labor planning decisions. For example, you might be able to look at the historical data to see if labor is being properly allocated and utilized. If you want to minimize critical idle times or increase fill rate efficiency, especially during periods of high demand, it may become apparent that more resources must be assigned to a certain dock or ULD to ensure no pallet or package is left behind.

In other words, SmartPack’s new automated performance monitoring, analysis and coaching capabilities significantly lightens the cognitive load of logistics managers, dock door worker, loaders and unloaders. It also frees up valuable manpower to implement highly calculated changes that will help improve shipping outcomes. I know that’s something T&L organizations will appreciate given that there is no margin for error in today’s high-tempo environment.

But this new layer of premium value functionality does more than merely improve the management of labor skills at loading stations. It also helps users dramatically improve overall business performance by enabling T&L organizations to:

- Gamify their operations at a facility, regional or even global level – Because we can now aggregate the data collected at every load point into a centralized “system of record,” SmartPack customers (and even their customers) gain a holistic view of every action taken during both inbound and outbound logistics operations – much like an enterprise resource planning (ERP) or customer relationship management (CRM) system works today. This allows for a side-by-side comparison of all cross docks within a wing, facility or geography.

If one dock is turning around half-empty trailers on a consistent basis and the others are averaging a 90% fill, then supervisors can more closely assess load construction to see if that particular crew is properly balancing and stacking freight, or if there’s something that’s reducing the work rate.

- Manage expectations – Logistics managers can also leverage the contextual data available regarding the broader inbound and outbound logistics operation to see if the goals being set for certain docks, shipments or periods of time are too ambitious based on historical performance trends. If it’s determined that further training is needed to improve work rates and meet strict turnaround times, then the historical data and images will prove useful in identifying specific workflow deviations and addressing the issues that contributed to prolonged idle times.

- Increase accountability – SmartPack offers a before and after view of load fullness, freight conditions and more should there ever be question of non-compliance or loss by a customer or partner further down the distribution channel and an investigation be required to pinpoint liability.

- Develop and execute contingency plans – Some carriers will leave trailers at a customer site for the customer to load over a period of time (typically one week). However, they may have to recall the trailers sooner given an unforeseen change in schedules or demand. Other times, inclement weather may cause carriers to accelerate or delay deliveries. If a truck or aircraft is late or needs to pull away early for any reason, then shippers can notify customers and collaboratively adjust inbound and outbound schedules accordingly to ensure trailer/ container capacity and resources are still maximized and a ripple effect does not occur in the supply chain.

- Comply with strict environmental quality standards – Whether your company has committed to reducing its carbon footprint or you are bound by CO2 emissions rules set by a regulatory body in a particular region, SmartPack will empower you to ship more with fewer trucks and containers.

In other words, SmartPack can be a very transformative solution for supply chain organizations that need to better manage increased cargo volumes and meet service-level agreements in a rapidly-evolving, on-demand economy. And the two dynamic rules I described above are just the first of many premium value offerings to come. We have strengthened our core competency in machine and computer vision significantly in the past several months, and we’re continuously innovating on the SmartPack platform in collaboration with T&L customers to ensure it provides increased value as supply chain demands grow and evolve.

Do You See What They See? If Not, Let’s Change That.

With all eyes now on the transportation sector’s ability to fulfill demands, it’s critical that you get eyes inside your trailers and containers as soon as humanely possible. Workers simply don’t have the time to give you the play-by-play, and you can’t afford to hold a truck or aircraft a minute longer than scheduled. At the same time, you can’t afford for that trailer or container to be underutilized.

With the insights your logistics managers will yield via SmartPack, and the prescriptive guidance the intelligent system will provide, your workers need to know exactly how to pack pallets and packages into the trailer or container the moment that door opens.

Contact the Zebra team to learn more or to request a pilot of the SmartPack solution at your facility.

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S. David Silk
S. David “Dave” Silk is a strategically-driven senior products and technology executive with significant experience leading new product development, launching products and creating new market categories. He is known as an innovation thought leader for his rigorous, yet common sense, approach to technology and business. In his current role as Senior Product Management Lead, Growth and Product Innovation, Mr. Silk is focused on new product development as well as new business development for Zebra.