Are you running on empty? In the world of Supply Chain, this is pretty much a rhetorical question, in that “empty” most likely refers to “empty containers” and much of world’s trade does indeed run on their effective utilization.
In fact, when it comes to the logistics arms of Supply Chain, the efficient management of empty containers is instrumental in ensuring the smooth flow of goods across the globe. The repositioning of empty containers is a highly complex resource optimization problem that, when done correctly, goes a long way in reducing overall cost of Supply Chain Operation but, as in many other optimization problems, it comes with a series of constraints, trade-offs, costs, and challenges that make building sustainable and production-level solutions notoriously difficult to achieve.
Let’s start with the most obvious assertion: Every business in this day and age is a Data business, and Supply Chain businesses are no exception. Where does the relevant data come from (Veracity), how well data represents all relevant stakeholders’ challenges and objectives (Consistency) and how up to date the required data is (Relevancy) are only a few data-specific questions that are not answered satisfactorily within your Supply Chain unit of a typical modern-day enterprise. Needless to say, without getting the right and reliable data on time and at the right place, the question of optimization becomes rather irrelevant to start with!
When it comes to managing empty containers, who makes the decision? The Finance folks, the good guys in the Operations department, the Procurement chaps, your mama? Or is it all of them (with the exception of your mama, perhaps)?
The truth is that many stakeholders are involved in this and from that, it follows that effective communication and coordination become that much more critical for overall success. However, in reality, lack of/inefficient communication and coordination among diverse stakeholders further exacerbate the challenges of empty container repositioning.
And it is not always people, who are at fault. The presence of siloed internal solutions and the painful lack of standardized processes makes timely identification and relocation of empty containers ever more difficult and with that, comes the inevitable delays and missing opportunities.
Not every problem can be blamed on bad, incomplete, or inconsistent data. Insufficient infrastructure and resources can, and often do, lead to significant challenges in effective repositioning of empty containers. Complicated transportation networks, inadequate storage facilities, and many other physical constraints can severely restrict the capacity to redistribute empty containers efficiently, resulting in increased costs and operational bottlenecks.
Trade route imbalance represents one of the biggest (if not the biggest) challenges to repositioning of empty containers. Uneven flow of goods within the underlying trade network typically translates to surplus and shortage of containers in different parts of the network, making effective and timely asset utilization a nightmare. And it should not come as a surprise that with this operational nightmare comes an unwelcome cost which, to make matters worse, cannot always be effectively predicted or smoothen out over time.
Unnecessary carbon emissions and generation of waste not only negatively impact an enterprise’s carbon footprint, but they also make for more expensive Operations. So, if you don’t do it for the environment, do it for your bottom line!
The management of empty containers incurs substantial costs for Supply Chain operators. These costs include, but are not limited to:
It is not just the fact that empty containers, like any other assets, are prone to wear and tear during storage and transit, requiring ongoing maintenance. This gradual depreciation in quality means that their impact on meeting demand depletes over time and therefore, any attempt in factoring them in as part of a comprehensive resource allocation solution needs to be constantly revisited. This exercise is not trivial and requires deep understanding of both data modelling and dynamic programming disciplines. Needless to say, building the right team to offer the right set of expertise is easier said than done!
Any proper and sustainable resource allocation solution must factor in many types of fees and financial constraints. After all, one of the main aims of such solutions is to reduce operational costs and to that end, effective modelling of both storage and handling fees, which come in many forms and guises, are instrumental in overall success of such solutions.
One obvious cost associated with repositioning of empty containers is related to their transportation. In general, moving containers between various locations within a network involves a number of modalities, such as rail, , each one with its own challenges and associated costs, which need to be represented individually within the larger dynamic data model. and different locations involves trucking, rail, air, road, etc., each of which incurring its own set of costs and logistical challenges.
And then, there is one of the most annoying costs of all, the darling of many in the Finance sector: The dreaded opportunity cost, that needs to be looked at and factored in. Having containers in storage where they may not be able to help address demand in other locations within a network means missing on precious revenue that your competitors might be only too happy to get their hands on. This means less profitability and, of course, less profitability means higher cost of doing business.
So, if efficient management of empty containers is so critical, then why so many companies fail to make a reasonable success of the exercise? Here is a non-exhaustive list of reasons that come to mind:
It is rather simple really: You can’t effectively use what you do not have or do not know about! The lack of visibility of the right data at the right time and the right place within a Supply Chain network can only lead to multiple pockets of manual work or result in the injection of many assumptions that may be either incomplete or downright incorrect. This makes the identification of network bottlenecks and the modelling of business rules and constraints nearly impossible.
The message here is simple: Get your input data right, and then we can talk about resource optimization!
Resistance to change within Supply Chain relates to three separate areas:
Fragmentation of a Supply Chain ecosystem can play at two separate levels:
Such inefficiencies lead to a painful lack of standards which, make effective collaboration between different stakeholders nearly impossible to achieve.
If you want to build a proper building, you need to start with a strong foundation. The only problem with that is that a strong foundation does not look nearly like a finished product and, as such, the short-term outlook does not necessarily offer strong Return on Investment (ROI) to your executives! The sad truth is that not many executives are willing to wait for the foundational work to bed in before the effort starts bearing fruit.
In a similar fashion, effective management of empty containers does require plenty of foundational work, such as efficient data management and clear workflow definitions before utilization of advanced analytics and algorithms can produce the magic results that transform the business.
In summary, short-term considerations, in place of long-term sustainable solutions, lead to inefficiencies and lost opportunities when it comes to the management of empty containers.
Putting the highly critical issue of “the right mindset” aside (see our earlier article On Merits of Digital Transformation in Supply Chain for more on this topic), there are many innovative and promising technologies that can help with improving the handling of empty containers. These include, among others, IoT, Blockchain and Smart Contracts, as well as Sustainable Eco-friendly solutions, each of which can help increase data visibility and accuracy as well as reduce negative environmental impact.
However, one technological approach that can drastically improve the management of empty containers relates to the effective use of Advanced Analytics, Machine Learning Algorithms and Dynamic Optimization Techniques.
Through such approaches, one can analyze large amounts of historical data to build trends and identify common patterns, anomalies, and seasonality behaviors. It is also possible to build algorithms that can learn from historical data as well as user input and respond in real-time to change.
Finally, Advanced Optimization techniques allow an enterprise to capture all relevant business rules, industry and 3rd party regulations and constraints around a cohesive data model that allows for effective allocation of all resources within any network of arbitrary complexity.
The effective repositioning of empty containers is an instrumental step towards a more optimized Supply Chain which, done consistently, will lead to reduced operational costs, better management of resources throughout an enterprise and tangible improvements in overall carbon footprints in a sustainable manner.
Any long-term solution requires a combination of cutting-edge technologies, collaboration across the supply chain and, ultimately, a shift in mindset.
At Tetrixx, we are obsessed with effective utilization of modern technologies to transform and improve how our clients do business. We would love to hear your take on this topic and, of course, would be happy to discuss with you many ways in which we can help you become a more competitive Supply Chain player in your specific domain. Find us at www.tetrixx.io for more details.