[Special Feature: Thinking about the Logistics Crisis] Hiroaki Matsukawa: The Essence of the 2024 Problem

In the late 1980s, the difference in logistics costs between Japan and the United States became an issue. According to a survey by Price Waterhouse, the ratio of logistics costs to sales for Japanese companies was 8%, which was said to be high. However, it was announced that this was just the tip of the iceberg, and it was estimated that there was a 25% difference when comparing logistics costs between Japan and the US. This was also the same period when logistics began to be called the "Dark Continent" [Figure 1]. What is noteworthy is the logistics costs for manufacturers. It can be seen that they were double those of the US. Why did such a phenomenon occur?

A manufacturer's profit is determined by the efforts of the sales department, known as a profit center, to increase sales, and the efforts of the manufacturing department, known as a cost center, to reduce costs. Therefore, thorough improvement activities were carried out at manufacturing sites through small-group activities. However, there are limits to improvement. A method adopted as a systematic improvement to further reduce costs was to shift logistics costs associated with manufacturing to the logistics department. At first glance, manufacturing costs could be reduced, but internal logistics costs ballooned and eventually became double those of the US.

To solve this problem, many manufacturers spun off or sold their logistics departments. However, selling the logistics department did not lower logistics costs. This is because transportation prices were subject to a permit system. A transportation company's total profit is not determined by price alone but also depends heavily on transportation volume. If freight rates are lowered slightly to increase volume and improve the loading ratio, total profit increases. The idea naturally arose that a competitive mechanism might be necessary for logistics as well. There is no doubt that the common understanding at the time was to design a system that incorporated market economy principles and encouraged competition to achieve logistics efficiency.

The enactment of the two logistics laws in 1990—namely, the deregulation of the motor carrier business and the freight forwarding business—marked the beginning of full-scale deregulation in Japan's transport industry. An important point was the change from a license system to a permit system for general motor carrier businesses and special consolidated motor carrier businesses.

This change made it easier to enter the logistics business, and the number of general motor carrier operators increased by approximately 14,000 (40%) over 10 years. Another reason for the ease of entry was the reduction of the minimum number of vehicles required to five. It is also said that the increase in general motor carrier operators was due to the many illegal "white-plate trucks" that existed before deregulation converting into legal operators [Figure 2].

On the other hand, the number of special consolidated operators did not increase even after deregulation. This is because, in the case of trunk line transport, it is essential to build not only consolidation points but also large-scale logistics networks. Furthermore, entry barriers did not lower due to the investment required for information network construction, such as cargo tracking systems. This is one of the important points that would later become a problem. Measures taken to encourage competition also included changing to a freight rate notification system. Until then, rates could not be lowered without government permission, but after deregulation, operators only needed to set and notify prices while monitoring the supply-demand balance, and price competition began among operators.

Due to this price competition, the management status of truck transport operators deteriorated. In fiscal 2001, the national average operating profit margin dropped to 0.6%. For operators with 10 or fewer trucks, the average ordinary profit margin was minus 1.3%, with 48% of companies being profitable. For those with 10–20 trucks, the ordinary profit margin was 0.1%, with 59% profitable. For those with 21–50 trucks, the ordinary profit margin was 0.8%, with 66% profitable. Even for operators with 100 or more trucks, it was only 1.2%, with 79% being profitable.

The point I want to emphasize is that the essence of the problem is not that entry increased and competition intensified. The essence of the problem is that, in addition to most new entrants being small-scale operators, a structural change occurred in the logistics industry involving secondary and tertiary subcontracting.

Let me explain the process of this structural change. Shipper companies place importance on logistics quality. It is natural to deliver goods to the receiving company without damage, and this includes safe, reliable, and prompt delivery. Furthermore, because many shipper companies are exposed to fierce market competition, demand can fluctuate significantly, and manufacturing and logistics volumes fluctuate accordingly. Contracting with a logistics company that can flexibly respond to such fluctuations in volume becomes a necessary condition for strengthening a shipper's competitiveness. Of course, responding quickly and providing compensation in the event of an accident is also an important factor when a shipper chooses a logistics operator. Unfortunately, small-scale operators cannot meet these conditions. Therefore, most large shipper companies sign contracts with large logistics companies. While it appeared that competition was intensifying in the logistics industry as a whole, the reality was that a structure advantageous to large companies was born.

In this way, deregulation did not reduce the logistics volume of large logistics operators, nor were they exposed to fierce competition, and their management improved. While proceeding with their own efficiency improvements, large logistics operators began to utilize outsourcing for increasing volumes. Small and medium-sized logistics operators jumped at this. Large logistics operators actively turned small and medium-sized operators—who were inexpensive and did not require the payment of fixed or indirect costs—into subcontractors, expanding their transport capacity and improving their own management status. This is the framework for the birth of primary logistics subcontracting.

Meanwhile, among small and medium-sized operators, excellent companies emerged that took on work from multiple large companies. They outsourced the portions that exceeded their own transport capacity, increasing capacity while saving on fixed and indirect costs just like the large companies, and improved their own management status. This is the framework for the birth of secondary subcontracting. By repeating this, tertiary and quaternary subcontracting were born, and it now reaches quintuary subcontracting. At the end of the chain, problems of overloading and overwork are becoming serious.

Of course, bad business practices are also involved in the multi-layered subcontracting structure, and further deep analysis is required to solve the problem.

Under the current Labor Standards Act, a driver's daily working hours are set at 8 hours and weekly working hours at 40 hours. However, it states that binding hours (including break times) can be extended up to 320 hours within a range not exceeding 293 hours per month and 3,516 hours throughout the year. While 293 hours may be exceeded in a month, the total number of times it is exceeded throughout the year must be kept within 6 times, and the total excess time must be within 320 hours. Furthermore, daily binding hours (24 hours from the start of work) are set at 13 hours or less, and even if exceeded, they must be within 16 hours, and drivers must be given 8 consecutive hours of rest within a 24-hour period. There is a constraint that the number of times daily binding hours exceed 15 hours is limited to twice a week; it is not the case that daily overtime can be freely extended as long as total overtime is kept within 320 hours.

Driving time is also regulated to be within 9 hours on average over two days, and weekly driving time is specified as up to 44 hours on average over two weeks. Regarding the two-day average, it is judged legal if the average with the following day is within 9 hours, even if the average with the previous day exceeds 9 hours, making it a relatively loose regulation. Furthermore, it is stipulated that a 30-minute break must be given after 4 hours of driving, and there is a rule that breaks of less than 10 minutes are not recognized as rest. In other words, unlike other types of labor, driving a car requires a minimum rest period of 10 minutes or more based on scientific evidence that frequent short breaks do not lead to recovery from physical fatigue, including mental fatigue. A total of 30 minutes or more of rest (in increments of 10 minutes or more) must be taken within a 4-hour and 30-minute period.

The biggest change in the new regulations to be enforced from April 2024 lies in the clarification of constraints on overtime work hours. Figure 3 shows the main contents of the revision.

The main changes regarding binding hours are the reduction of maximum daily binding hours to 15 hours, the reduction of maximum monthly binding hours to 284 hours, and the reduction of the maximum possible annual extension of binding hours to 310 hours. In particular, setting a cap of 960 hours for labor hours other than a driver's driving duties is unprecedented, and its impact is difficult to measure. A typical example is when shipper companies have drivers perform unloading work or warehouse work, but even under current rules, there are constraints on the maximum time, and recording this in daily reports is mandatory.

According to data compiled by the Japan Trucking Association, overtime hours exceed 960 hours per year at 30% of companies. If transport capacity is estimated using this data, without countermeasures, transport capacity will decrease by 14% in fiscal 2024 (equivalent to 400 million tons of cargo) and by 34% in 2030 (equivalent to 900 million tons of cargo). In this estimation, the data seems to be calculated directly as being unable to be transported, but strictly speaking, the content needs to be scrutinized. I must first point out that it is not correct to apply macro data directly to operational problems.

Next, there is an estimation regarding transport between Tokyo and Osaka. The distance is 550 kilometers. If one driver drives while following the rules, the actual binding time would be 12.5 hours. However, to keep annual non-driving work hours to 960 hours and binding hours to 3,300 hours from 2024, it is said that the daily binding hour limit must be set to 12 hours. Therefore, it will be necessary for two people to handle it, which will increase costs and heighten the possibility of delayed arrivals. However, the purpose of this estimation is to relax the maximum speed on expressways to 100 km/h, and it is not a comprehensive calculation of transport capacity.

In response to these issues, the government established and held the "Ministerial Meeting on Logistics Innovation in Japan" on March 31, 2023. For the purpose of "reviewing business practices, improving logistics efficiency, and changing the behavior of shippers and consumers," the "Policy Package for Logistics Innovation" was decided on June 2 as a fundamental and comprehensive measure.

While the various data estimations and the policy package are not incorrect, it cannot be said that the impact of the 2024 problem on our country's economy has been correctly estimated, and it is unclear whether the measures will directly lead to a solution. This is because the data used for the estimations is not only fragmentary but also ignores preconditions, fails to consider the relationships between data points, and lacks a problem analysis of the logistics system as a whole.

I am very much in favor of taking up the 2024 problem as a movement to carry out logistics reform. I believe that the multi-layered subcontracting structure in the logistics industry is a major problem, and being forced to perform many tasks outside of driving duties is also a major problem. I hope that the government's leadership will contribute significantly to solving these two problems and other derivative issues, such as overloading and serious accidents.

We need to reconsider how the 1990 deregulation changed our country's logistics industry over the following 10 years and simulate how the current tightening of regulations will change the logistics industry over the next 10 years. The 2024 problem has a structure where it significantly affects operators handling transport as subcontractors, which in turn affects large companies. We should objectively and scientifically conduct a dynamic simulation of the social system.

The estimation that the 2024 problem—that is, the tightening of regulations—will reduce logistics capacity is only the surface of the problem. The essence of the problem is to correctly analyze why such a problem occurred and to design a correct mechanism. This is because shouting about the 2024 problem for 10 years will not solve it. It is easy to estimate that the management status of small-scale operators will deteriorate and bankruptcies will increase due to the tightening of regulations. While this may resolve the multi-layered structure, we must think about how to deal with the problem of our country's total transport capacity decreasing.

What we must do now, in addition to investing in the development of specific technologies, is to urgently develop highly skilled logistics personnel from the perspectives of time competition, evolutionary competition, and sustainable development. Therefore, the essence of the 2024 problem is not a lack of capacity, but the design of a new mechanism and the development of highly skilled logistics personnel who can execute it. Unless we develop highly skilled logistics personnel who can scientifically analyze various levels of problems in the logistics field and provide the correct prescriptions, the 2024 problem could become a man-made disaster.

The importance of developing highly skilled logistics personnel is a common understanding in society, and the Ministry of Land, Infrastructure, Transport and Tourism has already held three symposiums. Regarding the profile of highly skilled logistics personnel, the following three abilities are highlighted:

(1) The ability to respond to digitalization and think in a data-driven manner

(2) The ability to manage the supply chain from the perspective of total optimization

(3) The ability to respond to social changes and promote the introduction of new technologies and cross-disciplinary collaboration

are being addressed.

The wave of digitalization is higher than expected. It is said that GAFAM (Google, Apple, Facebook, Amazon, Microsoft) creates more value than many developing countries in the world, but why is there currently no runner-up in digitalization? It is said that Japan is two laps behind the US in terms of the small number of personnel who have acquired IT knowledge. An even bigger problem is that few companies have mechanisms to accumulate IT technology. Even taking a single requirement definition in system development, it is common in Japan for vendor companies to conduct interviews on the current operations of user companies and for system developers to replace that with words they understand. This is a method that was criticized as status-quo-maintaining in the US in the 1970s. In digitalization, big data processing technology—how quickly large-scale problems can be solved—is expected to be fiercely contested over the next 10 years. Unfortunately, in Japan, both shipper companies and logistics companies are indifferent to this technology. In fact, to utilize digitalization for one's own operations, it must not be completely outsourced to external vendors. This is because technology is not accumulated, leading to higher IT investment and system operation costs.

Experience and intuition are important when making management decisions. However, the accuracy and speed of making decisions based on results obtained from analyzing data are qualitatively different. Even if one understands that a lack of accuracy and speed in decision-making can be fatal in business competition, they do not know how to analyze data or how to utilize it for decision-making. An action to take when the 2024 problem became clear is to analyze what measures should be taken using available resources and various laws as constraints. However, there are problems such as a lack of data, or even if it exists, it is siloed and cannot be analyzed correctly. Even if data exists, the methodology—what kind of model to build and what kind of algorithm to apply—is unknown. Ultimately, because the necessary data is unknown, data inventory cannot be performed, and the problem is left unaddressed. To break through this difficult situation, we must create a group of young people striving to become CLOs (Chief Logistics Officers).

Supply Chain Management (SCM) can be said to be a type of business model research. The birth of many SCM business models in the late 90s is typical. However, SCM is not just a business model. It is a business model that utilizes IT. In other words, a business model without digital technology cannot be called an SCM business model and cannot even open the door to total optimization.

On the other hand, pure total optimization cannot be achieved in SCM. To achieve total optimization, it is required to integrate or share information from independent companies in the supply chain, but the means to achieve this is organizational integration or strategic alliances, which essentially becomes a planned economy. As research to optimize the flow of goods in the supply chain, Clark & Scarf's (1960) echelon inventory is famous, but this concept implicitly assumes organizational integration as a precondition. In other words, to prove optimality, organizational integration must be assumed. Also, when aiming for optimization, it is always necessary to clarify the objectives and constraints. If either is missing, it cannot be said to be optimal. There is no such thing as universal optimality in the world, nor does eternal optimality exist. Discussing total optimization in the supply chain without such knowledge is ignorance and cannot be realized. Ultimately, total optimization in the supply chain is about finding a policy under individual optimization that is better than the sum of individual optimizations. It is a mistake to deny individual optimization and advocate for total optimization without understanding this.

Technology evolves forever. No matter how innovative a technology is, it will eventually become obsolete, and products born from that technology will disappear from the market. Products have two life cycles. One is the physical life cycle, and the other is the market life cycle. The physical life cycle is long, but the market life cycle is short because technological progress is fast. We must acquire the ability to learn with interest about rapidly advancing technology. People who run away from new technology because they are from a liberal arts background are not qualified to be leaders. Technology is not the privilege of the sciences. Having interest and meeting good teachers determines the "ability to respond to social changes and promote the introduction of new technologies and cross-disciplinary collaboration." Ultimately, even those from a science background who are not interested in technologies from other fields cannot acquire the "ability to promote the introduction of new technologies and cross-disciplinary collaboration." Therefore, in the development of highly skilled logistics personnel, it is required to give opportunities to learn to those who are willing to learn technologies from other fields with curiosity, especially young people, and this will contribute significantly to the sustainable development of the organization.

The 2024 problem is not a problem that will suddenly occur next April. Behind this problem is the passage of 34 years until its occurrence, during which the increase in general motor carrier operators and the decrease in special consolidated motor carrier operators progressed, creating distortions in the logistics industry. As soon as possible, an analysis of nationwide freight transport capacity and load, including railways and coastal shipping, and dynamic simulations of various measures should be conducted. Even just considering ISO 14083 measures, it is necessary to reconsider modal shifts, and if considering logistics capacity, it is necessary to consider leveling the entire system, including the time goods are left idle in warehouses. It is management negligence to force drivers into hard driving while viewing delays as a problem despite letting goods sit in warehouses.

I want to emphasize that logistics is classified into procurement logistics, internal (manufacturing) logistics, and product logistics. There is long-distance transport in procurement logistics, and there is long-distance transport in internal logistics. If capacity in procurement and internal logistics is utilized effectively, there is a high possibility that the problem of capacity shortage can be alleviated. In the first place, if we assume that all return trips in the Tokyo-Nagoya-Osaka logistics corridor are empty, it means twice as many drivers were working. By making just half of that efficient, the capacity problem can be kept within the allowable range of fluctuation.

Many problems also arise due to poor accuracy in logistics forecasting and planning. In long-distance transport, due to constraints on continuous driving time and continuous rest time, multiple drivers have sometimes driven a single truck. In the future, we must build a system for cooperation while competing and create a foundation for promoting logistics efficiency. If existing social resources such as Trabox are utilized effectively, only the mechanism needs to be changed, and no additional investment is required.

Finally, in commercial science, commercial distribution is called logistics, and research on the optimization of commercial distribution has been conducted for many years. Currently, commercial distribution and logistics (transport and delivery) are independent. First, in commercial distribution, shipper companies and transport operators need to cooperate to optimize, and based on that, logistics also needs to be optimized. While it is true that bad business practices exist, what is more important is to show that cooperation improves profits. Instead of selling off large amounts of data piecemeal, it is necessary to process it to generate value-added information and use it to show that cooperation generates profit. Data-driven scientific management methods must be incorporated into the decision-making of shipper companies and logistics companies and utilized for policy planning.