[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%. While this was considered high, it was reported to be just the tip of the iceberg; estimates suggested a 25% difference when comparing logistics costs between Japan and the U.S. It was during this same period that logistics began to be referred to as the "Dark Continent" [Figure 1]. A point of note is the logistics costs for manufacturers, which were found to be double those in the U.S. Why did this phenomenon occur?

A manufacturer's profit is determined by the efforts of the sales department (the profit center) to increase sales and the efforts of the manufacturing department (the cost center) to reduce costs. Consequently, thorough improvement activities were carried out on the manufacturing floor through small-group activities. However, there are limits to such improvements. To further reduce costs, a systematic improvement method was adopted: shifting logistics costs associated with manufacturing to the logistics department. At first glance, manufacturing costs were reduced, but internal logistics costs ballooned, eventually reaching twice the level of those in the U.S.

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 licensing system. A transportation company's total profit is not determined by price alone; it 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 emerged that a competitive mechanism was needed for logistics. There is no doubt that the common understanding at the time was to introduce market economy principles and design a system that 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 transportation industry. A key 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 ten 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 many illegal "white-plate trucks," which were common before deregulation, transitioning into legal operators [Figure 2].

On the other hand, the number of special consolidated operators did not increase despite deregulation. This is because trunk line transportation requires not only locations for consolidation but also the construction of large-scale logistics networks. Furthermore, the barriers to entry did not lower due to the necessary investment in 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. Previously, rates could not be lowered without government approval, but after deregulation, operators only needed to set and notify prices based on the supply-demand balance, sparking price competition among operators.

This price competition worsened the management status of truck transport operators. 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 only 48% of companies being profitable. For those with 10–20 trucks, the ordinary profit margin was 0.1% (59% profitable); for 21–50 trucks, it was 0.8% (66% profitable); and 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 simply that entry increased and competition intensified. The essence of the problem lies in the fact that most new entrants were small-scale operators, and a structural change occurred in the logistics industry involving secondary and tertiary subcontracting.

Let me explain the process of this structural change. Shippers place great importance on logistics quality. It is a given that products must reach the receiving company without damage, and this includes safe, reliable, and prompt delivery. Furthermore, because many shippers face intense market competition, demand can fluctuate significantly, causing manufacturing and logistics volumes to fluctuate accordingly. Contracting with a logistics company that can flexibly respond to such fluctuations in volume is a necessary condition for strengthening a shipper's competitiveness. Of course, the ability to respond quickly and provide compensation in the event of an accident is also an important factor for shippers when choosing a logistics operator. Unfortunately, small-scale operators cannot meet these conditions. Therefore, most large shippers sign contracts with large logistics companies. While it appeared that competition was intensifying across the logistics industry as a whole, the reality was that a structure advantageous to large companies was born.

Thus, deregulation did not reduce the volume for large logistics operators, nor did it expose them to intense competition; instead, their management improved. While advancing their own efficiency, large logistics operators began to utilize outsourcing for increasing volumes. Small and medium-sized logistics operators jumped at this opportunity. 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 transportation capacity while improving their own management status. This is the framework for the birth of primary logistics subcontractors.

Meanwhile, among the small and medium-sized operators, excellent companies emerged that took on work from multiple large firms. They outsourced the portions that exceeded their own transport capacity, saving on fixed and indirect costs just like the large firms, thereby increasing their transport capacity and improving their management status. This is the framework for the birth of secondary subcontractors. By repeating this process, tertiary and quaternary subcontractors were born, and now it reaches as far as quinary (fifth-tier) subcontractors. At the bottom level, problems of overloading and overwork are becoming severe.

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

Under current labor standards laws, a driver's working hours are set at 8 hours per day and 40 hours per week. However, duty hours (including break times) are limited to 293 hours per month and 3,516 hours per year, with the possibility of extending up to 320 hours. While the 293-hour monthly limit can be exceeded, the number of times it is exceeded must be kept to six or fewer per year, and the total excess time must be within 320 hours. Furthermore, duty hours for a single day (24 hours from the start of work) are set at 13 hours or less, and even if exceeded, they must be within 16 hours; drivers must be given 8 consecutive hours of rest within a 24-hour period. There is a constraint that the number of times daily duty hours exceed 15 hours is limited to twice a week, so it is not as if daily overtime can be freely extended as long as total overtime is kept within 320 hours.

Driving time is also regulated to an average of 9 hours or less over two days, and weekly driving time is limited to an average of 44 hours over two weeks. Regarding the two-day average, the regulation is somewhat loose, as it is considered legal if the average with the following day is within 9 hours, even if the average with the previous day exceeds 9 hours. Furthermore, it is stipulated that a 30-minute break must be given after 4 hours of driving, with a rule that breaks of less than 10 minutes do not count. In other words, unlike other types of labor, driving 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 and mental fatigue; a total of 30 minutes or more of rest (in increments of at least 10 minutes) must be taken within a 4-hour and 30-minute period.

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

The main changes regarding duty hours include shortening the maximum daily duty hours to 15 hours, shortening the maximum monthly duty hours to 284 hours, and shortening the maximum annual extendable duty hours to 310 hours. In particular, setting a 960-hour cap on labor hours other than driving duties for drivers is unprecedented, and its impact is difficult to gauge. A typical example is shippers having drivers perform unloading or warehouse work; even under current rules, there are constraints on maximum hours, and recording these in daily reports is mandatory.

According to data from the Japan Trucking Association, 30% of companies have overtime hours exceeding 960 hours per year. If transportation capacity is calculated using this data, without countermeasures, 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). I should first point out that while these calculations likely treat the data directly as "untransportable," the details need to be scrutinized, and it is not correct to apply macro data directly to operational problems.

Next, there is a calculation regarding transportation between Tokyo and Osaka. The distance is 550 kilometers. If one driver operates according to the rules, the actual duty hours would be 12.5 hours. However, to keep annual non-driving work hours to 960 and total duty hours to 3,300 starting in 2024, the daily duty hour limit would reportedly need to be 12 hours. Consequently, two people would be required, leading to increased costs and a higher possibility of delayed arrivals. However, the purpose of this calculation is to advocate for relaxing 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. On June 2, they decided on the "Policy Package for Logistics Innovation" as a fundamental and comprehensive measure aimed at "reviewing business practices, improving logistics efficiency, and changing the behavior of shippers and consumers."

While the various data calculations and the policy package are not incorrect, it cannot be said that the impact of the 2024 problem on the Japanese economy has been correctly estimated, and it is unclear if the measures are directly linked to solving the problem. This is because the data used for calculations is fragmentary, prerequisites are ignored, relationships between data points are not considered, and a problem analysis of the logistics system as a whole has not been performed.

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

We need to reconsider how the 1990 deregulation changed Japan's logistics industry over the following decade and simulate how the current tightening of regulations will change the industry over the next ten years. The 2024 problem has a structure where it significantly affects subcontractors responsible for transport, which in turn affects large companies. We should objectively and scientifically conduct dynamic simulations of the social system.

The calculation that logistics capacity will decrease due to the 2024 problem—that is, the tightening of regulations—is only the surface of the issue. The essence of the problem is to correctly analyze why such a problem occurred and to design a correct mechanism. Shouting about the 2024 problem for ten years will not solve it. It is easy to estimate that the management status of small-scale operators will worsen and bankruptcies will increase due to the tightening of regulations. While this may resolve the multi-layered structure, we must consider how to deal with the problem of Japan'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 professionals 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 cultivation of highly skilled logistics professionals who can execute it. Unless we develop highly skilled logistics professionals 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 professionals is a common understanding in society, and the Ministry of Land, Infrastructure, Transport and Tourism has already held three symposiums on the topic. Regarding the profile of highly skilled logistics professionals, 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, promote the introduction of new technologies, and facilitate 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 often said that Japan is two laps behind the U.S. in terms of the number of people with IT knowledge. An even bigger problem is that few companies have mechanisms to accumulate IT technology. Even taking the single example of requirement definition in system development, it is common in Japan for vendor companies to conduct interviews on the current operations of user companies and then translate that into language that system developers can understand. This is a method that was criticized as "status quo maintenance" in the U.S. in the 1970s. In digitalization, big data processing technology—specifically how quickly large-scale problems can be solved—is expected to be fiercely contested over the next ten years. Unfortunately, in Japan, both shippers and logistics companies are indifferent to this technology. In fact, to utilize digitalization in one's own business, it must not be completely outsourced to external vendors. This is because technology does not accumulate, 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 data analysis are qualitatively different. While people understand 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. When the 2024 problem became apparent, one necessary action was to analyze what measures should be taken using available resources and various laws as constraints. However, problems exist such as a lack of data, or even if it exists, it is siloed and cannot be analyzed correctly. Even if data is available, the methodology—how to analyze it, what models to build, and what algorithms to apply—is unknown. Ultimately, because the necessary data is not understood, 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 seen as a type of business model research. The birth of many SCM business models in the late 90s is a typical example. 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 necessary to integrate or share information from independent companies in the supply chain, but the means to achieve this are organizational integration or strategic alliances, which essentially becomes a planned economy. Clark & Scarf's (1960) echelon inventory is famous as research for optimizing the flow of goods in a supply chain, but this concept implicitly assumes organizational integration as a prerequisite. In other words, to prove optimality, organizational integration must be assumed. Furthermore, when aiming for optimization, objectives and constraints must always be clarified. If either is missing, it cannot be called 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 a supply chain means 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: a physical life cycle and a 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 technologies. Those who run away from new technology because they are from a liberal arts background are not qualified to be leaders. Technology is not the exclusive privilege of science and technology majors. Having an interest and meeting good teachers determines the "ability to respond to social changes, promote the introduction of new technologies, and facilitate cross-disciplinary collaboration." Ultimately, even those from a science and technology background cannot acquire the "ability to promote the introduction of new technologies and cross-disciplinary collaboration" if they are not interested in technologies from other fields. Therefore, in developing highly skilled logistics professionals, it is required to give opportunities to learn to those who are willing to learn technologies from other fields with curiosity—especially young people—which will contribute significantly to the sustainable development of the organization.

The 2024 problem is not a problem that will suddenly occur next April. Thirty-four years have passed leading up to this problem, during which the increase in general freight transport operators and the decrease in special consolidated freight transport operators have 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, as well as dynamic simulations of various measures, should be conducted. Even just considering ISO 14083 measures, modal shifts need to be reconsidered, and if we are thinking about logistics capacity, we need to consider leveling the entire system, including time spent sitting in warehouses. It is management negligence to force drivers into hard driving while ignoring the fact that delays occur while goods are sitting 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 used effectively, there is a high possibility that the capacity shortage problem can be alleviated. In the first place, if we assume that all return trips in the Tokyo-Nagoya-Osaka corridor are empty, it means twice as many drivers were working; simply making half of that efficient would keep the capacity problem within the allowable range of fluctuation.

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

Finally, in commercial science, the flow of commerce is called logistics, and research on the optimization of commercial flow has been conducted for many years. Currently, commercial flow and logistics (transportation and delivery) are independent, but first, in commercial flow, shippers and transport operators need to cooperate to optimize, and based on that, logistics must also 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 this to show that cooperation generates profit. Data-driven scientific management methods must be incorporated into the decision-making of shippers and logistics companies and utilized in policy planning.