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№ 2(124)
февраль, 2025 г.
PAPERS IN ENGLISH
ECONOMIC SCIENCES
ECONOMIC THEORY
USING TECHNOLOGIES TO OPTIMIZE LOGISTICS AND SALES
Akylbek Umarov
bachelor's degree, Aktobe's K. Zhubanov State University, Kazakhstan, Aktobe E-mail: [email protected]
ИСПОЛЬЗОВАНИЕ ТЕХНОЛОГИЙ ДЛЯ ОПТИМИЗАЦИИ ЛОГИСТИКИ И ПРОДАЖ
Умаров Акылбек
бакалавр,
Актюбинский государственный университет имени К. Жубанова,
Казахстан, Актобе
ABSTRACT
This article examines modern technologies aimed at optimizing logistics and sales in the construction industry. Special attention is given to the implementation of innovative solutions such as artificial intelligence (AI), big data analytics, blockchain, the Internet of Things, digital twins, and autonomous vehicles. The study explores the main challenges of construction material logistics, including high transportation costs, the complexity of demand forecasting, supply chain (SC) fragmentation, and the impact of environmental factors. It analyzes the advantages of using advanced technologies to enhance the transparency, efficiency, and sustainability of logistics operations. Examples of successful technology applications in global companies are provided, illustrating their potential to reduce costs, improve coordination, and minimize risks.
АННОТАЦИЯ
В данной статье рассматриваются современные технологии, направленные на оптимизацию логистики и продаж в строительной отрасли. Особое внимание уделяется внедрению инновационных решений, таких как искусственный интеллект (ИИ), аналитика больших данных, а также блокчейн, интернет вещей, цифровые двойники и автономные транспортные средства. Исследуются основные проблемы логистики строительных материалов, включая высокую стоимость транспортировки, сложность прогнозирования спроса, фрагментацию цепочек поставок (ЦП) и влияние экологических факторов. Анализируются преимущества использования передовых технологий для повышения прозрачности, эффективности и устойчивости логистических операций. Приводятся примеры успешного применения технологий в глобальных компаниях, что иллюстрирует их потенциал для снижения затрат, улучшения координации и минимизации рисков.
Keywords: logistics, supply chains (SC), construction materials, artificial intelligence (AI), big data.
Ключевые слова: логистика, цепочки поставок (ЦП), строительные материалы, искусственный интеллект (ИИ), большие данные.
Introduction
Modern logistics processes and supply chain (SC) management play a crucial role in the economy, ensuring the uninterrupted movement of goods and materials from producers to end consumers. In the construction
industry, which is characterized by high material intensity and operational complexity, the efficiency of logistics directly impacts product costs, project timelines, and the competitiveness of companies. However, traditional approaches to logistics management often face limita-
Библиографическое описание: Umarov A. USING TECHNOLOGIES TO OPTIMIZE LOGISTICS AND SALES // Universum: экономика и юриспруденция : электрон. научн. журн. 2025. 2(124). URL:
https://7universum.com/ru/economy/archive/item/19249
tions stemming from the difficulty of demand forecasting, high transportation and storage costs, and the need to rapidly respond to changes in market and production conditions. In such circumstances, innovative methods based on modern technologies are becoming increasingly relevant for improving SC efficiency.
Artificial intelligence (AI) and big data analytics technologies are powerful tools capable of fundamentally transforming logistics and sales management. They open new opportunities for data analysis and interpretation, process automation, SC transparency, and the optimization of operations across all stages. These technologies not only address existing challenges but also offer strategic advantages, such as cost reduction, improved demand forecasting, and solutions for sustainable development. The purpose of this article is to explore the potential of using AI and big data technologies to enhance the efficiency of managing logistics and SC in the construction materials sector.
Main part. Challenges in managing construction material SC
Logistics for construction materials are one of the most difficult and resource-intensive areas in the management of SC, as the specifics of the industry-meaning cargo is big and heavy-along with the additional demands against transport and storage processes place exceptionally high demands on transportation and warehousing. One major issue is the high costs involved in the transportation and warehousing of construction materials. Products like cement, metal, brick, and other components also have a huge mass and volume, and it automatically enhances the transport cost. Furthermore, this material requires big areas for storage; therefore, the operational cost for the warehouses is also enhanced. This issue is very severe in areas where the transport structure is not well developed or is narrow, as this increases the cost of logistics more.
Another important aspect is the difficulty in forecasting demand for construction materials. This demand has a distinct cyclic nature and is subject to seasonal variation and the economic situation, like the level of investment in construction and the realization of infrastructure projects. Forecasting errors result in material shortage or surplus, causing delay in construction, increase in costs, and problems with inventory management.
Fragmentation of SC is also a serious problem. Construction material delivery involves a large number of participants, including manufacturers, suppliers, transport companies, contractors, and end consumers [8]. Poor coordination among participants may lead to wasting time, misaligned actions, and a greater risk of mistakes, all of which seriously lower the overall efficiency of the whole logistics system.
The need for integration and transparency of operations also becomes a pressing issue. In most cases, construction companies still rely on outdated management methods, such as paper documentation or fragmented information systems, which make tracking the movement of goods difficult to manage. This creates other risks: disruption in delivery schedules and loss of control over the condition of materials that is so important for successful project execution. Furthermore, construction material logistics depends on a variety of external factors. Weather conditions, fluctuations in fuel prices, transportation availability issues, and geopolitical factors can have a significant impact on the stability of SC. Disruptions caused by such external influences lead to delays in large construction projects, which in turn increase timelines and costs.
An important challenge is the impact of environmental factors. The transportation and storage of construction materials are often associated with high carbon emissions and other environmental consequences, which, in the context of the global push for sustainable development, is becoming an increasingly critical issue. The demand for reducing the carbon footprint places additional pressure on logistics systems, requiring companies to implement environmentally friendly and energy-efficient solutions.
Thus, the traditional problems of construction material logistics require the search for innovative solutions aimed at increasing the efficiency and transparency of SC. The implementation of new technologies represents an important step in optimizing logistics processes. It is worth noting that with the development of technologies and automation, the construction materials logistics market is gradually becoming automated. Since 2020, the global market for logistics automation has been growing at a compound annual growth rate of 12,4%, the highest among all SC markets. By 2026, the global logistics automation market is expected to reach $82,3 billion (fig. 1).
2020 2021 2022 2023
Large Enterprises ■ Small & Medium Enterprises
Figure 1. Market volume of logistics automation by business size, billion dollars [6]
These figures reflect the rapid pace at which companies are implementing advanced technologies to automate their SC, enabling them to significantly accelerate processes, improve forecasting accuracy, and reduce reliance on human factors. The use of such solutions contributes to substantial reductions in time and costs, as well as minimizing risks related to errors and delays.
Artificial intelligence in construction material SC management
An important technology that significantly changes approaches to managing the supply of building materials is AI. Its application has become vital with the increased competition, market turbulence, and growing demands on the issues of delivery timelines and service quality for better optimization and enhancement of overall efficiency.
The forecast of the demand for building materials, often subject to fluctuations caused by the influence of external economic and political factors, is one of the most urgent tasks in building logistics. In such a context, AI can use machine learning algorithms to analyze efficiently vast amounts of data on historical consumption, seasonal variations, economic and climatic changes. This way, such systems are able to provide very good forecasts regarding building material needs, which would reduce excessive and insufficient building material conditions, extremely important for construction firms working with expensive and scarce resources [3]. Another important aspect of SC management is the optimization of delivery routes for building materials. This process involves considering the factors affecting road congestion, weather conditions, vehicle availability, and other unpredictable variables. Employing AI helps in the analysis of data in real time, optimizes routes according to the then prevailing situation, reduces time wastage in transportation considerably, and reduces fuel consumption. In addition, it can automatically provide alternative ways in case of prob-
lems arising from traffic or accidents to improve delivery time estimation with better service levels for the customers.
Automation of the operation in a warehouse is the most crucial ingredient of effective SC management, as building materials, most of the time, need a huge volume to store in the warehouse. With the help of AI, it is possible to increase the speed and accuracy of processing materials in warehouses. Robots on this basis are able to perform various actions, from receiving to placing, moving and shipping goods, with much fewer errors. Moreover, these systems can integrate data on material availability and movement, forecasting optimal inventory levels and avoiding both surplus and shortages. Algorithms can also dynamically redistribute materials within the warehouse, ensuring the most efficient use of space, which reduces costs and improves operational efficiency.
The management of risks associated with possible supply disruptions, environmental changes and natural disasters plays an important role in the management of SC of building materials. With the help of AI, companies can monitor all stages of delivery and quickly identify potential problems. For example, when predicting adverse weather conditions or other factors, it can offer alternative routes or delivery methods, minimizing the risks of delays and financial losses. Thus, AI allows not only to increase the security of supplies, but also to more effectively manage the risks associated with a changing external environment.
Its application in construction material logistics significantly optimizes costs. This includes not only logistics processes such as transportation and storage but also administrative costs related to inventory management and data processing. Implementing AI contributes to better service quality, improved forecasting accuracy, and reduced time spent on various operations. Using such technologies allows companies to substantially reduce operational costs and improve the overall efficiency of business processes.
An example of the effective use of AI is the system implemented by Caterpillar, a leading construction equipment manufacturer, to optimize logistics for delivering large-scale materials and equipment. The company uses solutions based on it, which analyze real-time data on road conditions, weather conditions and traffic congestion, which allows you to optimize delivery routes and minimize fuel costs and downtime. This solution has demonstrated its effectiveness by improving delivery time forecasting accuracy and enhancing customer service levels [1].
Thus, the implementation of AI in managing construction material SC opens up new opportunities for improving efficiency, reducing costs, and enhancing customer service. It helps address demand forecasting challenges, route optimization, warehouse automation, and risk management, providing significant competitive advantages for construction companies. In the face of global economic changes and uncertainty, such use becomes a critical factor in ensuring the stability and successful development of businesses in the construction industry.
Big data in construction material SC management
Big data technologies play a crucial role in modern construction material SC management. In the face of growing competition and uncertainty in the construction materials markets, as well as significant logistics and storage costs, their use helps optimize processes, improve decision-making speed, and reduce costs.
One of the most important applications of big data in construction material logistics is data collection, storage, and analysis. Historical order data, material demand data, information about seasonal fluctuations, as well as data about the availability of transport routes and weather conditions help create more accurate forecasts and determine optimal inventory levels. By using this data, companies can not only predict the demand for construction materials but also plan purchases taking external factors into account, significantly reducing risks associated with shortages or surpluses. An example of this is the use of analytical platforms in construction companies that collect and analyze real-time data about supply and demand, enabling them to adjust purchasing and warehouse inventory based on changes in the market situation. For instance, LafargeHolcim, the world's largest producer of construction materials, uses big data-based solutions to analyze market demand and optimize cement supplies. This allows them to accurately plan production and supply volumes, minimizing excess and shortage, while also reducing operational costs [2].
The use of big data for trend analysis in the construction industry is also an important aspect of SC
management. Information about trends in construction, customer preferences, and global economic changes, collected through various channels, enables companies to predict which materials will be in demand in the future. This helps in more accurate procurement planning and reducing excess inventory in warehouses. For example, by analyzing data on the preferences of developers, companies can prepare specific construction materials in advance, improving interaction with clients and reducing delivery time.
Special attention within the framework of using big data is paid to route optimization and supply monitoring. They allow you to track the movement of goods in real time along the entire SC - from the manufacturer to the end consumer. Data on traffic congestion, weather conditions, vehicle availability, and other factors help optimize delivery routes and minimize costs. Systems based on this database can automatically adjust routes and redirect vehicles if logistics problems arise, such as traffic jams or worsening weather conditions [4]. This increases the accuracy of forecasting delivery times and minimizes downtime, which is extremely important for construction projects where each delay can cause additional costs.
Forecasting and risk management also play a vital role in construction material logistics, and big data significantly enhances this function. Forecasting models using market data, weather conditions, political situation, and even economic indicators can predict potential SC disruptions or market changes. For example, such systems can take into account data on potential natural disasters or economic sanctions that may affect supplies from specific regions and proactively suggest alternative strategies.
Thus, big data opens up new opportunities for optimizing all stages of construction material SC management. Accurate material demand forecasting, delivery route optimization, supply tracking, and market trend analysis are made possible through the integration of big data. Implementing such solutions allows construction companies to not only reduce costs but also increase operational accuracy, improve customer service quality, and enhance risk management. In the constantly changing market conditions and uncertainty, such use becomes an important factor in achieving competitive advantages and ensuring business stability.
In addition to AI and big data analytics, there are several other advanced technologies that also play a significant role in optimizing logistics and SC for construction materials (table 1).
Table 1.
Technologies for optimizing logistics and sales [5, 7]
Technology Application in logistics and sales of building materials Advantages for logistics and sales
Blockchain Ensuring transparency of the SC, tracking the origin and quality of materials. Increasing trust between the participants in the chain, reducing the risks of fraud.
Internet of Things Monitoring the condition of materials and vehicles, improving inventory management. Increasing the accuracy of forecasting, reducing the cost of damage to materials.
Digital Twins Modeling of processes and facilities for forecasting and optimization of logistics. Improved forecasting and coordination, increased process efficiency.
3D printing Printing of building materials on site, reducing transportation costs and waste. Reduction of transportation costs, reduction of time for delivery of materials.
Autonomous vehicles and drones Delivery of materials to hard-to-reach areas, improving transportation efficiency. Reduced labor costs, increased safety, improved delivery speed.
According to the author, the use of advanced technologies significantly improves logistics processes and construction material SC management. Each of these technologies contributes substantially to enhancing transparency, security, and efficiency of logistics operations, enabling companies to more accurately forecast demand, optimize delivery routes, and improve inventory management.
Conclusion
The use of modern technologies in the management of logistics and SC of building materials opens up significant opportunities to increase efficiency, reduce costs and improve the quality of service. These innova-
tions make it possible not only to optimize logistics processes, but also to improve interaction between its participants, increase safety and improve forecasting accuracy.
Thus, the application of advanced technologies to optimize logistics and sales of construction materials becomes a strategically important tool for increasing competitiveness and business resilience in the context of global uncertainty and dynamic market changes. The implementation of such technologies contributes not only to improving operational efficiency but also to the creation of more flexible and sustainable business models that can easily adapt to changes in market and economic conditions.
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