Digital Transformation of Supply Chain Management


Supply chains may be intricate to manage effectively. This complexity differs based on the size of the business, the nature, and the quantity of the products being manufactured. There is a need for efficient management of the supply chain because the linkage of interconnected systems should coordinate smoothly with the objective of providing services and products in a cost-efficient and proficient way. The major elements of supply chain management encompass planning, preparation, manufacturing, and distribution/conveyance of services and products (Zheng et al. 1924). In supply chain management, digital transformation prevents interruptions between production and virtual design through the provision of tools that respond to any problem encountered in the manufacturing process. Digital systems in factories assist in the provision of an all-inclusive data-propelled user experience, which enhances agility and the entire manufacturing process. With the manufacturing digital transformation, a company has interconnected machinery and real-time diagnostics, so there is faster problem resolution, improved machine utilization, and no unplanned downtime.

First Thoughts

Each unplanned pause on the factory floor causes slowdowns and makes costs escalate. Without operational transparency and connected machinery, there is no visibility. If there is an issue in the old processes, you would lose so much time trying to figure out what is wrong. Nevertheless, digital transformation will lead to a lot of money saved and quicker processes. Connected machines are making an impact on manufacturing and factories all around (Zheng et al. 1926). Manufacturers are going digital to make every machine online, to make every process visible, and connect every aspect of the supply chain. This helps deliver increased availability, performance, and product quality which also, in turn, results in more effective workers and informed management teams.

Digital transformation in the manufacturing sector cuts downtime speeds cycle duration and accelerates marketing. Overall, digital manufacturing offers a collaborative platform for global industrial operations, connectivity for edge computing to big data analytics, brings together the virtual and real-world models and maintains long-term planning to real-time executions. It empowers the user experience with comprehensive decision support. Everything is connected and secured. Digital transformation helps in gaining a competitive advantage by increasing productivity, helping in successful assessment of demand and consequent supply, elimination of all lean progressions, and facilitation of the level of productivity. Digital transformation of the supply chain management assists in the reduction of operating expenses and ensures an efficient cost of production (Zhong et al. 617). Service provision to consumers and the quality of products have been improved by practices such as instant response, reviews to boost value, betterment of communication with clients, understand customers’ preferences, flexibility to the client at any place and time, and operation round the clock.

New Understanding of “Digital Transformation”

Digital transformations in the manufacturing industry such as multi-tier manufacturing have caused the industrial sector to go 4.0. The 4.0 industrial advancement means that technology not only leads to a sustainable supply chain, but it also initializes and maximizes economic gains, reduces environmental impacts, and contributes to social development (Zheng et al. 1926). Multi-tier supply chains which are the new Industry 4.0 are turning out to be vital strategic means of reducing costs, decreasing capital assets, and assembling products to make marketing productive despite the existence of competition. A multi-tier supply chain means that one buyer is linked to multiple suppliers and their integration is done solely because of interrelated databases and technologies. Databases and cloud technologies such as Enterprise Resource Planning (ERP) systems have made it easier for buyers and suppliers to stay connected and place an order at the instant when needed. This connection between the buyer and supplier will enable digitalization through cloud-based databases and other technologies. Industry 4.0 has ensured that by using multi-tier supply chains and advanced technological tools, the supply chain process is revolutionized.

How Digital Transformation Impacts Today’s Supply Chain Management

A change that is happening in manufacturing today is that it is increasingly digital, democratized, and effective. Digital transformation offers the ability to make sensors throughout the factory floor capture data in real-time while integrating that with sophisticated modeling and simulation tools in conjunction with the capabilities to deal with uncertainty. Companies can track every part and each process, and they can capture the errors before they propagate, which comes close to the full available power of artificial intelligence. Nowadays, Manufacturing is moving towards “digital lean” which consists of a blend of timeless lean values and continually evolving digital expertise to lessen waste and inconsistency in processes. Lean manufacturing focuses on tracking root causes of problems and waste with help of decision-making based on data (Zhong et al. 619). Digital transformation in manufacturing will allow companies to have the required data, information, and accelerate the waste identification process letting firms mitigate the waste faster than what organizations are presently used to by doing away with traditional methods. This will also help to target the hidden elements of waste, like information irregularity and latency, which usually get unnoticed hence leading to inefficiency.

While integrating digital transformation into supply chains, numerous forms of data should be considered, encompassing information emanating from production processes that are supplied with sensors and other components such as ERP, customer relationship management, and manufacturing execution systems (Zheng et al. 1934). With respect to existing information, the application of data analytics is crucial to the conversion of knowledge to practices that convey actionable insights. In digital transformation, machine learning techniques and information presented are essential in data analytics progressions. Machine learning expertise employs intricate computational algorithms in the processing of vast data sets. Additionally, data visualization devices assist manufacturers to easily understand the knowledge entrenched in the available information. Eventually, the application of earlier secluded sets of data in the collection and analysis of facts gives companies the ability to establish new methods of optimizing processes that have a great impact on production.

In supply chain management, digital systems based on a cloud storage are gaining more and more popularity. Service-based software architectures and technical solutions are being actively explored by various researchers because of their potential prospects for many manufacturing benefits (Zhong et al. 627). The main advantages of cloud services are the reduced cost of the equipment combined with immense computing power. Thus, it becomes possible to create a vast and reasonably cheap infrastructure, which, nevertheless, will fulfill all the load assigned to it. Besides, cloud services themselves already have a reasonably organized structure, making it easier to integrate other systems into them and monitor devices. An additional advantage of cloud services is the ability to combine them with the Internet of Things (IoT). In a production context, such collaboration simplifies the interaction between individual devices and enables the implementation of analysis and statistical data collection systems. With the help of IoT and cloud services, all devices are connected to one network. Since there is a continuous exchange of information, it becomes possible to achieve a high system automation level. Cloud computing is paramount in digital transformation and has been in existence for over two decades. However, despite the evidence demonstrating its market efficiencies, cost-benefits, and competitive advantages, a sizable proportion of the business segment continues to operate without it.

ERP should be directly used in various kinds of enterprises and organizations. Since such systems are understood more as a concept, each company can have an ERP system designed to solve specific problems that are relevant in a given place. ERP has several main uses, including customer service, financial accounting, and supply chain management. The latter example can be successfully combined with the IoT, thereby increasing the entire system’s efficiency and effectiveness. Warehouses are often overly complex schemes that require a tremendous amount of effort to manage effectively. This process can be optimized, for example, by using automated guided vehicles (AGV) (Zhang et al. 11890). Such robotic machines can perform heavy and dangerous tasks for humans with machine precision, thus increasing efficiency. However, the introduction and use of the Internet of Things, in this case, can further improve the effectiveness of the system. Since one of the IoT features is the constant bi-directional exchange of information, an entire closed ecosystem can be created in which the automatic redistribution of materials and resources is carried out.

The manufacturing community, which includes small to large companies, should start to adopt digital transformation to solve the challenges in their businesses’ supply chain management. Implementing them is nowadays a must instead of representing a competitive advantage. Companies that do not include digital tools in their processes are allowing their businesses to be prone to be disrupted by other manufacturers who use them (Zhong et al. 628). Based on their business climate and their challenges, companies can adopt these tools in multiple ways. They can be implemented to accelerate their time to market, quicken innovation, and optimize their company’s supply chain. Making the change to become a smart factory is a strong investment that includes some risks.

In the research from Zheng et al., they state that there are numerous areas that manufacturers are expecting big gains in the first 5 years after investing in smart factories (1938). Such areas encompass labor cost (growing nine times more), Material, Logistics, and Transportation (growing by eleven times), and overall productivity which would be expected to grow 7 times greater on average per company. Some other areas that they mentioned that will have massive growth over the next 5 years after the initial investment are on-time delivery, quality and scrap, and Capex and Inventory. The author further states that one of the most beneficial outcomes of investing and making the transition to smart factories is the change in a company’s capacity utilization. However, the benefits will also be reflected in organizational costs, its quality, the revenue streams, and even in the value that is being delivered to customers.

By reducing the waste labor productivity, an organization is expected to grow over the years. A quick glance at labor productivity inclinations shows that smart factory creativities will possibly enable the United States manufacturers to enhance the labor productivity development level during its years of operation. When one talks regarding Real-Time data precision, there is proof of manufacturing firms having confidence and effective communication with the suppliers (Zhong et al. 618). Sometimes this would mean that manufacturing companies have the facility of remote monitoring, proactive maintenance, availability of data, and the resources to analyze it. All these benefits create the opportunity to avoid having to take rushed solutions and taking risks in many situations. With the digital transformation in manufacturing, the industry can get closer to its customers. Tools like eCommerce platforms would allow companies to track the behaviors of different clients and identify trends by their demographics. It would permit companies to better understand customer behavior and to predict accurately the demand they are going to have and adjust their production appropriately.

The Future of Digital Transformation

Another method of automating ERP in the future of digital transformation will be to incorporate emerging technologies, such as artificial intelligence (AI) and other fundamental features, such as the IoT. These new technologies will be integrated into ERP systems to allow the management of business processes to be more comprehensive and seamless. More precisely, these newer ERP systems will allow organizations to enhance their workflows, record-keeping, and forecasting capabilities (Zhang et al. 11893). AI-enabled ERP systems are making their way into the enterprise software industry, and these new software solutions naturally leverage one of ERP’s strengths—automating repetitive processes and integrating transactions through several departments or silos. AI aims to tighten the integration of these processes and allow increased automation.

AI integration into ERP systems has the potential to move workers away from tedious and routine tasks (for example, processing sales orders) and toward analytical and innovative tasks that AI cannot easily handle. This enables workers to learn new skills and abilities that lead to their personal growth within the company, but also to become more involved and contribute to the achievement of the organization’s goals and success (Zheng et al. 1944). Additionally, AI would be capable of predicting and executing simple transactions. In the future of digital transformation, it will be vital to consider the speech recognition capabilities of modern inbound voice recognition (IVR) systems as an example. Numerous companies, such as banks and other financial institutions, use these programs to route callers to the appropriate customer service representative based on the underlying customer’s needs.

When used in conjunction with ERP software, AI-enabled voice interactions can serve a variety of purposes. They will allow users to perform tasks and work activities without using their hands, thereby increasing the accuracy and efficiency of tasks and work activities. Additionally, they can be used for voice recognition to verify users and approved acts, enhancing protection (Zhang et al. 11892). In a nutshell, the trend toward increased ERP automation is neither novel nor shocking. Enterprise resource planning has always been motivated by the aim of automating as much as possible in order to archive critical data to improve its quality and usability, save time and effort to improve the productivity of business processes, and eventually reduce costs to drive business development and profitability.

Robotics and manufacturing are natural partnerships. It is one step to the future and now due to such AI-intelligent technologies, the manufacturing process will be performed at the least number of errors. Robotics undertake a vital task in the manufacturing process (Zhong et al. 626). Through digital transformation, manufacturing robots will mechanize repetitive tasks, lessen margins of error to insignificant rates, and enable human employees to concentrate on more productive parts of the operation. The simplest way to examine the AI-intelligent expertise is to look for approaches where small cooperative robots could fit into the manufacturing line and boost efficiency. Examples encompass robotic “choose and convey” arms that can mechanically install parts or do monotonous repetitive jobs. By swapping even, a fraction of tasks, one can facilitate producers to reserve people for more high-value actions.

Final Thoughts

Digital transformation is a collective of traditional manufacturing processes improved with new progressing technologies while striving to drive manufacturing forward and address inefficiencies in the current sector. This should decrease the competition for enterprises that are following suit. Robotic AI is the way most enterprises are leaning towards 3D digital manufacturing, IoT in Manufacturing. Most industries have adopted a cloud base presence, which ultimately allows an organization to save money and manpower (Zheng et al. 1947). ERP is a system to help solve a problem and provide actual-time data for customers and end-users. Integrating smart manufacturing and intelligent factories comes the relevance of apparent and real-time data. It is transparent despite the increasing challenges in manufacturing industries. Manufacturers using advanced analytics and automation will find ways to convert them into opportunities that are a significant way to compete in their line of operation.

The overall companies’ goal or mission of manufacturing in current cases is to increase productivity, lower costs, and reduce errors in a bid to report accurate data. Digital manufacturing is making it possible to be efficient by utilizing enhancement tools. Some known challenges have been unemployment and resource constraints. Companies should save money by adopting an automated system. Studies have shown that digitizing the manufacturing industry is increasingly being adopted by companies to make it possible to use the driving factors to their advantage and get the maximum efforts out of it (Zhong et al. 628). Organizations must realize that digital business is a reality, a new way of having a successful business. From small to large, most industries should critically evaluate digital technologies and how they would impact their chain.


Supply chains may be difficult to manage efficiently. This complexity differs anchored in the size of the business, the nature, and the magnitude of products being manufactured. There is a need for well-organized management of the supply chain because the connection of unified systems should coordinate smoothly with the aim of providing services and products in a cost-efficient and proficient mode. With the manufacturing digital transformation, an establishment has interlinked machinery and real-time diagnostics, so there is quicker problem resolution, enhanced machine utilization, and no unexpected downtime. Companies are going digital to make every machine online, to ensure that every process is noticeable, and connect every facet of the supply chain. Digital transformation in the supply chain cuts downtime speeds cycle duration and fast-tracks marketing. Databases and cloud expertise such as ERP systems have made it possible for buyers and suppliers to remain connected and place an order at the instant when required. ERP has numerous main applications, including customer service, fiscal accounting, and supply chain management. Companies that do not comprise digital tools in their operations are allowing their processes to be prone to disruption by other organizations who use them.


Zhang, Chao, et al. “Manufacturing Blockchain of Things for the Configuration of a Data-and Knowledge-Driven Digital Twin Manufacturing Cell.” IEEE Internet of Things Journal, no. 7, no. 12, 2020, pp. 11884-11894.

Zheng, Ting, et al. “The Applications of Industry 4.0 Technologies in Manufacturing Context: A Systematic Literature Review.” International Journal of Production Research, vol. 59, no. 6, 2021, pp. 1922-1954.

Zhong, Ray, et al. “Intelligent Manufacturing in The Context of Industry 4.0: A Review.” Engineering, vol. 3, no. 5, 2017, pp. 616-630.

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