A pandemic, the war in Ukraine, the tense political situation between China and the US, or economic factors such as rising fuel prices and inflation, have made it necessary for companies to look hard for ways to rebuild supply chain resilience and security, and sources of supply chain optimization. One of these is investment in technology and broad-based digitization, which should extend to almost every area of supply chain operations.
According to the Digital Global Trends in Supply Chain 2022 survey, conducted by PwC, 63% of managers cite increasing efficiency, 59% cite cost reduction, and 21% cite process automation and analytics as top priorities in the supply chain. Similar findings were also included in the survey, conducted by IHS Markit. Building chain resilience was identified as a top priority by 35% of respondents, representing 85 countries and 36 different industries.
In the area of supply chain management, companies are looking for various ways to increase their efficiency and reduce risks. They are doing this by, among other things, increasing inventory reserves to respond more quickly to increases in demand and minimize supply outages, more emphasis on micro-manufacturing to reduce “last mile” costs, or improving supply chain forecasting. Any change in approach, however, requires investment in technology solutions to provide accurate and reliable real-time data and complex analytics to better control processes and resources.
Reliable data, presented in an appropriate, customized way, allows us to solve pressing issues related to each stage of the supply chain. And this is what companies are increasingly betting on. Traditional, unreliable and time-consuming solutions are beginning to be supplanted by technology 4.0. In uncertain times, we are starting to take more interest in how to anticipate undesirable situations and prevent them in advance, which in the long term translates into greater savings and reduced risk of loss, comments Szymon Miałkas of Blulog.
To confirm the growing role of data and digitization, it is worth citing results from a survey by global logistics group GEODIS, which indicate that data analytics will be a technology priority for implementation, as indicated by 41% of respondents. This was followed by respondents selecting IoT solutions (39%), cloud computing (39%) and predictive analytics (29%).
The 3 Most Desirable Technologies to Support Data Acquisition and Supply Chain Monitoring
One of the essential elements supporting the modern supply chain is Internet of Things (IoT) solutions. First and foremost, they allow the supply chain to be monitored in real time and data to be captured at every stage of the process. It’s not just location information that helps track shipments and easy identification during transportation or storage. IoT makes it possible to monitor parameters such as temperature, humidity or light, which makes it possible to see what condition a shipment is in, whether it was transported under appropriate conditions that could affect its condition, or whether it was, for example, opened during the logistics process.
Data acquired through IoT devices, such as RF or NFC sensors, helps minimize the risk of lost or misplaced shipments and loss of quality. Tracking parameters such as temperature is particularly important when transporting food products that may spoil. Food safety is one of the biggest challenges in logistics. Real-time control of conditions must therefore take place at every stage of the process – from the moment it leaves the factory to its delivery to the end user, the store. IoT provides us with all the necessary data that can help minimize losses, speed up processes, eliminate errors or tampering, and automate, explains Szymon Miałkas.
- Data analytics
Any data provided, such as from IoT devices, requires proper integration, processing and visualization, in such a way that the information is as precise and transparent as possible. This, however, is not so simple. In the aforementioned IHS Markit survey, respondents identified several problems in this area, including: integration of user data (18%), timely and easy access to data (18%), and manual data checking and errors (16%). The solution, then, may lie in systems that allow information to be extracted from various sources, easily processed and standardized. The more automated this process is, the lower the risk of errors, and the faster the company will begin to reap the desired benefits.
Artificial intelligence and machine learning are becoming increasingly popular in many areas of business and industry. In the supply chain, their use in predictive analytics may also soon find application. By quickly analyzing data, recognizing patterns and trends, adjustments can be made more quickly, such as by suggesting more cost-effective routes, anticipating potential problems. It’s also another step toward automation.
Data analytics will find its way into every company – just think of Blulog’s projects, which have already translated into savings. Our client DHL, thanks to the use of our loggers, can read data at every stage of transport. However, this is just one example of use, as the number of combinations in which data analysis can be used for predictive purposes is virtually endless – optimizing energy consumption, the temperature of heating or cooling equipment, introducing digital twins of packages or manufactured products. All this ultimately boils down to real savings, adds Szymon Miałkas.
- Cloud computing
Classic server solutions are slowly becoming obsolete, both functionally and financially. Above all, if a company wants to collect data and use analytics, and make it as accessible as possible from anywhere in the world, then cloud solutions are the best choice. Any applications developed in this environment are much easier to implement in the enterprise, because they are practically available immediately. It is also not cost-effective to build, expand and maintain your own infrastructure – the cloud allows you to increase resources depending on your current needs. Security issues are also important – already the native protection provided by reputable cloud providers stands at a very high level.
Digitization the Path to Stability
Progressive digitization is first and foremost an investment in increasing security and stability against changing economic and political conditions and the possibility of disruptions causing financial losses.
The turning point was the first wave of the pandemic, which caused massive supply perturbations and motivated organizations to implement analytics in their chains. Commodity suppliers are a case in point. McKInsey reports that as many as 75% of companies in this sector have implemented or begun to make stronger use of analytics since the pandemic broke out, and another 25% plan to do so in the coming years. Each economic sector has its own characteristics, of course, and the pace of transformation and its intensity will vary, but digitization is inevitable.