Supply chains are complex systems with many moving parts. To ensure that everything runs smoothly, analytics are used to optimize the flow of goods and materials through a supply network. Data analytics helps businesses optimize their supply chain processes and operations so that they can save time and resources. In this blog post, we’ll take a closer look at how analytics are used in supply chain planning and how they can help businesses achieve success.
Supply Chain Management Versus Business Analytics
Business analytics and supply chain management are both important components of running a successful business. However, they differ in terms of their focus and objectives.
Business analytics are a set of many components that are used to collect, process, analyze, predict, and present data in order to drive business decision-making. In contrast, supply chain management is the process of creating and fulfilling demands for goods and services between different parts of the supply chain in order to meet customer demand. Since supply chain management is focused on managing the flow of goods and materials, from suppliers to customers, there is a greater concern with logistical issues such as transportation and warehousing.
How Business Analytics Are Related to Supply Chain Management
Despite their inherent functional differences, both business analytics and supply chain management can be implemented together to help businesses stay competitive in today’s marketplace.
When applied to supply chain management, business analytics are used to identify inefficiencies and forecast future demand. This information is used to make informed decisions about where to source materials, how to allocate resources, and how to optimize the production process.
Supply chain management analytics is the application of big data and statistical techniques to the field of supply chain management. These analytics can be used to optimize various aspects of the supply chain, including inventory management, transportation, and warehousing. In recent years, the use of analytics in supply chain management has grown rapidly, as businesses have increasingly recognized the potential of big data to improve their operations. In fact, the supply chain big data analytics market is expected to reach $9.28 billion by 2026.
How Data Analytics Are Used in Supply Chain Management
By analyzing data from different parts of the supply chain, businesses can identify inefficiencies and potential improvements. The following are ways analytics are used in supply chain planning.
- Track the movement of goods through the supply chain, pinpointing delays and bottlenecks.
- Forecast demand, ensuring that the right amount of inventory is always on hand.
- Assess supplier performance, helping businesses to identify vendors who consistently deliver late or damaged goods. By leveraging data analytics, businesses in the supply chain can optimize their operations and improve their bottom line.
Data analytics can clearly provide businesses with the ability to make more informed decisions. By using analytics to improve their supply chain management, businesses can improve their overall efficiency and competitiveness.
What Are the Benefits of Supply Chain Analytics?
Supply chain analytics have the potential to transform businesses by enabling them to make better decisions about where to source materials, how to manage inventory, and how to optimize their production processes.
Information collected can help businesses to identify opportunities for cost savings and improve their overall competitiveness in the following ways:
- Greater visibility into supply chains
This is achieved through the use of data analytics tools that can track and analyze data from multiple sources. Once businesses have visibility into their supply chains, they can start to identify areas where improvements can be made.
- Efficient inventory management and replenishment planning
By having real-time visibility into inventory levels, businesses can avoid the need to overstock or understock materials, resulting in lower inventory costs. Analytics helps to create a clear plan by considering when and where businesses should ship products. There is greater efficiency in the distribution of products, resulting in increased customer satisfaction, as products will match what was promised.
- Optimized production planning
Understanding how materials are used throughout the production process can help businesses optimize their processes to reduce waste and increase efficiency.
With predictive analytics, businesses can find the best and most cost-effective suppliers. It takes into consideration scoring models for quality of vendors as well as their stability over time.
- Transportation efficiency
Analytics can predict and visualize the most efficient shipping routes, backhaul routes, shipment scheduling techniques, and any constraints and compliance that must be followed.
Get Started With Supply Chain Analytics
In today’s global economy, the supply chain has become increasingly complex, with goods often traveling thousands of miles before reaching the consumer. Data analytics play an essential role in supply chain planning by giving businesses greater insights into their operations. Machine learning and visualization tools help businesses make data-driven decisions and steps, which add data intelligence to the business. With the use of these tools and software in the supply chain, not only is the operation becoming easier, but the services are significantly improved.
When you’re ready to get started with better data analytics solutions, talk to the experts at GraceBlood.
Learn more about how to thrive in a world full of supply chain challenges in our free eBook: Supply Chain Insights