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How Analytics Can Improve the Efficiency of Supply Chain Management

Sept. 19, 2024

Supply chain management is a communications-intensive process in all aspects of an organization, from procuring raw materials to selling finished products. To optimize supply chain management efficiency, companies should use analytics. 

Analytics provide insights into how enterprises utilize resources and the impact of resource utilization on organizational effectiveness. This understanding can be used to better plan for and manage future projects.

The freight brokerage industry is one of the most intricate and fundamental segments of the transportation industry. Freight brokers need to leverage analytics tools and data analysis to streamline their supply chain management. 

Let's look at how analytics can improve supply chain management efficiency for freight brokerage and trucking industries by demonstrating how analytical solutions increase profitability by managing cost-to-serve risks.

The Growth of Data Analytics in Supply Chain Management

Supply chain management is an ever-evolving process within business environments. The overall coordination of all supply chain activities leads to the delivery of products and services from vendors to consumers. Supply chain management includes procurement, production and inventory management for marketing, sales, delivery and after-sales services.

Firms can optimize their operations and increase their bottom line by making data-driven decisions. Data availability and the decline in the price of computer power have led to the development of analytics.

Transportation companies are a vital component of supply chain management. The freight brokerage industry plays a massive role in supply chain management by providing solutions for transportation needs, including trucking, ocean shipping and air cargo solutions. 

Freight matching links transportation companies with freight brokers who supply goods and services to clients in a way that optimizes supply chain efficiency. 

Freight brokerage and trucking firms need to identify opportunities to improve their business operations by leveraging analytical solutions, such as data-driven decision-making, in the form of enterprise resource planning (ERP) software and analytics.

Analytics will be even more critical in the future as businesses work to become more adaptable and responsive to the constantly changing customer needs.

How Data Analytics is Modifying the Supply Chain Environment

Analytics provides operational insights to help businesses make the most of their freight brokers and trucking services. By leveraging analytical solutions, companies can remain competitive by better managing risk and working to reduce costs.

In the past, it took a lot of work to comprehensively understand the supply chain since several corporate sectors dispersed the data. However, organizations can now gather and store data from every link in the supply chain, owing to data warehouses and data lakes. 

Additionally, most supply chain management in the past relied on experience and intuition. With powerful data analytics technologies, however, supply chains are now governed by data-driven choices.

Supply chain managers can make data-driven decisions that boost productivity and efficiency. Managers may now make sense of big data sets and find hidden patterns and trends thanks to various powerful data analytics technologies. 

The desire for a greater rate of return through optimization has led to innovations in technology infrastructure, with the expansion of data analytics being a catalyst for this growth.

How Supply Chain Analytics Improves Efficiency

Companies use data analytics to monitor their supply chains in real-time, spot problems as they develop and swiftly adjust their plans. Analytics is also beneficial in many aspects of a trucking company's operations, such as driver recruitment, routing and scheduling, productivity measures, logistics, efficiency measurements and more.

Let’s see how supply chain analytics improves efficiency:

Optimized Production Schedules
Analytics allows freight transportation companies to create optimized production plans, improving efficiency. For instance, with the help of ETL (extract, transform and load) tools and predictive analytics solutions, businesses can streamline the management of their supply chains and enable data sharing across all business units in a company.

Predictive data analytics help optimize production plans by supplying information to aid decision-making regarding production runs. It can offer reliable information regarding client demand, production capacity, inventory levels and other aspects affecting production schedules.

Enhanced Cargo Shipments Efficiency
Analytics improves the efficiency of cargo shipments by helping ensure you utilize vehicles and conveyances appropriately. The advent of ERP systems and data analytics has helped freight transportation companies increase the performance of their supply chains.

Logistics organizations can use analytics to track and forecast shipments, optimize routes and enhance customer service for land freight operations. You can trace shipments and foresee delays with them. The logistics company can utilize data analytics to identify the reason for a shipment delay and take action to prevent it.

You can also use analytics to analyze how your freight network is currently used and find potential areas for improvement. Improved demand projections help you plan your transportation more confidently.

Inter-functional Collaboration
Inter-functionality is one of the most significant trends in the supply chain industry, which refers to the convergence of functions. Today, supply chain management requires companies to work closely with departments beyond their business operations. Data analytics allows supply chain managers to work across several different organizational boundaries.

Other Advantages of Data Analytics in Supply Chain Management

Here are extra advantages of data analytics in supply chain management:

Lowered Inventory Costs
Analytics can help in the management of inventory costs. By leveraging analytical solutions, freight transportation companies can lower their inventory costs. They can do this by analyzing how to optimize their capital expenditures and reduce over or understocking.

Businesses enhance their performance by identifying inefficiencies in their inventory management procedures with data analytics. Data analytics assist companies in gaining a competitive advantage and improving their bottom line by lowering inventory costs and streamlining operations.

Lowered Risks
A supply chain's performance can be affected by various hazards, such as interruptions in the flow of supplies, modifications in client demand and problems with suppliers. Organizations can recognize these risks beforehand and take action to reduce them by employing data analytics

Wrapping Up

Many organizations rely heavily on freight. It is challenging to keep track of all the shipments and handle them efficiently. By controlling all of their shipments in one location, digital freight forwarding platforms integrated with analytics enable businesses to streamline their supply chain.

Future expectations are that the supply chain will be even more data-driven and analytics-oriented, with organizations able to administer and manage their extended supply chains easily.

About the Author

Nick Fryer

Nick Fryer has over a decade of experience in the logistics industry, spanning marketing, public relations, sales enablement, M&A and more at 3PLs and 4PLs including AFN Logistics, GlobalTranz, and Sheer Logistics.

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