The Logistics Analytics Advantage: Business Intelligence & Optimized Operations

As retailers with overstock and “a range of measures of shipping demand across the U.S. are sliding, freight rates are falling as a result,” according to an article in The Wall Street Journal and various other sources. This pattern has reduced capacity, making it more challenging for shippers to get the shipping capacity they need as they also deal with other challenges affecting the supply chain.

In response, logistics professionals seek innovative ways to improve operations efficiency. Analytics and business intelligence can help. Logistics analytics relies upon data relevant to supply chain management and the logistics operations of a company. It can help shippers optimize operations by enabling them to track shipments, consider trends, create better delivery processes, streamline costs, consider supplier performance, and create better customer service.

Benefits of Logistics Analytics

Data analytics in logistics can provide shippers with a host of important benefits. These include the following.

Automated Data Collection Processes

Quality data is the key to meaningful analysis. You can automate the collection of certain data like that from carrier invoices, order files, and tracking events. Automated data collection processes introduce benefits that include:

• Faster data processing
• More accuracy
• Fewer resources spent on manual data entry
• Reduced costs spent on labor and errors
• Real-time insights and analytics, which guide decision-making
• Improved performance

Automation also helps create optimal efficiency in event tracking throughout a given supply chain. By tracking events, you can see exactly where a slowdown happened. You can also use data to detect the carriers that best suit your existing freight infrastructure and identify patterns like the carriers with the highest exceptions and freight loss instances. This kind of information helps shippers create a more dependable carrier network, allowing them to adjust to fluctuations within the industry as they arise.

Improved Real-Time Visibility

Gaining access to more relevant data creates more real-time visibility in logistics to help parcel shippers immensely. Increased data shares more information about the shipment process, and technology allows shippers to gain this information as it’s happening throughout the shipping process to stay on top of every step.

Improved visibility allows shippers to:

• Track their shipment progress better and immediately catch and address potential concerns
• Reduce delays by planning ahead and anticipating potential problem spots
• Communicate better
• Create more efficiency

Improved Supply Chain Efficiency

Parcel shippers can use analytics to improve supply chain efficiency. Through data analytics for logistics, shippers gain detailed insights into performance and cost. They can use the insights gained to create more efficient processes and better shipping strategies while they also continue to notice areas for improvement. Ultimately, making data-based changes like these can lead to significant benefits for supply chain efficiency, such as improved service levels, cost savings, and higher customer satisfaction.

Effective analytics can bolster performance related to various supply chain events:

• Allocation Strategies: Analytics reveals opportunities for consolidation, allowing shippers to maximize capacity. This benefit is significant when capacity is limited. 
• Mode Switching: Analytics can track when a parcel switches between modes, such as from a semi-truck to a last-mile delivery vehicle, and identify which of these mode switches are prone to slowdowns. Insights like these help shippers optimize strategies to avoid future issues. For instance, they may change modes for a certain part of the journey or change to a carrier or location that handles that mode or mode switch better, using data to show which modes, carriers, and locations are the most efficient.
• Hub Injection: Hub injection strategies often boost efficiency, yet in busy warehouses, they can sometimes lead to mishandling. Analytics can show shippers the sources of repeat exceptions, enabling them to refine their hub injection strategies around reliable logistics partners.

Challenges with Implementing Transportation Analytics

Data analytics in logistics and supply chain management are helpful to shippers, and the business intelligence they can glean from analytics is invaluable to improving supply chains and operations. Yet, that doesn't mean it's easy to reach the goal of analyzing data. There are numerous challenges to implementing analytics and keeping up with the process from then on. 

Cost of Technology

Shippers who want to implement analytics may find the cost of technology a major barrier to moving forward. Many shippers won’t have the budget for the necessary logistics analytics software and hardware needed to analyze big data, in addition to extra expenses for ongoing maintenance and upgrades. The running of this technology also requires expenditures on staff who can maintain it. The costs involved in adding this technology to a company can be prohibitive — an important factor that deters many shippers from taking full advantage of the opportunities analytics can provide.

The Difficulty of In-house Aggregation

Another challenge of doing it yourself with analytics is that aggregating raw data can be a complicated process. This requires the right tools and expertise, as well as the time and resources to go into the process. When your company cannot fully devote these factors to in-house aggregation, it’s easy to struggle with efficiently transforming large (sometimes massive) amounts of data into actionable analytics and insights that guide decisions. The process can become inefficient and even debilitating, defeating the purpose of trying to collect and use the data. This difficulty can prevent shippers from ultimately making decisions that can improve operations. In the end, the analytics efforts and the lack of strategic action cost valuable time and money.

Lack of Standardization

It’s not so difficult to collect data, but data from different programs, purposes, and parts of the organization are not standardized. It doesn’t match up to allow you to quickly and adequately compare and use it. When the data is not standardized, it can be challenging to compare it accurately across different sources, which hampers shippers’ ability to identify trends and take corrective action.

This challenge shows why standardizing the data becomes another part of the logistics analytics process. But, what ends up happening for many shippers who try in-house analytics is that they struggle to make sense of their data and instead end up in a state of confusion and inefficiency. Overall, achieving standardized data is essential for allowing shippers to maximize the value of their data and make informed decisions from that data.

Best Practices for Implementing Transportation Analytics

Shippers who are ready to move forward with using data to inform logistics decisions can follow best practices for doing so.

• Develop a Clear Implementation Plan: Create a comprehensive plan that lays out things like the type of data you will collect, how you will collect it, how you will standardize it, and how you will analyze the data and turn it into insights for decision-making. Determine the steps, resources, and staff members needed to implement data analytics.
• Take Advantage of Existing Tools: Shippers likely already have tools or access to tools that provide relevant data. Take an inventory of these tools and sources of data when starting your data analytics process. For instance, your company likely already has access to carrier tracking that helps you gain some visibility on your shipments. You also have data from things like carrier invoices and logistics systems like transportation management systems.
• Partner with the Experts: Another best practice is to work with experts in transportation data analytics and insights. This step can prevent or minimize the need for your company to implement its own data aggregation processes. You can cut down on a lot of costs and other resources. In addition, you can get more out of the data you collect by working with industry experts and getting started much faster.

Gain Expert Help with Business Intelligence

Logistics analytics can provide various benefits to shippers, including automated data collection, better real-time visibility, and improved supply chain efficiency. In addition, analytics can help companies perform better in response to various events in the supply chain, keeping up with changes as they occur, such as falling freight rates.

Intelligent Audit can provide the expertise shippers need to analyze logistics data effectively and gain business intelligence from it. Relevant services Intelligent Audit offers include:

• Real-time Visibility for Parcel Shipping: Through the use of innovative Application Programming Interface (API) strategies, Intelligent Audit has helped top parcel shippers gain end-to-end real-time visibility.
• Cloud-Based Communication: Intelligent Audit offers a cloud-based platform that removes outdated and inefficient processes and makes communication between logistics providers simpler and more convenient.
• Contract Optimization: Intelligent Audit’s experts offer industry-leading contract optimization backed by 20 years of industry experience. Shippers gain modern digital methods to replace manual processes.

Find out how Intelligent Audit can help your company implement data analytics for logistics and use that analysis to create better business decisions. Start a conversation with Intelligent Audit today.