Using Apples-to-Apples Logistics Data to Make Better Carrier Selection Decisions

Just a few short years ago, finding a carrier was no easy task – it seemed like they held all the cards. However, the logistics landscape has shifted dramatically to a shippers market. Now more than ever, it's crucial to use apples-to-apples data when selecting a carrier to capitalize on cost savings opportunities and improve carrier performance.

Shippers have every reason to be thrilled this season, thanks to an all-time low tender rejection rate, stable volumes, and a double-digit capacity increase in the freight market. Although carrier executives remain optimistic, predicting a better second half of 2023, consumer financial stresses could still lead to a worsening freight market. In this increasingly fractured freight market, leveraging accurate and relevant freight data when selecting a carrier is more important than ever. 

This article will provide a deep dive into the importance of data analytics in logistics, the pitfalls of bad-apple data, and how to harness the power of accurate information to make informed choices that positively impact your bottom line.

Bad-Apple Data Leaves Shippers With Soured Carrier Performance

Both Abraham Lincoln and Albert Einstein receive credit for the quote, “If it’s on the internet, it must be true.” While this bad apple data is easy to spot, bad apple data from a carrier isn't so obvious. The use of antiquated or bad apple logistics data in supply chains can lead to significant problems, impairing the ability of professionals to carry out their operations effectively. This, in turn, can result in biased decision-making, rendering benchmarking exercises essentially useless. Further, the increased risk levels and operational costs arising from outdated systems can cause supply chain leaders to lose sleep at night. Let's explore the negative impacts of these issues in more detail.

Biased Decision Making: Inconsistent data from a carrier database can introduce biases into the carrier selection process. Shippers may unknowingly favor certain carriers based on incomplete or inaccurate information, leading to suboptimal decisions and missed opportunities for improvement. For instance, outdated performance metrics may lead you to choose a carrier that no longer meets your service expectations, causing customer delays and dissatisfaction.

Ineffective Benchmarking: Establishing reliable benchmarks for carrier evaluation becomes a herculean task without standardized data. Comparing carriers objectively and identifying their strengths and weaknesses is challenging when dealing with disparate data sources and formats. Even the best logistics data analyst will struggle to pinpoint areas of improvement and capitalize on potential competitive advantages when using inaccurate freight data.

Increased Risk and Costs: Inconsistent data can result in selecting carriers that do not align with specific operational requirements or cost objectives. This can lead to increased risks, such as service disruptions or higher costs due to inefficient operations. For example, choosing a carrier with a history of late deliveries or damaged goods may drive up your overall logistics costs and negatively impact your brand reputation.

This case study highlights the pain of comparing apples-to-oranges data in carrier selection when a retailer recently chose a cheaper carrier with seemingly all-inclusive pricing. However, Intelligent Audit's machine learning and anomaly detection quickly identified hidden beyond charges, enabling the customer to switch to a more transparent carrier and save thousands in the long run.

What is Apples-to-Apples Logistics Data?

Apples-to-apples logistics data refers to standardizing data sets across operations, enabling full-chain benchmarking and performance analysis. Accurate data sets are crucial during difficult moments for the transportation industry, such as the current turbulent freight market. 

Accurate data can provide insights into the factors contributing to the softness in the market, such as the expansion of capacity over the past few years, which has led to an oversupply of trucks compared to relatively stable freight volumes. This information can help stakeholders identify potential areas for improvement or adjustment in their operations.

So, what does apples-to-apples logistics data bring to the table?

Objective Evaluation 

Standardized data enables fair and unbiased assessments of carriers' capabilities. It provides consistent metrics and performance indicators, which supply chain professionals can leverage to make informed decisions that align with their strategic goals and operational requirements. With the ability to consistently collect and analyze data, supply chain professionals can easily identify trends over time, allowing them to make more meaningful and data-driven decisions. The result is a more optimized supply chain that improves operational efficiency and profitability.

Risk Mitigation

When it comes to selecting carriers, detailed information is crucial. With standardized data, shippers can conduct thorough due diligence and assess a carrier's track record, reducing the chances of selecting an unreliable or underperforming carrier. Supply chain managers can ensure smooth sailing by minimizing disruptions and avoiding unnecessary costs and delays. Ultimately, this translates to happier customers, stronger relationships with business partners, and an optimized carrier network.

Cost Optimization

Analyzing carrier rates, comparing pricing structures, and negotiating contracts based on standardized data leads to more favorable pricing terms and improved cost efficiencies in supply chain management. This includes carrier rate benchmarking, a process whereby shipping rates are analyzed and compared to industry standards. Once the rates have been compared and benchmarked, it becomes easier to identify areas in which to reduce costs. By allocating resources more effectively, supply chain professionals can ensure their business runs at peak efficiency, with minimal wastage and maximum cost savings.

Now that we've established the importance of apples-to-apples logistics data, let's explore how to harness its power in your supply chain operations.

Steps to Harness the Power of Big Data in Logistics

Companies of all sizes grapple with the challenge of normalizing and making sense of the vast amounts of data available in today's data-driven world. When properly harnessed, data can unlock tremendous advantages for businesses, empowering them to draw valuable insights and drive greater efficiency and cost-effectiveness in managing their supply chains. 

Step 1: Invest in Data Analytics Tools and Technologies

Investing in technology and solutions is essential to fully leverage the benefits of apples-to-apples logistics data. These solutions enable supply chain professionals to collect, analyze, and visualize data from various sources, providing actionable insights that drive better decision-making. Data analytics tools and technologies in the freight industry are imperative to optimize carrier networks and logistics operations. By leveraging advanced analytics, businesses can achieve the following:

  • Accelerated decision-making, enabling the expansion of their network with more vendors, carriers, lanes, and other factors for increased efficiency
  • Enhancements across all processes, reducing the manual workload in managing back-office operations
  • Access to powerful and practical tools that simplify exception management and streamline workflows
  • Improved collaboration throughout the supply chain, including the returns process, fostering greater sustainability
  • Mobile access and advanced technology integration help achieve deeper learning 
  • Seamless collaboration with third parties involved in load matching, final mile delivery, and parcel services, leading to more effective processes and overall logistics optimization
  • Superior customer service and feedback cycles, utilizing insights from the entire shipment lifecycle to develop a metrics-driven, robust supply chain strategy.

Step 2: Establish Data Standards and Best Practices

Developing and implementing data standards and best practices across your organization is crucial for ensuring apples-to-apples comparisons. These logistical data standards create uniform definitions, metrics, and formats for critical data points and establish governance policies promoting data quality and consistency. 

Here are five best practices to employ data, utilize freight data, and gain valuable insights to reduce transportation costs: 

  • Bring Disparate Data Together & Normalize
  • Normalize & Standardize Data
  • Offer Actionable Insights to Help Reduce Transportation Costs
  • Connect Partner Data to Streamline Communication
  • Use Real-Time Data for Improved Deviation Response

Step 3: Collaborate with Carriers and Other Supply Chain Partners

Building a robust and collaborative relationship with carriers and other partners within the supply chain is essential, and this is where sharing knowledge, expertise, and best practices come into play. When everyone has the same knowledge and understanding of data standards, it's easier to achieve seamless data exchange, providing a more transparent and reliable view of operations. By establishing a foundation of trust and transparency, you can foster a culture of collaboration that leads to smoother data sharing and integration.

Step 4: Continuously Monitor and Optimize Carrier Performance

Apples-to-apples logistics data is not a one-and-done solution. Supply chain professionals must continuously monitor carrier performance and use data-driven insights to identify areas of improvement, optimize processes, and drive cost savings. This iterative approach ensures that your carrier selection process remains agile and responsive to changing market conditions. Additionally, by considering the expansion of your carrier network, you can take advantage of increased capacity, offering more flexibility and options in meeting your shipping needs.

Effectively tracking parcel carrier performance using apples-to-apples data and robust analysis is crucial to optimizing logistics operations. By utilizing data analysis, shippers can identify opportunities for improvement and know when to engage regional parcel carriers for the best results. Pre-auditing parcel invoices, exploring regional carriers' fees, and leveraging zone-skipping capabilities can reduce delivery costs and expedites. Incorporating technology for "what-if" scenarios and multi-regional network optimization strategies enables companies to remain competitive while decreasing their bottom line, ultimately enhancing customer experiences.

Find the Good Apples With Improved Carrier Selection from Intelligent Audit Today

Staying ahead in the logistics industry requires continuously optimizing carrier selection processes using data-driven insights. Intelligent Audit offers a comprehensive suite of services to help you achieve this goal, including powerful business intelligence and analytics, logistics network optimization, historical data assessment, logistics KPIs validation, cost analysis, carrier and distribution center network assessment, and network modeling.

Intelligent Audit empowers you to become a shipper of choice, leading to improved carrier acceptance rates and fostering better carrier relationships. By providing real-time and historical data carriers need to run their businesses, you can create a more efficient freight process that benefits everyone in your logistics network.

Take advantage of the opportunity to optimize your carrier selection process and transform your supply chain operations. Get started with Intelligent Audit today and experience the difference that accurate and standardized data can make in your logistics decision-making journey.

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