Logistics data plays a critical role in transforming business operations through real-time, actionable insights that can be leveraged to increase efficiency, reduce costs, mitigate risks, anticipate and respond to supply chain obstacles, and drive customer satisfaction. Logistics companies such as third-party logistics (3PL) and fourth-party logistics providers can help shippers make sense of their data with advanced technology and skilled practitioners. Sheer Logistics has extensive experience in helping our clients harness and analyze their supply chain data to empower them to make better, more timely business decisions that enhance their competitive advantage in a challenging global market.
In this blog, I will describe the various kinds of logistics data; explain the uses of logistics datasets in supply chain management; discuss how logistics data can be used for inventory management and transportation optimization and compliance and risk management; outline best practices for capturing accurate logistics data; and share examples of successful uses of big data in the logistics industry.
What is Logistics Data?
Logistics data refers to the many types of information that is generated and collected throughout the entire supply chain regarding the movement, storage, and handling of goods, including:
- Transportation Data
- Inventory Data
- Delivery Data
- Customer Data
- Financial Data
- Supplier Data
- Regulatory Data
Big Data and Supply Chain Management Go Hand-in-Hand
Companies have always looked for ways to reduce costs and increase efficiency. But in the past, businesses lacked powerful tools to accurately and automatically collect data, analyze it to find connections, and present these insights in a way that allows decision makers to see trends, forecast demand, and change procedures.
Create a Single Source of Truth
Data fragmentation is a key challenge for business leaders. Data is often “siloed” within a business unit or legacy system that is disconnected or poorly integrated with the business at large. Companies that experience rapid growth, particularly through mergers and acquisitions, are often confronted with the challenge of integrating data from multiple and disparate platforms.
Removing silos between departments and storing data centrally, either in a data warehouse or data lake, makes data available to stakeholders for analysis and more timely and accurate decision-making. Stakeholders can stay informed and collaborate in real time, ensuring issues get resolved more quickly.
Automation All Along the Supply Chain
Delivery systems and supply chains are a careful balance between over- and under-committing resources. If there are too many vehicles and resources assigned to one delivery route, then you’re spending more money than you need to, and you’re possibly expending assets that could be better used elsewhere. Underestimation means deliveries may arrive late or are not being made at all. Automation in the supply chain process creates optimization, and the right logistics data analysis tools can accurately predict future needs so resources can be allocated properly. This kind of efficiency lowers costs, improves delivery times and enhances customer satisfaction.
Look At Processes From a Different Angle
Old systems and outdated forecasting models simply won’t work in today’s changing markets. Modern supply chains require modern supply chain data solutions to analyze anomalies, interpret changing customer patterns, recognize new demand signals, and accurately predict forecasts. As your ability to leverage data improves, the benefits resonate throughout the company; vendors are paid on time, sales teams work from accurate forecasts, inventory managers are more effective, and C-level decisions become more timely and impactful.
At Sheer Logistics, Information is Power
Compiling data is the first step, but the real value of information comes from an analysis that converts it into actionable insights to improve your business. Even businesses with limited resources can benefit from the data their organization generates every day. The issue is that it can be jumbled in a mess of spreadsheets, systems, databases, and processes separate from each other. The reality is that you don’t need to be a Fortune 500 company to leverage the same powerful business intelligence tools.
Better Data, Presented Visually, Leads to Action
What starts with collection and continues with analysis ends with effective, actionable reporting. Nobody wants to sift through stacks of numbers with no meaning. Even if they are reported visually, the reports have to be able to explain what the data says instead of simply showing the numbers. What is the point of logistics data analysis if the product can’t be understood? The best transportation management systems are ones that explain the data as well as collect it.
Reports shouldn’t be static documents that simply explain what happened. True data analysis gives future insight so companies have the edge they need to move quicker, plan better, and take advantage of opportunities that their competitors are most likely missing.
Valuable logistics data analysis can only come by integrating data sources.
Sheer Logistics provides the software tools you need to make your company better:
Sheer TMS
The Transportation Management System (TMS) is a powerful tool that automates the full transportation lifecycle, allows you to fully manage and control carrier contracts and scorecards, and delivers the granular data your business needs to improve and grow.
SheerExchange Integration
We use our expertise to integrate the Sheer TMS solution with every corner of your business. Think of SheerExchange as a universal translator that allows your TMS system to gather, interpret, and categorize supply chain analytics data across any format.
Inventory Management and Transportation Optimization
Logistics data lends critical support to inventory management:
- Inventory Visibility: A real-time view of your inventory stock levels across warehouses, distribution centers, and suppliers is essential for optimizing inventory levels and captures data that sets the stage for demand forecasting and optimization.
- Demand Forecasting: Capturing data related to historical sales patterns and customer behavior enables businesses to predict future demand with greater accuracy, helping supply chain leaders to ensure optimal inventory levels while avoiding overstocks and stockouts.
- Reorder Point Optimization: Analyzing order fulfillment data, delivery schedules, and lead times enables companies to set optimal reorder points for goods, ensuring stocks remain at appropriate levels without the need to hold excess inventory.
- Improving Inventory Turnover: Analyzing your logistics data can help you reduce inventory of slow-selling items and prioritize high-demand products to free up warehouse space and capital and drive sales.
- Warehouse Optimization: Improve the efficiency of your inventory management and reduce handling costs by leveraging data on product movement within your warehouses.
Logistics data can also help you optimize your transportation operation:
- Route Optimization: Leverage data on traffic patterns, delivery times, and fuel consumption to select the most efficient routes for your shipments. This helps reduce transit times and optimize fuel consumption.
- Carrier Performance: Use logistics data to track carrier performance metrics including on-time delivery rates, delays, cost-per-mile, and more. This helps ensure you are selecting the right carrier and enhancing service while minimizing costs.
- Freight Consolidation: Logistics data can help you uncover opportunities to consolidate smaller shipments into full truckload or full container shipments, reducing miles, saving money, lowering greenhouse gas (GHG) emissions and helping you meet sustainability goals.
- Predictive Maintenance: Data from trucking fleet vehicles can signal when maintenance is required before a breakdown occurs. This helps maximize uptime and avoids costly shipping delays.
Compliance and Risk Management
Logistics data supports regulatory compliance and risk management by making readily available the relevant information needed to adhere to regulations and mitigate risks:
- Customs and Import/Export Compliance
- Environmental Regulations
- Product Safety and Standards
- Automated Record-Keeping
- Incident Reporting
- Driver Hours and Safety Regulations
- Identifying potential supply chain disruptions and operational risks
- Geopolitical Risks
- Risks related to weather and natural disasters
- Financial Risks
- Cargo Security
- Fraud Detection
- Claims Management
- Scenario planning and simulations
Best Practices for Ensuring Accurate Logistics Data
Your logistics data is only as useful as it is accurate. Here are some best practices for maintaining the reliability of your data:
- Standardize data collection processes
- Integrate systems and implement data exchange across the supply chain
- Validate and verify your data
- Conduct regular data audits
- Leverage machine learning and artificial intelligence (AI)
- Train employees on data management
- Leverage predictive data analytics and AI tools to identify patterns, trends and anomalies
- Ensure data security
- Employ Master Data Management (MDM) to maintain a single source of truth
- Gather shipment data with real-time tracking and monitoring
- Collaborate and share open data with supply chain partners
- Establish KPIs and metrics regarding data accuracy
Successful Examples of Using Big Data in Logistics
Sheer Logistics helped our client, a multinational beauty company, optimize its complex transportation network by integrating disparate systems using SheerExchange, our proprietary integration platform. We helped the client implement a Transportation Management System (TMS), streamlining processes across suppliers and modes of transport. The integration improved cost-to-serve, automated workflows, and reduced delivery times, with significant automation of operations in the U.S. and Canada. This partnership led to cost savings, enhanced efficiencies, and seamless SAP integration for financial and operational alignment. To read the complete case study, please click here.
What Kind of Data Analysis is Your Company Doing?
When your company correctly uses data, it means dollars saved, less stress, better efficiency, and more customers. It’s difficult to measure the impact that data analysis has on your business. Luckily, you have a business partner that helps you make the most of it.
- We tie data to your business goals
- We fully integrate your existing systems
- We analyze operational efficiencies
- We ensure that your data analysis strategy evolves as your business grows
- We strive practice continuous improvement and strive for supply chain excellence
Simply put, we help you make the most of big data and supply chain management. Call us today for a free consultation, and let’s develop a data-driven business intelligence plan for your company.
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