5 TMS Analytics That Enhance Supply Chain Processes

In the intricate web of supply chain management, the effective utilization of data is key to achieving operational excellence. Transportation Management Systems (TMS) play a central role in this regard, providing a wealth of data that, when harnessed effectively, can enhance decision-making, optimize processes, and drive overall supply chain efficiency. This article explores five TMS analytics that have the power to transform supply chain processes, providing insights into how businesses can leverage data-driven strategies to achieve better visibility, cost savings, and improved performance.


Route Optimization Analytics

Route optimization is a critical aspect of transportation management, and analytics within TMS can significantly enhance this process. By analyzing historical data, real-time traffic information, and various constraints, route optimization analytics empower businesses to design the most efficient and cost-effective routes for their shipments.

Key features of route optimization analytics include:

  • Real-Time Traffic Analysis: TMS analytics leverage real-time traffic data to dynamically adjust routes based on current conditions, minimizing delays and improving delivery accuracy. 
  • Historical Performance: Analyzing historical route performance allows businesses to identify trends, optimize for recurring scenarios, and refine routing strategies over time.
  • Cost Considerations: TMS analytics assess the cost implications of different routes, factoring in variables such as fuel consumption, tolls, and other expenses to determine the most cost-effective options. 
  • Environmental Impact: For businesses with sustainability goals, route optimization analytics can also consider the environmental impact, minimizing carbon emissions and aligning with eco-friendly initiatives. 
  • Dynamic Adjustments: The ability to make real-time adjustments to routes based on unexpected events, such as weather disruptions or road closures, ensures adaptability and minimizes disruptions to the supply chain.

Effective route optimization analytics not only reduce transportation costs but also enhance delivery reliability and contribute to overall customer satisfaction.


Carrier Performance Analytics

Analyzing carrier performance is a crucial aspect of transportation management, influencing decisions related to carrier selection, negotiations, and ongoing partnerships. TMS analytics provide insights into the performance of carriers based on key metrics, enabling businesses to make informed decisions that align with their objectives.

Important aspects of carrier performance analytics include:

  • On-Time Delivery Rates: Assessing carriers based on their historical on-time delivery performance, helping businesses select carriers with a proven track record of meeting delivery commitments.
  • Transit Time Variability: Analyzing the consistency of transit times offered by carriers, allowing businesses to choose carriers that provide reliable and predictable delivery schedules.
  • Cost-Efficiency Metrics: Evaluating carriers based on cost-related metrics, such as transportation costs per mile or per unit, to identify opportunities for cost savings without compromising service quality.
  • Communication Effectiveness: Assessing carriers based on their communication effectiveness, including responsiveness, issue resolution times, and overall collaboration, to ensure smooth operations.
  • Compliance and Regulatory Adherence: Monitoring carriers for compliance with regulations, safety standards, and other industry-specific requirements to mitigate risks and ensure regulatory adherence.

By leveraging carrier performance analytics, businesses can foster strategic partnerships with reliable carriers, optimize costs, and enhance overall supply chain efficiency.


Inventory Visibility and Management Analytics

TMS analytics play a pivotal role in providing visibility into inventory levels and optimizing inventory management across the supply chain. By analyzing data related to inventory movements, stock levels, and demand patterns, businesses can make informed decisions that balance the need for sufficient stock with the goal of minimizing holding costs.

Key elements of inventory visibility and management analytics include:

  • Real-Time Inventory Tracking: TMS analytics enable real-time tracking of inventory levels, providing businesses with accurate and up-to-date information on stock quantities across multiple locations.
  • Demand Forecasting: Analyzing historical data and demand patterns helps businesses forecast future demand accurately, enabling proactive inventory planning and minimizing stockouts or overstock situations.
  • Order Fulfillment Efficiency: TMS analytics assess the efficiency of order fulfillment processes, identifying areas for improvement and optimizing workflows to reduce lead times.
  • Supplier Performance: Analyzing the performance of suppliers based on factors such as lead times, order accuracy, and adherence to delivery schedules ensures a reliable and efficient supply chain.
  • Stock Turnover Rates: Assessing the rate at which inventory is sold and replaced helps businesses optimize stock turnover, reducing carrying costs and preventing obsolescence.

Effective inventory visibility and management analytics contribute to improved supply chain resilience, reduced holding costs, and enhanced responsiveness to changing market demands.


Cost Analysis and Optimization Analytics

Cost management is a critical aspect of supply chain operations, and TMS analytics provide valuable insights into various cost components associated with transportation and logistics. By analyzing cost-related data, businesses can identify opportunities for optimization, negotiate better rates, and enhance overall cost efficiency.

Crucial elements of cost analysis and optimization analytics include:

  • Transportation Costs: TMS analytics break down transportation costs, allowing businesses to understand the factors influencing costs and identify opportunities for optimization, such as route consolidation or mode selection.
  • Fuel Efficiency: Analyzing fuel consumption patterns and factors affecting fuel efficiency helps businesses identify areas for improvement, optimize routes, and reduce fuel-related costs.
  • Carrier Negotiations: TMS analytics provide data that supports informed negotiations with carriers, enabling businesses to secure favorable rates, discounts, and contractual terms.
  • Mode Selection Analysis: Evaluating the cost-effectiveness of different transportation modes (e.g., truckload, less-than-truckload, rail) helps businesses choose the most economical options for specific shipments.
  • Total Cost of Ownership (TCO): Assessing the TCO for transportation operations involves considering all relevant costs, including maintenance, labor, and equipment costs, to make comprehensive and informed decisions.

By leveraging cost analysis and optimization analytics, businesses can identify cost-saving opportunities, negotiate effectively with partners, and achieve greater overall supply chain efficiency.


Risk Management and Predictive Analytics

The ability to identify and mitigate risks is crucial for maintaining supply chain resilience. TMS analytics, particularly those focused on risk management and predictive analytics, empower businesses to proactively address potential disruptions and uncertainties.

Key aspects of risk management and predictive analytics include:

  • Supply Chain Visibility: TMS analytics provide comprehensive visibility into the entire supply chain, allowing businesses to identify potential points of failure and assess the impact of disruptions on operations.
  • Predictive Modeling: Using historical data and advanced analytics, businesses can create predictive models to anticipate potential risks, such as weather-related disruptions, geopolitical events, or supplier issues.
  • Lead Time Variability: Analyzing lead time variability helps businesses understand and mitigate the impact of unpredictable delays, allowing for better planning and responsiveness.
  • Supplier Risk Assessment: TMS analytics assess the risk associated with different suppliers, considering factors such as reliability, financial stability, and geographical location, to make informed supplier management decisions.
  • Scenario Analysis: Conducting scenario analysis based on different risk factors allows businesses to develop contingency plans and strategies for mitigating the impact of potential disruptions.

By embracing risk management and predictive analytics, businesses can enhance their ability to proactively address challenges, reduce the impact of disruptions, and build a more resilient and adaptive supply chain.



In the era of data-driven decision-making, TMS analytics have emerged as a transformative force in supply chain management. The five analytics discussed—route optimization, carrier performance, inventory visibility, cost analysis, and risk management—offer businesses the tools to unlock insights, enhance operational efficiency, and achieve strategic goals. Leveraging these analytics not only provides a competitive advantage but also positions organizations to navigate the complexities of the modern supply chain landscape with agility and resilience. As technology continues to evolve, businesses that harness the power of TMS analytics will be better equipped to adapt to change, optimize processes, and drive sustained success in the dynamic world of supply chain management.