Real-Time Transportation Planning: 2 Things to Check Now

Companies that leverage data more effectively enjoy a significant competitive advantage in the digital supply chain, particularly in transportation operations.

Transportation is the most dynamic activity in a supply chain, presenting more risk and reward depending on how a company responds to its changes. That’s where transportation planning in real-time makes a significant difference in outcomes.

Data-driven transportation planning that can adjust in real-time enables a company to adapt to shifting demand, disruptions, and regulatory changes. Short and long-term planning for transportation, fulfillment, and production schedules can be synchronized. As digitalization advances, this capability will become essential to remain competitive, and transportation fleets must begin taking steps now to transition.

Despite what’s at stake, most fleets struggle to transition to real-time planning and execution. According to Gartner, closing the gap between decision-making and execution is a focus for 96% of supply chain leaders. Yet, only 7% of businesses are capable of doing so.

The first step is knowing which data is required for dynamic transportation planning. Once established, the effort can focus on closing the gap between decision-making and execution. 

This article outlines basic data and functional requirements a delivery operation needs to support real-time transportation planning.  

1. Prioritize the Most Relevant Data

In addition to dynamic data elements, several other data types relevant to transportation decisions must be part of the data model used for planning.  

Operational Data: Information on the current operational constraints and costs considered when making transportation decisions, such as:

• Logistics productivity metrics and business requirements, and route histories.
• Characteristics of each vehicle in a delivery fleet: cargo capacity, physical dimensions and limitations, and performance characteristics such as fuel mileage and carbon emissions.  
• Product characteristics such as physical attributes,  hazardous classifications, and handling requirements.

Customer Demand Data: Accurately forecasting aligned with demand allows delivery operations to fulfill expectations more efficiently. Order volumes, seasonal patterns, customer geographies, and delivery windows are essential for projecting capacity and scheduling. 

Regulatory Data: A perfectly optimized transportation plan is worthless if it does not comply with transportation regulations, so this is a critical function for dynamic planning.  Route planning must consider limitations on driving time, like the ELD mandate and Hours of Service (HoS) rules in the US and digital tachographs in the EU.  

Additionally, certain roads may restrict vehicle weight or size and the transportation of hazardous materials.  Planning must be detailed enough to identify alternative roads in compliance; the shortest route possible is only sometimes the answer. 

Vehicle Data: Global Positioning System (GPS) and telematics data from fleet vehicles can report on the actual performance and location of vehicles, allowing further optimization of plans. 

Telematics data on fuel consumption, idle time, braking, and other variables can elevate exception detection and optimization to another level in real time, maximizing fleet profitability and sustainability.

Environmental Data: Changes in traffic or weather conditions can significantly undermine the best plan, so incorporating this data in real-time enables changes to avoid delays from traffic congestion, road construction, and inclement weather.  

2. Ensure Capabilities Support Continuous Updates 

Continuously updating a transportation plan requires delivering and analyzing diverse data spread throughout a supply chain. That is only possible with a coherent data model linking supply chain management functions to short- and long-term planning objectives. To accomplish this, the following capabilities are needed:

1. Use of IoT and other technologies to capture logistics data in real time. 
2. A supply chain digital twin to support rapid deployment and revisions to planning without impacting existing enterprise systems.
3. Vehicle Routing and Scheduling (VRS) optimization to formulate delivery plans and direct vehicle navigation.
4. Alignment between short and long-range transportation planning and daily fleet management using the VRS solution.
5. Continuous scenario planning simulations to determine the most efficient use of resources as conditions across the supply chain change.
6. An adaptive framework to accommodate the adoption of new technologies and business models.
7. Integration of inbound and outbound transportation planning across the entire supply chain.

Example of an Effective Solution

flexis SCM Transportation Planning and Scheduling is an example of a dynamic planning solution that supports the data and functionality requirements outlined. The technology continuously updates short and long-range transportation plans and can be tightly integrated with the flexis VRS solution to optimize routing for fleet operations. 

Conclusion

Real-time transportation planning will become vital for competitiveness in an increasingly data-driven supply chain. Ensuring data and functional requirements are intact to support it is a significant first step every fleet should take now. flexis AG provides solutions and services that help companies implement the requirements outlined. 

If you want to learn more, download your guide to Supply Chain Resilience and the new Normal.

In this Guide you will learn:

1. Why a strategic process in transportation planning is a top priority for digitalization
2. What megatrends will increase supply chain volatility

3. How to manage volatility and reinforce resilience