Tackling transportation waste: Driving efficiency and innovation in planning and execution

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Tackling transportation waste: Driving efficiency and innovation in planning and execution

2 minute read

In Lean Manufacturing, eliminating waste is a game-changer for enhancing a product's value stream. By meticulously mapping each stage of a product's life cycle, supply chain teams can pinpoint not only how to optimize processes but also how to cut waste effectively.

Waste reduction, which is a central tenet of Lean Manufacturing, targets seven key areas: overproduction, overprocessing, waiting, defects, motion, inventory, and transportation. Shining a spotlight on these areas with strategic planning and execution—bolstered by AI, unified decision-making, and interoperability—enables manufacturers to achieve sharper, value-focused outcomes and significantly reduce organizational waste. Our blogs on waste reduction has delved into these practices and applied them across planning and execution. 

Today, we turn our attention to waste caused by unnecessary transportation. This waste not only heightens the risk of product and inventory damage but also inflates costs, harms service quality, strains asset utilization, increases emissions, and disrupts the availability of materials for production. These issues often arise from limited visibility, poor inventory placement, and inefficient transportation stemming from mismanaged loads, non-optimized routes, and overproduction.


The risks of unmitigated transportation waste

Reducing transportation waste curbs unnecessary movement of products or supplies. Common inefficiencies include avoidable miles due to poor routing or unavoidable detours caused by unforeseen challenges such as sudden weather changes or global disruptions. Poor planning and inventory management leave goods where they are not needed, requiring additional or expedited transportation to move them to where they are needed. 

The concept of transportation waste also extends to data management. Redundant tasks and manual data entry often lead to inefficiencies as risky as those caused by physical transport. For example, when data is manually transferred between siloed solutions to a centralized spreadsheet for analysis, the data transfer (or data transportation) risks data inaccuracy due to poor mapping or manual data entry and delays due that could magnify issues down the line.

Examples of potential risks include:

  • Elevated costs and reliance on expedited loads
  • Inventory losses or damage during transport
  • Delayed production and services
  • Compromised customer service
  • Suboptimal asset and resource utilization
  • Overproduction or misplaced goods requiring additional transportation
  • Hampered material availability
  • Increased system errors due to poor data accuracy
  • Delayed decision making due to disconnected systems

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Reducing transportation waste

Critical strategies for reducing unnecessary transportation waste range from optimizing transportation routes to better planning and centralized data management:

  • Implementing improved solution connectivity reduces repetitive data transfer and manual data handling to minimize errors and delays.
  • Route optimization identifies the best pathways to move shipments, cutting unnecessary miles and associated costs, emissions, and risks.
  • Shipment consolidation finds compatible shipments to move together, while optimized load-building maximizes container capacity, together reducing total loads, extra miles and related inefficiencies.
  • Improved inventory placement ensures inventory is where and when it’s needed, avoiding needless, risky and costly movement to meet demand.
  • Tight collaboration with trading partners allows manufacturers to better understand inventory, production schedules and capacity across their network, while AI backed monitoring and issue resolution mitigate disruption.
  • Better order management focuses on real product availability and achievable customer expectations rather than rushed movements to fulfill immediate needs.
  • Strategic supply planning helps get the right supplies to the right places at the right time, ensuring continuous production without excess transportation.
  • Controlling overproduction limits unnecessary transportation by minimizing movement excess inventory from location to location.


Enabling these above reductions with cognitive solutions from Blue Yonder brings unified decision-making, interoperable solutions and other benefits to connect supply chain processes and data. The result is reduced data movement, enhanced forecasting for more accurate inventory planning and production, and synchronized operations for connected and accurate movement of goods.


Embracing AI for leaner transportation

Going one step further, adopting AI across transportation, planning and multi-enterprise networks empowers rapid adaptation to changes among trading partners, orders, and warehouses. AI begins by providing planners with a vigilant eye on network fluctuations affecting plans, supplier capacity, inventory, and schedules. This proactive stance keeps manufacturers ahead of disruption, avoiding reactive scenarios like expedited or partial loads. Instead, they benefit from precise planning and near-real-time monitoring, ensuring inventory reaches the right place at the right time without unnecessary moves. Practices like additional, expedited or partial loads to manage change become a thing of the past.

Consider AI agents actively surveilling a manufacturer’s multi-enterprise network for disruptions. After detecting issues, the agent escalates them to demand and supply planning solutions, which craft mitigation strategies. Planners can review AI recommended scenarios and uncover the right resolutions to resolve the issue. Connectivity with transportation then aids in rescheduling carriers to efficiently move the loads and minimize additional transportation. Backing this combination with transportation optimization solutions, logistics planners further enhance load consolidation and routing, cutting down miles, costs, and emissions. 

Additional AI use cases include:

  • Inventory Ops Agent: Ensures optimal inventory placement, aligning inventory availability with demand and virtually eliminating emergency transportation needs.
  • AI enhanced planning: Scenario testing driven by AI fosters accurate planning, reducing sudden transportation requests to meet demand or supply changes.
  • Gen AI assistants: Monitors shipment health with real-time tracking, leveraging AI to respond to real-time events, ensuring seamless movement of goods.

 

Transforming waste into opportunity

Lean Manufacturing focuses on waste reduction as a crucial component in optimizing product value streams. Mapping a product's lifecycle allows teams to identify inefficiencies in areas such as overproduction, inventory, motion, and transportation. Cognitive innovations from Blue Yonder elevate these efforts, effectively minimizing unnecessary movements and data redundancies. Addressing transportation waste through route optimization, shipment consolidation, and improved inventory placement helps to reduce risks like product damage, costs, and service delays. By reducing waste, transportation is transformed into a strategic advantage that enables businesses to elevate efficiency while cultivating a pathway to sustainable success and innovation.

 

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