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
