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Menlo Worldwide Logistics introduces CarbonNetTM
Menlo Worldwide Logistics, the global logistics subsidiary of Con-way Inc. (NYSE: CNW), announced the introduction of CarbonNetTM. Combining newly developed software with expertise in Lean tools and continuous improvement processes, CarbonNet is a carbon management technology that gives Menlo the ability to capture, calculate and manage emissions activity across the value supply chain.‘One of Menlo’s primary business priorities is to drive Sustainability practices throughout our operations, with a goal of zero waste,’ said Anthony Oliverio, vice president, supply chain services, Menlo Worldwide Logistics. ‘We developed CarbonNet with this goal in mind, so we can first accurately benchmark and measure the carbon footprint of our operations today, and then identify and capture reduction opportunities,’ he explained. ‘In effect, we are using ourselves as the pilot customer. As we map and measure our facilities and operations, we are applying lessons learned and refining the program. Our goal is to provide this as a service to our customers as well.’
Oliverio noted that the data and findings Menlo obtains in measuring natural resource consumption and associated carbon output of its own operations will be immediately valuable to customers for whom Menlo provides warehousing and transportation management services. Many of Menlo’s industrial customers are pursuing similar Sustainability initiatives and are seeking accurate, validated data, measurement tools and solution capabilities that can identify and deliver reductions in supply-chain-related carbon output.
Menlo has been piloting CarbonNet at 60 of its facilities in the United States for the past year. Emission source data was collected on each facility and an emissions baseline established. Measurements are currently being made against published industry indexes and standards to identify reduction opportunities to meet emissions reduction goals.
How it works
CarbonNet is supported by a team of Menlo Lean and process management experts using a cloud-based software program developed exclusively by Menlo and its IT team. The application is designed to be highly configurable, and can accept a wide variety of data inputs to catalog key emissions characteristics of a facility and the activities performed within, as well as the transport of products and materials between such locations. It can accept input as well from suppliers, vendors and other third parties whose activities could contribute to the makeup of a supply chain carbon footprint.
As it calculates values, the application takes into consideration the type of operation, design and size of facility, area of the globe in which it operates, number of employees, operating hours and other contributing factors. Additional elements which are captured for the emissions profile can include the energy impact of power equipment used in a facility, such as forklifts and pallet jacks, as well as heating and lighting systems, computing systems, water use and recycling programs. Another module of the application provides similarly configurable data capture capability, visibility into and measurement of transportation resources, such as airfreight, truckload or LTL trucking services, and what portion of the carbon footprint can be attributed to the energy use of these operations.
Ultimately, the system bundles all the inputs, provides an output which catalogs energy type and usage, and then calculates a carbon equivalency number to provide the initial baseline carbon footprint for the facility or the transportation operation. The ‘supply chain profile’ and baseline emissions output represent the first two phases of a five-step, Lean-based work process to define and establish a continuous improvement solution for carbon management in the supply chain.
Phase three involves analyzing the baseline outputs. This phase uses value stream map methodologies to assess the outputs against internal and external standards. The value stream map accomplishes two goals: identifying inefficiencies or waste in the ‘cu
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