Supply Chain Data Collection Can Help Improve Urban Logistics

Many businesses wonder how data collection can help meet the needs of their supply chain. While automated data collection solutions can meet the needs of diverse companies, there are other areas they can help improve. Edgar Blanco, director of MIT Megacities Logistics Lab, recently stated a study his organization is conducting is helping to create a solution that will map logistics systems in developing cities around the world. The research is aimed at improving urban planning and figuring out traffic on specific streets to make better bike and car lanes.

“All the models we have tried using for logistics [based on experience in the industrialized world] were not applicable,” Blanco said, according to MIT News. “We need to learn more about the logistics in megacities, mostly because they represent the future of urbanization … We not only have to design better logistics systems in the cities, we need cities that are designed better for logistics.”

The Atlantic Cities’ Jenny Xie wrote that having detailed information on patterns of delivery, parking areas and traffic disruptions can help urban planners determine how to best allocate city space. In an interview with the publication, Blanco provided the example of how data can help planners evaluate the effects of implementing bike lanes, which include less room for trucks. Being able to use data collected across multiple supply chains gives planners the ability to see how cities can be built and added to, thereby allowing them to minimize traffic problems.

Data Collection Also Leads to In-company Improvements

As professionals dealing with supply-chain management already know well, automated data collection can be used to make improvements and identify areas in which the company can become more efficient. The Harvard Business Review’s Ellie Moss gave an example of an office product retailer that was using excessive primary and secondary packaging for one product, which created a lot of unnecessary spending and waste. Once the company used data to recognize its inefficiencies, it agreed to reduce packaging, saving the organization time and money.

“One way to think about this new era of cross-supply chain optimization is that we are trying to get the supply chain to work more like a single vertically integrated company without actually becoming one,” Moss wrote.

She added that by combining collection tools and apps with the ability to use and make sense of data that was previously not available, organizations can ensure they have the right decision-makers and processes in place to get the best rewards from their enterprise. Being able to clearly see where improvements can be made will help organizations cut costs and hike up productivity.