Last-mile logistics data can be difficult to visualize and analyze. The CAVE Lab https://cave.mit.edu uses interactive visualization to improve data visibility, data analysis, and decision making for last-mile logistics challenges.
Together with MIT CTL’s corporate partners, the CAVE serves as an interactive decision-making space. By co-developing interactive visual analytics applications addressing specific, data-driven decision problems of our partners and presenting them in a way that optimally leverages human perception and cognition, we promote the effective future use of data and analytics by corporate and organizational decision-makers at all levels.
Complex data can be difficult to visualize and analyze. Working in cross-functional teams also adds a layer of complexity to making decisions from big data analysis. The CAVE Lab uses interactive visualization to improve data visibility, data analysis, and decision making for supply chain and logistics challenges.
The MIT CAVE Lab uses interactive visualization to improve data visibility, data analysis, and decision making for supply chain and logistics challenges.