The conventional wisdom surrounding clothing is that it fits into three simple categories: small, medium, and large. Stantt, a company that’s looking to meet its funding requirements via Kickstarter, hopes to change that in one of the more interesting applications of big data to a classic problem. Stantt started by 3D body scanning over 1000 men, ranging in age from 25 to 35, and each scan included approximately 200 body measurements. They then developed an algorithm – which extrapolates from chest width, waist width, and arm length, all common, at-home measurements – that determines which of over 50 sizes fits the individual. Though Stantt faces competition from the increasingly common ‘made-to-measure’ online sphere, Stantt is among the first fashion-oriented brand looking to leverage data to improve something we’ve considered standard for years.