In the continuous process industries, multiple grades of the same product are often made on the same production equipment. Key product properties for each grade are usually monitored separately because of inherent differences among grades. Although highly effective in detecting changes that affect individual grades such as changes in grade-specific raw material properties, this approach is usually slow in detecting changes common to all grades such as a drift caused by production equipment or changes in common raw materials. The case study of this paper illustrates a simple method of combining and monitoring data from multiple grades allowing speedy detection of changes affecting all grades and yet still permitting differentiation of overall process shifts from grade-specific shifts.