In this study, a second-order polynomial was employed to fit CCS across sugar cane farms within a mill region. Parameters estimated from the model were used within a linear programming model for better harvest scheduling to maximize gain in CCS in a harvest season. The parameters were also used to classify sugarcane farms into CCS trends groups. We applied this technique to three mill regions within the Australian sugar industry and showed potential gains in profitability from increased CCS to be A$ 1.10 per tonne of cane on average. A software package, encapsulating the statistical and linear programming models, was developed to enable the harvesting groups and growers within the industry to produce their own optimised schedules. In a trial application of the package during the 2003 harvest season, schedules were produced for about 20 growers.