Case Study: Western Australia Department of Agriculture achieves reliable wool price predictions with Palisade's NeuralTools

Western Australia Department of Agriculture - Customer Case Study

The Western Australia Department of Agriculture needed a numerical model to predict market prices for individual wool farm lots—especially less abundant types—where prices are dynamic, relationships between characteristics and price are nonlinear, and some data are missing. To tackle this, the department used Palisade’s NeuralTools to develop a practical, spreadsheet-based prediction tool for the Australian wool market (an industry worth AUD 3 billion and more than 450,000 lots sold annually).

Palisade’s NeuralTools was trained on nearly 6,000 records and tested on over 1,500 cases; using Best Net Search it selected a Generalized Regression Neural Network, and Variable Impact Analysis identified fiber diameter as the pivotal factor. By refining models with Live Prediction and simplifying inputs, Palisade delivered a reliable prediction model that improves price estimates for buyers and sellers and lets users explore how characteristics like staple length and strength affect price.

Western Australia Department of Agriculture

Kimbal Curtis

Wool Industry Specialist