Abstract

Aerospace is very important to the Canadian economy, with over 80,000 employees; generating over $20 billion dollars in revenue. However, the industry is facing many challenges. With the economic downturn, sales have been decreasing. Competition is growing with emerging countries entering the market, with the aid of government subsidies, as well as lower costs of production. Companies are struggling to stay competitive, and they are adopting various practices to deliver value to their customers. The principles of lean manufacturing strive to do just that, and while enjoying much success in production environments, lean principles have been found to be applicable in other areas of the enterprise, including accounting. This thesis presents the notion of target costing for new products, which is one of the pillars of lean accounting. In comparison to traditional costing of products, where the desired profit is added to the cost required to develop the product, target costing is ‘lean’ in the sense that it puts the focus on creating value for the customer by setting the price of the product based on the cost. A number of methods exist for determining target costs, however, the accuracy of such methods are critical. In this thesis, various types of target cost models are developed and compared to one another in terms of their accuracy. The models are based on parametric models, neural networks and data envelopment analysis. The models are then applied to predict the cost of commodities at a major Canadian aerospace company.