Other than identifying whether a company may fail or not, explaining why a company may fail is essential. The most common way of explaining is to use a template like the standards used in commercial society. Because of the existence of heteroscedasticity, it is impossible to expect that there is only one standard within an industry. For instance, it is unrealistic to use one standard to evaluate performance of both a new-born company and a fifty-year old company. This paper presents a method of searching for templates using probabilistic neural networks. Each template represents a number of companies, which have similar financial performance and therefore similar financial outcomes. A comparison between a company and a template can explain how badly a company performs and what the problem is if its financial situation is not sound. The method has so far been applied to a data set of 2408 UK construction companies.