Improving pipe failure predictions: Factors affecting pipe failure in drinking water networks.

To reduce leakage and improve service levels, water companies are increasingly using statistical models of pipe failure using infrastructure, weather and environmental data. However, these models are often built by environmental data scientists with limited in-field experience of either fixing pipes or recording data about network failures. As infrastructure data can be inconsistent, incomplete and incorrect, this disconnect between model builders and field operatives can lead to logical errors in how datasets are interpreted and used to create predictive models.