Maintenance and asset management of the UK sewerage network is based on a policy of selective rehabilitation of critical sewers which represent about 20% of most drainage systems. Continuing failures on an ageing network, together with customer and regulator pressure, have increased the need for water companies to become more proactive in the maintenance of non-critical sewers, which form the remaining 80% of the nation＇s sewerage assets. This paper describes a flexible methodology for directing proactive sewer maintenance in the light of a changing perception of how urban drainage systems should be managed. Until recently, non-critical (or category C) sewers received only reactive maintenance. What is now required is an effective means of directing maintenance resources so as to target those parts of the network in greatest need of attention. Management strategies can no longer focus on a preselected subset of assets but should identify the correct subset for each catchment for which maintenance activity will be most effective, Cost constraints prohibit the widespread collection of new data regarding the condition of all sewers, so the approach described here is based on the analysis of existing historical sewer event data and asset information. Appropriate forms of data analysis, within the constraints of current levels of data availability, have been evaluated, and a two-stage decision support model for sewer maintenance is proposed. This uses geographical information system (GIS) software to rank variable-sized grid squares into priority zones for action. A detailed analysis of each pipe length within those grid squares most at risk from sewer failure is then performed using a simple Bayesian statistical model. To demonstrate the approach the procedures are applied to a real catchment as part of a case study, and based on a wider analysis of data from several catchments observations are made concerning the factors most commonly associated with serviceability failures in sewers.