Purpose – The purpose of this paper is to help build up a relevant database for mapping technicaland financial effectiveness of production in order to make cost-effective maintenance decisions.Design/methodology/approach – A theoretical model is developed based on past research andexperience adopting a holistic systems approach on the production. A case study, which includesdatabases of two maintenance-used software programs, verifies the potential of applying the model.Findings – The main result achieved is a model for identifying relevant data required for accurateproblem tracing and localisation within maintenance and production processes using a top downapproach. The main conclusions are integration of IT and data resources within the enterprise isneeded for developing a holistic view of the production process and a well-formulated and documentedprocedure of data identification will ensure that the data can be traced back to root sources and in thisway we can support the work of continuous cost-effective improvement by eliminating root causes ofproblems at an early stage.Research limitations/implications – Further model verification by industrial case studies wouldbe of interest.Practical implications – The holistic approach and the model presented are applicable especially incapital intensive industries, where maintenance budget is not negligible and the amount of data toprocess is large. By structuring the data need and data identification process relevant performancemeasures will be monitored and advanced maintenance concepts can be applied.Originality/value – By applying the proposed model in industry, the data identification processitself and not the data contents is necessary to be standardised and structured. It shifts the focus of thequality aspect from just data level to both data and data collection level. The performance measureswill therefore not be chosen depending on what the IT applications can provide in first hand, but uponwhat is needed for cost-effective mapping, analysis, following up and assessment of maintenanceperformance.