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Big data and related technologies are expected to drastically change the way industrial maintenance is managed. However, at the moment, many companies are collecting large amounts of data without knowing how to systematically exploit it. It is therefore important to find new ways of evaluating and quantifying the value of data. This paper addresses the value of data-based profitability of maintenance investments.

An analytical wasted value of data model (WVD-model) is presented to quantify how the value of data can be increased through eliminating waste. The use of the model is demonstrated with a case example of a maintenance investment appraisal of an automotive parts manufacturer.

The presented model contributes to the gap between the academic research and the solutions implemented in practice in the area of value optimization. The model provides a systematic way of evaluating if the benefits of investing in maintenance data exceed the additional costs incurred. Applying the model to a case study revealed that even though the case company would need to spend more time in analyzing and processing the increased data, the investment would be profitable if even a modest share of the current asset failures could be prevented through improved data analysis.

The model is designed and developed on the principle of eliminating waste to increase value, which has not been previously extensively discussed in the context of data management.

The purpose of this paper is to create a cost model at the general equipment level for industrial maintenance services.

The study is divided into two main sections. In the first phase the idea is to create a framework for a cost model with a literature review. The second, empirical part of the study is based on costing information from interviews and information given by network companies: a pulp mill, a maintenance company and an equipment provider. The maintenance of three different equipment processes is examined in the network through a case study, to get more specific information from real world situations to develop the model.

The findings concern the cost items that should be considered in the model, the structure of the model, and how the general cost model is constructed. During the research the model has been extended, and new cost categories included.

The cost model can be used in various performance measurement and decision‐making situations, such as maintenance service pricing, contract negotiations, outsourcing decisions, and life cycle cost management.

The cost model differs from traditional cost models. Earlier models have focused on the perspective of either the service provider or the customer, but not on both perspectives at the same time. However, in order to achieve a win‐win situation in a business network, open books practice is expected from each member of the network.