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Due to recent technological developments, many maintenance managers become overwhelmed by the vast amount of data available to support their decision making. The purpose of this paper is to discuss identifying and eliminating waste in information management processes through a value stream mapping (VSM)-based method.

A theoretical framework is constructed based upon a review of the previous academic literature. The application of the framework is demonstrated with an empirical case example of a maintenance information management process within a food manufacturing company.

The paper highlights existing examples of applying VSM in information management; however, the knowledge is fragmented and has not been extensively applied in a maintenance context. The case example shows that the suggested process offers a feasible method of mapping and evaluating the inherent waste in information management processes.

The paper summarizes the existing body of knowledge on lean information management in maintenance, and presents a theoretical framework on how VSM can be applied in the context. An empirical example is provided to show the method applied to a real industry case. The results will illustrate how the framework can support companies in identifying the waste and development potential in their maintenance information management.

The role of management control is frequently emphasized in connection with inter-organizational relationships and value networks. For example, boundary-spanning cost and accounting control techniques have been studied in multifaceted empirical settings. The prevalence of such techniques is, however, currently unknown in conjunction with companies’ interests to increase inter-organizational integration in general. Additionally, also the nexus between the internal state of cost management and the company’s willingness to develop inter-organizational relationships requires further investigation. The paper aims to discuss these issues.

The study is based on an extensive survey that was responded to by more than 1,500 CEOs and CFOs from large, medium-sized and small Finnish enterprises in a variety of industries. As the authors chose the mixed-methods approach, both quantitative and qualitative data were collected for the study.

The findings suggest that companies can be allocated to five clusters: “the cost experts,” “the trustful,” “the holdouts,” “the trailblazers” and “the uncertain”. When the networking-oriented clusters, “the trustful” and “the trailblazers” are combined, the authors can conclude that 40 percent of the studied companies are interested in increasing inter-organizational integration. However, only 7 percent have boundary-spanning techniques in use. There is also a correlation between interest in integrating and developing cost management.

This paper contains several theoretical implications, although further research, e.g. comparative studies, is required to verify the findings. The scarcity of managerial implications can be regarded as a limitation.

This paper fills several untapped research gaps by studying inter-organizational integration in the cost management context from multiple, complementary perspectives with a particularly large set of data.

The purpose of this paper is to identify what is currently valued in maintenance services. The study first conceptualizes the value construct through an examination of its elements, including both financial and non-financial elements, and second provides insight into its actors’ (i.e. customer companies, service providers, equipment providers) attitudes toward value creation.

The study uses data collected from maintenance service professionals by an online survey. First an explorative factor analysis is conducted to examine the value construct. After this cluster analysis is conducted to define the actors.

The empirical findings suggest seven main elements that capture maintenance service value: relationship synergies, reliability of the service partner, development, availability, service solutions and problem solving ability, environment, health, safety and quality, and adaptability to suit different situations. Further analysis reveals that the actors can be divided into three main strategy types: basic, quality- and collaboration-oriented partners.

In previous studies the comprehensive nature of maintenance service value has received less attention, and the literature has focused on the technical and financial aspects. This paper provides a new conceptualization of the value creating elements, including also non-financial elements, and offers an integrated measure for the actors to identify the comprehensive value construct around maintenance services. In addition, the findings show that the actors in the field still have varying strategies when considering value creation. Communication and mutual understanding of the value creating elements are important so that right services are carried out and developed with the right partners.

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.