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The purpose of the paper is to propose a reference model describing a holistic view of the master data lifecycle, including strategic, tactical and operational aspects. The Master Data Lifecycle Management (MDLM) map provides a structured approach to analyze the master data lifecycle.

Embedded in a design oriented research process, the paper applies the Component Business Model (CBM) method and suggests a reference model which identifies the business components required to manage the master data lifecycle. CBM is a patented IBM method to analyze the key components of a business domain. The paper uses a participative case study to evaluate the suggested model.

Based on a participative case study, the paper shows how the reference model makes it possible to analyze the master data lifecycle on a strategic, a tactical and an operational level, and how it helps identify areas of improvement.

The paper presents design work and a participative case study. The reference model is grounded in existing literature and represents a comprehensive framework forming the foundation for future analysis of the master data lifecycle. Furthermore, the model represents an abstraction of an organization's master data lifecycle. Hence, it forms a “theory for designing”. More research is needed in order to more thoroughly evaluate the presented model in a variety of real‐life settings.

The paper shows how the reference model enables practitioners to analyze the master data lifecycle and how it helps identify areas of improvement.

The paper reports on an attempt to establish a holistic view of the master data lifecycle, including strategic, tactical and operational aspects, in order to provide more comprehensive support for its analysis and improvement.

Master data management (MDM) aims to improve the value of an organization’s most important data, such as customer data, by bridging the silos between organizational units and information systems. However, incorporating data management practices into an organization is not a simple task. The purpose of this paper is to provide a new understanding of the challenges in establishing and developing the MDM function within an organization.

This papers report an ethnographic study within a municipality. The data were collected from two consecutive MDM development projects over the time period of 32 months by observing MDM-related activities and interviewing appropriate actors. Observations, interviews, and impressions were documented to a diary that was later qualitatively analyzed. Various project documentation were also used.

In total 15 challenges were identified. Seven of these were not identified earlier in the literature. New challenges included legislation-driven challenges, mutual understanding of master data domains, and the level of granularity for those domains. Eight issues, such as data owner and data definitions, were MDM specific, others being more generic. All of the issues were identified as preconditions or as affecting factors for the others. Three of the issues were identified as pivotal. The issues emphasize strong alignment between the complex concept of MDM and the organization adopting it.

This research was based on a single qualitative case study, and caution should be exercised with regard to generalizations. The findings increase understanding about the complex organizational phenomena. The study offers public sector and private sector practitioners insights of the organizational issues that establishing a MDM function can encounter.

The issues discovered in the research shed light on the strong alignment between the complex concept of MDM and the organization. The results of this study assist researchers in their endeavor to understand the organizational aspects of MDM, and to build theoretical models, frameworks, practices, and explanations.

The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance.

The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size.

Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation).

The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio.

The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

The purpose of this paper is to share the experience of the document discovery process, during the implementation of an asset management system for a rail company. This system will deliver comprehensive enterprise asset management information from a single source, with information provided to mobile devices, for use by field workers. This case study presents the challenges encountered in the search, retrieval and management of documentation for use on a daily basis for civil standard maintenance tasks.

Evidence gathered for this paper was a result of direct and participant observation over a period of 18 months from 2014 to 2016. As a member of the project team, certain privileges were accorded to the researcher who was placed in a unique position to act as the main research instrument, able to collect data on the systems used as well as the everyday practices on information capture and document production.

Document quality and standards can be overlooked or deemed as not crucial; the value, significance and importance of documentation are lost when no one takes ownership; the understanding and application of standards, quality management and governance can have a direct bearing on the effective management and control of documents and subsequent records produced.

Research is limited, as this is a single case study.

By highlighting the challenges faced and the resolutions used, this paper hopes to offer a level of practical guidance with the detection process for maintenance tasks for the civil assets discipline for a rail network.

This case study contributes to the understanding of quality management and the role it plays in document management and in turn the search and retrieval process. It provides evidence that documents must be systematically managed and controlled to limit risk both internally and externally.

The purpose of this paper is to facilitate understanding of enterprise resource planning (ERP) system and data quality interdependency by presenting ERP systems’ use within data quality management.

The authors apply task technology fit (TTF) in an explorative study, conducting semi-structured expert interviews with participants in information technology strategic decision making. The authors analyzed the interviews with iterative descriptive and subsequent interpretive coding.

Although considered sustainable, continuously increasing regulations challenge ERP systems. However, compliance with regulations may serve as a bridge for organizations to engage in data analysis. Organizations are embedded into evolving task environments with the need to continuously adapt their systems or the organization and the need for contextual understanding of data quality.

With ERP systems being used for administrative functions, future research might draw on extant ERP systems research from the manufacturing sector. However, for insurance-specific tasks, ERP systems and their data need to be considered in a sector-specific context with the need for further research.

ERP systems are considered sustainable. High initial fit is desirable, but the sector's relevance for ERP system vendors might be more important for sustainability. Ensuring TTF will be an increasing challenge with increasing task non-routineness.

Applying TTF provides guidance for fit research, while the qualitative approach accounts for a deeper understanding, especially when exploring data quality issues since deficiencies might have several root causes. The authors show that ERP systems have an impact on data quality beyond its typically examined functionality.

The paper seeks to investigate the question as to how the business benefits of product data management (PDM) can be assessed and realized. In particular, it aims at understanding the means‐end relationship between PDM and product data on the one hand and a company's business goals on the other hand.

The paper uses a case study research approach. The case of Festo is unique and allows for detailed examination of both the business benefits of PDM and of the inter‐dependencies of various business benefit enablers. Due to the limited amount of scientific knowledge with regard to the management of PDM business benefits, the study is exploratory in nature. The conceptual framework used to guide the study combines business engineering concepts and the business dependency network technique.

The findings are threefold. First, the paper explicates and details the understanding of the nature of PDM business benefits. Second, it provides insight into the complexity and interdependency of various “means” – such as data ownership, product data standards, for example – and the “ends” of PDM, namely the contribution to a company's business goals. Third, the paper forms the baseline for a comprehensive method supporting the management of PDM business benefits.

Single‐case studies require further validation of findings. Thus, future research should aim at replicating the findings and at developing a comprehensive method for the management of PDM business benefits.

Companies may take up the results as a “blueprint” for their own PDM activities and may reflect their own business benefits against the case of Festo.

The paper is one of the first contributions focusing on the means‐end relationship between PDM and product data on the one hand and a company's business goals on the other.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The purpose of this paper is to provide a conceptual framework of the supply chain performance measurement system (SCPMS) lifecycle (highlighting key activities of the design, implementation, use and review phases) and to investigate how the different actors involved in the SCPMS perceive the system and can act to allow for an effective adoption.

The SCPMS lifecycle framework is developed grounding on performance measurement and supply chain (SC) management literature. To answer the two theory-building research questions, an in-depth case study involving seven firms across three tiers of the mass retail SC has been conducted.

The empirical evidence highlighted potential SCPMS benefits (including operational performance improvement, higher control, lower information overloading and higher SC integration) and criticalities/barriers to an effective adoption (lack of industry standards, lack of trust regarding data reliability, SCPMS as a tool of power, lack of interest in the system and the performance metrics). Several elements characterizing the SCPMS lifecycle could increase its effective adoption: engaging SC partners in the design phase; relying on a rigorous primary data collection and performance measures calculation; and actively exploiting the tool through a systematic discussion on performance and establishing incentive/disincentives plans.

The paper contributes to the conceptualization of SCPMSs and to clarify how to ensure an effective SCPMS adoption: apart from relationship-specific attributes, SCPMS lifecycle phases are suggested to have a key role.

Despite servitization being widely regarded as an essential catalyst to improve manufacturing firms' survival and competitiveness, how to attain servitization remains debatable. The primary objective of this research is to explore whether or not, how, and when the dynamic capabilities affect servitization in the digital economy background. This research investigates the relationships between servitization and dynamic capabilities by incorporating firm ownership, firm lifecycle stage, digital economy level and environmental uncertainty as contingency factors in the research framework.

This research develops and verifies a conceptual framework for manufacturing servitization by employing the fuzzy-set qualitative comparative analysis (fsQCA) in analyzing the secondary longitudinal data from 148 China-listed manufacturing firms involved in servitization from 2015 to 2020.

The analytical results of fsQCA identify several configurational solutions for the success of manufacturing servitization. Each factor can be an enabler for servitization success despite none of the factors discovered as an absolute condition. Manufacturing servitization success within the digital economy depends on the interactions between dynamic capabilities and contingency factors such as digital economy level, environmental uncertainty, firm ownership, and lifecycle stage.

All of the construct's measurements in this research adopt secondary data, and further investigation calls for primary data (e.g. survey) for higher validity.

This research extends the current view of servitization by proposing an integrative conceptual framework, allowing manufacturing servitization to be examined more pertinently and comprehensively. Second, the research is an initial attempt that adopts fsQCA in servitization studies. The study sheds light on the mechanisms of attaining servitization by revealing the importance of dynamic capabilities and their interactions with the contingency factors. Third, the research extends the application scopes of dynamic capability theory, firm lifecycle theory, contingency theory, and institutional theory. Fourth, the research findings enrich the understanding of servitization in the digital economy and give business practitioners insights on leveraging dynamic capabilities in different conditions to attain successful servitization under the current circumstances.