Purpose: The purpose of this paper is to contribute to the understanding of complexity and its management from an OM perspective, building on and extending the systematic literature review published in this journal in 2011, and provide a foundation for exploring the interactions between complexities and responses. Design/methodology/approach: The paper takes a subjective view of complexity, focusing on the “lived experience” of managers. It takes an updated systematic literature review, and demonstrates the comprehensiveness of a framework to classify complexities of projects. It reports the findings from 43 workshops with over 1,100 managers. Findings: First, the complexity framework is effective in aiding understanding. Second, and somewhat unexpectedly, managers were able to identify strategies to reduce the majority of complexities that they faced. Third, the workshops identified a typology of responses to residual complexities. Research limitations/implications: The framework has demonstrated its utility, and a gap in understanding emergent complexities is identified. The framework further presents the opportunity to explore the recursive nature of complexity and response. Practical implications: This paper provides a framework that is both comprehensive and comprehensible. The authors demonstrate that complexities can be reduced and provide a means to assess responses to residual complexities, including potentially matching managers to projects. Originality/value: This work extends the previous systematic review combined with extensive empirical data to generate findings that are having impact in practice, and have the potential to strengthen a relatively neglected area within OM. A research agenda is suggested to support this.

Purpose: The purpose of this paper is to understand the context of major projects and their management from an OM perspective; the authors provide a foundation for exploring how the body of work on lean production (the “old” theory) can contribute to the development of major projects (the “new” context). In doing so, it extends the prevailing economic approach to major projects (best described as “predict and provide”) and posits the development of an alternative approach based on extending the lean production logic to this new context (referred to as “predict and prevent”). Design/methodology/approach: The paper investigates the scope for adopting lean practices in context of major project. To this effect the authors review the current state of both lean thinking and major project management, and use “Universal Credit” as an exploratory case study to illustrate and verify the arguments in practice. Findings: Two main findings are proposed: first, the authors demonstrate the inherent performance challenge of major projects in OM terms, which the authors argue presents significant scope for the application of OM concepts to improve major project performance. Second, using lean thinking as framing, the authors identify three distinct process levels and common wastes in major projects, and identify five principles how lean could improve the delivery of major projects. Research limitations/implications: Major projects present an untapped area for OM research; based on the exploratory case the authors propose ways how OM concepts can be applied to this new context. Further research will be needed to validate and generalise. Practical implications: Major projects, including organisational transformations, IT-enabled change, major events and large infrastructure projects, constitute a large proportion of economic activity. Despite their prominence, however, they are also commonly associated with low success rates. This paper provides one route for exploring how a successful set of principles could be applied to improving their performance. Originality/value: This work translates a popular set of ideas from OM to strengthening a relatively neglected context within OM. An agenda for further research is suggested to support the development of this application.

Analyzing and leveraging data effectively has been an advantageous strategy in the management workflows of many contemporary organizations. In business and finance, data-informed decision workflows are nowadays essential for enabling development and growth. However, there is yet a theoretical or quantitative approach for analyzing the cost–benefit of the processes in such workflows, e.g., in determining the trade-offs between machine- and human-centric processes and quantifying biases. The aim of this work is to translate an information-theoretic concept and measure for cost–benefit analysis to a methodology that is relevant to the analysis of hybrid decision workflows in business and finance. We propose to combine an information-theoretic approach (i.e., information-theoretic cost–benefit analysis) and an engineering approach (e.g., workflow decomposition), which enables us to utilize information-theoretic measures to estimate the cost–benefit of individual processes quantitatively. We provide three case studies to demonstrate the feasibility of the proposed methodology, including (i) the use of a statistical and computational algorithm, (ii) incomplete information and humans’ soft knowledge, and (iii) cognitive biases in a committee meeting. While this is an early application of information-theoretic cost–benefit analysis to business and financial workflows, it is a significant step towards the development of a systematic, quantitative, and computer-assisted approach for optimizing data-informed decision workflows.

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