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The front-end phase plays an important role in achieving project success, and establishment of performance measurement systems considering project challenges or pitfalls is a way of keeping track of this phase. Early warning signs, a type of proactive performance indicators, may serve as means for improving decision-making and project processes aiming for short- and long-term project success. In this paper, the authors present findings from a study on early warning signs (EWS) in hospital projects' front-end. A preliminary systematisation of identified signs as a contribution to front-end improvement is provided.

The paper is based on a mixed methods approach, using a sequential, exploratory research design comprising document studies, interviews and a survey.

The authors identified 62 challenges for hospital projects' front-end performance and further established four categories of EWS as follows: (1) structure and tools, (2) context and frame factors, (3) management and (4) relational factors and properties. This mirrors the presence of hard and soft issues from previous studies. There is need for clarifying terminology and raising consciousness on EWS. Processual approaches to identify EWS are considered more useful than subsequent established indicators.

The findings from this paper provide insight into EWS in hospital projects' front-end phase. This adds to the general understanding of EWS and contributes to more knowledge on the front-end phase in general.

In the project initiation phase, an appraisal is needed to clarify the strategic problem and alternative solutions. Full-scale construction projects and simple solutions (do-minimum alternatives) should be assessed. The do-nothing alternative is the baseline for the appraisal and an option in itself. The paper explores the role of do-nothing and do-minimum alternatives in public project appraisal, which may significantly impact the attractiveness of a construction project.

The paper presents an empirical study from Norway, which requires external quality assurance (QA) of early project appraisals. The data include an extensive document review of 112 projects and interviews with 41 experts involved in the appraisal processes.

Of 112 appraisals, 110 recommended a major construction project, including cases where the benefits and value were low or uncertain. The do-nothing alternative was generally included as a reference but not treated as a viable option. Do-minimum alternatives were often not explored. By contrast, the external QA reports recommended do-nothing or do-minimum in 28 cases. Interestingly, although political decision-makers rarely reject projects, they may put them on hold indefinitely, implying that the actual outcome in many cases is still do-nothing.

The paper addresses a topic that has been understudied in the literature. The findings contribute to the broader literature on project initiation processes, project appraisal and how to reduce the risk of bias and manipulation in appraisals.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.