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Breakthrough improvement requires management decisions, which indicates that making sense of existing opportunities is important. This is a particular challenge when the improvement is a possibility and not a problem. The purpose of this paper is to propose the practice of doing an Opportunity Study as the way to create a sense of management urgency for realising dormant possibilities.

A process-based Opportunity Study is presented consisting of a Diagnosing-Analysing-Solving (DAS) approach. Benchmarks are defined and compared with the actual performance resulting in a quantifiable improvement potential (D). Main causes are analysed (A), which leads to proposed solutions (S). The Opportunity Study practice is applied to a cement milling process, a cement plant and a supply network for cement-based building products.

Results indicate that applying DAS methodology highlights realisable opportunities in all of the studied cases. This seems to be a necessary, but not sufficient criterion to create a sense of urgency for facts based change.

The results indicate that there is need for further research for looking at the process of sense making and to what extent facts alone can drive change initiatives.

Results indicate that by a simple review, focusing on what a system can do instead of which the problems are, valuable opportunities for improvement could be detected.

The paper highlights the value of focusing on opportunities.

This study aims to establish a comprehensive satisfaction analysis framework by mining online restaurant reviews, which can not only accurately reveal consumer satisfaction but also identify factors leading to dissatisfaction and further quantify improvement opportunity levels.

Adopting deep learning, Cross-Bidirectional Encoder Representations Transformers (BERT) model is developed to measure customer satisfaction. Furthermore, opinion mining technique is used to extract consumers’ opinions and obtain dissatisfaction factors. Furthermore, the opportunity algorithm is introduced to quantify attributes’ improvement opportunity levels. A total of 19,133 online reviews of 31 restaurants in Universal Beijing Resort are crawled to validate the framework.

Results demonstrate the superiority of Cross-BERT model compared to existing models such as sentiment lexicon-based model and Naïve Bayes. More importantly, after effectively unveiling customer dissatisfaction factors (e.g. long queuing time and taste salty), “Dish taste,” “Waiters’ attitude” and “Decoration” are identified as the three secondary attributes with the greatest improvement opportunities.

The proposed framework helps managers, especially in the restaurant industry, accurately understand customer satisfaction and reasons behind dissatisfaction, thereby generating efficient countermeasures. Especially, the improvement opportunity levels also benefit practitioners in efficiently allocating limited business resources.

This work contributes to hospitality and tourism literature by developing a comprehensive customer satisfaction analysis framework in the big data era. Moreover, to the best of the authors’ knowledge, this work is among the first to introduce opportunity algorithm to quantify service improvement benefits. The proposed Cross-BERT model also advances the methodological literature on measuring customer satisfaction.

The purpose of this paper is to investigate how organisational learning (OL) can occur through process improvement (PI) activities, leading to sustained improvements over time in the context of small- and medium-sized enterprises (SMEs).

The authors study PI practices in six engineering-oriented SMEs via interview-based case studies. The authors draw from a range of literature and use an OL conceptual framework informed by Crossan et al.’s (1999) 4I framework as an analytical lens.

The OL perspective provides new insights to conceptualise the nature of PI as a multi-level practice in SMEs. Effective PI practices within SMEs are shown to be consistent with OL concepts, enabling firms to translate individually identified improvement opportunities into organisational-level changes that result in sustained benefits. A new conceptual model is presented that explains how SMEs can learn through improvement activities. The key role of management support, both operational and strategic, is highlighted. It is necessary for management to provide sufficient PI opportunities to enable and sustain beneficial learning.

The study is based on a sample of engineering-oriented SMEs located in the UK. Further case-based, longitudinal, and survey-based research studies with firms of different types will enhance the generalisability of the findings, allowing the confirmation and extension of the new conceptual model.

The findings provide a theoretically underpinned framework for achieving OL in engineering-oriented SMEs through PI activities. The new model highlights the key mechanisms that enable learning from improvement activities. The findings highlight the key role played by management in introducing additional learning opportunities in the form of new business that requires exploratory learning. Without this, the reduction in improvement opportunities reduces the benefits that can be realised from PI.

OL provides a multi-level perspective to understanding how smaller firms are able to undergo systematic improvements and the support required to continually improve.

The purpose of this paper is to propose and describe a method that uses recurrent problems to increase the efficiency and effectiveness of the diagnosis of new product development (NPD) processes and supports the identification of improvement opportunities. The proposed method, called Diagile, is based on recurrent current reality trees (CRTs) and is a new way of building CRTs that includes best project management practices, and the identification and prioritization of improvement opportunities. To support the execution of the method, recurrent problems were identified and a computational tool to aid the diagnosis, a database of improvement opportunities and an automated spreadsheet to prioritize improvement projects were developed.

The proposed method was evaluated through a controlled experiment at a multinational manufacturer of office supplies.

The results achieved confirm that the use of the Diagile method increases the diagnostic efficiency and effectiveness when compared to diagnoses performed by the traditional CRT method.

The validity of the method must be tested on a larger scale, since this work involved only one controlled experiment for this purpose. The experiment involved the participation of postgraduate research assistants, who cannot be considered specialists in the diagnosis of NPD. One could question whether the method will be as helpful for proficient users as well. The authors did not have proficient users available to run the experiment. However, the authors believe that such a specialist would save time in carrying out a diagnosis with Diagile, and also be more effective in validating the diagnosis. However, this assumption could not be tested here and can therefore be considered a limiting factor of the experiment. Nevertheless, the positive results of the evaluations of the companies and users of the two case studies corroborate the statement that the objective of this work was attained.

The greater efficiency and effectiveness provided by the proposed Diagile method was also evident in the identification and prioritization of improvement opportunities. The experimental group drew up a more relevant and coherent list of improvement projects than the control group, and provided documentation for these projects in the form of project charts. The authors believe these results can be of a great impact if implemented by practitioners.

This paper proposes a new way to perform diagnostic of NPD process. In particular, this process is well known to be highly strategic, nevertheless, normally excluded out of improvement initiatives because of its complexity. The diagnostic method proposed is a powerful tool to assist practitioners finding systemic improvement opportunities, expanding the assessment to all dimensions of a business process, e.g. people, technology and process activities.

The goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects.

Using a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis.

Seven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification.

Any starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list.

Learners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities.

Any successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.

This paper highlights one of the limitations of the continuous improvement (CI) philosophy and contends that CI cannot go on forever. It further suggests that in order to further improve organizations need to increase the system boundary, and proposes ways of doing so.

In order to highlight the limits of CI this paper describes a case study. Using a literature review, it further proposes nine ways of increasing system boundary.

The first finding is that CI is not limitless and there is a logical point where CI cannot be economically justified. At that point, the possibility of increasing the system boundary is required. This paper proposes nine possible ways of expanding this boundary.

The paper presents ways of bringing about radical improvements by increasing the system scope. These ways can be explored by practitioners to bring about major improvements, once incremental improvements have been exhausted.

This paper presents ways for companies to explore radical improvement possibilities, once the incremental improvements have reached a level where they can no longer be financially justified.

New ways of working (NWW) change some fundamental processes in the workplace. NWW practices like teleworking, flexible workspaces, and flexible working hours lead to different behaviors of employees. But does the employment of NWW practices also have an impact on the innovation behavior of employees? This chapter explores this relationship and uses qualitative data from case studies to illustrate the complex linkages between three components of NWW and IWB.

The purpose of this paper is to investigate, through a comparative analysis, the applicability of lean manufacturing practices, such as value stream mapping (VSM), for productivity improvement in recycling centres (RCs) aided by multi-criteria decision analysis.

The study is carried out in five RCs that sort the municipal solid waste of Porto Alegre, one of the main cities in Brazil. Since all of the centres present their labour composed by poor communities’ members, cultural and social characteristics may represent an incremental challenge for lean implementation. Further, these centres are organised in cooperatives, in which decisions are taken through a participatory way and all their members are entitled to vote, undermining and retarding the decision-making process.

The integration of a multi-criteria decision-making tool to the lean practices enables the prioritisation of improvements, complementing the final stage of VSM. In particular, this contribution becomes especially important in cooperatives managed by community, where decisions are often complex and time-consuming. Finally, despite the increasing pressure for better performance of RCs, the existent mindset is still far from the private sector, where lean practices were conceived. Further, the findings suggest that, despite processes similarities, it is not feasible to declare the existence of a one-best practice to such scenario.

In theoretical terms, the authors demonstrate through a multi-case study the adequacy of analytic hierarchy process as a decision analysis tool complementary to the VSM, enabling a broader perspective about this subject. Concerning the practical contribution, the comprehension of the adaptation needs for lean practices implementation within the production context of solid waste RCs provides a framework with guidelines for this sector, when incorporating lean activities. Lean practitioners and eventual municipal authorities involved in improving productivity of community-managed RCs might benefit from this framework, since they will be able to emphasise the development of recommended and already tested lean practices that tend to improve their operational performance.

This paper presents a methodology to nominate and select improvement projects that are perceived as adding value to customers (both internal and external). The structure of the methodology can be explained in three “stages”. First, the methodology suggests a new way of categorizing improvement opportunities, i.e. reactive‐proactive, to “upgrade” the little Q ‐ big Q categorisation. Then, it develops a roadmap that links performance indicators and improvement projects for both reactive and proactive improvements. Finally, it suggests an algorithm to select the improvement project, where the assessment of to what extent the nominated improvement projects add value to customers relies on the comparison between Overall Perceived Benefits (OPB) and Overall Perceived Efforts (OPE). The improvement project perceived as having the largest impact on adding value to customers receives the highest priority.

The research introduces means for improving premanufacturing processes (design, procurement and bidding) by leveraging digitalisation in offsite construction. Specifically, this paper proposes a framework that provides measures for the planning and implementation of digitalisation in offsite construction by positioning building information modelling (BIM) as the key technology and lean principles to add value and reduce waste.

The paper follows the design science research approach to develop the proposed framework and attain the aforementioned objective. The developed framework includes data collection, value-stream mapping and simulation to assess current processes, develop and propose improvements. An empirical implementation is employed to demonstrate the applicability of both the framework and the measures used to evaluate the outcomes.

The application of the proposed three-stage framework resulted in 9.45%–23.33%-time reduction per year for the various improvement categories in premanufacturing phases. Employing simulation and applying the developed measures provide incentive for upper management to adopt the suggested improvements. Additionally, while the empirical implementation was tested on a modular construction company, the methods used indicate that the framework, with its generic guidelines, could be applied and customized to any offsite company.

While several studies propose that BIM-Lean integration offers an advantage in the context of production systems, this paper focuses on the initial design and planning phases, which are mostly overlooked in the literature. Moreover, the present study provides quantitative evidence of the benefits of data integration through BIM technology.