A systemic methodology for the reduction of complexity of the balanced scorecard in the manufacturing environment

[EN] The main objective of this paper is to develop and validate a methodology to select the most important key performance indicators from the balanced scorecard. The methodology uses and validates the implicit systemic hypothesis in the balanced scorecard model, together with a qualitative and statistical analysis. It helps to determine a small set of indicators that summarizes the company's performance. The method was tested using actual data of 3 complete years of a multinational manufacturing company's balanced scorecard. The results showed that the scorecard can be summarized in six metrics, one for each dimension, from an initial scorecard composed of 90 indicators. In addition to reducing complexity, the method tackles the hitherto unresolved issues of the analysis of the trade-offs between different dimensions and the lagged effects between metrics.Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2020). A systemic methodology for the reduction of complexity of the balanced scorecard in the manufacturing environment. Cogent Business & Management. 7(1):1-18. https://doi.org/10.1080/23311975.2020.1720944S11871Anand, M., Sahay, B. S., & Saha, S. (2005). Balanced Scorecard in Indian Companies. Vikalpa: The Journal for Decision Makers, 30(2), 11-26. doi:10.1177/0256090920050202Banker, R. D., Chang, H., Janakiraman, S. N., & Konstans, C. (2004). A balanced scorecard analysis of performance metrics. European Journal of Operational Research, 154(2), 423-436. doi:10.1016/s0377-2217(03)00179-6Bansal, A., Kauffman, R. J., & Weitz, R. R. (1993). Comparing the Modeling Performance of Regression and Neural Networks as Data Quality Varies: A Business Value Approach. Journal of Management Information Systems, 10(1), 11-32. doi:10.1080/07421222.1993.11517988Boj, J. J., Rodriguez-Rodriguez, R., & Alfaro-Saiz, J.-J. (2014). An ANP-multi-criteria-based methodology to link intangible assets and organizational performance in a Balanced Scorecard context. Decision Support Systems, 68, 98-110. doi:10.1016/j.dss.2014.10.002Chytas, P., Glykas, M., & Valiris, G. (2011). A proactive balanced scorecard. International Journal of Information Management, 31(5), 460-468. doi:10.1016/j.ijinfomgt.2010.12.007Dong, Y., & Qin, S. J. (2018). A novel dynamic PCA algorithm for dynamic data modeling and process monitoring. Journal of Process Control, 67, 1-11. doi:10.1016/j.jprocont.2017.05.002Ferenc, A. (2011). Balanced scorecard measurement applications at a car manufacturer supplier company. https://pdfs.semanticscholar.org/f10e/409533c49dd2934ace78405126978302ab96.pdfFisher, R. A. (1992). Statistical Methods for Research Workers. Breakthroughs in Statistics, 66-70. doi:10.1007/978-1-4612-4380-9_6Gans, D. J. (1981). Corrected and Extended Tables for Tukey’s Quick Test. Technometrics, 23(2), 193-195. doi:10.1080/00401706.1981.10486265Grillo, H., Campuzano-Bolarin, F., & Mula, J. (2018). Modelling performance management measures through statistics and system dynamics-based simulation. Dirección y Organización, (65), 20-35. doi:10.37610/dyo.v0i65.526Gurrea, V., Alfaro-Saiz, J.-J., Rodriguez, R., & Verdecho, M. J. (2014). Application of fuzzy logic in performance management: a literature review. International Journal of Production Management and Engineering, 2(2), 93. doi:10.4995/ijpme.2014.1859Hoque, Z. (2014). 20 years of studies on the balanced scorecard: Trends, accomplishments, gaps and opportunities for future research. The British Accounting Review, 46(1), 33-59. doi:10.1016/j.bar.2013.10.003Junior, I. C. A., Marqui, A. C. & Martins, R. A. (2008). Multiple case study on balanced scorecard implementation in sugarcane companies. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.572.3364&rep=rep1&type=pdfKaplan, R. S. (2009). Conceptual Foundations of the Balanced Scorecard. Handbooks of Management Accounting Research, 1253-1269. doi:10.1016/s1751-3243(07)03003-9Ku, W., Storer, R. H., & Georgakis, C. (1995). Disturbance detection and isolation by dynamic principal component analysis. Chemometrics and Intelligent Laboratory Systems, 30(1), 179-196. doi:10.1016/0169-7439(95)00076-3Malmi, T. (2001). Balanced scorecards in Finnish companies: A research note. Management Accounting Research, 12(2), 207-220. doi:10.1006/mare.2000.0154Morard, B., Stancu, A. & Jeannette, C. (2013). Time evolution analysis and forecast of key performance indicators in a balanced scorecard. Global Journal of Business Research, 7(2), 9–27.Noerreklit, H., & Schoenfeld, H.-M. W. (2000). Controlling Multinational Companies: An Attempt to Analyze Some Unresolved Issues. The International Journal of Accounting, 35(3), 415-430. doi:10.1016/s0020-7063(00)00064-9Rodriguez, R. R., Saiz, J. J. A., & Bas, A. O. (2009). Quantitative relationships between key performance indicators for supporting decision-making processes. Computers in Industry, 60(2), 104-113. doi:10.1016/j.compind.2008.09.002Sanchez-Marquez, R., Albarracin Guillem, J. M., Vicens-Salort, E., & Jabaloyes Vivas, J. (2018). A statistical system management method to tackle data uncertainty when using key performance indicators of the balanced scorecard. Journal of Manufacturing Systems, 48, 166-179. doi:10.1016/j.jmsy.2018.07.010Sánchez Márquez, R., Albarracín Guillem, J. M., Vicens-Salort, E., & Jabaloyes Vivas, J. (2018). Intellectual Capital and Balanced Scorecard: impact of Learning and Development Programs using Key Performance Indicators in Manufacturing Environment. Dirección y Organización, (66), 34-49. doi:10.37610/dyo.v0i66.534Verdecho, M.-J., Alfaro-Saiz, J.-J., & Rodriguez-Rodriguez, R. (2014). A Performance Management Framework for Managing Sustainable Collaborative Enterprise Networks. Lecture Notes in Computer Science, 546-554. doi:10.1007/978-3-662-44745-1_54Walczak, S., & Cerpa, N. (1999). Heuristic principles for the design of artificial neural networks. Information and Software Technology, 41(2), 107-117. doi:10.1016/s0950-5849(98)00116-

Marketing and sustainability

'Marketing and sustainability' is based on an original booklet written by Martin Charter in 1990. The text has been updated and re-written to take account of the changing and emerging debate of marketing’s role in relation to sustainable development. This booklet has been produced as a supporting publication for the Sustainable Marketing Knowledge Network (Smart: Know-Net) a web-based information and communication platform for marketers interested in sustainability, available at www.cfsd.org.uk/smart-know-ne

Governance for sustainability: learning from VSM practice

Purpose – While there is some agreement on the usefulness of systems and complexity approaches to tackle the sustainability challenges facing the organisations and governments in the twenty-first century, less is clear regarding the way such approaches can inspire new ways of governance for sustainability. The purpose of this paper is to progress ongoing research using the Viable System Model (VSM) as a meta-language to facilitate long-term sustainability in business, communities and societies, using the “Methodology to support self-transformation”, by focusing on ways of learning about governance for sustainability. Design/methodology/approach – It summarises core self-governance challenges for long-term sustainability, and the organisational capabilities required to face them, at the “Framework for Assessing Sustainable Governance”. This tool is then used to analyse capabilities for governance for sustainability at three real situations where the mentioned Methodology inspired bottom up processes of self-organisation. It analyses the transformations decided from each organisation, in terms of capabilities for sustainable governance, using the suggested Framework. Findings – Core technical lessons learned from using the framework are discussed, include the usefulness of using a unified language and tool when studying governance for sustainability in differing types and scales of case study organisations. Research limitations/implications – As with other exploratory research, it reckons the convenience for further development and testing of the proposed tools to improve their reliability and robustness. Practical implications – A final conclusion suggests that the suggested tools offer a useful heuristic path to learn about governance for sustainability, from a VSM perspective; the learning from each organisational self-transformation regarding governance for sustainability is insightful for policy and strategy design and evaluation; in particular the possibility of comparing situations from different scales and types of organisations. Originality/value – There is very little coherence in the governance literature and the field of governance for sustainability is an emerging field. This piece of exploratory research is valuable as it presents an effective tool to learn about governance for sustainability, based in the “Methodology for Self-Transformation”; and offers reflexions on applications of the methodology and the tool, that contribute to clarify the meaning of governance for sustainability in practice, in organisations from different scales and types

Big data in higher education: an action research on managing student engagement with business intelligence

This research aims to explore the value of Big Data in student engagement management. It presents an action research on applying BI in a UK higher education institution that has developed and implemented a student engagement tracking system (SES) for better student engagement management. The SES collects data from various sources, including RFID tracking devices across many locations in the campus and student online activities. This public funded research project has enhanced the current SES with BI solutions and raised awareness on the value of the Big Data in improving student experience. The action research concerns with the organizational wide development and deployment of Intelligent Student Engagement System involving a diverse range of stakeholders. The activities undertaken to date have revealed interesting findings and implications for advancing our understanding and research in leveraging the benefit of the Big Data in Higher Education from a socio-technical perspective

Construction IT in 2030: a scenario planning approach

Summary: This paper presents a scenario planning effort carried out in order to identify the possible futures that construction industry and construction IT might face. The paper provides a review of previous research in the area and introduces the scenario planning approach. It then describes the adopted research methodology. The driving forces of change and main trends, issues and factors determined by focusing on factors related to society, technology, environment, economy and politics are discussed. Four future scenarios developed for the year 2030 are described. These scenarios start from the global view and present the images of the future world. They then focus on the construction industry and the ICT implications. Finally, the preferred scenario determined by the participants of a prospective workshop is presented

Requirements engineering for computer integrated environments in construction

A Computer Integrated Environment (CIE) is the type of innovative integrated information system that helps to reduce fragmentation and enables the stakeholders to collaborate together in business. Researchers have observed that the concept of CIE has been the subject of research for many years but the uptake of this technology has been very limited because of the development of the technology and its effective implementation. Although CIE is very much valued by both industrialists and academics, the answers to the question of how to develop and how to implement it are still not clear. The industrialists and researchers conveyed that networking, collaboration, information sharing and communication will become popular and critical issues in the future, which can be managed through CIE systems. In order for successful development of the technology, successful delivery, and effective implementation of user and industry-oriented CIE systems, requirements engineering seems a key parameter. Therefore, through experiences and lessons learnt in various case studies of CIE systems developments, this book explains the development of a requirements engineering framework specific to the CIE system. The requirements engineering process that has been developed in the research is targeted at computer integrated environments with a particular interest in the construction industry as the implementation field. The key features of the requirements engineering framework are the following: (1) ready-to-use, (2) simple, (3) domain specific, (4) adaptable and (5) systematic, (6) integrated with the legacy systems. The method has three key constructs: i) techniques for requirements development, which includes the requirement elicitation, requirements analysis/modelling and requirements validation, ii) requirements documentation and iii) facilitating the requirements management. It focuses on system development methodologies for the human driven ICT solutions that provide communication, collaboration, information sharing and exchange through computer integrated environments for professionals situated in discrete locations but working in a multidisciplinary and interdisciplinary environment. The overview for each chapter of the book is as follows; Chapter 1 provides an overview by setting the scene and presents the issues involved in requirements engineering and CIE (Computer Integrated Environments). Furthermore, it makes an introduction to the necessity for requirements engineering for CIE system development, experiences and lessons learnt cumulatively from CIE systems developments that the authors have been involved in, and the process of the development of an ideal requirements engineering framework for CIE systems development, based on the experiences and lessons learnt from the multi-case studies. Chapter 2 aims at building up contextual knowledge to acquire a deeper understanding of the topic area. This includes a detailed definition of the requirements engineering discipline and the importance and principles of requirements engineering and its process. In addition, state of the art techniques and approaches, including contextual design approach, the use case modelling, and the agile requirements engineering processes, are explained to provide contextual knowledge and understanding about requirements engineering to the readers. After building contextual knowledge and understanding about requirements engineering in chapter 2, chapter 3 attempts to identify a scope and contextual knowledge and understanding about computer integrated environments and Building Information Modelling (BIM). In doing so, previous experiences of the authors about systems developments for computer integrated environments are explained in detail as the CIE/BIM case studies. In the light of contextual knowledge gained about requirements engineering in chapter 2, in order to realize the critical necessity of requirements engineering to combine technology, process and people issues in the right balance, chapter 4 will critically evaluate the requirements engineering activities of CIE systems developments that are explained in chapter 3. Furthermore, to support the necessity of requirements engineering for human centred CIE systems development, the findings from semi-structured interviews are shown in a concept map that is also explained in this chapter. In chapter 5, requirements engineering is investigated from different angles to pick up the key issues from discrete research studies and practice such as traceability through process and product modelling, goal-oriented requirements engineering, the essential and incidental complexities in requirements models, the measurability of quality requirements, the fundamentals of requirements engineering, identifying and involving the stakeholders, reconciling software requirements and system architectures and barriers to the industrial uptake of requirements engineering. In addition, a comprehensive research study measuring the success of requirements engineering processes through a set of evaluation criteria is introduced. Finally, the key issues and the criteria are comparatively analyzed and evaluated in order to match each other and confirm the validity of the criteria for the evaluation and assessment of the requirements engineering implementation in the CIE case study projects in chapter 7 and the key issues will be used in chapter 9 to support the CMM (Capability Maturity Model) for acceptance and wider implications of the requirements engineering framework to be proposed in chapter 8. Chapter 6 explains and particularly focuses on how the requirements engineering activities in the case study projects were handled by highlighting strengths and weaknesses. This will also include the experiences and lessons learnt from these system development practices. The findings from these developments will also be utilized to support the justification of the necessity of a requirements engineering framework for the CIE systems developments. In particular, the following are addressed. • common and shared understanding in requirements engineering efforts, • continuous improvement, • outputs of requirement engineering • reflections and the critical analysis of the requirements engineering approaches in these practices. The premise of chapter 7 is to evaluate and assess the requirements engineering approaches in the CIE case study developments from multiple viewpoints in order to find out the strengths and the weaknesses in these requirements engineering processes. This evaluation will be mainly based on the set of criteria developed by the researchers and developers in the requirements engineering community in order to measure the success rate of the requirements engineering techniques after their implementation in the various system development projects. This set of criteria has already been introduced in chapter 5. This critical assessment includes conducting a questionnaire based survey and descriptive statistical analysis. In chapter 8, the requirements engineering techniques tested in the CIE case study developments are composed and compiled into a requirements engineering process in the light of the strengths and the weaknesses identified in the previous chapter through benchmarking with a Capability Maturity Model (CMM) to ensure that it has the required level of maturity for implementation in the CIE systems developments. As a result of this chapter, a framework for a generic requirements engineering process for CIE systems development will be proposed. In chapter 9, the authors will discuss the acceptance and the wider implications of the proposed framework of requirements engineering process using the CMM from chapter 8 and the key issues from chapter 5. Chapter 10 is the concluding chapter and it summarizes the findings and brings the book to a close with recommendations for the implementation of the Proposed RE framework and also prescribes a guideline as a way forward for better implementation of requirements engineering for successful developments of the CIE systems in the future