Performance measurement systems in supply chains

PurposeThe purpose of this paper is to determine the key supply chain performance measurement system (SCPMS) implementation variables, on which the top management should focus, so as to improve the effectiveness and efficiency of supply chain (SC).Design/methodology/approachIn this paper, an interpretive structural modeling (ISM)‐based approach has been employed to model the SCPMS implementation variables. These variables have been categorized under “enablers” and “results.” The enablers are the variables that help boost the SCPMS implementation variables, while results variables are the outcome of good SCPMS implementation.FindingsThe paper highlights the variables associated with implementation of SCPMS. A key finding of this modeling is that awareness about performance measurement system (PMS) in SC is a very significant enabler. For better results, top management should focus on improving the high‐driving power enablers such as awareness of PMS in SC, commitment by the top management, consistency with strategic goals, funding for PMS implementation, and effective information systems.Originality/valueIn this paper, an interpretation of SCPMS implementation variables in terms of their driving and dependence powers has been carried out. Those variables possessing higher driving power in the ISM need to be taken care of on a priority basis because there are a few other dependent variables being affected by them.

Manufacturers have been exploring innovative strategies to achieve and sustain their competitive advantages by facing a new era of intensive global competition. Such a strategy is Supply Chain Management (SCM), which has gained a tremendous amount of attention from both researchers and practitioners since the last decade. Well-designed supply chain systems can substantially improve efficiency and product quality, and eventually enhance customer satisfaction and profitability. There is still a lack of integration between Performance Measurement Systems (PMSs) and practical requirements for supply chains. Performance Measurement (PM) is a vital task in SCM because it can help to monitor the progress, identify weak areas, enhance motivation, and strengthen accountability. The methodologies of business PM have been evolving for decades; numerous theories and models of PMS, ranging form design to implementation, have been proposed. However, the vast majority of PM models have concentrated on single business organisations or on partial performance areas. A commonly accepted PMS for supply chains is hardly available. This paper sets out to discuss and review recent development of PMSs, in particular those in relation to SCM, and to suggest further research direction in supply chain PMSs.

The purpose of this paper is to explore the interactions among the imperative barriers of supply chain performance measurement (SCPM) system implementation in the Indian automotive companies. The Indian automotive companies have been facing various issues in implementation of SCPM system. We have used interpretive structural modelling (ISM) approach to investigate the interaction among different barriers in implementation of SCPM system in the Indian automotive industry. The results indicate that lack of awareness related to SCPM system and lack of top management dedication are the most significant barriers. On the other hand, disinclination of the support from distributors, dealers, retailers, lack of training manpower, and inefficient information technology system are the weak barriers. The results also reveal that there is a strong dependence among the barriers. Finally, various guidelines are provided for improving the performance and efficiency of the Indian automotive supply chains.

Performance measures and metrics (PMM) is identified to be an essential aspect of managing diverse supply chains. The PMM improves the firm’s performance by providing open and transparent communication between the various stakeholders of an organisation. The literature suggests that big data analytics has a positive impact on the supply chain and firm performance. Presently, the literature lack studies that recognise the PMM relevant to big data-driven supply chain (BDDSC). The present study is based on a comprehensive review of 66 papers published with the primary objective to identify the various PMMs used to evaluate the BDDSC. The findings suggest that the PMMs applicable to BDDSC can be classified into two non-mutually exclusive categories. The first category represents 24 performance measures used to evaluate the performance of the big data analytics capability and the second category represents 130 measures used for assessing the performance of BDDSC processes. The study also reports the emergence of new performance measures based on increasing use of predictive and social analytics in BDDSC. Based on the results of the study a framework on BDDSC performance measurement system is proposed which will guide the managers to have a robust performance measurement system in their organisation.

The process of choosing appropriate supply chain performance measures is difficult due to the complexity of these systems. The paper presents an overview and evaluation of the performance measures used in supply chain models and also presents a framework for the selection of performance measurement systems for manufacturing supply chains. Three types of performance measures are identified as necessary components in any supply chain performance measurement system, and new flexibility measures for supply chains are developed.

Risk management and performance measurement should be linked together to enable, to each supply chain partner, to define and guide its overall risk profile, as well as to shape its strategic direction. In this frame, the aim of this paper is to propose and to validate an integrated approach for relating risk management into supply chain performance measurement system. The proposed approach is carried out in two sequential phases. After identifying flow, missions and goals of an organization, the first phase focuses on the application of the Supply chain operations reference (SCOR) model and the Activity Breakdown Structure (ABS) to identify supply chain processes and activities. After that, Risk Breakdown Structure (RBS) and Risk Breakdown Matrix (RBM) are applied to identify critical risks and to give a set of performance metrics that is based on those risks. Finally, the second phase completes this set by using the Balanced Scorecard (BSC) framework. For a validation purpose, the proposed approach is applied to the Higher Institute of Industrial Management (ISGI, Sfax-Tunisia) library. A comparative analysis between the identified metrics and those required by the standard ISO 11620 (version 2008) shows the significance and the importance of the proposed approach.

In this article we report the first in-depth investigation of quality measurement practices from a supply chain perspective. Quality measurement in a wood products supply chain was studied in great detail with the objective of increasing the understanding of quality performance measurement practices in a secondary wood products supply chain. Opportunities for improvement were also identified. A single-case study was used as the main research approach, with 30 interviews and observation as major data collection methods. Findings revealed a high degree of internal integration in the focal company, made possible in great part by a continuous improvement effort that expands all of its facilities. Opportunities for improvement were found in external integration, particularly regarding supplier quality management. A disconnect was identified between supply chain members in regard to quality information; particularly, there was a lack of true supply chain quality measures reflecting the contribution of each entity to the overall quality. Results from this research highlight the importance of adopting a systems perspective when designing a supply chain performance measurement system. Poor quality at any point in the supply chain is detrimental to customer satisfaction, hurts profitability, and eventually translates into higher costs for downstream business segments and for the final customer; the end result is a decline in competitiveness of the entire system.

Every firm has to manage its strategic relationships to reach a distinctive competitive advantage. In practice, collaboration is much less adopted than predicated. Especially when a leading actor is missing and mutual trust is lacking, it all becomes a matter of bargaining power. Thus, full collaboration and integration is often far from realized, the two largest barriers being the lack of availability of a supply chain performance measurement system (PMS) and not effectively sharing the risks and benefits derived from collaboration. Within this framework, the contract design plays a relevant role because contracts are primarily seen as a means of coordination. The aim of this article is twofold: to classify risk- and benefit-sharing tools initiating from contract typologies and to identify the drivers in order to choose the most appropriate form of coordination. In order to develop their theory, the authors reviewed evidence that derived from multiple in-depth case studies from different industries. Relevant data and information were collected through direct interviews with operations and supply chain managers and through secondary sources.

PurposeThe purpose of this paper is to assess the current state of performance measurement (PM) in academic literature and in the automotive supply chain (SC). The research question is to what extent PM systems (PMS) in academic literature and in industry are applicable in automotive logistics.Design/methodology/approachThe authors use a combination of a systematic literature review (SLR) and an industry survey. The SLR is used to identify literature on design aspects for PMS and current PMS reported in academic literature. The survey adds an industry perspective and is used to validate the design aspects found in literature. The synthesis aims to deliver both, current research gaps and needs in industry.FindingsThe findings from SLR indicate, there is a broad base of literature regarding design aspects for PMS. Literature on PMS in context of automotive logistics is nevertheless rare. The industry survey leads to the conclusion that conformity with design aspects from literature increases added value of PMS. Nevertheless, current PMS show improvement needs in automotive context. Academic literature lacks detailed process orientation, transparency and is seen as too high level to be helpful for practitioners. For systems in industry, the SC perspective can be improved. In addition, applicability for continuous improvement is identified as research need in industry and literature.Research limitations/implicationsDue to the selected survey approach, additional research is required to obtain more generalizable results. To increase reliability and validity, a selection of the findings should be further analyzed, e.g. by focusing on regions outside Western Europe or a more in depth analysis of selected aspects. In addition insights into selected research topics highlighted in the paper should be assessed in detail by applying different methodologies (e.g. case studies) to validate the findings.Originality/valueThe findings add to the research on PMS. Latest academic literature is reviewed. The findings are combined with an industry perspective. The combination of SLR and a broad survey enables us to draw conclusions which are relevant for researchers and practitioners alike. Where academic research should focus more on the practical applicability, industry can benefit from the findings by integrating a more holistic perspective into their PMS, especially with a SC wide evaluation.

An innovative supply chain performance measurement system incorporating Research and Development (R&D) and marketing policy

Purpose Existing supply chain (SC) performance models are not able to cope with the potential of intensive SC digitalisation and establish a relationship between decisions and decision criteria. The purpose of this paper is to develop an integrated knowledge-based system (KBS) that creates a link between decisions and decision criteria (attributes) and evaluates the overall SC performance. Design/methodology/approach The proposed KBS is grounded on the fuzzy analytic hierarchy process (fuzzy AHP), which establishes a relationship between short-term and long-term decisions and SC performance criteria (short-term and long-term) for accurate and integrated Overall SC performance evaluation. Findings The proposed KBS evaluates the overall SC performance, establishes a relationship between decisions (long-term and short-term) and decision criteria of SC functions and provides decision makers with a view of the impact of their short-term or long-term decisions on overall SC performance. The proposed system was implemented in a case company where the authors were able to develop a SC performance monitoring dashboard for the company’s top managers and operational managers. Practical implications The proposed KBS assists organisations and decision makers in evaluating their overall SC performance and helps in identifying underperforming SC functions and their associated criteria. It may also be considered as a tool for benchmarking SC performance against competitors. It can efficiently point to improvement directions and help decision makers improve overall SC performance. Originality/value The proposed KBS provides a holistic and integrated approach, establishes a relationship between decisions and decision criteria and evaluates overall SC performance, which is one of the main limitations in existing supply chain performance measurement systems.

PurposeThe purpose of this paper is to discuss which are the most important critical success factors (CSFs) to be attained for determining whether a group of companies in a supply chain (SC) is prepared to undergo a qualitative improvement initiative (QII). By answering four critical research questions, the paper focuses on the role of performance measurement systems (PMSs) as a CSF to support QII and discusses which PMS is more appropriate for the different SC context existing in the new economy.Design/methodology/approachThe methodology adopted in this research relies on different approaches. In order to evaluate the readiness of a company in the SC to start a QII, the authors propose a checklist of CSFs defined through a literature review. Further, to evaluate the impact of PMSs to support QII at the SC level, the authors review PMS literature and discuss the characteristics of the various PMS available. Last, in order to select the best PMS to support the QII of companies belonging to different SC, the authors propose a classification matrix based on the SC characteristics.FindingsThe main findings of this research is the understanding of the PMS role in supporting QII at SC level.Research limitations/implicationsThe research presented in this paper needs to be validated through the use of case studies, in order to optimize the methodology proposed.Practical implicationsThis paper offers to academics, managers and practitioners a structured methodology to select the right PMS to support QII in specific SC contexts.Originality/valueFew researches are available exploring the correlation between PMS and QII, especially in particular collaborative environments such as SCs. As a consequence, the methodology and findings of this paper add value to the existing body of knowledge and offer good insights for addressing future research.

This paper deals with the issue of performance measurement system in public sector organization of developing counties through various key performance indicators, keeping in view Pakistan Railways as a case study. This paper also highlights different KPI at three different stages of performance measurement in such type of organizations to propose a complete framework. The subject study is of qualitative nature and it involved literature review of different research studies conducted on performance measurement systems in public sector organizations around world, examination of departmental source record/documents, and interviews of stakeholders. According to some reports Pakistan has the weakest higher education system in the world showing its tendencies towards research environment. Public sector organizations have always been a neglected area in terms of research perspective in the third world countries like Pakistan. PSOs either lack the basic frameworks of performance measurement system or having incomplete/inadequate systems of performance measurement resulting in a further downfall instead of any improvements, which is evident from their performance as well as source documents. The scope of this paper is limited to the inbound material supply chain portion only of Pakistan Railways. Due to lack of an ERP and anticipated difficulty in data collection in a consolidated manner, financial flow and information flow of supply chain is not included in the subject study and only material flow has been taken into account. The findings can be applied to related Public sector organizations’ dealing with the same predicaments by using similar performance measurement system based on KPIs keeping strategical, tactical, and Operational, sides in the internal and external perspective. There is major gap in terms of studies on Public Sector Supply Chain Management specifically of Pakistan Railways. The subject case study is unique in its scope in terms of its design and pattern.

This paper is to investigate the current challenges, trends, relevance and the concept of supply chain performance measurements in developing nation basic metal industries. This paper gives an overview of different performance measurement tools that can be applied to measure and improve the supply chain systems of an organization. Since the study is focuses on supply chain performance measurements practices in the Ethiopian basic metal industries. The paper identifies and discusses the main motives and impact of supply chain performance measurement practice on the performance of basic metal manufacturing industries in Ethiopia and provided solutions to areas that needed improvement. While the study reviews the relevance of the main strategies, models and tools to measure the performance of supply chain in manufacturing industries is done though the research is conducted based on a qualitative methods. Structured questionnaires, field observation and oral interviews research techniques is use to get primary data from the sectors. Performance measure sets is identified through descriptive analysis. This study found that, large number of companies that now accomplish performance measurement systems at local and global level. Even though, most manufacturing firms use traditional performance measurement systems such as financial performance measurement systems. But this traditional performance measurement systems were not properly evaluates the performance and competitiveness of the whole supply chain systems of manufacturing sectors. Also according to this research proposes that the concept of supply chain performance measurement is not fully hold by the Ethiopian basic metal industries and highlights the difficulties associated with its implementation. Therefore, to tackle the challenges and attempt to the current performance measurement limitations, further studies need to involving other sectors and industries needs to be undertaken in order to gain an in-depth understanding of the key factors associated with the accomplishment of supply chain performance measurement practices in Ethiopia.

PurposeThe purpose of this paper is to extend the understanding of how internal organisational processes change in response to external demands, by investigating the changes undertaken by two Polish business schools (b-schools) in anticipation of and in response to the demands of accreditation agencies (AAs) and other powerful stakeholders. Specifically, it examines the internal research-related performance measurement (PM) system and changes in the use of performance information (PI).Design/methodology/approachThe case study method is adopted, using data from publicly available documents and interviews with the faculty and management at the two schools. The data are interpreted and analysed using the neo-institutional theory.FindingsPowerful stakeholders are the primary reason for changes in PM systems and the manner in which PI is used. Specifically, AAs reflect an additional layer in the PM system, allowing for a downward cascading PI effect. This also leads to a wider use of PI across different organisational levels.Research limitations/implicationsThis study focusses on two case studies in a region still undergoing transition. Thus, this analysis could be reinforced through additional cases, different data collection methods and cross-country and between-country comparative analyses.Originality/valueThe changes in PM systems and particularly the use of PI are discussed in the context of Polish higher education (HE) and, more broadly, the entire Central and Eastern Europe (CEE) region. Moreover, the consideration of two b-school cases facilitates a comparative analysis of the differences in PM systems and the use of PI in the context of stakeholders’ PI needs.