Lean Supply Chain Management measured through the balanced scorecard
Noelia Garcia-Buendia (firstname.lastname@example.org) Universidad de Jaén, Spain
Thomas Borup Kristensen Aalborg University, Denmark
José Moyano-Fuentes Universidad de Jaén, Spain Juan Manuel Maqueira-Marín
Universidad de Jaén, Spain
The purpose of this paper is to propose a performance measurement framework to evaluate lean supply chain management (LSCM) performance. A literature review has been performed to identify the main objectives and performance indicators in LSCM.
After a pretest of the initial elements, a Delphi study involving academics and practitioners has been carried out to refine the most relevant goals and metrics. Finally, an integrated performance measurement framework based on the balanced scorecard approach is proposed. This paper contributes to the body of knowledge in performance measurement.
Keywords: lean supply chain management, balanced scorecard, performance measurement
Lean management (LM) has been adopted by many firms in different sectors in recent decades with the expectation of improving their competitiveness (Moyano Fuentes and‐ Sacristán Díaz, 2012)‐ . The extension of LM to all processes in the focal firm and across suppliers and customers to eliminate waste and inefficiencies is known as Lean Supply Chain Management (LSCM).
Some recent studies have shown the relevance of performance assessment in the LSCM literature, becoming one key aspect within this context (Garcia-Buendia et al., 2020, 2021). Performance evaluation is important to measure the success of lean organizations. The lack of clear understanding about lean performance assessment and the unavailability of appropriate performance measures have led to conflicting results in lean implementation (Sangwa and Sangwan, 2018). Furthermore, performance evaluation should consider obtained results but also organizational goals, aligning
performance assessment and strategy (Melnyk et al., 2014).
Kaplan and Norton (1992) proposed the balanced scorecard (BSC) to evaluate corporate performance from four different perspectives: financial, customer, business process, and learning and growth. After that, Brewer and Speh (2000) adapted this tool to the supply chain sphere. Based on this method, Sangwa and Sangwan (2018) have developed a theoretical performance measurement framework to evaluate the effect of lean implementation in all functions of an organization. Additionally, some authors have developed conceptual frameworks to assess LSCM performance based on the scientific literature (Afonso and Cabrita, 2015; García Buendía et al., 2019). However, research literature as the only resource to design an assessment framework for LSCM may seem insufficient, being necessary the expert validation by academics and practitioners specialized in LM and supply chain management (SCM). Specifically, this research study investigates the following questions:
RQ1. Is it possible to reach a compromise between researchers and practitioners regarding objectives and performance indicators to create a LSCM balanced scorecard?
RQ2. What should be the objective reference against which to compare the real results achieved through LSCM and those planned?
The purpose of this paper is to identify the most relevant goals and performance measures in LSCM and to propose a performance measurement framework that aligns both dimensions of an organization’s strategy as a BSC to evaluate LSCM performance.
This study is organized as follows. This section contextualizes and introduces the research gap, questions and motivation of the present paper. Next section provides an explanation of the methodology used. Then, main findings of the study are presented and discussed. The final section summarizes the paper and offers some conclusions.
The research methodology adopted by the authors has consisted in four phases. First, the identification of LSCM organizational goals and performance indicators through a literature review. Then, a pretest is carried out to ensure that the selection of elements is relevant and information susceptible to be further analyzed is clear. The third step involves quantitatively testing the identified goals and indicators using a Delphi study to verify if they are indeed relevant, and identifying the objective reference against which to compare the actual results achieved in each indicator through LSCM and those planned. This provides more objectiveness, confidence and solid directions for the fourth step: offering practical recommendations through the proposal of a LSCM balanced scorecard. Figure 1 describes the steps followed.
Figure 1. Procedure followed in this study
Literature review and pretest
During Phase 1, a literature review has been performed to identify the main goals and performance indicators in LSCM assessment. The initial review returned around 350 performance measures from 85 papers dealing with this topic. This raw data was analyzed, duplicate indicators removed, and the most used indicators selected by the research team. Twelve organizational goals and twenty-nine performance indicators were included in the first draft of the questionnaire design.
A thorough pretest of the initial list of elements was carried out in Phase 2. Two academics and two practitioners with experience in LSCM examined the list of elements and definitions provided by the research team, and analyzed structure and content of the first draft. Different proposals were suggested, including the removal of some elements, the addition of some relevant indicators, and the modification of various concepts and definitions. Then, suggestions and feedback were discussed by the research team in order to reach a consensus and make the final decision. Finally, the number of performance indicators increased to thirty-five indicators. Table 1 shows the definitive list of measures to be embedded in the first questionnaire of the Delphi study.
Table 1 – List of performance indicators for a LSCM balanced scorecard BSC perspective Organizational goal Performance indicator
Revenue growth Return on assets Cost reduction
return on investment (ROI) return on sales (ROS) return on assets (ROA) cash conversion cycle market share
Customer satisfaction Delivery efficiency Customer value
on-time delivery delivery service rate lead time
customer rejection rate customer satisfaction rate
responsiveness to customer demands joint product development with
joint problem solving with customers certified customer relationship Business process Waste reduction
Supplier relationships Process optimization
inventory turnover ratio productivity
average cost per unit total product cycle time capacity utilization rate first time through
joint problem solving with suppliers suppliers delivery reliability
supplier rejection rate
joint product development with suppliers
supplier lead time certified suppliers
degree of supply base consolidation product development cycle time
Learning and growth
Product/process innovation Information flow
Human capital management
accident frequency rate employees' training rate absenteeism rate
employee turnover employee engagement Note: Elements in italics indicate the additions and suggestions from the pretest
Additionally, the literature review has enabled the identification of active researchers in the study of this topic, scholars that have made key contributions to the field, and representatives from firms that are acknowledged experts in the practice of LSCM.
In Phase 3, a two-round Delphi study has been carried out, bringing together Danish and Spanish experienced practitioners in LSCM with international leading researchers in lean and supply chain management. This work brings together two different groups of experts – researchers and managers – committed to participate in the study. The aim has been to identify and prioritize the goals and performance indicators to evaluate the results derived from LSCM. Moreover, experts were also asked to suggest the most appropriate references against which to compare the actual results achieved through LSCM and those initially planned.
The procedure for selecting experts was based on the guidelines provided by Okoli and Pawlowski (2004) following Delbecq et al. (1975), as a rigorous method to ensure the identification of relevant experts who have deep understanding of the issues under study. A Delphi study does not attempts to be representative of any population but to compose a group decision mechanism formed by qualified experts (Okoli and Pawlowski, 2004).
Experts were divided into panels (Melnyk et al., 2009; Okoli and Pawlowski, 2004).
Their size and constitution were defined based on the nature of the research questions.
In this case, two relevant categories of experts have been considered to hold the most accurate and valuable knowledge about LSCM: academics and practitioners. The design of the study in two different panels enabled the comparison of the perspectives of the different groups. The research team defined different approaches to identify relevant experts able to participate in the study, considering scientific literature, organizations, and professional roles. Personal contacts from the research team fitting the criteria were considered at the beginning, and additional qualified experts were also contacted to avoid any bias.
The list of academics was populated via a literature review about LSCM and performance. The list of practitioners includes mostly personal contacts of the research team with plenty of experience in LM and SCM. Experts were ranked in priority for invitation to the study based on their qualifications, academic production and impact, and professional experience. The target panel size was 15 participants following the recommendations from the Delphi literature of selecting at least 10 people (Okoli and Pawlowski, 2004).
The research team invited up to 34 academics to participate in the study until 15 academics’ confirmation was reached. Similarly, 15 managers were contacted to participate and all of them accepted the invitation. Each invitation was sent via email accompanied by an explanation of the subject of the study, the procedure to be
followed, and the commitment required to completing the study.
Finally, round 1 of the Delphi study was completed by 12 academics from different countries such as Australia, Brazil, Denmark, Italy, the Netherlands, Spain, Sweden, Switzerland, and the USA, and with an average experience of 20 years in LSCM. 13 practitioners with an average experience of 13 years from different sectors as aerospace, automotive, consulting, manufacturing, and retail replied to the first round. Delphi’s round 2 was answered by 10 academics and 12 practitioners. Table 2 shows the composition of each panel during each phase of the Delphi study.
Table 2 – Composition of the Delphi panels
Delphi stage Panel
Total Academics Practitioners
Accepted invitation 15 15 30
Round 1 12 13 25
Round 2 10 12 22
Participants were asked to evaluate the relevance of the proposed organizational goals and performance indicators in LSCM assessment by using a 5-point Likert scale from 1 “low relevance” to 5 “extremely relevant”. Definitions for all the indicators were included, so the information presented would be as much clear and unambiguous as possible. Blank spaces were inserted in the questionnaire so respondents could add any comment, suggestion or proposal.
Fuzzy Delphi method was used to process information received from round 1 of the study. The integration of fuzzy set theory and the traditional Delphi method was proposed by Ishikawa et al. (1993) as a way to improve the proficiency of experts’
judgments. This combination has been previously used in recent operations management-related literature (Chang and Cheng, 2019; Hsu et al., 2017; Kumar et al., 2019; Lee et al., 2018; Tsai et al., 2020), Some of the advantages attributed to this method are the requirement of a small number of samples to achieve objective and reasonable results, and the reduction of survey times and costs for collecting expert opinions. A brief stepwise process of the fuzzy Delphi method (Ishikawa et al., 1993) is given below.
Linguistic terms are transformed into their corresponding triangular fuzzy numbers, based on the concept of membership function introduced by Zadeh (1965). The significant value of element b is evaluated by respondent a as j = (xab; yab; zab), a = 1, 2, 3, …, n, and b = 1, 2, 3, …, m. Then, the weight jb of element b is calculated as jb = (xb; yb; zb), where xb = min(xab), yb =
)1n , and zb = max(zab).
A convex combination value Db is generated by an α cut approach:
ub = zb – α(zb – yb), lb = xb – α(yb – xb); b = 1, 2, 3, …, m.
where α value can range from 0 to 1 based on the optimistic or pessimistic perception of respondents. The value of α = 0.05 represents the intermediate condition.
The exact value of Db can be generated as follows:
ub+(1−λ)lb (ub, lb)=λ¿
where λ represents the degree of optimism for a decision maker and it is used to balance radical judgements from the group of experts.
)is the threshold for screening the most relevant elements. If Db ≥ δ, the element is accepted. Otherwise, it should be rejected.
Results and discussion
This section presents and discusses the findings obtained from the Delphi study, and proposes a performance measurement framework to evaluate LSCM performance.
Twelve organizational goals and thirty-five performance indicators classified in the four perspectives of the balanced scorecard were assessed in the first round of the Delphi study. Fuzzy Delphi method was applied to refine the most relevant elements with a threshold (i.e., δ) of 0.848. Table 3 shows the eight organizational goals and sixteen performance indicators accepted and forwarded to the second round evaluation.
Table 3 – Results from Round 1
BSC perspective Organizational goal Performance indicator
Financial Cost reduction cash conversion cycle
Customer satisfaction Delivery efficiency Customer value
on-time delivery delivery service rate lead time
customer rejection rate customer satisfaction rate
responsiveness to customer demands
Waste reduction Supplier relationships Process optimization
inventory turnover ratio productivity
defect rate first time through
suppliers delivery reliability supplier rejection rate supplier lead time Learning and growth Information flow accident frequency rate
An analysis of the median, mean, and standard deviation of the values given to the different elements of the questionnaire by each panel has been carried out. In general, practitioners have rated the proposed elements higher than academics. The main differences are observed in the financial perspective and the learning and growth perspective, where practitioners perceive goals and performance indicators much more relevant than academia. The most similar values provided by academics and practitioners are located in the customer perspective. Additionally, the most significant perspective in LSCM performance assessment is the customer one for both academics and practitioners. However, the second most relevant BSC perspective is business
process for academia and learning and growth for practitioners. Financial perspective is the least important for both panels.
Accepted indicators from round 1 were used in round 2 for the identification of the reference values against which to compare the actual results achieved through LSCM and those planned. Participants were asked to determine whether the suggested performance indicators should be compared to a target established by the firm, a value from the previous year, results obtained by competition, or other kind of reference, in the assessment of LSCM performance. Figure 2 shows the results from this second round for both panels individually and globally considered.
Figure 2 – Results from Round 2
In general, targeted or historic data from the firm is preferred by both academics and practitioners over the competition results as a reference against to compare the LSCM performance achieved. Light differences can be observed between the academic and practitioner panel. Academics seem to barely choose target value for the financial and customer-related measures, and value from last year in the business process dimension.
On the other hand, practitioners do not show a clear predominance between a definite target and a historic value. Just a few experts chose competence as a reference. Some respondents have added major improvements, sector average, customer requirements, and benchmarks as additional references to be taken into account in the LSCM assessment. For some experts, the use of a single reference as target established by the firm or value from last year is not enough to fully understand LSCM performance.
Proposal of a LSCM balanced scorecard
Organizational goals and performance indicators under study have shown a strong alignment with the four perspectives of the BSC, which makes it suitable to be considered as a performance measurement framework for organizations implementing LM along their supply chain.
According to our results, the assessment of LSCM performance must reflect the reduction of costs as a main financial goal of the firm. Revenue growth and return on assets have been perceived as less important organizational objectives in the LSCM evaluation. The cash conversion cycle is the most relevant indicator to assess the LSCM performance from a financial point of view, whereas profitability, ROI, ROS, ROA, and market share are not greatly significant indicators. This contrast some trends found in the literature, where a more meaningful relevance has been given to financial aspects in LSCM. In fact, some respondent did not find easy to associate financial goals and indicators to the LSCM performance assessment.
Regardless, the results obtained from the Delphi study underline the minor relevance of the financial elements in the LSCM performance assessment compared to other perspectives of the BSC. This may indicate that the extension of LM along the supply chain is perceived to enable operational performance rather than financial outcomes.
Then, the implementation of LSCM might be determined by the desire of achieving operational improvements in the supply chain where financial aspects are left a marginal importance. This perception could lead to a weak compromise and support from top management in the decision of adopting and pursuing the extension of LM across suppliers and customers. Since the link between LSCM implementation and financial performance does not seem to be very relevant, the former runs the risk to appear disconnected from essential strategic decision in any organization.
The customer dimension in LSCM performance evaluation is strongly marked by metrics related to quality and time. On-time delivery, delivery service rate, lead time, responsiveness to customer demands, customer rejection rate, and customer satisfaction rate have been the most relevant performance indicators selected to evaluate the results derived from LSCM. Elements based on a collaborative and cooperative relationship with customers, such as joint product development, joint problem solving, and the relationships with customers certified in quality and delivery, have been considered to perform an inessential role in the evaluation of LM along the supply chain.
The most relevant LSCM organizational objectives within the customer perspective are customer satisfaction, customer value, and delivery efficiency. In this case, the preponderance of customer relationship management has been emphasized in the Delphi study.
The business process perspective focuses on productivity, quality, waste reduction, and supplier relationships of the focal firm. The three objectives proposed in the questionnaire, i.e., waste reduction, supplier relationships, and process optimization, have been confirmed as truly relevant for LSCM. Waste reduction is the primitive main goal of LM, so its priority in the extension of LM along the supply chain is also a key aspect. Supplier relationships must be a strategic objective when implementing LM along the supply chain given the influence that suppliers conduct might have on focal firm activity.
Inventory turnover ratio, productivity, defect rate, first time through, suppliers delivery reliability, supplier rejection rate, and supplier lead time have been agreed to define the most relevant performance indicators in LSCM assessment. These indicators
are related to internal process of the focal firm and also business processes of the supply chain. It is essential to evaluate focal firm performance but also suppliers’ performance along the supply chain. Average cost per unit, total product cycle time, capacity utilization rate, joint problem solving with suppliers, joint product development with suppliers, certified suppliers for reliability in quality and delivery, degree of supply base consolidation, and product development cycle time show less relevance.
Finally, learning and growth perspective deals with information and human resource management issues. This dimension includes the information flow as the most relevant organizational goal in LSCM, and accident frequency rate and employee engagement as meaningful performance indicators in LSCM. Regarding the LSCM objectives, product and process innovation and human capital management are considered less significant.
Similarly, performance indicators as employees’ training rate, absenteeism rate, and employee turnover received lower scores.
It should be noted that the learning and growth perspective of the BSC is possibly the less studied dimension in the literature about LSCM and performance. Financial and operational measures can be easily found in previous works, but issues related to the measurement of innovation and social aspects of the focal firm and the supply chain are not so frequent. This fact is reflected in the number of organizational goals and performance indicators selected for the Delphi study from the literature, but also in the scores provided by experts. In this regard, some respondents suggested goals related to environmental performance, reverse logistics, circular economy, or supply chain integration within this perspective.
In light of the findings obtained from the Delphi study, Figure 3 shows the proposed LSCM balanced scorecard.
Figure 3 – LSCM balanced scorecard proposed Conclusions
This paper provides a LSCM balanced scorecard based on the consensus between experienced academics and practitioners in LSCM regarding the objectives and performance indicators that should be used to assess the achievement of each objective within the four BSC perspectives. Additionally, this work proposes what it should be
the objective reference for each identified performance indicator against which to compare the actual results obtained and those planned.
This study has identified organizational objectives and a set of performance measures that can help managers in selecting and prioritizing the best-suited performance indicators to fulfill the strategic goals of their firm. It will facilitate managers to monitor the LSCM implementation process, allowing to detect significant deviations in the planned results and thus, to make the appropriate decisions at the right time to correct these deviations and achieve the projected results. This would help to achieve more robust and reliable LSCM implementation processes, strengthening the usefulness of the lean supply chain strategy. Our paper also contributes to the performance evaluation of LSCM and its tangible impact on the firm’s objectives.
The authors acknowledge the financial support of Spanish Ministry of Science, Innovation and Universities (Research Project PID2019-106577GB- I00/AEI/10.13039/501100011033) and UJA-FEDER Andalusian Operational Program (Research Project 1261128).
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