Identification and Prioritization of Lean Waste in Higher Education Institutions (HEI): A Proposed Framework

: Waste in HEIs is difficult to identify, so identifying and prioritizing waste is challenging. This research aims to develop a framework within which to identify and prioritize waste reduction in HEIs. The novelty of this study is that it analyzes and prioritizes waste in HEI from the perspec ‐ tive of four stakeholders in teaching, research, and community services, as well as supporting activ ‐ ities. The process of waste identification was undertaken via observation and literature review, while prioritization of waste was based on the criticality level of waste ( CLoW ). Determining the criticality level of waste ( CLoW ) consists of two stages: the first stage is calculating waste scores using questionnaires from students, lecturers, and education staff; the second stage is calculating the critical level of waste using a questionnaire from HEI leaders and analyzing it with fuzzy meth ‐ ods. This study identified 59 types of waste and grouped them into eight types: over ‐ production, over ‐ processing, waiting, motion, transportation, inventory, defects, and underutilization talent. Waste occurs in three HEI activities: teaching, research, community service, and supporting activi ‐ ties. The results also show the priority order of waste reduction and proposed improvements to reduce waste. This study offers a practical contribution to the management of HEIs to identify and prioritize waste reduction. The theoretical contribution of this study is that it fills the research gap of waste reduction prioritization in all aspects of HEI activities involving all HEI stakeholders in ‐ volved in the business process, namely, students, academics


Introduction
Lean manufacturing (LM) has reduced waste and increased efficiency [1].LM is a method for improving quality and efficiency in manufacturing and service industries [2][3][4].Initially, LM was implemented in the automotive industry, then adopted by other industries, including textile, construction, food, medical, electrical and electronics, ceramic, furniture, and service [5,6].Lean manufacturing is a management philosophy and methodology concerned with the endless pursuit of eliminating waste [7].Waste is anything that adds cost, but not value, to a product or final customers [8].Waste was initially recognized in manufacturing as excessive movement, excessive transportation, waiting time, excess inventory, defective products, excess production quantities, and excessive processes.
Quality excellence and process efficiency have become very important in educational institutions [9,10].Higher education institutions (HEIs) are continuously challenged to meet increasing customer demands; therefore, many have turned to continuous improvement methodologies to leverage organizational resources.So, adopting various frameworks as a mechanism for the assurance of quality education and research outcomes has become an accepted practice [11].LM is a suitable methodology for improving performance and embedding a continuous improvement culture.LM can be viewed from the perspective of education as a methodology that enables universities, schools, and teachers to effectively and efficiently teach all students by removing or minimizing wastes or losses associated with the educational process [12].Several higher education institutions (HEI) have used the LM concept to improve the efficiency of scientific activities by eliminating waste and activities that do not add value.HEI faces many challenges and enhances through quality assurance in all its processes [13].Eliminating waste and increasing efficiency can increase student satisfaction and minimize costs [14] as well as leverage its sustainability [15].Sustainability in HEI consists of four dimensions: economic, environmental, institutional/educational/political, and social/cultural [16].The significant positive effect of LM on economic performance indicators (e.g., profitability, profit margin, and return on investment) [17,18].Meanwhile, based on studies by Lima, et.al [19], LM reduced cost, made better use of resources, increased productivity, decreased processing time, and eliminated documents lost.
Waste in HEI can be grouped into overproduction, over-processing, waiting for time, unnecessary motion, transportation, inventory, defects, and underutilized people [20,21].Meanwhile, Kang and Manyonge [22] identified the types of waste and classified them based on the perspectives of three stakeholders: students, academics, and non-academic staff.To successfully develop LM, an organization must identify and prioritize the waste to be reduced [23,24].According to Klein et al. [25], systematic waste reduction is the goal of LM implementation, so prioritizing waste reduction is necessary.Furthermore, systematic identification and waste reduction can increase efficiency, productivity, and competitiveness.In general, industries that always eliminate waste in every process benefit from low inventories of semi-finished goods and finished products, high product quality, increased flexibility, and the ability to meet customer demands and lower operating costs [26].Several researchers have conducted research to determine waste reduction priorities in the manufacturing [24,[26][27][28][29][30][31][32][33][34] and healthcare sectors [35].However, less research is conducted on HEI.
Meanwhile, several researchers have determined the ranking of waste in HEI.Kazancoglu and Ozkan-Ozen [20] identified and determined the priority of waste in a business school.In this study, waste priority was determined by a committee of academic staff using the fuzzy decision-making trial and evaluation laboratory (DEMATEL).Meanwhile, Klein et al. [25] used the analytical hierarchy process (AHP) to compare and prioritize waste between the primary and branch campuses.Nonetheless, the weaknesses of this study include the subjectivity of the assessment and the use of the arithmetic average of the assessments made by several directors of the study center [25].Another study used the waste relationship matrix (WRM) [36], failure mode effect analysis (FMEA), and interpretive structural modeling (ISM) [1] to determine the priority of waste reduction.The limitation of this research is that it only used academic staff as respondents from two faculties, and the identification of waste is only in the teaching and learning process.Further research can be carried out on other processes and involve all stakeholders [1,36].Another research possibility is the identification of waste in online, offline, and hybrid teaching.
Previous research on waste prioritization in HEIs only involved one stakeholder in one of the activities in HEIs.This article aims to analyze waste and proposes an alternative method to prioritize waste reduction in HEI.Prioritizing waste reduction involves many stakeholders such as students, academic staff, non-academic staff, and HEI leaders.Therefore, the novelty of this study is that it analyzes waste prioritization in HEI from the perspective of four stakeholders in teaching, research, and community services, as well as supporting activities.
The remaining sections of this manuscript are organized as follows: Section 2 is a literature review of waste and LM as well as waste in HEI; Section 3 presents a proposed framework to determine waste reduction priorities in HEI; Section 4 presents results and discussion; and Section 5 presents conclusions.

Waste and Lean Manufacturing
The Japanese manufacturing industry, especially Toyota, developed the LM concept.LM is a waste reduction technique that many authors have suggested.The goals of implementing LM are lower production costs, increased output, and shorter production times [37].In practice, LM maximizes product value by minimizing waste.LM defines the value of a product/service as what is perceived by the customer [38].The basic principle of Lean manufacturing (LM) is LM thinking.LM thinking consists of five principles: determining product value based on customer needs, identifying product value streams in the process, uninterrupted value flow, pulling information from consumers (pull system), and pursuing perfection [39].LM is known as a waste reduction technique.At first, Taichi Ohno [8] grouped waste into seven categories: overproduction, over-processing, waiting, transportation, unnecessary inventory, unnecessary motion, and defects.Furthermore, Liker (2004) added the eighth form of waste-unused employee creativity/talent [20].The concept of eliminating waste has had a significant impact on various industries.

Waste in HEI
The application of LM principles in HEI has resulted in significant improvements.The main goal of implementing LM is to eliminate waste.Several HEIs have used the LM concept to improve the efficiency of scientific activities by eliminating waste and activities that do not add value.HEI faces many challenges and must improve quality through quality assurance in all its processes [13].Some researchers categorize waste in HEI into four general categories, namely, people waste, process waste, information waste, and asset waste [40].However, most researchers classify waste as transportation waste, inventory, motion, waiting, over-production, over-processing, defects, and the underutilization of people [20,25,36].There are several wastes in the daily operations of the teaching, research, administration, finance, and human resources in the HEI.Moreover, as opposed to a manufacturing system with tangible results, HEI procedures are less visible, making it more difficult to spot problems as they arise [41].Table 1 displays examples of waste in manufacturing and HEI.Source: elaborated by authors based on Douglas et.al.[14], Sanahuja [12], and Klein et.al.[25].
Academic freedom and autonomy are the challenges to LM implementation in the HEI context.The university complexity is increased because the boundaries of academic freedom and diversity are not clear [25].

Proposed Framework
HEI stakeholders include academic staff, non-academic staff, students, government, industry, and parents [42].But in several articles, the ranking of waste in HEI is carried out by the committee [20], the director of the study center [25], and academic staff [1,36],.Other several articles identified students as HEI stakeholders [43][44][45][46][47][48].Meanwhile, other researchers involved lecturers and students in their research [49,50], and graduate users [51].Other research involved students, academic staff, HEI leaders, and graduate users [52].Waste prioritization must involve stakeholders directly involved in HEI's business processes.This framework aims to determine waste reduction priorities in HEI. Figure 1 shows the several stages in the framework.The process of prioritizing waste involves students, academics, non-academic staff, and heads of study programs.Prioritizing waste is determined based on the criticality level of waste (CLoW) value, which is calculated through several stages, as follows.

Identification of Waste.
Identification of waste through literature review and direct observation.

Assessment of Occurrence Level
Assessment through a questionnaire by students, academics, and non-academic staff.Each respondent assesses the occurrence of every waste by selecting one of the four alternative answers consisting of 1 (never occurs), 2 (rarely occurs), 3 (often occurs), or 4 (very often occurs).

Waste Score Calculation
Based on the results of the questionnaire, the waste score is calculated and normalized using Equations ( 1) and ( 2) = waste th score;  = number of answers Never Occurs of th waste;  = number of answers Rarely Occurs of th waste;  = number of answers Often Occurs of th waste;  = number of answers Very Often Occurs of th waste;  = normalized waste th score

Assessment of Criticality Scale Waste
The assessment is through a questionnaire filled out by HEI leaders.They assess the criticality scale of each waste using a Likert Scale which consists of a value of 1 (very not critical), 2 (not critical), 3 (quite critical), 4 (critical), or 5 (very critical).

Fuzzy Number Transformation
Rensis Likert (1932) introduced the Likert scale, widely used in survey research.The popularity of the Likert Scale is due to several things, including its being easy to modify and compile, easily analyzed by statistical methods, and having high reliability.However, on the Likert scale, respondents are forced to choose an option that may be different from their actual choice [53].Some academics argue that the answers in the Likert Scale are ordinal scale data and that the operations of addition, subtraction, division, and multiplication and the calculation of the mean and standard deviation cannot be done [54].Due to the limitations, the questionnaire answers were analyzed using the fuzzy method; the Likert scale is converted into a fuzzy number.The fuzzy number used is a triangular fuzzy number (TFN) because it is easy to understand and calculate, and it can be applied in uncertain environments [55].
Calculation of critical scale using the fuzzy method follows the steps below.

Transformation Criticality Scale into Fuzzy Number
Each criticality scale answer is converted into a Triangular Fuzzy Number (TFN).The TFN value consists of the lowest value (l), the middle value (m), and the highest value (u).Table 2 shows Transformation into TFN. , = highest value (u) of  ;  = number of the respondent;  = the number of waste.

Calculate the Criticality Level of Waste (CLoW) Value and Prioritize Waste Reduction
Calculation of the CLoW value of each waste using Equation (5).

𝐶𝐿𝑜𝑊 𝑁𝑆 𝑉
The waste that has the largest CLoW value is the waste that is prioritized to be reduced (eliminated).Determining waste reduction priorities based on CLoW means considering the level of occurrence and criticality of waste and shows that the prioritization of waste reduction involves various stakeholders, namely, students, academics, non-academic staff, and HEI leaders.

Result and Discussion
The framework is used at a private university in Indonesia, which was established in 1960.Currently, the university has 22 departments, 1 postgraduate school, a vocational school, engineer professional programs, pharmacist professional programs, nurse professions, teacher professional education, and medical professional education.The university has more than 7000 students and 400 academic staff.
Waste in HEIs is categorized into eight categories of waste, as shown in Table 3. Waste was found in three pillars of the HEI process: teaching, research, and community service, as well as supporting activities.

Research and Community Services
A questionnaire was developed to assess the occurrence level of waste displayed in Table 1.The questionnaire can be seen in Table A1 in Appendix A. After evaluating and obtaining permission from the leadership of the university, the questionnaire was distributed to students, academics, and non-academic staff.The questionnaire was distributed offline and online in September-October 2022.Respondents filled in the questionnaire anonymously.Questionnaires were distributed to all academics, and nonacademic staff of all departments and work units at HEIs and distributed randomly to the students.Seven hundred fifty respondents, consisting of students, academics, and nonacademic staff, assessed waste occurrence.The details are presented in Table 4.The results of the questionnaire and waste score are displayed in Table 5. Score waste calculation and normalization used Equations ( 1) and ( 2).An example calculation of waste excessive/repetitive information/announcement (OPR1) is as follows:  The criticality scale of waste was assessed through a questionnaire by 39 HEI leaders consisting of deans, deputy deans, heads of department, and heads of quality assurance offices.The assessment uses a Likert scale and is transformed into a fuzzy number, as in Table 2.The mean fuzzy number is calculated using Equation (3).To get a single value of the criticality scale, defuzzification is performed using Equation (4).To calculate CLoW, we used Equation (5).The average fuzzy number, defuzzification value, and CLoW value, as well as the rank of waste, can be seen in Table 6.In this research, waste has been identified in the three pillars of the HEI process: teaching, research, and community Service [59], as well as supporting activities.As seen in Table 3, 59 types of waste have been identified and grouped into eight types: overproduction, over-processing, waiting for time, motion, excessive transportation, inventory, defects, and underutilized talent.LM aims to improve efficiency and effectiveness by reducing waste.Furthermore, efficiency and performance improvement will improve quality, and HEIs must work together with all stakeholders [60].Because of the number of waste in HEI, the priority of waste reduction must be determined.Waste reduction prioritization is based on the criticality level of waste (CLoW) value.The CLoW calculation consists of two stages: the first stage is calculating the waste score through students, academics, and non-academic staff questionnaires; the second stage is calculating the criticality scale of each type of waste by deans, deputy deans, heads of department, and heads of quality assurance offices.Having four stakeholders, this study represents the population better than the previous studies, which only include one stakeholder [1,20,25,36].
According to the Pareto principle, the first twenty percent or twelve top ranks of the CLoW should be prioritized for reduction, as can be seen in Table 7.

WAIT1 Course schedules that cause students to wait Teaching
To reduce the prioritized waste, several activities are proposed, among others: a. Redesign of university information systems.Table 7 shows the waste that is prioritized to be eliminated is "The information system or internet broke down" (WAIT4).Whereas the utilization of information and communication technology (ICT) is an absolute necessity that must be undertaken and utilized by HEIs.Therefore, every HEI needs a reliable and integrated academic information system.Based on interviews, the current state of the information system includes a lack of data integration between departments and supporting work units; there is still a lot of manual data or documents; the information system network often breaks down.Therefore, the university must improve its information system and transform it into internet-based technology.Information systems integrate all components, such as people, management, business processes, and organizational culture [61].As likewise argued by M. Akour and M. Alenezi [62], the development of internet-based technology has changed the educational environment and aided HEIs in making the switch to digital learning.The use of information systems is essential and necessary to achieve good university governance [63,64].Several improvements to the information system that can be made include integrating all academic and nonacademic data throughout the university and digitizing all processes and documents.HEI information system improvements are expected to reduce some other waste including waiting to find files, books, or documents (WAIT5), repeated entry of the same data (OPC5), long bureaucracy (OPC8), waiting for document approval (WAIT2), repeated document checks and/or approvals (OPC3); b.Improvement of procurement and maintenance systems.Effective procurement planning and procurement and maintenance processes will support the smooth running of business processes.Currently, the university does not have an adequate procurement system.This causes the procurement process to take a long time and sometimes the procurement of goods does not match what is needed.Some of the improvements that can be made include establishing a procurement system and increasing the expertise of procurement staff.Improvement of the procurement and maintenance system will reduce waste waiting for the procurement of goods (WAIT3), awaiting repair of broken facilities (WAIT6), and broken equipment or infrastructure (DEF4); c.International journal subscriptions.For conducting good research, appropriate and up-to-date journal references are required.

Conclusions
The criticality level of waste (CLoW) framework developed in this article can be used by organizations, especially HEIs, to determine waste reduction priorities.This framework has been applied to a private university and can be applied in a public university because both have the same business process, namely, the three pillars of the HEI process: teaching, research, and community service, as well as supporting activities.The prioritization of waste that must be reduced becomes the starting point for the improvement plan.HEI stakeholders include students, graduate users, students' families, university leaders and employees, suppliers, secondary schools, other universities, industry, the state, government, taxpayers, and professional organizations [42,65].In this article, we determined the priority of waste reduction, considering the input of four stakeholders, namely students, academics, non-academic staff, and HEI leaders.It is relevant because these four stakeholders can determine the existence of waste.The practical contribution of this study is that this framework can be used for waste prioritization in HEI as well as in school.The theoretical contribution of this study is to fill the research gap of waste reduction prioritization in all aspects of HEI activities, involving all HEI stakeholders involved in the business process (i.e., students, academics, non-academic staff, and HEI leaders).The limitation of this research is that it only determines the priority of waste reduction and provides suggestions for improvement.Considerably more work will need to be done to develop selection methods of improvement projects to reduce waste.Another possible future research avenue would be to use multi-criteria methods to determine CLoW.

Table 1 .
Examples of manufacturing waste and HEI.

Table 2 .
Transformation of criticality scale.

Table 4 .
Respondent assessment of waste occurrence.

Table 5 .
Result of the questionnaire and waste score.
To obtain the necessary articles, HEI must subscribe to enough appropriate journals.Currently, universities subscribe to journal databases via Science Direct limited to several disciplines.However, research requires interdisciplinary analysis, so the university should subscribe to another journal database.In addition, academic staff and students can access the database of journals subscribed to by The Directorate General of Higher Education-Ministry of Education and the Cultural Republic of Indonesia and the National Library of Indonesia.It will reduce the lack of research and community service (UT4) and the unabsorbed research and community services budget (UT6 and UT7); d.Improve work equipment and laboratory equipment and provide teaching and research software.Besides providing laboratory equipment and research and teaching software, resource sharing is important.Any equipment and software must be shared with other departments.It will reduce waste equipment movement (MOT2), no necessary equipment available in the room/classroom (TRP4), and waste required materials/ equipment not available (INV3); e. Integrated course schedule development.Course schedules and room usage should be prepared jointly between study programs.It will reduce waste course schedules that cause students to wait (WAIT1), unbalanced lecture daily schedules (OPR4), moving between classrooms (MOT1), inappropriate class capacity (INV2), and unused classrooms (DEF5).