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MEASURING AND EVALUATING SUPPLY CHAIN MANAGEMENT
PERFORMANCE OF A COMPANY USING THE SCOR METHOD
Bella Devi Sekar Jati
1
, Firman Pribadi
2
, Nuryakin
3
Master of Management, Muhammadiyah University of Yogyakarta, Yogyakarta, Indonesia
*
bellasekarjati60@gmail.com
2
firmanpribadi@umy.ac.id
3
nuryakin@umy.ac.id
PAPER INFO ABSTRACT
Received: March
2022
Revised: April
2022
Approved: April
2022
Background: The problem with IUP SUMANTO is that it has n
systematically taken performance measurements with a particular model. The
supply of materials in the form of mined sand has problems so it experiences
delays and also has an impact on shipping to sand depots to consumers. With
this problem, the performance of Supply Chain Management (SCM) is
considered not optimal, so research is needed to measure its performance
from the company's supply chain.
Aim: This study aims to measure the performance of Supply Chain
Management (SCM) using the Supply Chain Operation Reference (SCOR)
method to optimize every activity in the company's SCM.
Method: The research was conducted with a qualitative approach through
direct observation, interviewing company experts along with filling out
special questionnaires and documentation. Performance measurement
focused on five core processes, namely Plan, Source, Make, Deliver, and
Return. There are 18 indicators studied with indicators that have the attributes
of Reliability, Responsiveness, and Agility. The method used in this study is
the Analytical Hierarchy Process (AHP). The final value is obtained by
multiplying the performance value with the weight of importance. This
research was conducted at a sand mining company in Yogyakarta.
Findings: The results of this study indicate that the performance of SCM in
the sand mining company is in the good category with a final performance
rating of 77.05 on a scale of 0 to 100. For indicators that have a low-
performance rating below 70, suggestions for improvement will be given.
KEYWORDS
supply chain management (SCM), supply chain operation reference (SCOR),
analytical hierarchy process (AHP)
INTRODUCTION
Today, many companies compete selectively in modern times that aim to want freedom of
competition between companies. The importance of a universal economy and more selective
competition gives awareness to various companies that it is important in managing supply
chains (Ahmad & Yuliawati, 2013).
In this global era, there is a significant impetus to develop the world economy to grow in
market services, which gives a result of the competition of tight businesses and produced by
many companies such as in manufacturing with a wide stage to reach market services and
product manufacturing to add value. This service is exemplified by marketing services,
operations management services, and supply chain services (Liu, Wang, Long, Shen, & Shi,
2019).
Services in the management of operations in the company are strongly related to the series
of Supply Chain Management (SCM) activities. SCM is all parties in the company with its
direct or indirect role to meet customer demand including factories, suppliers, transporters,
warehouses, retailers, and even the customer itself (Chopra & Meindl, 2013).
Measuring and Evaluating Supply Chain Management Performance of a Company Using the SCOR Method
923 Interdisciplinary Social Studies, 1(7), Apr 2022
There are several models used to summarize problems in the inflow and outflow in
building a fairly accurate Supply Chain Management model (Belov, Boland, Savelsbergh, &
Stuckey, 2020). (Belov et al., 2020) Supply Chain Management is built from existing activities
in the Supply Chain including factories (Manufacturers), suppliers, transporters, warehouses,
and etailers. A supply chain is a network of a series of activities (e.g. suppliers, manufacturers,
warehouses, distributors, and retailers) that, through coordinated plans and activities, develop
products by converting raw materials into finished products (Chiadamrong & Piyathanavong,
2017). Unlike supply chain design issues related to the latest Supply Chain configuration, the
redesign problem assumes that the Supply Chain is already there and focuses on repeated
designs to take advantage of any activities contained within the Supply Chain (Hammami &
Frein, 2014).
Supply Chain Management (SCM) has three perspectives as processes, philosophies, and
governance structures that all add value to theoretical understanding and practice in carrying
out supply chain activities. The supply chain has processes in the efficiency of the supply chain,
understanding and improving the activities involved, such as information sharing and
sustainability of its activities. Supply Chain Management (SCM) as a philosophy is essential
to understand the value that can be added to internal integration following the concept of supply
chain orientation (Ellram & Cooper, 2014).
The practice of supply chain activities is a series of activities of organizations or companies
in promoting the effectiveness of the management of upstream activities (Customers,
information, logistics, and outsourcing) and downstream activities (supplier partnerships,
planning, procurement) as well as internal lean activities (supply chain, sub-contracts, storage)
(Gilal, Zhang, Gilal, Gilal, & Gilal, 2017).
Activities in Supply Chain Management (SCM) must be ensured following customer
demand so that it is smooth the flow of its activities. The role of SCM will reduce costs in each
supply chain series with quality control so that quality results and will further provide value to
customers in serving their demands. Supply Chain Management (SCM) activities start from
the relationship of business units with their cooperation to provide what customers want.
Related businesses include suppliers, manufacturing plants, distribution, retail and logistics,
and CS services (Hasibuan et al., 2018).
In every industry, a series of activities starting with the collection of materials then
produced and stored until distribution to consumers is an important link in each activity. The
most important aspect is the improvement and how to survive from the beginning of activities
in the supply chain to the hands of consumers in continue to compete in an increasingly
developed market. In maintaining the product, the company must be careful in supervising
every activity in the supply chain rangakaian (Fauziya & Sitorus, 2019).
The principle of production in operations carried out on each business unit must pay
attention to its external elements, namely from input to output to provide value to consumers.
The integrated approach of Supply Chain Management (SCM) includes a series of material
supply activities, production, and distribution to consumers. The provision of the material in
question is raw materials, semi-finished materials, production, and tools that complement
production activities for the fulfillment of consumer demand (Widyarto et al., 2012).
Based on previous research to redesign Supply Chain Management (SCM) activities if
implemented correctly, improving production performance requires the use of model Supply
Measuring and Evaluating Supply Chain Management Performance of a Company Using the SCOR Method
924 Interdisciplinary Social Studies, 1(7), Apr 2022
Chain Operations Reference (SCOR) to identify processes within the relevant supply chain and
Analytical Hierarchy Process (AHP) in the selection of targets to identify processes within the
relevant supply chain and analytical hierarchy process (AHP) in the selection of targets to
identify processes within the relevant supply chain and analytical hierarchy process (AHP) in
the selection of targets to identify processes within the relevant supply chain and analytical
hierarchy process (AHP) in the selection of targets to identify processes within the relevant
supply chain and analytical hierarchy process (AHP) in the selection of targets to identify the
relevant supply chain and analytical hierarchy process (AHP) in the selection of targets to
identify processes within redesign (Palma-Mendoza, 2014). Supply Chain Operations
Reference (SCOR) is a model widely used in assessing the performance of Supply Chain
Management (SCM) regardless of its generic properties as well as from Supply Chain
Management (SCM) experts weighing to build a model with analytical hierarchy process
(AHP) (Sellitto, Pereira, Borchardt, Da Silva, & Viegas, 2015).
The Analytical Hierarchy Process (AHP) model includes parsing a problem in decision
making into a hierarchical form that leads to a part of the problem that can be easily realized
and evaluated. The Analytical Hierarchy Process (AHP) also determines the priority of
elements at each level of the hierarchy of each decision and synthesizes priorities to determine
the overall priority of alternative decisions so that it is easier to decision making (Gupta,
Mehlawat, Aggarwal, & Charles, 2018).
There are constraints on each company related to Supply Chain Management (SCM) that
exists in the company's internal scope. As in a sand mining company that has obstacles, namely
how to handle production included in the supply chain network to be optimal. There is an
impact arising from Supply Chain Management (SCM) activities, such as in IUP SUMANTO
which has production work problems related to Supply Chain Management (SCM), materials
obtained from sand mine production occur problems resulting in delays in supplying materials
from the mine to the sand depot used as a marketing place.
In sand mining companies, especially in IUP SUMANTO is an industrial mining material
mining business that was once called mining C excavation material. Highly selective
competition between similar businesses, especially in the Special Region of Yogyakarta and
surrounding areas, IUP SUMANTO is determined to have the best quality product results and
market-appropriate prices. The existence of the same type of business competes between its
businesses and also between Supply Chain Management (SCM) activities. Therefore, IUP
SUMANTO needs to supervise Supply Chain Management (SCM) activities to be optimal in
its performance because it is very important. The problem with IUP SUMANTO is that it has
not systematically taken performance measurements with a particular model. The supply of
materials in the form of mined sand has problems so it experiences delays and also has an
impact on shipping to sand depots to consumers. With this problem, the performance of Supply
Chain Management (SCM) is considered not optimal, so research is needed to measure its
performance from the company's supply chain.
Therefore, the purpose of researchers is to take measurements and evaluate the
performance of Supply Chain Management (SCM) which further provides data for the
company about the current state of its performance from the best set of supply chain activities
desired by the company which is then used to formulate improvement proposals af r measuring
and evaluating the performance of Supply Chain Management (SCM) so that the company can
Measuring and Evaluating Supply Chain Management Performance of a Company Using the SCOR Method
925 Interdisciplinary Social Studies, 1(7), Apr 2022
improve so that it has optimal results in managing operations in the sand mining industry to
compete with other companies.
METHOD
A research method called a descriptive study with a qualitative approach is the method of
this research. This study contains an analysis of events that occurred during observation.
The qualitative approach is twofold, namely interactive and non-interactive. This research
includes interactive dues such as ethnographic methods, phenomenological methods, case
studies, basic theories, and critical studies. This type of research is more about research for
case studies in a company whose approach focuses on studies that can change and occur at any
time.
This research focuses on measuring supply chain performance using the SCOR model
which will later be known on which parts need improvement because of the optimal
performance of the existing supply chain. The research was conducted at IUP SUMANTO
which produces sand. The research location at one of the sand mining sites in the Progo River
area, Dusun Jalan, Banaran Village, Kapanewon Galur, Kulon Progo Regency, Yogyakarta
Special Region, and at the IUP SUMANTO sand depot which is located in Banaran Village,
Kapanewon Galur, Kulon Pfrogo Regency, Yogyakarta Special Region.
In this study, the primary data sources are supply chain activities including heavy
equipment suppliers, unloading, mining, sand transportation, stockpiles, disposal, offices, the
environment around mining activities, and the final warehouse to be brought to customers for
all activities in all divisions in the company.
Data processing techniques applied by researchers begin with the calculation of supply
chain performance. Then continued with the Analytical Hierarchy Process (AHP) and the
normalization of Snorm de Boer.
This research is based on the SCOR method and is also used tools to help with calculations
with Microsoft Excel. In Microsoft Excel, there is a basic count in performing scor and AHP
assessment results. The formulas that will be used are basic formulas that are already in this
software.
RESULTS AND DISCUSSION
Plan Process Reliability Attribute Indicator
The weighting of each indicator is taken from the questionnaire data that is used as a matrix
to compare. The stages performed are the same as in the process matrix and the previous
attribute matrix. Normalization and consistency calculations are also the same as process
elements and attributes. The following is the result of calculation, normalization to consistency
in the indicator attributes reliability of the planning process.
Table 1. Plan Process Reliability Attribute Indicator Matrix
Percentages of
Production Unit to
Production Planning
Plan
Employee
Reliability
Energy Used
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926 Interdisciplinary Social Studies, 1(7), Apr 2022
Percentages of Production
Unit to Production
Planning
1
0,33
1
Plan Employee Reliability
3
1
5
Energy Used
1
0,20
1
Total
5,00
1,53
7,00
Table 2. Normalization of Plan Process Reliability Attribute Indicators
Percentages of
Production Unit to
Production Planning
Plan
Employee
Reliability
Energy used
Percentages of Production
Unit to Production Planning
0,20
0,22
0,14
Plan Employee Reliability
0,60
0,65
0,71
Energy Used
0,20
0,13
0,14
Table 3. Weight and Consistency Results Of Plan Process Reliability Attribute Indicators
Total
Weight
Matrix
Eugen
Vector
Eugen
Value
λmax
CI
CR
Percentages of
Production Unit to
Production Planning
0,56
0,19
3,01
3,03
0,01
0,03
Plan Employee
Reliability
1,97
0,66
3,06
Energy used
0,47
0,16
3,01
Plan Process Responsiveness Attribute Indicator
The weighting of each indicator is taken from the questionnaire data that is used as a matrix
to compare. The stages performed are the same as in the process matrix and the previous
attribute matrix. The following is the result of calculation, normalization to consistency in the
attribute indicator responsiveness of the planning process.
Table 4. Plan Process Responsiveness Attribute Indicator Matrix
Time to Market
Production Schedule
Time to Revise
Production Schedule
Time to Market Production
Schedule
1
3
Time to Revise Production
Schedule
0,33
1
Total
1,33
4
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Table 5. Normalization of Plan Process Responsiveness Attribute Indicator
Time to Market
Production Schedule
Time to Revise
Production Schedule
Time to Market Production
Schedule
0,75
0,75
Time to Revise Production
Schedule
0,25
0,25
Table 6. Weight and Consistency Results Of Responsiveness Process Plan Attribute
Indicators
Total
Weight
Matrix
Eugen
Vector
Eugen
Value
λmax
CI
CR
Time to Market
Production Schedule
1,5
0,75
2
2
0
0
Time to Revise
Production Schedule
0,5
0,25
2
Source Process Reliability Attribute Indicator
The following is the result of calculations, normalization to consistency in the source
process reliability attribute indicator.
Table 7. Source Process Reliability Attribute Indicator Matrix
Supplier Source
Fill Rate
Supplier
Relationship
Minimum
Order Quantity
Supplier Source Fill
Rate
1
5
0,50
Supplier Relationship
0,20
1
0,20
Supplier Reliability
2
5
1
Total
3,20
11,00
1,70
Table 8. Normalization of Source Process Reliability Attribute Indicator
Supplier Source
Fill Rate
Supplier
Relationship
Minimum
Order Quantity
Supplier Source
Fill Rate
0,31
0,45
0,29
Supplier
Relationship
0,06
0,09
0,12
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928 Interdisciplinary Social Studies, 1(7), Apr 2022
Supplier
Reliability
0,63
0,45
0,59
Table 9. Weight and Consistency Results Of Source Process Reliability Attribute Indicators
Total Weight
Matrix
Eugen
Vector
Eugen
Value
t or
λmax
THERE
CR
Supplier Source
Fill Rate
1,06
0,35
3,06
3,05
0,03
0,05
Supplier
Relationship
0,27
0,09
3,01
Supplier
Reliability
1,67
0,56
3,09
Source Process Agility Attribute Indicator
The following is the result of calculations, normalization to consistency in the source
process agility attribute indicator.
Table 10. Source Process Agility Attribute Indicator Matrix
Supplier
Flexibility of
Order Quantity
Supplier
Flexibility of
Order Unit Type
Minimum
Order Quantity
Supplier Flexibility
of Order Quantity
1
3
0,20
Supplier Flexibility
of Order Unit Type
0,33
1
0,14
Minimum Order
Quantity
5
7
1
Total
6,33
11,00
1,34
Table 11. Normalization of Source Process Agility Attribute Indicator
Supplier
Flexibility of
Order Quantity
Supplier
Flexibility of
Order Unit Type
Minimum
Order Quantity
Supplier
Flexibility of
Order Quantity
0,16
0,27
0,15
Supplier
Flexibility of
Order Unit Type
0,05
0,09
0,11
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929 Interdisciplinary Social Studies, 1(7), Apr 2022
Minimum Order
Quantity
0,79
0,64
0,74
Table 12. Weight and Consistency Results Of Process Agility Attribute Indicator Source
Total
Weight
Matrix
Eugen
Vector
Eugen
Value
λmax
THERE
CR
Supplier Flexibility of
Order Quantity
0,58
0,19
3,04
3,07
0,03
0,06
Supplier Flexibility of
Order Unit Type
0,25
0,08
3,01
Minimum Order Quantity
2,17
0,72
3,14
Make Process Reliability Attribute Indicator
The following is the result of calculations, normalization to consistency in the indicator of
reliability attributes of the making process.
Table 13. Make Process Reliability Attribute Indicator Matrix
Material Efficiency
(YIELD)
Schedule
Achievement
Material Efficiency (YIELD)
1
3
Schedule Achievement
0,33
1
Total
1,33
4
Table 14. Normalization of Make Process Reliability Attribute Indicator
Material Efficiency
(YIELD)
Schedule
Achievement
Material Efficiency
(YIELD)
0,75
0,75
Schedule Achiement
0,25
0,25
Table 15. Weight and Consistency Results Make Process Reliability Attribute Indicator
Total
Weight
Matrix
Eugen
Vector
Eugen
Value
λmax
CI
CR
Material
Efficiency
(YIELD)
1,5
0,75
2
2
0
0
Schedule
Achievement
0,5
0,25
2
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930 Interdisciplinary Social Studies, 1(7), Apr 2022
Total Weighting
In Table 16 is a total weighting of processes, attributes to indicators. The matrix amounts
to one large weight of 1 because there is no other option or there is only one interest.
Table 16. Total Weight
Level 1
Performance
Indicator
Weight
Level 2
Performance
Indicator
Weight
Level 3 Performance
Indicator
Weight
PLAN
0,06
Reliability
0,83
Percentages of Production
Unit to Production Planning
0,19
Plan Employee Reliability
0,66
Energy used
0,16
Responsiveness
0,17
Time to Market Production
Schedule
0,75
Time to Revise Production
Schedule
0,25
SOURCE
0,14
Reliability
0,26
Supplier Source Fill Rate
0,35
Supplier Relationship
0,09
Supplier Reliability
0,56
Responsiveness
0,11
Supplier Responsiveness to
Order Revision
1
Agility
0,63
Supplier Flexibility of
Order Quantity
0,35
Supplier Flexibility of
Order Unit Type
0,09
Minimum Order Quantity
0,56
MAKE
0,53
Reliability
0,83
Material Efficiency
(YIELD)
0,75
Schedule Achievement
0,25
Responsiveness
0,17
Make item Responsiveness
1
DELIVER
0,21
Reliability
0,50
Order Delivery Full
1
Responsiveness
0,50
Delivery Lead Time
1
RETURN
0,06
Responsiveness
1
Product Replacement Time
1
Performance Calculation
The performance result is the calculation of weight multiplied by the score. Table 17 is the
result of calculating the performance of each indicator. Each indicator has a weight obtained
from the questionnaire results that have been processed in the form of a matrix and the weight
value is the Eugen Vector on each matrix. The score is the result of the data in the company
and has been normalized with the formula Snorm de Boer. Next wit same formula is done to
get the results of the calculation of attribute performance and can be seen in Table 18. The final
result of the total performance of IUP SUMANTO is obtained from the results of performance
calculations from processes originally related to indicators to performance attributes. So that
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931 Interdisciplinary Social Studies, 1(7), Apr 2022
the calculation of the IUP SUMANTO performance measurement value is 77.05 which can be
seen in Table 19.
Table 17. Indicator Performance Calculation
Level 3 Performance Indicator
Weight
Score
Weight x Score
Percentages of Production Unit to Production
Planning
0,19
74
14,06
Plan Employee Reliability
0,65
93
60,45
Energy used
0,16
74
11,84
Time to Market Production Schedule
0,75
100
75,00
Time to Revise Production Schedule
0,25
100
25,00
Supplier Source Fill Rate
0,35
74
25,90
Supplier Relationship
0,09
100
9,00
Supplier Reliability
0,56
80
44,80
Supplier Responsiveness to Order Revision
1
80
80,00
Supplier Flexibility of Order Quantity
0,35
0
0,00
Supplier Flexibility of Order Unit Type
0,09
0
0,00
Minimum Order Quantity
0,56
74
41,44
Material Efficiency (YIELD)
0,75
65
48,75
Schedule Achievement
0,25
70
17,50
Make item Responsiveness
1
100
100,00
Order Delivery Full
1
100
100,00
Delivery Lead Time
1
100
100,00
Product Replacement Time
1
80
80,00
Table 18. Attribute Performance Calculation
Level 2 Performance
Indicator
Weight
Final Value
Weight x Final
Value
Sum
Reliability
0,83
14,06
11,67
88,67
60,45
50,17
11,84
9,83
Responsiveness
0,17
75,00
12,75
25,00
4,25
Reliability
0,26
25,90
6,73
55,63
9,00
2,34
44,80
11,65
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Responsiveness
0,11
80,00
8,80
Agility
0,63
0,00
0,00
0,00
0,00
41,44
26,11
Reliability
0,83
48,75
40,46
71,99
17,50
14,53
Responsiveness
0,17
100,00
17,00
Reliability
0,50
100,00
50,00
100,00
Responsiveness
0,50
100,00
50,00
Responsiveness
1
80,00
80,00
80,00
Table 19. IUP SUMANTO Performance Measurement Value Calculation
Level 1 Performance
Indicator
Weight
Total Each
Attribute
Weight x
Total Each
Attribute
Performance
PLAN
0,06
88,67
5,32
77,05
SOURCE
0,14
55,63
7,78
MAKE
0,53
71,99
38,15
DELIVER
0,21
100,00
21
RETURN
0,06
80,00
4,8
Discussion of SCOR Performance Results
The result of the calculation of the performance measurement assessment that has been
passed is that each indicator has a weight that is not the same as the other and has a size scale
that is also not the same. Furthermore, researchers equalize the parameters through
normalization, among others, with the formula Snorm de Boer and some basic formulas of
percentage calculation to obtain the score value. Furthermore, researchers weighting at the
level of interest at each level, namely from level 1, level 2, and level 3 with the Analytical
Hierarchy Process (AHP) method based on the results of questionnaires from experts of this
company, namely KTT (Head of Mining Engineering).
Based on the results of the count that has been made that the highest weight assessment
for the process at level one is in the delivery process of 100. The second priority is the plan of
88.67. The next option is the process of return, make and source. The performance results of
each level are done by way of normalization score multiplied by the weight which is the result
of the AHP matrix, namely Eugen Vector.
The total performance value of SCM in IUP SUMANTO is 77.05 on a scale of 0 to 100.
This value has shown that SCM performance in the IUP SUMANTO sand mine is at a good or
good level by the performance indicator monitoring system. The calculation results were
obtained from 18 performance indicators measured. Can be seen in Table 4.53. which is a high-
value performance that is between 70 to 100. The lowest performance that is worth below the
underperforming number 70, is presented in Table 4.54. further repairs were made by IUP
SUMANTO.
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Table 20. Highest Performance Value
Level 1 Performance
Indicator
Level 3 Performance
Indicator
Performance
Value
PLAN
Time to Market Production
Schedule
75
SOURCE
Supplier Responsiveness to
Order Revision
80
MAKE
Make item Responsiveness
100
DELIVER
Order Delivery Full
100
Delivery Lead Time
100
RETURN
Product Replacement Time
80
Table 21. Lowest Performance Value
Level 1 Performance
Indicator
Level 3 Performance Indicator
Performance
Value
PLAN
Percentages of Production Unit to
Production Planning
14,06
Plan Employee Reliability
60,45
Energy used
11,84
Time to Revise Production
Schedule
25
SOURCE
Supplier Source Fill Rate
25,9
Supplier Relationship
9
Supplier Reliability
44,8
Supplier Flexibility of Order
Quantity
0
Supplier Flexibility of Order Unit
Type
0
Minimum Order Quantity
41,44
MAKE
Material Efficiency (YIELD)
48,75
Schedule Achievement
17,5
Based on the results of the table above shows 18 indicators have 6 indicators that are of
high value that are above 70. Indicators that have high values are Time to Market Production
Schedule, Supplier Responsiveness to Order Revision, Make item Responsiveness, Order
Delivery Full, Delivery Lead Time, and Product Replacement Time. Indicators that already
have a high value can then be maintained so that the IUP SUMANTO company becomes better.
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Of 18 indicators it turns out to have 12 indicators of low value so it is necessary to make
improvements for each performance indicator. In the process of planning or planning in the
Percentage of Production Unit to Production Planning indicator, it is necessary to improve
performance in production or mining by making more detailed mining planning by considering
the heavy equipment to be used and what needs to be added to be more effective. Furthermore,
the Plan Employee Reliability indicator should be planned for training and certification to
employees so that reliability is more improved and related to production to be better in sand
mining planning. Concerning the Energy used indicator that is intended to use diesel should be
done more detailed calculations in its use because if the diesel is used too much but does not
reach the production target it will be said to waste too much energy. Furthermore, in the Time
to Revise Production Schedule indicator, the production schedule should be made in reserve if
it is necessary to replace the production schedule when rainfall is heavy because mining
production is very dependent on the weather.
The indicator in the sourcing process, namely Supplier Source Fill Rate should be
calculated if added for heavy equipment in the form of excavators which previously amounted
to 2 to 3, if it can still be following the calculation of profits then suppliers, namely heavy
equipment contractors, should add it. Furthermore, the Supplier Relationship indicator should
be for companies with contractors or suppliers often hold meetings or communications related
to solving problems so that contractors can meet planned production targets. Then the Supplier
Reliability indicator should be for excavator operators to be given training again so that
reliability increases so that productivity becomes more effective. In indicators related to
improving the performance of suppliers, namely the Supplier Flexibility of Order Quantity
indicator, the Supplier Flexibility of Order Unit Type indicator is related to the increase in the
number of sand mine production, but from July to December 2021 there has been no increase
in production and there is a decrease every month. The company must emphasize more to the
supplier to increase the production of sand mines or it could try to find other suppliers to
continue to increase production so that the company is more developed in meeting consumer
demand. Furthermore, the Minimum Order Quantity indicator is related to the marketing party
in marketing sand for 6 months there has been no increase in demand so that from suppliers or
heavy equipment contractors also do not improve the performance of mining sand because they
feel they have met consumer demand. The marketing department should be more effective in
marketing the sand that is currently around the Special Region of Yogyakarta and trying to be
outside the area.
In the making process in Material Efficiency (YIELD) you should improve the
performance of sand mining because every sand mining is ensured not only sand but sirtu and
waste in the form of mud are mined, if a lot of waste is mined then reduce the amount of sand
needed. Furthermore, the Schedule Achievement indicator is related to the production time
which from July to December 2021 should produce every day according to the production
schedule plan but some days do not produce due to high rainfall, therefore a backup schedule
should be made in case of high rainfall that allows for the next day to increase production time
from 8 hours to 10 hours so on so that it increases the production of sand mines.
Measuring and Evaluating Supply Chain Management Performance of a Company Using the SCOR Method
935 Interdisciplinary Social Studies, 1(7), Apr 2022
CONCLUSION
1) Based on the results of the study obtained supply chain management (SCM)
performance assessment at IUP SUMANTO based on the scor method of 77.05 from a
scale of 0 to 100. This value has shown that SCM performance in the IUP SUMANTO
sand mine is at a good or good level following the performance indicator monitoring
system. 6 indicators are high value above 70, namely Time to Market Production
Schedule, Supplier Responsiveness to Order Revision, Make item Responsiveness,
Order Delivery Full, Delivery Lead Time and Product Replacement Time. Indicators
that already have a high value can then be maintained performance;
2) The results of performance measurements based on the AHP method are low values on
12 performance indicators. The indicators are Percentages of Production Unit to
Production Planning, Plan Employee Reliability, Energy used, Time to Revise
Production Schedule, Supplier Source Fill Rate, Supplier Relationship, Supplier
Reliability, Supplier Flexibility of Order Quantity, Supplier Flexibility of Order Unit
Type, Minimum Order Quantity, Material Efficiency (YIELD), Schedule Achievement.
The determinant of low-performance indicators is a value below 70 according to the
performance indicator monitoring system;
3) The proposed improvement that should be made after measuring and evaluating data
for supply chain management (SCM) performance is to ask heavy equipment suppliers
to improve their performance or add heavy equipment related to sand mining
production and provide training and certification of operators and other employees to
help understand production improvements, in addition, the marketing department is
also briefed to find additional consumers to increase demand. so that the products and
suppliers are moved to be more effective in mining, then the creation of a new schedule
as a backup when the rainy season arrives and in case of high rainfall that makes
production stop but can run with a new schedule the next day for additional production
time.
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