Developing Construction Project Material Procurement Strategy using Integrated FMEA-DEA Approach in Kraljic’s Portfolio Matrix

This research aims to develop procurement strategies for the Central Services Division at PT Freeport Indonesia, focusing on construction material procurement. The study integrates Failure Modes and Effects Analysis (FMEA), Data Envelopment Analysis (DEA), and the Kraljic’s Portfolio Matrix to address inefficiencies and improve material management practices. These methodologies help identify critical risk factors, assess supplier performance, and categorize materials based on their impact and supply risk. The study identifies that the procurement items are distributed across the Kraljic quadrants as follows: six items in the Leverage quadrant, ten items in the Strategic quadrant, nine items in the Bottleneck quadrant, and nine items in the Non-Critical quadrant. The findings provide a robust framework for enhancing procurement strategies, leading to cost savings, reduced material wastage, and improved operational efficiency.

Introduction

In the latter half of the 20th century, Indonesia’s mining industry underwent unprecedented expansion thanks to the discovery of vast mineral reserves. Among them was the Grasberg mine, operated by PT Freeport Indonesia (PTFI), which became renowned as one of the world’s largest deposits of gold and copper (PT. Freeport Indonesia, 2023). This landmark achievement attracted international investment and expertise, leading to the implementation of several underground mine expansion projects that were created to extend the life of the mine and access deeper ore reserves as open-pit mining reached its limits. Underground mining was anticipated to allow PT Freeport Indonesia to continue mining at the Grasberg mining complex until 2041.

To support and execute the underground mines expansion project, PTFI established the Central Services Division (CSD), which provides engineering, project management, construction, and commissioning (EPCC). The CSD also provides engineering and technical support to the company’s other divisions. The CSD faces challenging material management circumstances. This support is crucial for the integrated and efficient functioning of the company’s operations, especially in a complex mining environment.

Within years, some business issues related to material management arose from the current CSD operation. The dynamic of industry and PT Freeport Indonesia’s change affected those business issues, which can be dissected into two primary logistical challenges that impede operational efficiency:

Problem 1: Project Material not Available during Construction

This issue pertains to a critical supply chain inefficiency, manifesting as a deficiency in ensuring the suitable materials are available at the right time and place to meet construction schedules. This unavailability can be attributed to several factors, such as poor demand forecasting, lag in supplier lead times, or inefficiencies in inventory management. The repercussions of this unavailability are multifaceted, impacting the immediate timelines and cost structures of specific projects and the broader operational throughput.

Problem 2: Excessive Project Material Inventory at CONS Yard

Conversely, the second problem highlights an issue of inventory excess, wherein there is an accumulation of project materials beyond the current and projected needs. This can lead to wasted resources due to material perishability and reduced storage effectivity. This reflects a misalignment between inventory holding practices and the just-in-time (JIT) inventory philosophy, which advocates minimizing inventory levels and aligning them closely with the project schedules. Addressing this problem would involve strategies such as inventory optimization models, which balance the carrying costs against the ordering costs and service level requirements.

Both problems signify a disconnect between the anticipated project schedules and the realities of the material lifecycle within the CSD’s Material Management. The CSD needs to reevaluate its strategic procurement strategy.

Efficient procurement is critical for the success of large-scale construction projects. PT Freeport Indonesia (PTFI) has encountered significant challenges in managing surplus, stand-by materials, and material delivery delays, particularly in its Central Services Division. In recent years, the complexity of supply chains has increased, necessitating more sophisticated procurement strategies (Bardy & Hillebrand, 2011). Adopting a holistic, process-oriented approach to procurement that encompasses the entire value chain from sub-suppliers to end-users is important (Bardy & Hillebrand, 2011). This study addresses these challenges by integrating Failure Modes and Effects Analysis (FMEA), Data Envelopment Analysis (DEA), and the Kraljic Portfolio Matrix. These methodologies provide a comprehensive approach to identifying risks, evaluating supplier performance, and strategically categorizing materials, ultimately enhancing procurement and inventory management processes.

Literature Review

Integrating FMEA, DEA, and the Kraljic Portfolio Matrix provides a comprehensive approach to optimizing procurement strategies. FMEA allows for the identification and prioritization of risks in the procurement process. DEA evaluates the efficiency of suppliers and internal processes, highlighting areas for improvement. The Kraljic Portfolio Matrix then categorizes procurement items, guiding strategic decisions based on supply risk and profit impact. This integrated approach ensures that procurement strategies are robust, data-driven, and aligned with the overall cost reduction and operational efficiency goals.

Kraljic’s Portfolio Matrix

The Kraljic Portfolio Matrix, introduced by Peter Kraljic in 1983, is a strategic tool for classifying procurement items based on their supply risk and profit impact. Kraljic’s model divides items into four categories: non-critical, leverage, bottleneck, and strategic. Each category requires a different procurement strategy. For example, leverage items are typically high in profit impact but low in supply risk, suggesting that the organization can use its purchasing power to negotiate better terms. Bottleneck items have high supply risk and low-profit impact, requiring strategies to ensure supply continuity. This model helps companies to prioritize their procurement efforts and develop tailored strategies for different categories of items (Kraljic, 1983).

Failure Mode and Effects Analysis FMEA

FMEA is a highly effective and well-established method for identifying, categorizing, and analyzing failures to assess their associated risks. By implementing this method, we can identify failures and avoid their occurrence (Dagsuyuet al., 2016). Various industrial standards, such as those set by the Society of Automotive Engineers, the US Department of Defense, and the Automotive Industry Action Group, incorporate the Risk Priority Number (RPN) as a quantitative method to evaluate and prioritize potential failure modes. The RPN considers factors such as the likelihood of a failure occurring, the severity of the consequences if it does occur, and the ability to detect the failure before it causes harm.

This comprehensive approach allows organizations to proactively identify and address high-risk failure modes to enhance the safety and reliability of their products and processes. FMEA identifies potential failures by assigning a value or score for each failure mode based on occurrence level, severity level, and detection level (Stamatis, 2003). FMEA uses a score of 1 and 10 (with 1 being the best and 10 being the worst case) is given for each of the three factors and a risk-priority-number (RPN). Thus, the RPN value helps the FMEA team to identify the components or subsystems that need priority actions for improvement (Dinmohammadi & Shafiee, 2013).

Three main FMEA types have been formed since it was first developed, as follows (Carlson, 2012):

1. Design FMEA

2. Process FMEA

3. System FMEA

In certain studies, Failure Mode and Effects Analysis (FMEA) has been combined with Multiple-Criteria Decision-Making (MCDM) techniques to improve the process (Chanamool & Thanakorn, 2016). Different decision-making methods have been used to prioritize the risks identified in the FMEA. (Yousefiet al., 2018). One of these techniques is Data Envelopment Analysis (DEA) (Chinet al., 2009), which will be explained in the following section.

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a linear programming methodology used to assess the efficiency of decision-making units (DMUs) such as schools, hospitals, or sales outlets (Charneset al., 1978). DEA evaluates relative efficiency in situations with one or multiple inputs and outputs. The model needs to be run individually for each unit to determine the relative efficiency of all DMUs. DEA categorizes DMUs into efficient and inefficient units. Initially proposed by Charneset al. (1978) (CCR model), other scholars further refined DEA. The DEA models traditionally rely on the linearity assumption for the virtual inputs and outputs (i.e., the weights coupled with the ratio scales of the inputs and outputs imply linear value functions) (Despotiset al., 2010). Data Envelopment Analysis is a technique that enhances FMEA’s assessment capabilities. It suggests that DEA can provide a more comprehensive ranking of failure modes by considering multiple criteria and offering corrective information on the severity, occurrence, and detection of failures (Chang & Sun, 2009).

Research Methodology

This study employs a mixed methods approach to integrate FMEA, DEA, and the Kraljic Portfolio Matrix for material management optimization. Data were collected through interviews with stakeholders, analysis of inventory records, and field observations. The FMEA process involved identifying potential failure modes, their effects, and causes within the procurement process, assigning severity, occurrence, and detection scores to calculate the Risk Priority Number (RPN).

The author requested decision-makers to complete a questionnaire to assess the specified risk criteria using the FMEA approach. This method involves decision-makers drawing on their experience with each supply risk to evaluate the Occurrence (O), Severity (S), and Detection (D) factors for every failure mode and commodity criterion. The FMEA measures the maximum and minimum scoring of S, O, and D of every failure mode, which are geometrically averaged to reflect the overall risks of the failure modes. DEA was used to evaluate the efficiency of procurement processes and purchase order commodities.

The evaluation of commodities according to Profit Impact is quantitative. Using the DEA model, commodities evaluated their efficiency score to help classify them into high- and low-profit impacts for the Kraljic Portfolio Matrix. Inputs include quantity purchased, and outputs include lead time, total purchased value, and cost per unit.

After the scoring and DEA model implementation are completed, the assessment of supply risk and profit impact is consolidated within the Kraljic Portfolio Matrix utilizing Orange software. Orange is a powerful open-source data mining and machine learning tool that offers a user-friendly visual programming interface for robust data analysis and visualization. Notably, Orange employs the Euclidean distances model to transform all scores, ensuring a comprehensive and accurate perspective for decision-making.

Result

The research methodology involved the utilization of Process FMEA (Failure Mode and Effects Analysis) to systematically identify potential failure modes, their corresponding effects, and the root causes of failures. Additionally, the study entailed documenting the existing process controls implemented within the procurement of construction materials in the Central Services Division. The sub-processes within the procurement workflow were carefully assessed to identify those with higher priority levels, upon which detailed investigations into failure, effects, causes, and controls were executed. All data were identified through discussion and observations in the Central Services Division. The complete Process FMEA information is available in Table I.

Table I. Procurement of Construction Material FMEA

Process	Process step	Potential failure mode	Potential effects of failure	Potential causes of failure	Current process controls
Procurement of construction material	Create material take off	Incorrect material and quantity requirement	Project delays, purchasing delays, cost overruns, overstocking, surplus material	Poor planning, wrong design, miscommunication,errors in bill of material	Engineering Services Requisition (ESR) review through call center
	Request quotation, request for bids	Delays in RFQ and bid issuance	Purchasing delays, Project delays	Administrative and communication bottlenecks	Communication email, request for a bids call center
	Vendor selection	Incorrect supplier chosen	Poor quality, material delivery delays	Inadequate supplier evaluation, limited supplier	Bidding process, result review email
	Placing purchase order	Purchase order errors	Incorrect material, delivery delays, incorrect quantity, overstocking	Data entry errors	Material take off call center step-by-step review process
	Delivery scheduling	Delays in material delivery	Construction project delays	Logistics issues, supplier issues, custom clearance issues	Regular follow-ups with the expediting team, monitoring through the SAP system
	Receive and inspect materials	Incomplete or defective materials received	Rework or project delays	Poor supplier quantity/quality control	Inspection upon arrival, packaging check, and count
	Inventory management	Inventory mismanagement	Missing damaged material	Poor inventory and material tracking, lack of real-time data, inadequate storage facilities	Inventory database system, SAP system

Upon completing the identification of all pertinent information in the Process FMEA, a scoring process was carried out for Severity (S), Occurrence (O), and Detection (D) by six internal Central Services stakeholders. This group of stakeholders comprised the Construction Manager, Procurement Section Head, Engineering Manager Section Head, Field Engineering Section Head, Senior Material Control Staff, and Project Control Section Head. The failure modes identified in FMEA are summarized in Table II.

Table II. Procurement Process Failure Modes

Failure mode	Coding
Incorrect material and quantity requirement	FM1
Delays in RFQ and bid issuance	FM2
Incorrect supplier chosen	FM3
Purchase order errors	FM4
Delays in material delivery	FM5
Incomplete or defective materials received	FM6
Inventory mismanagement	FM7

To obtain the final values of the risk priority number (RPN) for every commodity and its associated failure modes, the author calculates the RPN using the geometric mean of every scoring of Severity (S), Occurrence (O), and Detection (D) in the questionnaire on the respective failure mode and then multiplies it as shown in (1).

(1) $$\begin{array}{r}RPN=Severity\times Occurance\times Detection\end{array}$$

Every stakeholder is asked to score 1 to 10, with 1 being the best and 10 being the worst case for each of the three factors and a priority (RPN). An example of RPN’s calculation is available in Table III.

Table III. The RPN for Commodity (Example)

Commodity	Incorrect material and quantity requirement
	S	O	D	RPN
Actuator	6.45	2.49	2.18	35.09
Audible device	4.48	1.82	2.04	16.61
Cable brackets	7.54	1.70	2.85	36.56
Cable trays	7.74	1.91	3.05	45.05
Cables	7.94	3.91	2.94	91.46

The complete list of supply risk RPN results for every commodity in a respective failure mode is available in Table IV. The next step is to evaluate supply risk and profit impact using the DEA model. Every commodity is calculated using the DEA model to obtain its efficiency score. For supply risk, the DEA model uses virtual input as input and risk criteria, which is the aggregate RPN of the commodity, as output. Meanwhile, for profit impact evaluation, the DEA model uses the total quantity purchased of the commodity as input. The model’s output uses Lead Time, Total Purchase Value, and commodity cost per unit obtained from internal Central Services data, which is shown in Table VIII.

Table IV. The FRPN of Supply Risk

Commodity	FM1	FM2	FM3	FM4	FM5	FM6	FM7
Actuator	46.59	75.6	43.9	45.36	116.48	46.59	75.6
Audible device	25.92	37.54	24.96	24.64	72.58	25.92	37.54
Cable brackets	43.2	37.44	25.27	27.22	63.84	43.2	37.44
Cable trays	52.48	69.44	33.26	30.24	90.71	52.48	69.44
Cables	112.64	84.66	48.64	61.71	103.68	112.64	84.66
CCTV	26.21	24.96	23.18	24.84	43.47	26.21	24.96
Circuit breakers	89.22	103.36	59.16	69.12	136.4	89.22	103.36
Compressor	55.49	66.96	57.02	52.9	95.68	55.49	66.96
Conveyor	134.06	151.01	107.52	85.56	186.37	134.06	151.01
Doors	62.72	61.15	73.42	58.88	102.08	62.72	61.15
Ducting	182.78	207.36	239.62	105.79	286.72	182.78	207.36
Electrical fittings	103.36	95.68	98.6	73.08	168.9	103.36	95.68
Electrical panels	103.36	102.67	86.77	59.16	149.41	103.36	102.67
Electrical switch	98.19	109.12	92.8	73.08	163.07	98.19	109.12
Flowmeter	92.93	86.64	63.23	48.38	99.36	92.93	86.64
FSS	206.64	155.65	125.12	81.6	203.11	206.64	155.65
Furniture	51.84	32.83	32.64	27.1	68.82	51.84	32.83
Gatic ditch	36.29	32.83	26.88	28.34	68.82	36.29	32.83
Geotextile	63.23	51.84	40.8	34.5	95.04	63.23	51.84
Interface panel	117.76	119	95.3	62.64	146.16	117.76	119
Lighting	111.87	91	47.42	47.04	116.93	111.87	91
Lube pump	119.23	106.4	113.09	74.4	160.08	119.23	106.4
Paints	33	23.12	16.46	20.16	49.39	33	23.12
Pipe fittings	109.3	62.4	61.2	47.04	123.42	109.3	62.4
Pipes	67.32	39.6	37.63	27.1	81.66	67.32	39.6
PLC panel	146.83	153.92	167.44	98.95	198.4	146.83	153.92
Remote	125.12	131.04	109.3	83.75	182.53	125.12	131.04
Steel	134.06	127.3	87.7	70.99	163.33	134.06	127.3
Switch	87.36	87.58	92.16	57.34	110.43	87.36	87.58
Terminations kits	118.56	98.21	83.6	63.84	154.01	118.56	98.21
Transformer	133.76	137.1	117.04	66.96	168.91	133.76	137.1
UPS	67.2	62.93	71.28	46.37	122.73	67.2	62.93
Valves	161.28	140	105.79	69.6	183.74	161.28	140
Wall material	27.04	23.04	21.74	24.19	61.82	27.04	23.04

The complete list of evaluated supply risks and their impact on profits, as determined by the DEA model, is detailed in Table V.

Table V. Commodity Supply Risk and Profit Impact Efficiency Score

Commodity	Supply risk	Profit impact
Actuator	0.48045	0.81636
Audible device	0.27927	0.90793
Cable brackets	0.39764	0.58215
Cable trays	0.43651	1
Cables	0.69479	1
CCTV	0.20717	0.40613
Circuit breakers	0.75909	0.77129
Compressor	0.42512	1
Conveyor	0.80012	0.49000
Doors	0.46952	0.47250
Ducting	1	0.79059
Electrical fittings	0.84010	0.58127
Electrical panels	0.80665	1
Electrical switch	0.80665	0.90884
Flowmeter	0.59435	0.46744
FSS	1	0.73360
Furniture	0.26980	0.30645
Gatic ditch	0.27812	0.19162
Geotextile	0.35280	0.40303
Interface panel	0.71871	0.58068
Lighting	0.53412	1
Lube pump	0.71716	0.72261
Paints	0.20014	0.34519
Pipe fittings	0.61495	1
Pipes	0.41402	0.57221
PLC panel	0.97463	1
Remote	0.67950	1
Steel	0.86593	0.40128
Switch	0.73235	0.65047
Terminations kits	0.79874	0.65300
Transformer	0.70404	0.67584
UPS	0.53452	0.85305
Valves	0.85122	0.74583
Wall material	0.29615	0.38339

The Orange software is used to analyze the efficiency scores for each commodity, and it will generate a Euclidean matrix. This Euclidean matrix, which represents the distances between different commodities regarding their efficiency scores, will then be fed into the Kraljic Portfolio Matrix. Kraljic’s Portfolio Matrix is a strategic tool used in procurement and supply chain management to classify products based on their importance and supply risk. This step is a crucial part of the analysis process. It helps in making informed decisions about procurement strategies, as shown in Fig. 1. The summary of classification obtained from plotting commodity supply risk and profit impact in the Kraljic Portfolio Matrix is shown in Table VI.

Fig. 1. Kraljic portfolio matrix for construction material procurement using euclidean distance model.

Table VI. Commodity Classification

Commodity	Class	Commodity	Class
Actuator	Bottleneck	Gatic ditch	Non-Critical
Audible device	Bottleneck	Geotextile	Non-Critical
Cable brackets	Non-Critical	Interface panel	Leverage
Cable trays	Bottleneck	Lighting	Bottleneck
Cables	Bottleneck	Lube pump	Strategic
CCTV	Non-Critical	Paints	Non-Critical
Circuit breakers	Strategic	Pipe fittings	Bottleneck
Compressor	Bottleneck	Pipes	Non-Critical
Conveyor	Leverage	PLC panel	Strategic
Doors	Non-Critical	Remote	Bottleneck
Ducting	Strategic	Steel	Leverage
Electrical fittings	Leverage	Switch	Leverage
Electrical panels	Strategic	Terminations kits	Strategic
Electrical switch	Strategic	Transformer	Strategic
Flowmeter	Leverage	UPS	Bottleneck
FSS	Strategic	Valves	Strategic
Furniture	Non-Critical	Wall material	Non-Critical

The non-critical quadrant comprises nine commodities with low-profit impact and low supply risk. While necessary, these commodities do not significantly affect the company’s profitability or supply stability. The Leverage quadrant contains six commodities with high-profit impact and low supply risk. These commodities contribute significantly to profitability and are sourced from stable markets. The Bottleneck quadrant is also one of the large quadrants, with nine commodities, indicating that many procurement commodities have a low-profit impact but high supply risk. If not managed properly, these items can disrupt operations. The strategic quadrant, which contains 10 commodities and is the largest among all quadrants, encompasses those with both high-profit impact and high supply risk. These commodities are critical to the company’s operations and profitability, necessitating a robust strategic approach.

Recommendation and Discussion

The Kraljic Portfolio Matrix is a critical tool for developing tailored procurement strategies by categorizing materials based on supply risk and profit impact. This framework aids organizations like PT Freeport Indonesia optimize their procurement process to enhance efficiency, minimize risks, and achieve cost savings. Below is a detailed narrative elaboration of the recommended procurement strategies for each matrix quadrant.

Leverage Items (High-Profit Impact, Low Supply Risk)

Materials in this category include steel, electrical fittings, conveyors, interface panels, switches, and flowmeters. These items are characterized by their significant impact on profits and relatively low supply risk. The primary strategy for leveraging items is maximizing purchasing power and negotiating favorable terms to reduce costs.

Recommended Strategies: To capitalize on the high-profit impact and low supply risk, competitive bidding should be employed to drive down prices. This involves inviting multiple suppliers to bid for contracts, fostering competition, and securing the best possible deals (Gaddeet al., 2010). Additionally, volume consolidation can be used to negotiate bulk discounts. By consolidating purchase orders, PT Freeport Indonesia can leverage higher volumes for better pricing and terms (Monczkaet al., 2015). Long-term contracts with suppliers can ensure price stability and supply security, further enhancing procurement efficiency. Continuous market analysis is crucial for monitoring market trends and leveraging opportunities to secure favorable pricing (Caniels & Gelderman, 2005). Based on Table VII, Leverage-class commodities with a total purchase value of $520,093.00 offer significant opportunities for cost savings through negotiation and bulk purchasing due to their high volume and relatively stable supply markets.

Table VII. Total Purchased Value of Commodity Classification

Non-Critical/routine	Leverage	Bottleneck	Strategic
$ 1,058,170.00	$ 520,093.00	$ 2,0687,298.00	$ 1,400,984.00

Central Services Division must carefully follow the recommended strategy for competitive Bidding to drive down prices. From previous experience, the lowest prices vendors offer are not always the suitable choice. CSD always considers the delivery or lead time of material to be the most prominent criterion. Most leverage items depend on an importation scheme; the local content produced, such as flowmeter, switch, conveyor materials, and electrical fittings, is still low. This significantly affects the supply, which depends on the global supply chain and government regulation. Every stakeholder should consider balancing on-time delivery and the lowest cost offered.

The procurement strategy of consolidating volume to negotiate a bulk discount applies in the Central Services Division. Leverage items such as steel, electrical fittings, switches, and conveyor materials are often used in CSD construction projects. CSD can also create agreements or joint purchase agreements with other divisions, such as Operation Maintenance and Mill. Both divisions will require the same material to maintain their facility’s operation.

The long-term contracts with suppliers’ strategy, which can ensure supply price and security, have already been implemented in PT. Freeport Indonesia. Conveyor material suppliers like Sandvik already have a long history in PT. Freeport Indonesia. Sandvik has already established its vendor-managed warehouse and permanent representative on-site. This is to ensure the availability of material and technical assistance required on-site. The strategy needs to expand to other leverage items, such as flowmeters, which are also very critical parts and widely used in operations.

Strategic Items (High Profit Impact, High Supply Risk)

Strategic items such as FSS, ducting, valves, PLC panels, termination kits, circuit breakers, transformers, lube pumps, electrical switches, and electrical panels require close collaboration with suppliers due to their high impact on profits and high supply risk. With the total purchased value of $1,400,984.00 as shown in Table VII, these items are critical to the organization’s operations and necessitate a strategic approach to ensure reliability and mitigate risks. The high total purchased value highlights the importance of ensuring reliable supply chains.

Recommended Strategies: Developing strategic partnerships and alliances with key suppliers is essential. Such partnerships foster trust and cooperation, improving supply chain integration and risk management (Kraljic, 1983). Risk-sharing agreements can be implemented, where both parties share the risks and rewards, thus ensuring mutual commitment to supply continuity. Joint ventures or investments in suppliers may also be considered to secure long-term supply and strengthen relationships. Supplier development programs can be established to work closely with suppliers, improving their processes and capabilities to ensure a reliable supply of high-quality materials (Gelderman & Van Weele, 2003).

Developing strategic partnerships and alliances with key suppliers is feasible to implement and already has. CSD uses partnerships and alliances with key suppliers such as Transavia Otomasi, Siemens, ABB, and Beckers for strategic items such as PLC panels, electrical switches, and electrical panels. This becomes important to make sure all systems or infrastructures that have been constructed by the Central Services Division have proper integrations and to make sure all technical problems are efficient to manage.

Risk-sharing agreements can be implemented, where both parties share the risks and rewards. In the context of the construction industry, this strategy can be implemented with contractors and clients, who may share risks related to project delays and cost overruns. For the Central Services Division, strategic items such as Fire Suppression System (FSS) and ducting material can implement this strategy. The Central Services Division can create agreements with suppliers not only to provide material but also to provide services in installing and commissioning the material or system. There are several potential vendors that are able and have experience, such as PT Javaland for the FSS system and Daikin Indonesia or ODG for the HVAC ducting system.

Due to company policy, investments in suppliers, which may be considered to secure long-term supply and strengthen relationships, might not be feasible. CSD is a division inside PT. Freeport has no authority to invest in or create a joint venture with suppliers. This strategy might be feasible at the corporate supply chain management or global supply chain level at the parent company, FCX, which is responsible for operations in several sites, such as North and South America, including Indonesia.

Bottleneck Items (Low-Profit Impact, High Supply Risk)

Bottleneck items include remote controls, cables, pipe fittings, lighting, cable trays, compressors, and audible devices. Table VII provided information that with the largest total purchase value of $2,687,298.00, these items pose a high supply risk but have a low profit impact. The focus for these items should be on ensuring supply continuity and minimizing the risk of disruptions.

Recommended Strategies: To manage bottleneck items effectively, diversification of the supplier base is critical. Relying on multiple suppliers reduces dependency on any single supplier and mitigates the risk of supply interruptions (Seuring & Muller, 2008). Stockpiling can be employed to maintain higher inventory levels, providing a buffer against supply chain disruptions. Establishing contingency plans and agreements with suppliers ensures quick response times during shortages. Additionally, identifying and qualifying alternative sources of supply is crucial for mitigating risk and ensuring continuous supply (Kraljic, 1983).

Diversification of the supplier base is critical to resolve bottleneck supplier issues. Relying on multiple suppliers reduces dependency on any single supplier and mitigates the risk of supply interruptions. For bottleneck items such as cable, the Central Services Division still relies heavily on outside Indonesian suppliers (Okonite and Olex, which are US-based cable manufacturers) that have high supply risk regarding the availability and supply chain risk. It is recommended to diversify it with Indonesian suppliers to reduce supply risk. Companies like PT Jembo, one of the leading cable manufacturers in Indonesia, need to be considered by the procurement and bidding team. Its relative proximity to the site will be an advantage.

The Central Services Division can implement the strategy of stockpiling bottleneck commodities to maintain higher inventory levels and provide a buffer against supply chain disruptions. Bottleneck commodities that are relatively general in terms of usage in construction projects, such as lighting, cable trays, and audible devices, will benefit from material availability. The Central Services Division needs to conduct an inventory analysis to determine the optimal stock level on-site based on historical usage rates, historical lead times, and projected or future plans for construction projects.

Stockpiling strategies also need to balance. With limited storage space in the on-site consolidation center, stockpiling strategies must ensure space and resources to accommodate higher inventory. Do not proceed with this strategy if it causes logistic and storage issues.

Establishing contingency plans and agreements with suppliers ensures quick response times during shortages. Internally, the Central Services Division doesn’t have any contingency plan or agreement with suppliers; the development and documentation of a contingency plan are required. The division can look back on what happened when disruptions in the global supply chain affected project progress, such as during the COVID-19 global pandemic. Also need to be considered are negotiation agreements with suppliers that include clauses for expedited delivery and prioritized production during emergencies.

Non-Critical/Routine Items (Low-Profit Impact, Low Supply Risk)

Non-critical or routine items like gatic ditch covers, geotextiles, furniture, wall materials, paints, CCTV, doors, pipes, and cable brackets have a low-profit impact and low supply risk. Although this class poses a low-profit impact and low supply risk, the total purchased value as shown in Table VII is moderately high at $ 1,058,170.00, which is even higher than leverage class items. The strategy for these items should focus on efficiency and cost- effectiveness.

Recommended Strategies: Standardizing specifications can significantly reduce complexity and procurement costs for non-critical items. Automated ordering systems can streamline procurement processes, reducing administrative overhead and enhancing efficiency (Lambert & Cooper, 2000). Utilizing preferred suppliers can benefit from economies of scale and ensure consistent quality. Adopting just-in-time inventory practices helps minimize holding costs and avoid overstocking, ensuring that inventory levels are kept optimal (Gunasekaran & Ngai, 2005).

The strategy of standardizing specifications can significantly reduce complexity and procurement costs for non-critical items. The engineering team of the Central Services Division needs to emphasize standardization or limit design variability without sacrificing the safety factors or operability expectations. With this strategy, any surplus (leftover) and stand-by material will be easier to reallocate to more priority works or projects. On the other side, with standard specifications, engineering will maintain lower supply risk due to more common products and vendors in the market. The most feasible commodities for implementing this strategy are wall/building materials, paints, and pipes.

Utilizing a preferred supplier strategy can benefit economies of scale and ensure consistent quality. Historical data on purchase orders for every commodity in construction material procurement will be valuable for this strategy. The current process in the Central Services Division has already implemented this strategy but is not yet consistent due to many suppliers not always being available to provide the quotation or product. Close or more intense communication in supplier relationships needs to be emphasized, or a database of preferred suppliers should be created or categorized.

Implementing automated ordering systems can streamline procurement processes, reduce administrative overhead, and enhance efficiency. It is crucial to align this strategy with the preferred suppliers’ approach to leverage the benefits of automated ordering systems effectively in non-critical/routine commodities. The speed of procurement and just-in-time delivery became the main key performance indicators. Central Services Division has a limited on-site consolidation center of construction materials, and this strategy will reduce the probability and occurrence of long-term storage that can risk material missing and damaged.

Commodities can now be categorized into four quadrants, each with more specific strategies within these quadrants. It is possible to move between these quadrants, which can be triggered by either market changes or company decisions (Rahman & Nofrisel, 2018). In general and in simple ways, the Central Services Division can do two things—find new suppliers to move the product to a better area or take advantage of economies of scale if possible. On the other hand, changes in the market can happen when the number of suppliers increases, new technology is introduced, or regulations change. Another thing that can be considered is that the Central Services Division needs to reach out to its suppliers to reduce supply risk to justify the profit impact of commodities.

Conclusion

By categorizing procurement items based on the Kraljic Portfolio Matrix, PT Freeport Indonesia ultimately Central Services Division can develop tailored strategies that address the unique characteristics of each category. Leveraging competitive bidding and volume consolidation for leverage items, fostering strategic partnerships with suppliers for strategic items, diversifying suppliers, maintaining higher inventories for bottleneck items, and streamlining procurement processes for non-critical items will enhance procurement efficiency, reduce costs, and mitigate risks. Integrating these strategies ensures that procurement practices align with the overall goals of increasing construction material availability at the site, reducing excessive inventory, cost reduction, and operational efficiency, ultimately contributing to the organization’s success.

Appendix

Table VIII. Internal Data of Profit Impact

Commodity	Total quantity purchased	Tota purchased value	Lead time	Cost per unit
Actuator	2	$ 16,563.00	208.5	$ 8281.26
Audible device	3	$ 11,499.00	255.5	$ 3832.92
Cable brackets	26643	$ 327,543.00	175.96	$ 61.12
Cable Trays	9	$ 5,980.00	363	$ 664.51
Cables	64931	$ 1,182,568.00	128.06	$ 25.64
CCTV	1	$ 2,036.00	106	$ 2035.68
Circuit breakers	10	$ 20,715.00	254.75	$ 2538.5
Compressor	1	$ 44,482.00	119	$ 44481.85
Conveyor	121	$ 118,111.00	159.33	$ 1152.99
Doors	20	$ 49,089.00	132.36	$ 2743.3
Ducting	3301	$ 438,462.00	228.06	$ 3301.58
Electrical fittings	1495	$ 12,659.00	210	$ 214.65
Electrical panels	80	$ 399,446.00	290.39	$ 7245.27
Electrical switch	8	$ 20,693.00	291.5	$ 2303.9
Flowmeter	8	$ 27,626.00	111.5	$ 1942.21
FSS	625	$ 127,705.00	222.38	$ 6406.68
Furniture	229.7	$ 33,540.00	99.86	$ 1742.02
Gatic ditch	10	$ 3,106.00	67	$ 487.43
Geotextile	10070	$ 63,165.00	139.67	$ 6.39
Interface panel	652.5	$ 135,492.00	153.66	$ 8565.27
Lighting	749	$ 662,282.00	291.38	$ 1315.36
Lube pump	13	$ 63,451.00	152.25	$ 4073.78
Paints	6072	$ 253,774.00	79.71	$ 228.24
Pipe fittings	1499	$ 742,077.00	173.11	$ 931.95
Pipes	466	$ 312,879.00	150	$ 2466.63
PLC panel	4	$ 37,271.00	253.75	$ 7072.83
Remote	1	$ 10,660.00	261	$ 10660
Steel	504	$ 156,519.00	112.33	$ 3711.57
Switch	25	$ 69,686.00	197.94	$ 6278.25
Terminations kits	15	$ 14,817.00	230.38	$ 1463.33
Transformer	35	$ 85,838.00	203	$ 6781.28
UPS	6	$ 11,187.00	269.67	$ 3636.48
Valves	54	$ 192,586.00	223	$ 6014.98
Wall material	100	$ 13,038.00	138	$ 177.43