Vendor Managed Inventory for Strategic Supply Chain of Explosive Material in Coal Mining Operation

The research observed the Supply Chain (SC) of Ammonium nitrate (AN), a critical and high-value explosive material in coal mining operation, which faces disruptions due to fluctuations of global and domestic coal demand, impacting to AN demand volatility. The lengthy, complex, dependency on sole suppliers, and non-integrated business process, coupled with specific mining conditions, results in long procurement lead times, high inventory costs, and coal production halt. This research used Kepner-Tregoe Analysis (KTA), Business Process Engineering (BPE), Vendor Managed Inventory (VMI), and Economic Order Quantity (EOQ) methods to appraises the complex SC situation, assess the business processes, develop an effective and efficient inventory management model and quantify the cost analysis. The VMI design will streamline SC processes by segregating the responsibilities: vendor manages daily procurement and warehouse operations, while the company provides oversight. It also aims to minimize unpredictable delivery times, elimination of shortages through optimized vendor stock, price and fall pricing stability via long-term agreements, enhanced cash flow through a monthly invoice, usage-based reconciliation, and a significant reduction in ordering and inventory holding costs. Eventually, this research contributes the benefits to Company, vendor, and as references for SC experts to develop a strategic SC Management through VMI implementation. 

Introduction

The study observed current AN SC and internal business process of PT Kideco Jaya Agung (KJA), Indonesia third largest single coal producer. The study also observed historical procurement from 2022–2024 for cost analysis, a period characterized by a sharp increase in demand and production in 2022 followed by a downturn in 2024. There are challenges in coal industry facing by the coal producer today, declining and stagnant coal prices, stringent national regulation of unfavorable Domestic Market Obligation (DMO) including potential conflicts with international coal prices, difficulties in fulfilling obligations due to coal quality, national government royalty increments to 28% of selling price, requirement to deposit 100% of Foreign Exchange Earnings from Export, or retention of into a special government account for 12 periods of month.

Global and domestic Coal demand volatility complicates Ammonium Nitrate (AN) SC at KJA. Manual, lengthy processes—from planning to payment—lack of integration and automation, causing data integrity issues. Warehouse management, handled by the mining department, and invoice verification, done by the procurement department, create conflicts of interest and potential audit risks. There are restricted regulations, limited sources of qualified suppliers who have permit licenses for supplying the explosive material, consequently, it creates high dependency and potential risk on late shipment, stock shortage, and high price. For each order, there is always a process of sourcing, price negotiation, ensuring ship availability, and confirming the delivery schedule. Disruptions in all these processes pose significant risks to the Company. The SC issues lie in maintaining a balance between minimizing costs and enhancing customer service with effective process execution. To avoid delays and shortages that could halt production, the company decided to maximize warehouse capacity. Increasing inventory stock levels to maximum ultimately leads to high inventory holding costs.

To address the needs, the company chooses a VMI model as the strategic solution to implement and apply the EOQ as supporting method to determine the optimal order quantity, allowing for a comparison of ordering and carrying incurred costs, calculating the percentage of savings and other variables achieved.

The objective of this research is to identify the most strategic, effective and efficient approach for AN supply chain, going beyond improvements through VMI by achieving the comprehensive design of VMI model and improved business process. It is also expected that this research will have an impact on cost reductions by analyzing and quantifying the cost calculation incurred in materials, ordering, and inventory holding by comparing expenses under the conventional method, the EOQ method, and with VMI implementation.

Literature Study

Determining the inventory model is a crucial part of supply chain management operations as it leads to cost reduction and efficiency by providing options related to inventory value and procurement timing (Ahakonyeet al., 2024). The supply chain involves the strategic design and management of the flow of materials, information, and finances across a supply chain, from raw material acquisition to final product delivery (Thomas & Griffin, 1996).

Kepner-Tregoe Analysis (KTA)

The Kepner-Tregoe Analysis (KTA) method categorizes how to analyze a problem into five areas (Markopouloset al., 2022):

• appraising the situation or business issues to be observed,

• finding the information about why it happens and what the causes of the problem that,

• identify what alternative solutions are available and make proposed choice,

• mitigate and manage risk residual, and

• areas for improvement.

The challenge is to overcome many future problems and potential risks residual, requiring a shift in mindset from intuition and experience to a structured way of thinking (Markopoulos & Vanharanta, 2015). Therefore, instead of discussing opinions, intuitions, and influences too deeply, KTA can be a tool and teach methods and a framework for thinking to overcome these problems (Kahnemanet al., 2021).

Business Process Engineering (BPE)

Business Process Engineering (BPE) is a strategic management approach that involves rethinking and redesigning core activities as a foundation to achieve significant improvements in performance and efficiency, and also creating ideas on how to accelerate work and production, so that the problem of conventional, over control bureaucracy and rigid process can be eliminated (Guoet al., 2020). BPE plays a vital role in complex SC Management to improve interconnected activities to deliver and satisfy customers with minimal total cost, effective, and efficient (Barbosa-Póvoa & Pinto, 2018). An important part of supply chain management is facilitating the flow of goods and information from various sources to the point of use, then how to make plans, rules, technology improvements and processes in various activities such as requisition, warehousing, purchasing, distribution, and production (Al-Shboul, 2017).

Real-time transactions and adaptation to increasingly dynamic changes and information will improve and strengthen supply chain operations that are able to answer the challenges of volatility and uncertainty (Núñez-Lópezet al., 2025). SC business processes rely on flexibility, agility, leanness and speed in meeting and the ability to respond quickly to unexpected events, uncertainty or changes in the market (Benzidiaet al., 2021).

Therefore, a business process can generally be referred to as a complex business activity, which describes the workflow from one person to another, and on a larger scale can be depicted from one department to another, from company to supplier or from company to customer, etc. (Juriket al., 2025). Each business process model that is depicted has different characteristics and some of the existing characteristics include the process objective, process owner, process customer, process input, process output, process efficiency, regulator, process risk and resources as well as important notes in each process (Salieiev, 2024). The company’s ability to quickly adapt to changing market conditions and the use of new technologies is far more important than company size, and this requires companies to be able to create a model application program that orchestrates all sub-processes and services to be integrated, seamless (Schäfferet al., 2021). Diagrams for each activity are suitable for visually describing the process, showing the process sequence and steps in execution, whether manually or automatically, and this process model will help in increasing work efficiency and effectiveness (Figl, 2017).

Vendor Managed Inventory (VMI)

VMI is a solution to bridge or penetrate the just-in-time and stockless purchasing methods, where the supplier is responsible for majority of inventory and supplies the items in short notice (Dong & Xu, 2002). VMI can benefit both parties, the company and the supplier, resulting in better inventory management and ensuring timely stock procurement, minimizing carrying costs and stockouts, so that inventory management principles work as effectively and efficiently as possible by optimizing stock levels, order quantities, ordering times, and delivery times (Lotfiet al., 2022). VMI is an effective supply chain strategy that can give benefits and strategy which enables organizations to share their information between companies and suppliers (Ashrafet al., 2021). In VMI, there is collaboration and shared responsibility between the company as the employer and the vendor as the supplier of goods and services to achieve improving effectiveness and efficiency of procurement and inventory management (Lotfiet al., 2024). In VMI model, supplier provides and manages the product to be sold, once they are issued then the company pays vendor for the sold inventory, until then supplier retains the ownership until the products has been sold (Golpîraet al., 2023).

VMI is a business form with contractual agreement where the vendor is responsible for managing the inventory at the warehouse as this can reduce inventory, lessen the fluctuation effect and reduce stock-outs (Moscaet al., 2019). The workings of the VMI process, delving into contract structures, pricing mechanisms, cost allocation, and invoicing and payment procedures must be designed to optimize mutual benefits (Niaet al., 2015). Compared to short-term agreements, where VMI is found that it could not provide significant benefits to suppliers and even decrease their profits, the long-term contracts are more likely to provide high profits and sales guarantees for suppliers (Dong & Xu, 2002). In a VMI buyer-supplier relationship, three performance outcomes are typically measured: first, customer satisfaction and the service levels achieved for stock issuance and item provision; second, improvements in supply chain control, particularly in maintaining a lean and compliant operation; and third, though less emphasized, reductions in ordering and inventory holding costs (Claassenet al., 2008).

Economic Order Quantity (EOQ)

There is inefficiency in the inventory management procedure due to inconsistency in inventory management, which causes stock shortages, failure to meet company needs targets, and slowness in the issuing and production processes (Niaet al., 2014; Chuang & Chiang, 2016; Rizaet al., 2018; Datta & Pal, 1988). EOQ models are commonly employed in procurement and inventory control, but their analysis is often hindered by several unrealistic and tenuous assumptions, rigid in theory, which can limit their practical applicability in real operation (Salameh & Jaber, 2000). The EOQ model offers a simplified approach to inventory management and to examine the advanced models and quantitative techniques, the robust assumptions and considerations for demand variability, lead time uncertainty, and supply chain disruptions must be included (Ran, 2017).

The fundamental EOQ model is established on several assumptions, which may not be entirely accurate in practical applications in company business practice, as these assumptions may include the demand is steady in fixed numbers and can be predicted over time, the procurement lead-time between placing the order to receiving is constant and rarely changes, the cost of each order remains the same regardless of the order quantity variation, and the cost of holding one unit of inventory in the warehouse per year remains constant (Jaber & Peltokorpi, 2024). The components of ordering costs include the buyer’s salary, administrative overhead, communication costs, utilities, and other expenses incurred during the order placement process, while the holding costs comprise depreciation of inventory value, storage maintenance, insurance, damage of material, and other associated costs incurred for maintaining inventory (Kumar, 2016).

The classic EOQ model formula can be calculated as follows (Sphicas, 2014; Aprilianti & Ishak, 2023):

(1) $$\begin{array}{r}EOQ=\sqrt{\left(\frac{2DS}{H}\right)}\end{array}$$

where D, S and H denote the annual demand in units, ordering cost per order, and holding cost per unit per year. The total annual cost (TC) associated with the EOQ model can be calculated as follows:

(2) $$\begin{array}{r}TC=OC+HC\end{array}$$

The OC and HC formulas can be further derived into:

(3) $$\begin{array}{r}OC=\left(\frac{D}{Q}\right)S\end{array}$$

(4) $$\begin{array}{r}HC=\left(\frac{Q}{2}\right)H\end{array}$$

where OC, HC, D, Q, S, and H denote the ordering cost, holding cost, annual quantity demand, order quantity, cost per order, and holding cost per unit per year (fixed N% rate of material price).

Frequency of order (F) can be formulated as follows:

(5) $$\begin{array}{r}F=\left(\frac{D}{Q}\right)\end{array}$$

If there are 360 days in a year, then for a certain number of F orders, the formula for the required lead-time per order (T) is:

(6) $$\begin{array}{r}T=\left(\frac{360}{F}\right)=\frac{(360\times Q)}{D}\end{array}$$

Methodology

Fig. 1 outlines the major stages and sequential research steps:

Fig. 1. Research design stages.

1. Research Problem Identification: using the Kepner-Tregoe (KT) method to appraise the current SC situation, by identifying, providing alternative solutions, mitigating risks, and answering the problems in the Research Questions,

2. Hypothesis and Conceptual Model Design: finding the theoretical foundations related to business process assessment, process engineering, modeling, optimal cost calculation, and create a framework for developing a strategic VMI model,

3. Collecting all relevant data, both qualitative data such as documents, forms, report samples, business process flow charts, and quantitative statistical data such as historical purchases,

4. Conducting qualitative data analysis, performing business process and statistical data customization, redrawing SC processes for easier understanding, analyzing the process quantitatively using the EOQ method for optimal cost calculation, 5) generating results and discussion, and recommendations.

This research uses mixed methods the mixed-methods approach, combining qualitative for SC and business process analysis, and quantitative methods for cost analysis. Both qualitative and quantitative methods can be illustrated diagrammatically in Figs. 2 and 3.

Fig. 2. Qualitative method.

Fig. 3. Quantitative method.

Qualitative Data Collection and Analysis

The multiple data includes the KJA Company Profile ( https://www.kideco.co.id/), a sample of the KJA Management Monthly Report, the Supply Chain Management Induction slide, contract document, AN procurement and inventory management business process flowcharts. On-site observations and in-dept discussion were conducted to gain firsthand insights into the operations and understanding of the existing processes and understanding the pre-VMI context.

The KTA diagram (Fig. 4) below depicts the analysis steps undertaken to identify potential risks associated with the current AN supply chain. It outlines potential root causes, preventive measures, and contingency plans.

Fig. 4. KTA diagram.

The author elaborates that the analysis of the problems faced and to be improved in the SC can be detailed as follows:

Complex, lengthy and entire manual process which involve several stake holders.

• Risky: high security and safety standards, and restricted government regulations in managing the explosive material.

• Reliance on suppliers: All procurement and warehousing activities are controlled in-house, but there is a high degree of reliance on suppliers for delivery and stock availability.

• Non-standard business processes: some processes such as warehouse activities handled by mining users should be shifted to supply chain management for control and compliance purposes.

• Cash flow mechanism: the invoicing, verification, and payment mechanism based on the quantity received for each order. The VMI arrangement moves the invoice process to the end for better cash flow, done only once a month, and based on the consolidated usage for one month.

• Pricing: sourcing and negotiation processes are always conducted with several vendors whenever there is a need for ordering. There are no long-term strategic contracts that truly bind the certainty of the base price and price adjustment formula which is highly exposed to a direct impact on the cost.

Quantitative Data Collection and Analysis

The study examined three years of KJA historical procurement statistical data of AN (2022–2024), during a period of significant coal market volatility. Data summary was provided in XLS format. A detailed review was conducted in all fields and simplified (PO number, date, vendor name, item code, item description, quantity, price, unit of purchase, total amount, agreed lead time, and actual lead time). Data is customized and re-summarized in tabular spreadsheets format. Additionally, a manual formula was added to calculate ordering costs, carrying costs, and total cost.

From data collection, field discussions, and observing the data conditions above, it is evident that there are some weaknesses found in terms of:

• Lack of data integrity: manual transaction recording when processing the requisition, purchase, receipt, issuance, invoice, results in the absence of a single uniform data platform that can provide reliable data.

• Excess stock and high inventory value: There was a larger buffer stock to provide assurance of availability and fulfillment of User needs instead of using modern inventory method to get optimum level.

• Inventory holding cost: the magnitude of material price changes gives a direct impact on all other related costs, especially holding costs. There was a problem of balancing stock against optimal carrying costs which created a significant risk of stock shortages and production stoppages.

Finding and Discussion

Business Process Review

High safety standard requirements, restricted government permits and regulations, the involvement of multiple large-scale stakeholders, lengthy and non-integrated business processes, high value and criticality to production, all of them illustrate the magnitude of the Ammonium Nitrate (AN) procurement and inventory processes, thus necessitating a more strategic, effective, and efficient AN Supply Chain (SC).

Author identifies 12 steps of end-to-end SC processes that must be followed, starting from:

• AN requirement planning by the contractor, as end-customer,

• consolidation of material requisition by the drill and blast provider, as customer,

• purchase requisition by Mining,

• sourcing and purchase order by Procurement,

• delivery by supplier,

• goods receipt at the transit warehouse by Procurement,

• transportation to the distribution warehouse by supplier,

• goods receipt at the distribution warehouse by Mining,

• goods issue from warehouse by Mining,

• invoice submission by supplier,

• invoice verification by Procurement, and

• payment by Finance, not including the multi-level manual approval processes at particular stages. The length of those SC stages, involving numerous bureaucratic documents and approvals, makes this process time-consuming, complex, and in need of simplification to become more effective and leaner.

It is apparent that certain functions are not performed by the appropriate roles. The author observes this as an issue stemming from non-standard business processes and a lack of control functions. For example, warehouse activities such as goods receipt, request consolidation, stock purchase requests, and issuing at the distribution warehouse are being performed by Mining (the user’s representative), which should be assigned to Warehouse personnel. Procurement is performing warehouse work (goods receipt at the transit warehouse) and finance work (invoice verification). The process needs to be improved by clearly defining distinct roles: Mining, representing the user, should not be given access to manage inventory; standardize the Warehouse role for managing goods issuance, receipt, and stocking; assign the Buyer responsibility for purchasing; and have Finance handle both invoice verification and accounts payable.

The use of manual forms and communication media among stakeholders above (Company, customer, and vendor), and between personnel in different departments (mining, warehouse, procurement, and finance) further complicates the SC process, as transactions are not interconnected, not recorded in real-time, and lack reliable data integrity for reporting and analysis across all departments. Improvements in application systems and business models are needed to connect complex business activities (Juriket al., 2025). Business Process Engineering involves redesigning core activities for improvement and efficiency, implementing changes to existing processes, and proposing ideas to expedite work, thereby eliminating issues related to bureaucratic control, rigid processes, and traditional methods (Guoet al., 2020). This research highlights the need to transition the inventory management model from its current traditional approach to a strategic VMI-based system.

Author also observes that the direct involvement of several large-scale stakeholders with different roles, namely 1 the Coal Owner, 4 AN supplier, 2 Drill and Blasting (DB) service provider as the user, and 5 Mining Contractor (MC) as the end-user of AN that increases the complexity of the entire SC process. Workflow and communication among stakeholders are traditional, using manual forms, and are not integrated or have no interface. There is no requisition, warehousing, or purchasing application system to support electronic processes. Recording and reporting are done independently by each stakeholder, a single reliable data source does not exist. In terms of supply and demand, the Company must consider the varied supplier’s ability to deliver and the differing demand of each mining contractor. In practice, estimated usage requirements have a high potential to change and deviate from the initial plan due to adjustments in monthly coal production targets based on weather conditions, sales targets, and coal inventory stock level at pit and port. Similarly, the estimated delivery lead time also changes to accommodate supplier ship availability and schedules. Observed data reveals a significant discrepancy between promised and actual shipment lead times.

The engineering business process from the conditions before and after the assessment, as well as an overview of the SC process with the future VMI design, can be seen in Figs. 5 and 6.

Fig. 5. Current existing business process (before VMI).

Fig. 6. Re-engineered business process (after VMI).

VMI Design

Considering the issues in the Supply Chain (SC) and the results of the business process assessment above, and to answer the questions in the Research Question, namely the ideal VMI design for the conditions in coal mining, then how VMI can transform and improve a company’s business processes for greater effectiveness and efficiency, and how VMI can optimize costs and compare conditions before and after VMI implementation, the main VMI aspects, strategy and arrangement summary can be designed as follows:

1. Key Stake Holders and Roles Identification: The VMI design must review and identify all key stakeholders in the SC process and explain the functions of each role. In the AN supply chain case study in coal mining operations, the key roles can be divided into 4, namely: Company (coal mining owner, who assigns tasks and coal production target to the customer and end-customer), Drill and Blast Provider (customer, who requests AN and performs blasting), Mining Contractor (end-customer, who conducts production plan, over burden and coal getting, and AN demand planning), and supplier (material supply and transportation). The complete SC processes, along with their improved mechanisms, should be visualized, from coal production planning to AN requirement, requisitions, procurement, shipments, receiving, issuing, invoicing, and payment.

2. Responsibilities Segregation: In the proposed VMI design, there is a separation and extension of responsibilities given to the vendor. In addition to supplying goods, the vendor also handles operational purchasing administration and inventory management, which was previously done entirely by the Company. The company has more accountability in consolidation, controlling suppliers’ performance and analysis.

3. Long-Term Contract Agreement: Several aspects that must be considered in agreement VMI are:

• Contract Period: Quantity and price fluctuations occur annually, and even in almost every transaction. On one hand, the Company needs supply assurance with low prices. On the other hand, vendors need sales assurance with competitive prices, coupled with the requirement to place additional personnel at the customer’s work site. There are initial investment costs such as physical storage, work equipment, and operational vehicles. Vendors tend to need a guarantee of sales commitment to be able to provide better service, and to reduce operational costs that ultimately shift a lot to them. With a long contract, prices can be relatively maintained and even reduced despite the increased workload posing more risk. Based on the author’s experience in managing similar large-scale contracts and discussion with process owner, contract administration requires a rather lengthy process, it could take 2–3 months from sourcing to contract finalization. Therefore, considering administrative aspects and the vendor’s assurance, it is recommended that the ideal contract duration be 2 years or more, and must be reviewed regularly, quarterly and annually.

• Vendor Selection: This assessment should encompass safety compliance, comprehensive permits and legal documentation for mine site and explosives warehouse operations, consistent product quality, competitive pricing, efficient delivery timelines, sustained support capabilities, and the vendor’s capacity to provide dedicated personnel, equipment, and manage daily operational purchasing and warehousing at the mining site. Keep maintaining standard contractual relationships with non-VMI vendors serves as a strategic contingency to mitigate potential disruptions during VMI operations.

• Pricing: Significant price variations among vendors annually necessitate careful management of potential fluctuations with each order. Current sourcing practices, as observed in the process flow and discussions with the Buyer, involve extensive negotiations to determine final order prices. To mitigate market volatility, establishing a mutually agreed-upon base price during the initial contract phase, coupled with a transparent price adjustment formula (rise and fall scheme), is crucial. The base price can be derived from the 12-month average and prevailing market conditions, while monthly adjustments should reflect the current market price. The final price, comprising the base price plus the adjustment, will be applied to each monthly invoice.

• Warehouse Location and Ownership: the warehouse location must be far from residential areas, within the mining site, and requires a management permit from the police and government, which must be renewed every year. Explosives storage license is only granted to the concession landowners (coal owners). It requires a large investment for the vendor to build similar warehouses and collaborate for permission to operate. As a compromise, the company can lend warehouse facilities to the vendor, but this will still be under the supervision from the Company assigned to ensure regulatory compliance. Just to provide an overview of the warehouse space requirements, from data observed, with an average monthly demand of 2,000–3,000 tons (equivalent to 80,000–120,000 × 25 kg bags) the company requires approximately 1000–1500 m² of storage area for single warehouse, including security post, open yard for trucking, unloading, and muster point.

4. Business Process Improvement and Effectiveness: The long supply chain and non-standard company business processes, multi-level approvals at several stages, manual and non-integrated communication, are targets that must be improved with the implementation of VMI. Improvements in business processes that occur include:

• Role Enhancement: Warehousing activities (goods receipt, goods issue, stocking) and procurement activities (purchase order, manage delivery) which are carried out by Mining and Procurement, will be replaced by the vendor in line with the delegation of operational responsibilities. Material requisitions will be consolidated by the Company’s warehouse (no longer to Mining) before being forwarded to the vendor’s warehouse for withdrawal.

• Invoice and Payment Mechanism: With proposed VMI, invoices are submitted based on the consolidated usage of AN (goods issue) within one month’s basis, not upon receipt of the order (goods receipt) as a normal purchase order. Verification is carried out by finance using the rise and fall price formula at the time of the issuing period, by comparing the recorded issue transactions with the consolidated results of the Warehouse supervisor (Company) and the vendor’s finance. Specifically for AN transaction, the Purchase Order (PO) released to the supplier initially by the company is non-commercial, has no value, and only serves as stock replenishment.

5. Cost Reduction: The application of a strategic inventory model like VMI should provide a cost reduction effect from incurred costs. From the observed data, ordering costs are relatively small, but holding costs are significant. This is because all received purchase values are stored as holding costs until they are issued. Improved processes and efficiency through VMI provide a direct and significant cost reduction effect for the Company. With purchasing and management processes handled by the vendor, the resulting ordering and holding costs may be reduced to zero from the Company’s perspective.

Cost Analysis

Regarding the quantitative historical procurement data statistics, the author analyzes and summarizes the source data into the summary table below:

Table I presents a summary of AN procurement data from 2022–2024, revealing fluctuating purchase volumes correlated with declining national and global coal demand. There are many variations in the delivery lead-time difference from what was promised versus actual, and this certainly disrupts the supply chain and poses risks.

Table I. Purchase Order Summary 2022–2024

Year supplier	Qty (D)	Avg price (P)	Amount (V)	Frequency of order (F)	Average qty/Order (Q = D/F)	Plan/Act avg lead-time
2022	26,226	1,291	33,092,424	20	1311	12/15
ARMINDO	500	1,643	826,700	2	250	14/16
ASA	1300	1,886	2,451,800	1	1300	15/13
DAN	7350	1,055	7,812,450	5	1470	14/26
MNK	9000	1,287	11,264,400	8	1125	7/12
TRIFITTA	8076	1,270	10,737,074	4	2019	14/8
2023	24,500	1,074	26,420,500	12	2041	11/21
DAN	11,500	1,021	11,639,500	7	1642	14/27
MNK	8500	1,016	8,422,500	3	2833	7/12
TRIFITTA	4500	1,344	6,358,500	2	2250	14/10
2024	24,104	941	22,488,806	22	1095	11/15
DAN	8500	933	7,956,000	5	1700	14/26
MNK	13,946	933	12,928,299	9	1149	7/9
TRIFITTA	1658	969	1,604,507	2	361	14/14
Grand total	74,830	1,100	82,001,730	54	1385	11/17

Conventional Cost Determination

Ordering Cost (OC), Holding Coat (HC), and Total Cost (TC) for conventional calculations, are obtained, as shown in the following simplified formula:

$$\begin{array}{r}OC=F\times S\end{array}$$

$$\begin{array}{r}HC=Q\times H\end{array}$$

$$\begin{array}{r}TC=OC+HC\end{array}$$

where F, S, Q and H denote the frequency of order, cost per order, quantity demand, and annual holding cost per unit (consists of holding costs that are constant and in variable form per unit).

Assuming each order quantity is held as an inventory and depleted only upon the subsequent order, the calculated indicative Ordering Costs (OC) consists of employee salary $200, administrative overhead $20, communication expenses $15, utilities $10, and miscellaneous expenses $5, totaling $250 per order, and that this cost is considered constant for each order released, the total Ordering Cost (OC) is calculated as follows:

$$\begin{array}{r}OC=F\times 250\end{array}$$

Assuming the annual indicative Holding Cost comprises employee salaries of $0.41/unit, warehouse leasing expenses of $0, depreciation of $0, annual utilities of $0.01/unit, material insurance of $80/unit, and miscellaneous expenses of $60/unit, totaling $140.41/unit, and that this cost is considered constant per unit annually, the total annual Holding Cost (HC) per unit is calculated as follows:

$$\begin{array}{r}HC=Q\times 140.41\end{array}$$

where $140.41 is assumed as a constant value for a year, no increment and dependent on variable units.

From the OC and HC formulas above, a cost summary is created in Table II.

Table II. Cost Summary by Conventional Method

Year supplier	Qty (D)	Amount (A)	Frequency of order (F)	Lead time (T)	OC	HC	TC	% HC (HC/A)
2022	26,226	33,092,424	20	15	5000	3,682,393	3,687,393	11.1%
2023	24,500	26,420,500	12	21	3000	3,440,045	3,443,045	13.0%
2024	24,104	22,488,806	22	15	5500	3,384,443	3,389,943	15.0%
Average	24,943	27,333,910	54	17	4500	3,502,293	3,506,793	12.8%

While direct holding costs were low, significant inventory holding expenses and high % holding rate arose from excessive stock levels, inefficient inventory management, and infrequent procurement.

EOQ Cost Analysis

Storing high-value materials like AN in-coal mining operation incurs high costs for the warehouse. Although the Economic Order Quantity (EOQ) calculation method is often unrealistic to meet the assumptions and constant conditions, the author used EOQ method as a basis for mathematical cost calculation of optimum inventory and to compare how much the Company can save the AN cost and what other strategic steps should be taken afterward.

The classic EOQ model can be calculated as follows (Sphicas, 2014; Aprilianti & Ishak, 2023):

$$\begin{array}{r}EOQ=\sqrt{\left(\frac{2DS}{H}\right)}\end{array}$$

$$\begin{array}{r}OC=\left(\frac{D}{Q}\right)SHC=\left(\frac{Q}{2}\right)H\end{array}$$

$$\begin{array}{r}OC=\left(\frac{D}{Q}\right)S\end{array}$$

$$\begin{array}{r}TC=HC+OC\end{array}$$

$$\begin{array}{r}F=\left(\frac{D}{Q}\right)\end{array}$$

$$\begin{array}{r}T=\left(\frac{360}{F}\right)=\frac{(360\times Q)}{D}\end{array}$$

where D, S, H, OC, HC, Q, F, and T denote the annual demand in units, cost per order, holding cost per unit per year, total ordering cost, total holding cost, annual quantity demand, frequence of order and time need to order.

Assuming the same constant H ($140.41) and S values ($250) as the previous Conventional calculation, then for each year analyzed, the EOQ, OC, HC, TC results, and other relevant variables (F, and T) can be summarized in Table III.

Table III. Cost Summary by EOQ Method

Year supplier	Annual demand (D)	Cost per order (S)	Holding cost per unit (H)	EOQ	OC	HC	TC	F	T
2022	26,226	250	140.41	306	21,453	21,453	42,908	86	4.19
2023	24,500	250	140.41	295	20,737	20,737	41,473	83	4.34
2024	19,566	250	140.41	293	20,568	20,568	41,136	83	4.38
Average	23,430	250	140.41	298	20,919	20,919	41,839	84	4.30

It is seen that the economic order quantity is very small, the optimum ordering and holding costs are equal, resulting in an optimum total cost. Other variables, the number of orders is high, meaning there is a high ordering frequency, averaging 84 times and within a very short time range, averaging 4.30, round up to five days.

Cost and Other Variables Comparison

The comparison of costs and other parameters between the conventional and EOQ methods can be seen in Table IV below:

Table IV. Cost and Other Variables Comparison

Year supplier	Conventional						EOQ						% Difference
	Q	OC	HC	TC	F	T	Q	OC	HC	TC	F	T	Q	TC	F
2022	1311	5K	3682K	3687K	20	15	306	21.5K	21.5K	42K	86	5	−77	−99	77
2023	2041	3K	3440K	3443K	12	21	295	20.7K	20.7K	41K	83	5	−86	−99	86
2024	1222	5.5K	3384K	3,389K	22	15	293	20.5K	20.5K	41K	83	5	−73	−99	73
Average	1385	4.5K	3502K	3,506K	18	17	298	20.9K	20.9K	42K	84	5	−78	−99	79

Table IV presents a significant result alteration from conventional and EOQ methods in terms of order quantity, costs, order frequency, and purchasing lead-time. The author highlights a decrease in the average order quantity (Q) of −78%, and a decrease in Total Cost (TC) of −99%. This decrease is due to the achievement of optimum order quantity and minimum total cost, which requires routine ordering, with a frequency increase of +79%, and expected delivery +71% faster. Thus, the significant decrease in order quantity is balanced and caused by an increase in order frequency and a significant improvement in delivery time. Looking at the cost comparison table above, the application of the EOQ method would provide the optimum cost and optimum order quantity for the Company. However, as previously discussed, there are potential risks with unpredictable shipment, fluctuated price and demand, and dependency on sole suppliers which impact uncontrolled conditions. These changes can invalidate the initial assumptions of fundamental EOQ model. There is a vessel capacity factor used by the vendor to load optimally at 1500 tons, it is clearly impossible and inefficient to force the vendor to only ship an average of 298 tons per shipment, or 80% lower. Another fact that occurs in the field is that the actual delivery time currently averages 17 days, far from the optimum condition assumed by EOQ at five days. Another impact, with an order frequency increase from 18 to 84 times per year, it will require additional Buyers to process.

VMI addresses this by shifting the traditional SC processes and reducing these potential risks and high costs to suppliers. No longer focusing on optimizing the EOQ method in a business practice that is clearly unrealistic to implement. Instead, creating a strategic inventory management model, mitigating risks beyond the Company’s control, while transforming ineffective and non-standard internal business processes. With the VMI model, the vendor is given more responsibility in carrying out daily operational procurement and inventory, but still with the control function carried out by the Company. From the Company’s perspective, the ordering and inventory holding cost issues arising from the procurement and inventory processes will be entirely absorbed by the vendor. No longer worrying about managing long sourcing, price discussions, delivery times, and so on. Of course, there is compensation requested by the vendor. Expected price increment, expected long-term contract duration, facility and equipment loans, key personnel or security support, and so on. VMI eliminates several manual forms and non-integrated communications related to daily operations that are now transferred to the vendor. However, it is still necessary to build an electronic communication bridge throughout Company and vendor for data and report integrity. All of these have been explained in the VMI Design section.

Conclusion and Recommendation

Ultimately, VMI transforms the Company’s SC processes to strategic, effective and efficient SC. Cost calculations using the EOQ method show a total cost reduction of up to 99% compared to the conventional method, a 78% reduction in order quantity, and a 12-day improvement in delivery time. However, this EOQ method has limitations and is not realistic to fully implement. Shifting the daily operational of procurement and inventory from the Company to the vendor provides a solution to mitigate procurement risks and significant inventory holding costs. Conceptually, from the Company’s perspective, all activities and costs are absorbed by the vendor.

The author primarily focuses on the Company’s perspective, without extensively discussing the vendor’s point of view, how vendors perceive the division of responsibilities as both suppliers and those responsible for daily operations. How vendors see in detail the opportunities or benefits obtained, how it impacts their costs and SC processes with the delegation of responsibility for running customer’s daily operational procurement and inventory.

The author also mentions that there is non-integrated process, still manual communication, independent record and reporting, but does not discuss and not cover much about the needs and in-depth solutions. Future research is also expected to propose designs on how to create a uniform platform or with different application interfaces that integrate end-to-end SC processes and communication between stakeholders electronically. Finally, it needs a more comprehensive review of company business, capture and appraise the supply chain and internal business process issue, perceived pain points, and the future Company’s needs to what extent, before determining the most suitable inventory model to implement.

Conflict of Interest

Conflict of Interest: The authors declare that they do not have any conflict of interest.