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Healthcare Logistics Cost Optimization Using a Multi-criteria Inventory Classification
Abstract
In this paper, a system dynamics model of a hospital logistics system is developed to evaluate different inventory management techniques. The paper introduces a multi-criteria inventory classification method that takes into account the criticality, cost, and usage value of items. Based on the model, extensive simulations were conducted to evaluate the cost of inventory management for items based on the criticality of need, service level assignments and consumption rates. The analysis presented provides useful guidelines for the health practitioners and decision makers how inventory management cost could be optimized using a classification system depending on the criticality of the items.
... This model was used to analyze the inventory management strategies used before and after the introduction of VMI for a two-level supply network with a single supplier and buyer. Several numerical examples were utilized to illustrate the use of the suggested strategy, using various buyer (21,30,45) [25] have expanded the EOQ model. In this article, there is only one retailer and one supplier, and no products are involved. ...
In this paper, we categorise and critically evaluate the current modelling and analysis approaches and procedures created by researchers and scientists in inventory management systems across different sectors such as healthcare, supply chain, and routing problems. Furthermore, we discuss recent trends and advancements in inventory management systems that deal with shortage. Based on our literature review, we propose a comprehensive research structure that is appropriate in the current environment and helpful in future study directions.
... The service's quality depends on this collection of things, which are designated with the letter "E." "D" denotes desired products that, even if unavailable, do not interfere with a hospital's ability to function. Al-Qatawneh and Hafeez then expand on the item classification by taking into consideration usage frequency in addition to cost and criticality [6, 16,17]. ...
Store management includes managing warehouses, inventory data, holding and storing medications, and safeguarding and protecting products. In the supply chain, a store is where we keep stock. Keeping goods on hand ensures that upcoming client demand will be met. As a result, every company keeps a certain amount of inventory on hand to meet client demand. Inventory requires many points of stocking and typically has more items than other hospital inventories. The trade-off between inventory costs and the degree of necessary service that each surgeon expects to get makes inventory management in an OR (operating room) more challenging than it would be in a manufacturing environment. The store's management should facilitate the most efficient and dependable supply chain possible without significantly compromising quality, wasting resources, or committing theft. It has been noted that the volume of data is growing exponentially over time. Scientifically, vast databases are also becoming increasingly relevant to shared resources. These sorts of enormous and vast databases are often kept in cloud-based data centers. Since the majority of scientific data is in huge volumes and organizations and industries may not always have access to the storage space, processing resources, computing capacity, or upkeep of such data. As a result, the majority of businesses employ cloud services.
... In SD models, decision environments are represented through the dynamic behavior of the system based on what is known about the state of the system using its variables and inventory levels [22]. These models have been used to identify, evaluate, and assist in making economic decisions for a variety of systems, such as for enhanced oil recovery operations [109] for industrial production and distribution systems [110], and for inventory logistics within healthcare systems [111]. The aggregate decision-making representations of these models can result in chaos due to the human decision-making behaviors of a significant minority within the model [85]. ...
Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.
... Several studies related with the inventory management in pharmaceutical industries and health facilities (hospitals and clinics) conducted by Al-Qatawneh (2011) that uses a multi-criteria inventory classification in hospitals that aims to optimize costs in inventory control. Çalışkan, C. (2020) developed an Economic Order Quantity (EOQ) formula for deteriorating items (food and medicine) which provides an optimal solution for inventory levels. ...
This research aims to observe current inventory management applied by one of the medical equipment distributors specializing in eye health devices, and provide recommendations for an optimal inventory management system to achieve cost efficiency afterward. The method used in this research is quantitative, focusing on processing and analyzing numerical data obtained from the company to calculate safety stock and the number of orders. In addition, ABC classification is also used in data processing to group items based on their value. Items belonging to class A (having a value of 80% for the company) will be used in the data processing. The next step is to conduct forecasting simulations for demand forecasts. The results of the forecast will be used for calculating the safety stock and order quantity. The output from the results of data processing and analysis in this study shows 67 items included in class A, which will then be processed using Minitab software for forecasting. Based on comparing the four forecasting methods, the one with the lowest error value is Trend Analysis. If the company can apply the storage method according to the fixed-time period model calculation, there is a potential savings of US $ 717,133 or 63% of the total overstock
... 9,10 Hospital management has always been concerned with optimizing logistics costs in a healthcare supply chain. 11,12 But pharmacy inventory management is a complex process and the usual problems encountered when inventory is not tracked properly and inefficiency is excessive losses, improper technology use, and lack of logistical infrastructure to store drugs, improper monitoring of drug expiration times, distribution problems, and irrational usage of drugs. 13 This accelerates the probability of stock out and overstocking of essential drugs resulted in wastage or blockade of financial resources, increase in out-of-pocket expenditure, and ultimately decline in the quality of healthcare services. ...
Introduction:
Inventory management is a complex process that accelerates the probability of stock-out and overstocking if not tracked properly. Classification of drugs based on their criticality, cost burden, and in combination is important to make inventory decisions and optimize the quality use of scarce resources. This study analyzed the pharmaceutical inventory management systems of Dessie Referral Hospital using the ABC-VEN matrix for the years 2013 to 2017.
Methodology:
Cross-sectional study design was used to review logistic data retrospectively from health commodity management information system and manual records. Data were collected from January 1-20, 2018 in Dessie Referral Hospital.
Results:
In the five-year ABC-VEN analysis, 310 (17%), 368 (20.18%), and 1146 (62.83%) items were class A, B, and C, while 610 (34.56%), 1125 (63.74%), and 30 (1.7%) of pharmaceuticals were V, E, and N, respectively. Among these, 139 (7.88%) and 339 (19.21%) of AV and CV pharmaceuticals utilized 43.52% and 2.89% of annual drug expenditures, respectively. Category I, II, and III pharmaceuticals also accounted for 43.68%, 54.79%, and 1.53% of items with their respective USD drug expenditure of 2,268,405.64 (84.49%), 411,961.18 (15.34%), and 4483.97 (0.17%). The pharmaceutical inventory cost projected to be 1,619,351.79 USD in 2025 and total cost (β= 10.68, p = 0.001), class A (β= 8.68, p = 0.001), class B (β= 1.27, p = 0.007), class C (β= 0.72, p = 0.03), and E items (β= 6.08, p = 0.01) were statistically significant with inventory cost.
Conclusion:
A huge amount of budget is invested in class A and category I, which pinpoints the need for strict inventory control to prevent wastage and accumulation of capital in buffer stocks. ABC-VEN analysis should be routinely performed before initiation of any new procurement for efficient use of scarce resources.
... available. The item classification is then extended by Al-Qatawneh and Hafeez (2011) such that in addition to the cost and criticality, usage frequency is taken into account. Given the most important items, extracted using the above-discussed methods, inventory models need to be established to decide on the inventory control para- meters for these items. ...
Operating rooms are considered a significant revenue source, as well as the main source of waste and cost, among the hospital’s departments. Any cost savings in operating rooms will have a broad financial impact. Over the last decades, many researchers and practitioners have conducted studies to deal with the issue of managing surgical supplies and instruments, which are highly affected by surgeons’ preferences. The purpose of this article is to present an up-to-date review of research in the field of inventory management of surgical supplies and instruments. We have analysed the literature in a systematic manner and organised the identified papers into two groups: the papers that were published by scientific researchers and developed optimisation techniques and the papers that were published by practitioners and reported their observations of the current issues in the operating room. We also identify the future research directions leading to operating room inventory cost reduction.
... Expenditure for forthcoming years was fore-casted by regression analysis using NCSS software. A system dynamics model [30] of a hospital logistics system is introduced to evaluate different inventory management techniques and developed a multi-criteria inventory classification method that takes into account the criticality, cost, and usage value of the items. They evaluated the cost of inventory management for items based on the criticality of need, service level assignments and consumption rates and the guidelines for the health practitioners and decision makers how inventory management cost could be optimized using a classification system depending on the criticality of the items. ...
In this article we propose pharmaceutical inventory model for perishable products with pre and post discounted selling price and time dependent cubic demand. Mostly the pharmaceutical company considered the constant rate of deterioration. In the majority of the earlier studies, the demand and holding cost has been considered to be constant function, which is not true in most of the practical situations as the manufacturing medicine/setting machine cost and patient record keeping costs or even cost of keeping the pharmaceutical items in the cold storage increases with time. In view of this, we develop a pharmaceutical inventory model in which the time dependent demand is cubic and holding cost is linear function of time. Also we introduce both pre and post-deterioration discounts on unit selling price which determine discount to be given on unit selling price during deterioration so as to maximize the total profit. Finally, numerical examples and sensitivity analysis are given for illustration of the model. © 2018, Research Journal of Pharmacy and Technology. All rights reserved.
... The drugs are classified into four classes, ranging from very important drugs to not important drugs, which then determine the inventory strategy for each drug in order to optimize hospital pharmacy inventory. Al-Qatawneh and Hafeez [2] develop a multi-criteria classification system depending on the criticality, cost and usage value of items to assign different service level percentages to items and hence to optimize the overall inventory cost and to ensure the availability of items that are critical for patient care. For instance, high-cost orthopedic materials are characterized by high demand uncertainty and high service requirements, which will drive a large amount of safety stock for that item [30] . ...
The patient care processes in hospitals are supported by a range of operational activities including inventory management and distribution of supplies to point-of-care locations. Hospitals carry large amounts and a great variety of items, and the issues of storing and distributing these items throughout the hospital supply chain are of great importance to providing high-quality patient service. Healthcare logistics encompasses the process of handling physical goods (e.g. pharmaceuticals, surgical medical products, medical equipment, sterile items, linen, food, etc.) and the associated information flows, from the reception of the goods within a hospital to their delivery at patient care locations. The medical supply costs constitute the second largest expenditure in hospitals, after personnel costs. A high-performing supply chain may realize improved outcomes (e.g. safe and quality patient service) and greater efficiency. Logistics managers need to identify opportunities to improve the logistics processes in order to lower costs and to improve patient care quality. However, in order to improve the logistics processes, you must understand how the healthcare supply chain is currently performing. Measuring the performance of the supply chain is fundamental to identify and address deficiencies in the logistics activities, and it serves as a good input for managerial decision-making. The purpose of this article is to present existing research on performance measurement at the internal hospital supply chain (e.g. inventory management, distribution activities), and more specifically in the operating theatre since it is among the most critical resources for a hospital. At the operating theatre, the requested items should be available at the right time at the right place, in the right condition, at the lowest cost possible. Furthermore, we will also discuss literature on multi-criteria decision-making techniques. It enables researchers to build a performance measurement framework and to prioritize between multiple performance indicators since a diverse group of stakeholders with conflicting interests is involved in the internal operating room supply chain.
https://www.sciencedirect.com/science/article/pii/S0305048317302438
... Expenditure for forthcoming years was fore-casted by regression analysis using NCSS software. A system dynamics model [30] of a hospital logistics system is introduced to evaluate different inventory management techniques and developed a multi-criteria inventory classification method that takes into account the criticality, cost, and usage value of the items. They evaluated the cost of inventory management for items based on the criticality of need, service level assignments and consumption rates and the guidelines for the health practitioners and decision makers how inventory management cost could be optimized using a classification system depending on the criticality of the items. ...
The inventory management system plays a vital role in a pharmaceutical industry. For every business, managing an inventory is important whether it is small or big, domestic or international business. In a pharmaceutical company, the raw materials have an expiry date associated with them so it becomes important to set a minimal safety stock for such items. The companies mostly try out keeping a minimum stock of products which will help in tracking our business easily. In this article, we present an overall review of the Pharmaceutical Inventory literature since the early 1968 and the models available in the relevant literature have been suitably classified. The motivations and extensions of various models in each subclass have been discussed in detail.
... Overall supply chain cost is affected by the introduction of new drugs in the market (Prosser and Walley, 2006) which turn into variation in prescription among the physicians. The healthcare inventory management cost can be optimised on the basis of various criteria such as criticality and usage value of items (Qatawneh and Hafeez, 2011). Few cases of hybrid stockless inventory management are studied (Royer et al., 2002). ...
The inventory management process is an essential concern for a hospital because it affects the clinical, managerial and financial outcomes and comprises of large part of overall supply chain cost. It is responsible to supervise and control on the inventory at central stock and various individual care units (ICUs). This paper presents an interpretative structural model (ISM) for the hospital inventory management with sixteen key factors. Expert's opinions on all factors have been translated into the structural model to establish some interrelationships among the factors. Matriced Impacts Croises Multiplication Applique and Classment (MICMAC) analysis has been done to categories the factors on the basis of their driver and dependence powers. The study may offer directions to the hospital administration to take key decisions to improve overall inventory management performance and reduction of cost.
... Several authors followed Danas with a multi-attribute classification of drugs. Al-Qatawneh and Hafez [20] tested classification of medications based on criticality, usage and cost using a system dynamics model and applying continuous replenishment for inventory management. Their model showed a positive influence on costs with controlled service levels. ...
As supply chain costs constitute a large portion of hospitals' operating expenses and with $27.7 billion spent by the US hospitals on drugs alone in 2009, improving medication inventory management provides a great opportunity to decrease the cost of healthcare. This study investigates different management approaches for a system consisting of one central storage location, the main pharmacy, and multiple dispensing machines located in each department. Each medication has a specific unit cost, availability from suppliers, criticality level, and expiration date. Event-driven simulation is used to evaluate the performance of several inventory policies based on the total cost and patient safety (service level) under various arrangements of the system defined by the number of drugs and departments, and drugs' criticality, availability, and expiration levels. Our results show that policies that incorporate drug characteristics in ordering decisions can address the tradeoff between patient safety and cost. Indeed, this study shows that such policies can result in higher patient safety and lower overall cost when compared to traditional approaches. Additional insights from this study allow for better understanding of the medication inventory system's dynamics and suggest several directions for future research in this topic. Findings of this study can be applied to help hospital pharmacies with managing their inventory.
Developing nations often face unique challenges in preparing and responding to health emergencies, and the efficiency of their medical supply chains plays a pivotal role in mitigating the impact of crises. Emergency Medical Supply Chain Optimization Readiness in Developing Countries necessitates a nuanced understanding of the differences between routine and emergency protocols, with a focus on their distinct implementation strategies. Emergency protocols in the medical supply chain of developing countries should first and foremost emphasize a risk-based approach to resource allocation. This involves conducting thorough risk assessments to identify potential scenarios and allocating resources based on the severity and likelihood of different emergencies. Training simulations play a crucial role in preparing for emergency medical supply chain optimization in developing countries to identify gaps and enhance their readiness. In conclusion, an integrated approach encompassing adaptive supply chain models, resource allocation strategies, capacity scaling, and ongoing training and simulation efforts is essential for achieving optimal emergency medical supply chain readiness in developing countries.
Logistics in health and wellbeing is crucial in managing all the materials, services, and data that make healthcare easier to deliver. This complex field needs careful management and co-ordination of the aspects such as transportation, storage, and distribution so as to improve the flow of medical goods and services within health structures. The importance of logistics in relation to healthcare can be attributed to a variety of factors such as enhancing the quality of patient care, availability of vital drugs, and overall progression of the quality of care rendered. Through sound supply chain approaches, hospitals and other healthcare centers can overcome supply chain disruptions, optimize procedural processes, and tackle logistical issues to strengthen the readiness and effectiveness of healthcare services delivery. This chapter seeks to discuss logistics in the context of the healthcare industry while focusing on the components, methods, and major significance of flexibility particularly in situations where systemic disruptions like the COVID-19 contagion occur.
The inventory management system plays a vital role in a pharmaceutical industry. For every business, managing an inventory is important whether it is small or big, domestic or international business. In a pharmaceutical company, the raw materials have an expiry date associated with them so it becomes important to set a minimal safety stock for such items. The companies mostly try out keeping a minimum stock of products which will help in tracking our business easily. In this article, we present an overall review of the Pharmaceutical Inventory literature since the early 1968 and the models available in the relevant literature have been suitably classified. The motivations and extensions of various models in each subclass have been discussed in detail. Keywords: Inventory, Perishable items, Pharmaceutical inventory, RFID technology, Drug inventory
The main purpose of the study is to explore the influence of product variety on inventory at hospitals. The part of the study involves in understanding the behavior of product substitution for the different types of products such as sterile and non–sterile product. The potential product reduction and the corresponding impact on cost are studied. An additional study of the impact on product variety when the cost per order varies is done. The study includes the impact of product reduction in the Hospital’s Central Storeroom on the subsequent level, the Nursing Units.
The current replenishment system for products is a homegrown ad-hoc system used in both the Hospital's Central Storeroom and the Nursing Units. A new model is developed for the Hospital’s Central Storeroom for exploring all the possible combinations of products that can be substituted by similar products within a product group. At the Nursing Units, a new two-bin replenishment system is suggested. The impact of the product variety decision at the Hospital’s Central Storeroom on the Nursing Units is studied.
Results were calculated for two cases, a simple baseline case when substitution is based on the functionality of the product only, and one case where the substitution is based on both functionality and the cost of each product. Overall, the results show 13.6 % reduction in total number for the baseline case. When including cost considerations, the effect is reduced to approximately 11% in average reduction of product variety, and an average reduction in cost of NOK 3.6 Million among all the scenarios.
When the cost per order variable changes there is an effect on the product reduction. For the Hospital’s Central Storeroom, a cost reduction of NOK 3.6 million approximately is achieved. Among the Nursing Units, the results vary a lot depending on what products that can be substituted with each unit and product group. 54% of these units reduce their costs, and 46 % have a higher cost. In total it will be a slight increase, 1.25% (NOK 45,000) of cost savings made at Hospital's Central Storeroom. In conclusion, the total effect for both the Hospital’s Central Storeroom and all the Nursing Units is NOK 3.56 million.
In conclusion, product variety on inventory at the hospital has a significant effect on the inventory level, making it an excellent study area of study for future research considering other issues like medical personnel preference, coordinated replenishment within and across hospitals, automated replenishment, floor space, and so on.
Inventory management in a healthcare system needs to be compatible with its operations and critical characteristics ensuring minimization of inventory-related cost as well as maximization of service level with a significant reduction in the price of treatment and wastage of resources. Over the years, numerous approaches and methodologies have been developed by the researchers and practitioners for modelling and analysis of varieties of inventory management systems in the healthcare sector considering these aspects. In this paper, the existing modelling approaches and solution methods concerning inventory systems in healthcare are classified and critically reviewed. An integrated research framework as applicable in the present context is presented as a direct consequence of the review of the literature with future research directions.
This article aims to formulate and solve a routing problem for the collection of surplus leftover medicines and supplies in the minimum possible time. To solve the problem, two metaheuristics called simulated annealing (RS) and particle swarm optimization (PSO) are applied. Additionally, factors such as collection list size (TLR), size of collection car fleet (TFCR), as well as hospital room quantities are modeled. From the experimental validation it was detected that the levels of the PSO metaheuristic with the TLR level of 250 products, generates shorter collection times with values of 58.30 and 57.30 minutes / set of routes. Meanwhile, a combination of the TLR levels of 400 products, with the RS metaheuristic, produces the lowest average routing time with values of 99.33 and 101.24 minutes / set of routes. These results showed the effectiveness of metaheuristics to solve the problem of routing in hospital logistics.
In a healthcare system, predominantly in hospital systems, varieties of patient with distinct medical condition visit in search of care and treatment. A typical multispecialty hospital system consists of various departments like cardiology, neurology, gynecology, ophthalmology, etc., for the treatment of various patients with various medical conditions ranging from less critical conditions like fever, infections, fracture, etc., to extremely critical conditions like ischemic heart diseases, chronic obstructive pulmonary disease, urinary tract infection, etc. Thus, a hospital system with various departments/specialties appoints various specialized physicians in each domain, and maintains large quantity and variety of physician preference pharmaceutical products in the hospital inpatient pharmacy unit for both scheduled and emergency patients. Depending on the medical condition of patients and specialty, inpatient pharmacy maintains inventory of set of medicines, such as medicines acting on the respiratory tract, cardiovascular medicines, medicines affecting blood, anesthetics, analgesics/antipyretics, anti-allergics and medicines used in anaphylaxis, antidotes, anti-infective items, plasma substitutes, dermatological medicines, diuretics, gastrointestinal medicines, vitamins and minerals, medicines acting on ear, nose and oropharynx which are dispensed to wards, operating theaters, critical care units, and other department within the hospitals. Based on the timeliness of administering the medicines, the set of medicines are classified with the characteristics that the patients requiring medicines without any delay are the most critical patient and so on. Therefore, depending on the criticality of patient condition and specialty/department, set of medicines are classified. The number of patients in a hospital unit at a particular time and their medical condition and reaction to treatment during their length-of-stay is random and changes with time, so the demand of required medicines is stochastic and highly uncertain. Thus, the classification of medicines helps in determining the demand pattern and distribution of each classes and the corresponding inventory strategy for them in order to optimize the hospital inpatient pharmacy inventory so that right quantity of medicines are available at right time considering the constraints and conditions of a typical hospital system. Thus, the characteristics, such as arrival rate, transferal and discharge rates, demand distribution, list of medicines, their administration time, etc., need to be analyzed for which relevant data are collected through observations, hospital information system records and discussion with expert medical personnel and hospital administration of a multispecialty hospital in India. The purpose of the paper is to introduce the applicability of classification of pharmaceuticals based on the patient medical condition within the environment of a hospital inpatient pharmacy for improving the performance of inventory management system in hospitals.
Hospital material management has been identified as one key cost containment lever to cope with steadily increasing healthcare costs in industrialized countries. The purpose of this work is to present the state-of-the-art of research on material logistics management in hospitals. Particular focus is given to articles that apply quantitative methods. Our contribution is threefold: First, we provide research guidance through categorizing literature and identifying major research streams. Second, we discuss applied methodologies and third, we identify future research directions. A systematic approach is undertaken in order to identify the relevant literature from 1998 to 2014. Applicable publications are categorized thematically and methodologically and future research opportunities are worked out. In total, 145 publications are identified and discussed in this work. The literature is categorized into four streams, i.e., (1) Supply and procurement, (2) Inventory management, (3) Distribution and scheduling, and (4) Holistic supply chain management. The use of optimization techniques is constantly gaining importance. The number of respective publications has continually grown and has peaked over the last three years. Optimization has been successfully applied in research streams (1), (2), and (3). Category (4) comprises a rather qualitative research field of literature dealing with supply chain management issues.
Hospital operations and patient care are inextricably linked to the supply chain. Like buyers in other industries, pharmacy material managers are challenged to develop inventory policies in light of changing demand, limited suppliers, manufacturing issues, and regulatory rulings that affect drug supply. While these challenges are similar to those in many industries, the impact of drug shortages is quite different as they can have detrimental impacts to patient care and the cost of care. This chapter addresses the inventory management of supplies that directly impact patient care with a focus on pharmaceuticals. The chapter discusses the unique modeling challenges associated with inventory decisions for these products such as their multi-echelon nature, the potential for perishability and/or obsolescence, and internal production/preparation lead times. The chapter also explores the broader implications of the impact of demand uncertainty and inventory management strategies on hospital operations and cost with a particular focus on the comparison between stationary and nonstationary demand. Finally, future research opportunities are discussed.
This paper models a type of vendor-managed inventory (VMI) agreement that occurs in practice called a (z, Z) contract. We investigate the savings due to better coordination of production and delivery facilitated by such an agreement. The optimal behavior of both the supplier and the retailer are characterized. The optimal replenishment and production policies for a supplier are found to be up-to policies, which are shown to be easily computed by decoupling the periods when the supplier outsources from those when the supplier does not outsource. A simple application of the newsvendor relation is used to define the retailer's optimal policy. Numerical analysis is conducted to compare the performance of a single supplier and a single retailer operating under a (z, Z) VMI contract with the performance of those operating under traditional retailer-managed inventory (RMI) with information sharing. Our results verify some observations made in industry about VMI and show that the (z, Z) type of VMI agreement performs significantly better than RMI in many settings, but can perform worse in others.
An important contributory factor to the bullwhip effect (i.e. the variance amplification of order quantities observed in supply chains) is the replenishment rule used by supply chain members. First the bullwhip effect induced by the use of different forecasting methods in order-up-to replenishment policies is analysed. Variance amplification is quantified and we prove that the bullwhip effect is guaranteed in the order-up-to model irrespective of the forecasting method used. Thus, when production is inflexible and significant costs are incurred by frequently switching production quantities up and down, order-up-to policies may no longer be desirable or even achievable. In the second part of the paper a general decision rule is introduced that avoids variance amplification and succeeds in generating smooth ordering patterns, even when demand has to be forecasted. The methodology is based on control systems engineering and allows important insights to be gained about the dynamic behaviour of replenishment rules.
Purpose – To introduce the applicability of the Ned-MASTA classification method for medicines within the environment of a hospital pharmacy and the virtual pharmacy inventory system that forms a virtual pharmacy inventory of hospitals within the same geographical region providing the infrastructure for the cooperation of hospital pharmacies in order to improve the efficiency of their operations. Design/methodology/approach – A survey that was conducted in Greek hospitals identified the inefficiencies of their logistics systems that are similar to inefficiencies identified through surveys in hospitals worldwide. It was considered vital and necessary to investigate the solutions that are provided in other industries facing similar problems. The case of spare parts inventory for production machines was found to present similarities with the management of medicine stock within the hospital pharmacy. The approach that was followed for the case of spare parts was modified and included in the system that forms a virtual hospital pharmacy inventory; this made the approach applicable in the hospital environment and further improved the efficiency of the use of hospital pharmacy resources. Findings – The MASTA classification approach was modified to fit in the operation of the hospital pharmacy and a system was constructed to form the virtual pharmacy inventory. The applicability of the system is demonstrated through an application scenario. Research limitations/implications – The system is in the form of a prototype under evaluation. It has not been applied yet thus results that are based on actual applications are not presented. Practical implications – It demonstrates the idea of a solution to the inefficiencies of the hospital pharmacy and sets the ground for discussing the proposed solution. Originality/value – This study introduces a new approach to the problems and inefficiencies of the hospital pharmacy management.
This is a real-world application of the ABC inventory classification method to a 200-bed acute-care community hospital. Management of 47 consumable supply items in the respiratory therapy department is demonstrated through a step-by-step presentation. As competition in nonprofit service organizations increases, operations managers will need to utilize more cost-minimizing approaches like the ABC method to aid in policy formulation.
Background:
The basic principle of inventory control is ABC based on cost criteria and VED on criticality.
Methods:
Based on ABC-VED matrix, economic analysis of drug expenditure of priced vocabulary of medical stores (PVMS) section 01 for the year 2003 of a 190 bedded service hospital was under taken.
Result:
Out of 493 drugs in PVMS section 01, only 325 drugs were being used in the reference hospital. The total cost of drugs used was Rupees 55,23,503. Of these 325 drugs, 47(14.4%) drugs were Category A, consuming 70% of total expenditure, 73 (22.46 %) drugs Category B consuming 20% and rest 205 drugs (63.7 %) Category C drugs cost only 10% of expenditure. VED categorization done by consensus opinion of medical officers, found 24 (7.3%) drugs vital, 160 (49.3%) essential and rest 141 (43.3 %) desirable.
Conclusion:
On coupling the two techniques ABC-VED matrix was made and drugs were classified in to Category I (AV+BV+CV+AE+AD) comprising 68 drugs, Category II (BE + CE +BD) 159 and Category III (CD) 98 drugs. The management of Category I drugs was monitored by top management resulting in better control on the annual expenses and at the same time making available the vital Category II by middle and Category III at lower mangerial level.
Recently, there has been a rebirth of interest in supply chain demand amplification, a trend accelerated by the availability of a wide range of simulation packages. However, although this approach provides some guidance on design improvements possible in a given situation, it rarely offers insight for the future. In the present paper the use of simple filter theory is proposed to help bridge this gap. The example chosen to illustrate the approach is a three-echelon system in which there are factory, distributor, and retailer activities. The results vividly confirm an optimal design previously obtained via a multi-attribute utility technique (MAUT) expert system. However, the knowledge gained via filter theory should improve yet further the effectiveness of the expert system. This is because the sequential steps to be followed when varying the echelon dynamics as part of the search procedure can be greatly improved. The paper concludes by showing how simulation results might be used to confirm the supply chain dynamic design which will minimize stockholdings in the presence of demand fluctuations. However, it should be noted that in common with the successful application of systems dynamics techniques in production-distribution systems generally, the solutions are most applicable to the medium-term operations horizon. The latter term may need re-definition for use in ‘lean’ supply chains. Our intuitive reaction is that a scientific definition may well turn out to be a multiple of the largest remaining process lead-time in the slimmed down supply chain rather than being the customary arbitrary choice of, for instance, a 12-month period.
In an inventory and order based production control system (IOBPCS), there are three fundamental system parameters. One of these, the production delay time, is beyond the control of the IOBPCS designer. Indeed, the production delay may be highly variable with time due to a variety of problems commonly found in manufacturing industry. This uncertainty must be countered by the proper use of a feedback loop which detects and operates on inventory deviations. The IOBPCS designer is thus left with the forward path demand averaging time and feedback path gain to adjust, as best he can.This paper studies the ability of the IOBPCS to recover from shock demands, and to protect the manufacturing process from random variations in consumption. It is shown that the feedback path is of fundamental importance in good control, and that adequate performance cannot be obtained by feedforward alone. Dynamic recovery is examined graphically by separately identifying the feedforward and feedback components. Random disturbance rejection is studied via the noise bandwidth concept. Finally, performance optimization is undertaken using coefficient plane models related to ‘standard forms’ and hardware systems. One good compromise design achieved has the time-to-adjust inventory, demand averaging time, and production delay time all of comparable magnitude.
Campbell Soup's continuous replenishment (CR) program is a novel innovation designed to improve the efficiency of inventory management throughout the supply chain. With CR (1) retailers pay a constant wholesale price but continue to participate in consumer promotions, (2) retailers transmit to the supplier daily inventory information via electronic data interchange (EDI), and (3) the supplier assumes responsibility for managing retailer inventories, i.e., vendor managed inventories (VMI). We develop simple inventory management rules to operate CR, and we test these rules with a simulation using actual demand data provided by Campbell Soup. On this sample we find that retailer inventories were reduced on average by 66% while maintaining or increasing average fill rates. This improvementreduces a retailer's cost of goods sold by 1.2%, which is significant in the low profitmargin grocery industry. Furthermore, these savings could have been achieved without VMI.
In a recent paper, Cetinkaya and Lee (2000) model integrated inventory control and shipment scheduling in connection with vendor-managed inventory (VMI). The model is optimized by an approximate technique. This note provides a simple procedure for exact optimization, and illustrates that the errors when using the suggested approximate technique may be very large for certain types of problems. We also suggest a new approximation and an adjustment that can be used to improve both the original and new heuristic.
Vendor-managed inventory (VMI) is a supply-chain initiative where the supplier is authorized to manage inventories of agreed-upon stock-keeping units at retail locations. The benefits of VMI are well recognized by successful retail businesses such as Wal-Mart. In VMI, distortion of demand information (known as bullwhip effect) transferred from the downstream supply-chain member (e.g., retailer) to the upstream member (e.g., supplier) is minimized, stockout situations are less frequent, and inventory-carrying costs are reduced. Furthermore, a VMI supplier has the liberty of controlling the downstream resupply decisions rather than filling orders as they are placed. Thus, the approach offers a framework for synchronizing inventory and transportation decisions.
In this paper, we present an analytical model for coordinating inventory and transportation decisions in VMI systems. Although the coordination of inventory and transportation has been addressed in the literature, our particular problem has not been explored previously. Specifically, we consider a vendor realizing a sequence of random demands from a group of retailers located in a given geographical region. Ideally, these demands should be shipped immediately. However, the vendor has the autonomy of holding small orders until an agreeable dispatch time with the expectation that an economical consolidated dispatch quantity accumulates. As a result, the actual inventory requirements at the vendor are partly dictated by the parameters of the shipment-release policy in use. We compute the optimum replenishment quantity and dispatch frequency simultaneously. We develop a renewaltheoretic model for the case of Poisson demands, and present analytical results.
The paper outlines the development of simulation models that describe the dynamic implications of various supply chain redesign strategies adopted by a major European manufacturer of personal computers. The strategies adopted in the real world supply chain, and replicated in the simulation models, are the introduction of the just-in-time philosophy in manufacturing plants, the development of a global materials planning system that attains visibility of total supply chain stock, a strategic supplier sourcing policy and the by-passing of the distribution network so as to directly interface with the customer.Simulation results suggest that dynamic perfomance improvements (which have an impact on customer service level achievement, stock holding requirements and production on-costs) were achieved by each consecutive redesign strategy. The paper concludes that the simulations are useful in educating and informing supply chain designers in other supply chains of the relative dynamic benefits of different supply chain redesign strategies.
The paper describes the application of a general methodology for modelling and simulating the dynamic behaviour of a logistical control system. The methodology is described via the use of an industrial case study. The key features of the methodology are the utilisation of systems modelling media (such as conceptual, mathematical and computer simulation models) for developing an understanding of, and redesigning, the structural elements of logistical systems. The paper concludes with a description of the improvement in performance predicted via the redesign of the case study logistical control system and an outline of the spreadsheet application, and its limitations, of continuous simulation to ease its use in an industrial environment.
Electronic data interchange (EDI), used traditionally to exchange business documents, has recently been extended to facilitate interorganizational collaborative processes such as the continuous replenishment program (CRP). The key characteristics of CRP are the sharing of real-time inventory data by retailers with manufacturers and continuous replenishment of retailer inventory by manufacturers. Prior research on EDI has focused on the transaction efficiency of EDI. We analyze the impact of information sharing and continuous replenishment in the CRP context and study the factors that affect the value of CRP. The study quantifies the value derived from CRP and the optimal number of retailers a manufacturer should partner with.
Supply chains are a complex combination of “man” and “machine” and usually difficult to design. In this paper we argue that systems engineering can be used as an effective tool for this purpose as it comprehensively takes into account intricacies associated with modelling the attitudinal, organisational and technological issues. We describe the analysis and modelling of a two-echelon steel industry supply chain that services the construction industry using an integrated system dynamics framework as an example to good total system design. Key features of the framework are outlined and implementation details are provided. One objective of the design is to move more rapidly towards a minimum reasonable inventory (MRI) scenario in the presence of capacity constraints, breakdowns and material supply lead-time bottlenecks. Simulation results are presented showing how the developed model may be viewed as a “Management Information System” to investigate various business strategies.
Using a spreadsheet to analyze inventory
- J Pinkerton
Pinkerton, J., 1987, "Using a spreadsheet to analyze inventory," Purchasing World, August, 46-47.
Dynamics of pipeline control
- R Mason-Jones
Mason-Jones, R., 1995, "Dynamics of pipeline control," 14th European Conference on Operational
Research, 3-6 July, Jerusalem.
- R G Coyle
Coyle, R.G., 1977, Management System Dynamics, John Wiley & Sons, New York.
A study of inventory classification in healthcare logistics using system dynamics modeling
- L Al-Qatawneh
Al-Qatawneh, L., 2006, "A study of inventory classification in healthcare logistics using system dynamics
modeling," Ph.D. dissertation, Sheffield Hallam University.