This section will analyse several models, equations, calculations, propositions, tables, and discussion points presented in the previous section. This will contain the main discussion points about all the sections mentioned from section 2.3.1 to 2.3.4.
3.1 Model Analysis
3.1.1 Study 1: Information inaccuracy in inventory systems: stock loss and stock out – Kang & Gershwin (2005)
Kang and Gershwin’s “Information inaccuracy in inventory systems: stock loss and stock out” analyses major key points that this study emphasizes. The research is an investigation of information systems within inventory and supply chain management, specifically the problems that arise from inventory inaccuracy, the causes of inventory of inventory inaccuracy and how it impacts the overall performance of the information system. The study by Kang & Gershwin also provides recommendations for contingency plans when inventory inaccuracy occur as well as a compensation method for inventory inaccuracy including implementation of Auto ID systems such as RFID technology. The first model that the study looks into is the (Q,R) policy (Kang & Gershwin, 2005).
The (Q,R) policy has been one of the most prominent inventory policies used throughout supply chains in various industries. The concept of the (Q,R) policy emphasizes continuous monitoring of inventory, establishing a fixed quantity on order (Q) which will be placed when the total number of inventory available for sale and the inventory ordered but have not been received becomes less than or equal to an established reorder threshold (R). In a perfect world where all information is accurate, this method will be ideal to use because it establishes the perfect reorder time and the correct quantity of inventory available for sale while maintaining inventory storage at a minimum level. However, the reality of inventory and supply chain management will always experience inventory inaccuracy from known or unknown sources of stock loss. The demand for purchase and stock loss fluctuates and information will never be consistent regardless if the stock loss is known or unknown. Due to this face, the stochastic simulation model looks into the effects of stock loss to the performance of the (Q,R) policy where there is a discrepancy between inventory on-hand and the inventory record.
The Stochastic Simulation Model runs a simulation that illustrates the effects on an unknown stock loss that has not been mitigated as time progresses. The main assumptions can be found in section 22.214.171.124 Stochastic Simulation Model. The single-item inventory model with an average demand of 10, standard deviation of 2, average daily stock loss of 0.2, lead time of 3 periods, and a fixed order quantity of 50 was used to run a simulation and we can see the results in Figure 2. The results of the stock loss at just 2% of the average demand becomes significant as we move along the x-axis. It can clearly be seen that as time progresses, the actual inventory on hand deviates from the inventory record, causing more out of stock periods resulting in high loss of sales. As the accumulation of stock loss grows over time, stock outs become common to the point where the inventory record stays above the established reorder point, which then creates freeze on replenishment orders resulting to devastating out of stock periods and loss of sale. Figure 3 also illustrates the effects of stock loss on out of stock periods when stock loss deviates from average demand (Kang & Gershwin, 2005).
Based on Figure 2 and Figure 3, it can be concluded that even a small percentage of undetected stock loss that accumulate over time cause disruption in replenishment orders, leading to a significant portion of consumer demand to be classified as lost sales due to out of stock periods. A single stock loss that is undetected, whether this occurs during shipments, based on theft, or anything that can cause the inventory record to deviate from actual inventory on hand can potentially cost more than the actual item lost. The effects of the loss of a single item, the effects vary depending on the product’s price range, can potentially cost the business loss sales of up to 10-20 times higher than the price of the actual product due the domino effect it creates between the inventory management procedures (Kang & Gershwin, 2005).
As opposed to the randomness of the demand for purchase and stock loss used in the stochastic models, the Deterministic Model uses constant demand for purchase and stock loss. By using the various calculations presented in the deterministic model created by Kang and Gershwin, the results are similar to the simulation done in the stochastic model. Unknown stock loss, left untreated within the supply chain, increases its effect to the inventory inaccuracy. The variance between the actual inventory and the inventory record increases as time passes from the initial event that cause stock loss, and this directly affects the overall performance of the supply chain. Figure 4 illustrates the results of the stock out calculation found in 126.96.36.199. Deterministic Model under S out, and how it is similar to the simulation points from Figure 3.
The Sensitivity Analysis tests the most affected areas of the system’s performance when stock loss occurs. This has been studied by comparing stock outs to fluctuations in order quantity (Q) (Figure 6) and lead time (L) (Figure 5). With the assumption that the inventory manager or whoever is responsible for the inventory does not know about the stock loss and by studying Figure 5, the system performance is greatly affected by stock loss when the lead time is shorter. By looking the figure from a logical perspective, the shorter lead time for the product to arrive, the more sensitive the system will be to stock outs caused by inventory inaccuracy. Similar to Figure 5, Figure 6 , the lower order quantity will be much more sensitive to stock out as opposed to larger order quantities because smaller order quantities have smaller safety stock which increases the chances of out-of-stock.
By studying the Sensitivity Analysis conducted by Kang & Gerswhin (2005), we can conclude that systems that experience shorter lead times and lower quantities on order are more sensitive to stock outs caused by stock loss compared to systems with longer lead times and larger order quantities. Smaller lead times and order quantities mean lower safety stock which inevitably does little to protect fluctuations in consumer demand or inventory inaccuracy caused by various types of errors. Stock loss or other causes of loss sales can potentially ruin and inventory management system especially if it’s a lean system. Compensation methods such as safety stock or Auto ID such as RFID systems are thus recommended to prevent inventory inaccuracy and to improve inventory records.
Kang and Gershwin provided techniques that are recommended to help improve inventory accuracy. The methods are analysed to show their effects on controlling various types of errors and to help improve the systems overall performance. The simulation done in section 188.8.131.52. Stochastic Simulation Run was used to illustrate the impact of the recommend compensation methods to unknown stock loss within a system under the (Q,R) policy. In this discussion, the first compensation method, safety stock will be analyzed. Safety stock is defined as extra stock that is used to protect the current inventory from unexpected variables. This is also called the buffer stock for uncertain events to help companies prevent complete out of stock situations and inevitable loss in sales. Safety stock is determined when a reorder point has been established and based on the quantity of orders placed during the reorder point, retailers usually increase the order quantity during these reorder points, i.e. 51 instead of 41 units (2005) (Kang & Gershwin, 2005).
Manual inventory verification is another recommended compensation technique that helps improve inventory accuracy in inventory records. This involves a manual count of inventory on a specific interval such as daily, weekly, monthly, bi-yearly, or annual cycle count to improve inventory records and to ensure that on-hand inventory matches with the system information. Manual reset of the inventory record is another recommended compensation technique. This technique involves manually considering patterns in available data to determine inventory errors within the inventory records. Constant decrement of inventory record is also a method that can be used because decrease the inventory record based on the average stock loss of a timeframe can improve inventory records in the long run. Lastly but the most important aspect of improving inventory records especially in this study is the implementation of Auto-ID (Kang & Gershwin, 2005).
Auto ID such as RFID technology essentially provides the most accurate information when it comes to the stock quantity because the system traces each item. RFID readers and tags allow inventory records to account for every item on-hand that is available for sale and will have the capability to provide automated inventory counts. Radio Frequency Identification technology allows inventory managers to have a transparent view of their stock and to be able to improve the supply chain performance based on the data gathered within the information system. It is thus easier to create re-order points, order enough stock at the correct times, and to predict consumer demand throughout various time-frames.
Figure 7 illustrates the effects of the compensation methods above based on a system following the (Q,R) policy. According to Figure 7, manual inventory verification such as inventory counts done bi-annually helps improve inventory records because it enables the supply chain to correct their inventory inaccuracies as opposed to leaving the error to build up and ruin the system performance. Reset record also provides important information to prevent inventory inaccuracy because determining patterns helps detect inventory errors. Decrementing the inventory record according to Figure 7 also illustrates a significant improvement in the inventory records because the deduction of inventory based on the demand of stock loss over time keeps out of stock periods low and will eventually close in on actual inventory. Finally, Auto ID illustrates the best technique because it allows the perfect information to be transferred to the inventory managers to detect inventory inaccuracies at an early stage, ideal transparency on inventory on-hand/inventory in transit, and achieves “the best stockout-inventory compromise” (Kang & Gershwin, 2005). RFID technology thus proves to be the best option in terms of preventing inventory inaccuracy and improving inventory records in the event of stock outs due to stock loss based on Kang and Gershwin’s study (2005). However, we will discuss the weaknesses of RFID’s in section 3.3 Strengths and Weaknesses of RFID implementation.
Kang & Gershwin’s study of the causes and compensation methods of inventory inaccuracy within a system that can potentially experience stock outs due to unknown stock loss concluded that if left undetected, stock loss has the potential to significantly damage supply chain and inventory management processes. The longer it takes for any corrective action towards actual causes of discrepancies in the inventory record vs the actual on-hand inventory, the more frequent out-of-stock periods will be which will inevitably lead to greater loss in sales. Auto ID systems such as RFID technology has the best ability to combat inventory inaccuracy in inventory records. RFID technology provides an almost complete inventory transparency to businesses as well as other important information that are vital to improving business processes that keep the cost at a minimal level without jeopardizing the maximum profitability (2005). Further conclusions will be discussed in section 4. Conclusion.
3.1.2 Study 2: Inventory Inaccuracy, Double Marginalization, and RFID Adoption – H. Sebastian Heese (2007)
H. Sebastian Heese’s study analyses several scenarios in inventory record inaccuracy within supply chain. These scenarios are (i) the effects of inventory record inaccuracy in an integrated supply chain with/without RFID, (ii) the effects of inventory record inaccuracy in decentralized supply chain with/without RFID as well as (iii) the effects of double marginalization in the adoption of RFID. The effect of inventory record inaccuracy in an integrated supply chain without RFID based on Heese’s analysis provides several results in its effects on optimal order quantity (2007)
Shrinkage, a form of inventory inaccuracy, proposes two contradictory results based on Proposition 1. Shrinkage has the potential to increase the optimal order quantity for the supply chain to have enough safety stock that can compensate for unexpected stock loss. Shrinkage can also decrease optimal order quantity because production costs can potentially increase. Increase production cost will take away from profitability, which will inevitably decrease monetary assets, thus decreasing the optimal order quantity. Figure 7 illustrates the relationship between the level of optimal order quantity with and without inventory inaccuracy. Based on Figure 8 from Heese’s study, optimal order quantity will always be higher when there is inventory inaccuracy compared to supply chains without inventory inaccuracies (Heese, 2007).
The adoption of RFID technology to an integrated supply chain results in significant improvements in inventory transparency and inventory records. In contract, RFID implementation is an expensive investment and it can be concluded that this increase in cost can be associated with an increase in per-unit cost. Proposition 2 illustrates potential profit and projections on optimal order quantity in an integrated supply chain adopted RFID technology (Heese, 2007). Item level RFID adoption will vastly improve inventory transparency because it provides inventory managers within reliable data which then can be used to improve profitability through sophisticated analysis. RFID technology enables inventory managers to analyse fluctuations in consumer demand, product flow through the supply chain stages, and can optimize overall inventory processes. Visibility of inventory decreases the potential for inventory inaccuracies to occur with the supply chain. It can easily be assumed that having the ability to gather real-time inventory information on an item-level can help inventory managers to keep enough inventory at a lowest possible level where profitability is maximized, as opposed to a supply chain without accurate inventory records (Heese, 2007).
The effect of inventory record inaccuracy in a decentralized supply chain in Heese’s study illustrates a scenario where the manufacturer sets the wholesale price and is influenced by the decisions of the retailer on ordering. In this situation, the manufacturer is indirectly influenced by adjustments made by the retailer based on the inventory inaccuracies they are experiencing. Proposition 3 shows that in a decentralized supply chain with inventory inaccuracy, the higher critical fractiles, the double marginalization problem increases when there is inventory inaccuracy without RFID adoption. Proposition 4 illustrates when RFID adoption has been put in place in a decentralized supply chain. The implementation of RFID technology helps restore optimal levels of order quantity which aligns the motives of the manufacturer and the retailer when experiencing inventory inaccuracies. The manufacturer will only profit from RFID adoption if the retailer also sees positive results within their system. If the retailer experiences inventory inaccuracies, then the wholesale surcharge increases and conversely, if the retailer does not experience inventory inaccuracies, the RFID adoption cost will be split equally (Heese, 2007).
Proposition 5, 6, and 7 analyses the cost threshold for when RFID adoption becomes profitable. Various conclusions can be made based on the when RFID adoption is optimal in integrated and decentralized supply chains. First, during a low critical fractile, both integrated and decentralized supply chains will find RFID technology implementation profitable at the same cost. Proposition 6 shows that double marginalization in a decentralized supply chain “does not distort the evaluation of RFID” (Heese, 2007). In contrast, the benefits of adopting RFID technology are higher in a decentralized supply chain because it mitigates the effects of double marginalization. In a decentralized supply chain with double marginalization without RFID, high fractiles experience negative drawbacks when experiencing inventory inaccuracy. Therefore, the study concludes that RFID adoption is much more beneficial in decentralized supply chains especially ones that are experiencing double marginalization. The adoption of RFID technology mitigates majority of the negative effects of inventory inaccuracy, keeping the optimal order quantity aligned between all parties involved while decreasing the potential cost of discrepancies within the inventory records (Heese, 2007).
3.I.3 Study 3: A literature review on the impact of RFID technologies on supply chain management (Sarac et al., 2010)
The literature review conducted by Sarac et al., (2010) on numerous publications on RFID technology concluded that RFID implementation has the capability to minimize “inventory inaccuracy, the bullwhip effect, and replenishment policies (2010). The study aims to provide a list of benefits that RFID technology can potentially bring various supply chains by using analytical models, simulation models and ROI calculations. The study also provides evidence using published case studies and experiments (Table 6) analysing the effects of RFID technology on various supply chains. The study also includes an analysis of return-on-investments. It is imperative to understand that RFID adoption does not mean that it will automatically improve the supply and result in profitable margins (Sarac et al., 2010).
The list from Table 3 are publications about RFID technology and its effects on supply chain. Studies reviewed by Sarac et. al.,(2010) concludes that RFID technology’s most beneficial attribute is the real time information it provides to inventory records. Item-level RFID tagging enables inventory managers to have a transparent view various logistical deployments at the warehouse. A study by Kim et al., (2008b), one of the publications in Table 3, simulated the effects of RFID implementation within a “vehicle deployment and shipment” model (2008b). The simulation concluded that when RFID technology is integrated to the warehouse management system, the technology provides the real-time information that has the potential to reduce labor costs by optimizing labor utilization and improve customer satisfaction by decreasing delays (Kim et al., (2008b).
Real-time information has the potential to mitigate errors that cause inventory inaccuracy. According to majority of the publications, Table 4, in the literature review performed by Sarac et al., (2010), RFID technology’s ability to provide real-time information about inventory, with the assumption that the cost of implementing will be outweighed by its benefits, improves the efficiency of supply chain processes in place, lower storage costs by optimizing inventory management, and can increase the communication of all parties involved within the supply chain. Inventory inaccuracies can be mitigated such as theft, misplacement of inventory, transaction errors and other types of known and unknown errors that cause discrepancies in inventory management. Figure 9 categorizes the benefits of RFID in three groups (i) revenue, (ii) operating margin, and (iii) capital efficiency (Sarac et al. 2010).
The objective of this study is to identify key inventory inaccuracies in supply chain and the impact of RFID technology implementation. Figure 9 provides a summary of different facets where RFID implementation can be most beneficial. Revenue increases because RFID technology improves inventory management by drastically improving stock visibility through the inventory process. This allows the inventory managers to key things that can improve supply chain processes. The first is that inventory transparency allows inventory managers to mitigate transaction errors, inventory shrinkage, internal and external errors, and other situations that cause inventory inaccuracy. Another benefit from inventory visibility is that allows inventory managers to keep stock at a minimal level, driving the cost of storage down, while maintaining the optimal level where on-hand inventory is maximized to meet the demands of current and potential sales. Stock out periods will decrease, causes of stock loss are mitigated immediately, and the current and expected demand are met due to inventory transparency (Sarac et al., 2010).
Operating margins benefit from the reduction of excess stock and stock loss which drives down the cost of goods due to RFID technology. Real-time information provided by RFID technology within the internal information system reduce labour costs by optimizing shipment procedures such as shipping and receiving stock processes. An example of reduction in labour costs in supply chain caused by the implementation of RFID technology is that it elevates manual tasks at the warehouse such as manual inventory cycle counts performed by warehouse employees, manual reassurance of stock availability by physically walking to the storage location to verify, and scanning barcodes during the pick and pack stage of prepping a purchase order at the warehouse floor. However, Sarac et al., (2010) study also notes the importance of understanding the monetary costs of implementing RFID technology in the supply chain.
RFID implementation is a significantly large investment therefore it’s important to understand various costs associated with the system. Figure 10 illustrates a high level break down of costs associated with RFID implementation. The costs are categorized under hardware costs, software costs, system integration costs, installation costs, personnel costs, and business process reengineering costs. Hardware costs include but are not limited to RFID readers, tags, antennas, connectors, computers, and network components just to name a few. Software costs include the software that will be installed in the system as well as other database systems that will be used to store information from the RFID tags. (Banks et al. 2007). The remaining types of costs are self-explanatory and the costs may vary depending on the size and scope of the organization. While understanding the costs of implementing RFID technology is important, understanding the return-on-investment is also important.
RFID implementation is an expensive investment and it is important to calculate the return-on-investment to understand the costs and benefits of the implementation. In the study by Gaukler et al., (2007), splitting the cost of implementation between the manufacturer and retailer is the most ideal option to maximize revenue in supply chain. ROI analysis is also important because it allows the company to know if the investment costs will be worth it in the long run. Basic ROI calculation can be done using Equation 1, as well as a simplified calculation of ROI including the time value of money using Equation 2. It should also be understood that there are certain limitations to all of the case studies, experiments, calculations, and other analysis mentioned in the previous sections. Section III.II.II will discuss certain limitation in Sarac et al., (2010) literature review. However, based on the studies mentioned in the previous sections in this study, several benefits can be concluded. Inventory management processes are improved due to inventory transparency from real-time information, optimization of supply chain processes, reduction of inventory inaccuracies and stock loss, and improved communication between all parties involved in the supply chain process (Sarac et al., 2010).
3.1.4 Study 4: Impact of RFID technology on supply chain decisions with inventory inaccuracies (Fan et al., 2015)
“Impact of RFID technology on supply chain decisions with inventory inaccuracies” by Fan et al., (2015) studies the effects implementing RFID technology in a centralized and decentralized supply chain experiencing inventory inaccuracies such as shrinkage and misplacement. To distinguish the two types, a centralized supply chain is a supply chain where the manufacturer and the retailer are treated as the same decision-making entity while a decentralized supply chain contains individual entities acting on each other’s best interest to ultimately maximize their individual profits. In practice, it’s not common to be purely centralized or a decentralized supply chain. A prime example would be Walmart, a multinational retailer corporation which owns and operates their own retail stores to their own manufacturing locations. The study done by Fan et al., (2015) empowers this dissertation’s objective which is to provide evidence that RFID technology is a viable and important aspect of the future of supply chain because it provides examples of how it mitigates one of the most important obstacles in supply chain, inventory inaccuracies in inventory management.
The effect of implementing RFID technology varies depending on the state of the supply chain and the level of awareness of the retailer or manufacturer about inventory inaccuracies. In the first section, Fan et al., (2015) investigated a centralized supply chain where the retailer is fully aware of the inventory inaccuracies with and without RFID technology adoption.
Equation 3 illustrates a scenario where the retailer understands that there are inventory inaccuracies in the process and looks to optimize the supply chain without RFID adoption. The equation then leads to the equation for an optimal order quantity is used for Equation 4 which is the optimal ordering quantity when the retailer in the centralized supply chain understands that there are inventory inaccuracies within its operations and seeks to optimize the processes without using RFID technology. Equation 5 illustrates a similar scenario as Equation 3 but with RFID technology while Equation 6 illustrates a similar scenario as Equation 4 but again, with RFID technology implementation. These equations provide the basis of comparison of the optimal order quantity and the optimal level of value of RFID when experiencing shrinkage and misplacement (Fan et al., 2015).
Figure 12 illustrate the comparison between optimal order quantity with and without RFID adoption within a centralized supply chain experiencing inventory shrinkage and misplacement. The order quantity without RFID is smaller than with RFID when shrinkage and misplacement is low enough. However, RFID technology clearly looks like the safer option because of how stable the order quantity is throughout the plan. If shrinkage and misplacement are more common, the immediate response of the supply chain without RFID is to increase order quantity to compensate for lost product and loss sales (Fan et al., 2015). It’s also not an option to mitigate shrinkage or redeem misplaced items without RFID better than with RFID. Inventory traceability is one of the key benefits of using RFID technology and this decreases the optimal order quantity because the system will enable the inventory planner to maximize profit by ordering just enough to satisfy potential sales but low enough to minimize costs.
Figure 13 illustrate the effects of shrinkage and misplacement on the optimal value of RFID. The plane shows several key points that must be understood when choosing to adopt RFID technology. Adopting RFID technology does not automatically mean that all inventory inaccuracies will disappear and that profits will ensue. By looking at Figure 13, benefits from RFID technology depend on the fixed costs of implementing the RFID technology. It is evident that the cost of the RFID technology plays a significant part in the profitability of any business. The cost of the RFID tag and the readers will determine if it’s worth investing and evidently, if the cost will not be covered by the profits. Figure 13 illustrates that RFID technology, with accordance to its cost, will help the business with profitability because it can mitigate shrinkage and misplacement (Fan et al., 2015).
The second section of the study, Fan et al., (2015) investigated decentralized supply chains with and without RFID adoption when experiencing inventory inaccuracies. A decentralized supply chain is when each facet of the supply chain act independently to ultimately maximize their profits. In this study, the manufacturer is a Stackelberg leader, meaning that the manufacturer makes the decision first, while the retailer reacts the decision. The manufacturer sets the wholesale price and the retailer orders. Equations 7, and 8 illustrate the expected revenue of the manufacturer and the retailer in a decentralized supply chain experiencing inventory inaccuracies without RFID. Equation 9 illustrate the optimal order quantity of the retailer and Equation 10 show the optimal wholesale price of the manufacturer to maximize profit without RFID technology.
Equation 11 and Equation 12 are similar to Equation 7 and 8 however, these equations represent a decentralized supply chain when RFID technology has been adopted. Equation 11 illustrates the expected revenue of the retailer with RFID and inventory inaccuracies and Equation 12 represents the expected revenue of the manufacturer with RFID and inventory inaccuracies. Lastly, Equation 13 and 14 represent the optimal wholesale price and the optimal ordering quantity in a decentralized supply chain with RFID and inventory inaccuracies (Fan et al., 2015). The equations mentioned above are used as the basis of comparison for a decentralized supply chain with and without RFID technology (Fan et al., 2015).
Using equations 11,12, 13, and 14, several points can be made about RFID adoption in a decentralized supply chain. Manufacturers and retailers can maximize profit by optimizing wholesale prices and ordering quantity. RFID technology however improves inventory traceability which depletes the effects of inventory inaccuracies within the supply chain. Using Fig 14 for reference, because there are less inventory inaccuracies, then the wholesale price set by the manufacturer will be less with RFID than without if the retailer decides to take on all the incurring costs associated with RFID technology. RFID costs as well as the percentage that the technology can mitigate inventory inaccuracies also play a significant role in profitability. In a decentralized supply chain with inventory inaccuracies studied by Fan et al., (2015), retailer’s profit depends heavily on the price of the tags and other costs associated with RFID compared to manufacturers. However, it is important to understand that in the real world, profitability when sharing costs depends on the influential power of the actors within the supply chain. Obviously, companies like Walmart or Target will have more of an influential power compared to smaller companies that are trying to implement RFID technology in the supply chain.
The study by Fan et al., (2015) investigated the impact of RFID technology within centralized and decentralized supply chains with inventory inaccuracies. This dissertation aims to provide useful information with regards to the influence of RFID technology in various scenarios in supply chain and how it has the potential to answer inventory inaccuracy problems that have plagued industries for many years. By using the investigations made by Fan et al., (2015) as well as the other works previously mentioned, several key points can be concluded about the effects of RFID technology in supply chain and inventory management. First, in a centralized supply chain, having inventory inaccuracies such as shrinkage and misplacement does not automatically mean that investing in RFID technology will solve all of the key issues. The costs associated with RFID technology must also be considered and the type of product that the retailer is selling because shrinkage rate must also be accounted for. RFID technology serves to be advantageous, however the cost but reach a certain threshold for the system to be beneficial to a company experiencing inventory inaccuracies.
Second, in a decentralized supply chain where the manufacturer is a Stackelberg leader and the retailer takes on the RFID costs, the retailer will be more sensitive with the price tag compared to the manufacturer. However, an optimal level of cost sharing ratio can be achieved but it relies heavily on the influential power of the actors. Manufacturers such as Walmart can mandate RFID technology and put all the financial burden on its suppliers because of its influential power. Retailers and suppliers hardly have a say on these types of costs especially when big box retailers such as Walmart are valuable channels for sales who typically mandate these implementations.
The following section discusses the limitations of the studies that were summarized and analysed in sections 2.3 and 3.1. The limitations mentioned in the sections are not the only limitations in the studies. Further limitations might have been left out due to either time constraint or lack of purpose for the context of what this dissertation’s objective.
Most of the models, shown in section II.II.II.I Information inaccuracy in inventory systems: stock loss and stock out, are limited to the most simplistic supply chain process using a single-item inventory model. With this limitation, it is imperative to understand that the complexity of each model increases as supply chain stages increase. This current evaluation of Kang and Gershwin’s study also limited the amount of information transferred form the actual work itself, such as exact calculations, to avoid replicating their work within this study. The all-around message that should be concluded from this analysis is that inventory inaccuracy increases when stock loss is left untreated. There are multiple compensation methods and techniques that can be used to prevent or at least decrease the discrepancies within inventory records.
The compensation methods recommended by Kang and Gershwin also have their own limitations. The investigation is limited to the analysis and evaluation of a “stockout-inventory performance” when choosing the right compensation method. However, this should not be the only basis for choosing the correct method. The number of methods mentioned are also limited because there are numerous other inventory management techniques that can be used to mitigate inventory inaccuracy problems. Higher safety stock is limited to provided proper mitigation of inventory inaccuracy if is caused by a “nonzero-mean” error. Manual verification is limited to the resources of the company due its cost of implementing and the level of potential loss of sales during inventory cycle counts. It is also limited to the intellect of the individuals performing the manual count and it can also be prone to human error. Resetting the inventory record is limited to the ability of the business to create such a sophisticated type of analysis. The wrong conclusion can lead to frequent overstock or out-of-stock periods. Decrementing inventory information is limited to the stakeholders involved and is dependent on the quality of information available in lowering stock out levels based on analysis (Kang and Gershwin, 2005).
Certain limitations must be considered for the models that were used in in Heese’s study on Inventory Inaccuracies, Double Marginalization, and RFID adoptions to achieve desired results. Uncertainty reflected in the work are based on independent variables picked at random as well as similar densities to achieve the desired setting. This was done to visualize the demand with comparative analysis of profit as well as a method to achieve results that show optimal RFID adoption threshold for both manufacturer and retailer. Various calculations were also made by Heese’s to guarantee that the results are not biased such as “conducting numbering experiments based on normally distributed demand and order yield, varying cost parameters as well as means and standard deviation for both random variables” as well as varying “the maximum possible values for demand and yield, included cases where the distributions have practically infinite support” (Heese, 2007). These calculations are in the Appendices section of Heese’ study and these calculations have not been included in this study to avoid duplications of work and ultimately, to avoid plagiarism. For reference, of these in-depth calculations, please see “Inventory Inaccuracies, Double Marginalization, and RFID adoption” by H. Sebastian Heese, 2007.
The results of the calculations emphasize the fact that double marginalization and inventory inaccuracies intensifies each other whenever it has been experienced in a decentralized supply chain. The optimal RFID technology cost threshold can potentially be lower in the study compared to a large-scale adoption outside of the limited single-period newsvendor model used in this study. It is also assumed that any left-over inventory is equivalent to the desired quantity as opposed to real-life scenario where left-over inventory can potentially be excess or unwanted stock creating more storage costs etc. In the study, it is also assumed that the manufacturer decides on the wholesale price. This assumption excludes analysis of RFID adoption mandated by large manufacturers that consider maintaining wholesale price, mitigating the actual effects of double marginalization to decentralized supply chains. The limitations of Heese’ study that are previously stated are the most important limitations to be discussed and further empirical study can be conducted to determine other limitations. Further research should also be conducted before any of the findings can be translated to actual practice (Heese, 2007).
3.2.3 A literature review on the impact of RFID technologies in supply chain management – Limitations
There various limitations within the publications and the literature review by Sarac et al., (2010). Majority of the studies account RFID technology provides the complete answer to inventory management issues and all causes of inventory inaccuracies within the supply chain. Most of the studies also consider the most basic simulation model of a specific scenario which limits the simulations validity in a more complex environment. The literature review also accounts for simplistic calculations such as basic equations to calculate ROI when dynamic systems require complex calculations to account for verifiable results. RFID technology is also viewed by the publications as a replacement for current systems such as the barcode system, limiting its potential for its integration within already existing systems. These are several highlighted limitations involved in this study of Sarac et al, (2010) and if time was not an issue for this research paper, more details about optimal manufacturer to retailer cost splitting could have been made and more limitations could have been mentioned.
Fan et al., (2015) investigated the effects of RFID technology in a centralized and decentralized supply chain under inventory inaccuracies such as shrinkage and misplacement. In this study, there are a several limitations that must be addressed to show the validity of the work. One of the key limitations is that the manufacturer determines the wholesale price of the product, while the retailer then orders based on the wholesale price. The manufacturer is then classified, in terms of economics, as a Stackelberg leader. Also, the demand in the scenarios are uniform compared to the stochastic demand which will always be subject to the bullwhip effect of consumer demand (Fan et al., 2015).
For both the centralized and decentralized supply chain analysis in the study of Fan et al., (2015), shrinkage and misplacement occur immediately after an order has been placed. The inventory inaccuracies also do not overlap but evidently, misplacement and shrinkage can occur simultaneously or even at the same time in real-life situations. Also, misplacement of products in the study can be recovered completely. RFID tagging will be on an item level, however there a multiple type of RFID tagging that can be placed on a master case pack level or a pallet level. The study is limited to item-level RFID tags. Another key limitation in this study is that retailers are aware of the inventory inaccuracies which limits the study to supply chains that are aware of discrepancies in information, leaving out retailers that are not aware of any inventory inaccuracies (Fan et al., 2015).
In the decentralized supply chain analysis, the study focused on the “impact of the RFID cost on the manufacturer’s decision” instead of the impact of other benefits associated with RFID implementation such as inventory transparency and improve real-time information for the supply chain information systems. Implementing RFID technology in the decentralized supply chain in the study done by Fan et al., (2015) takes away inventory misplacement. This limits the study to not only item-level RFID tagging, but also other scenarios such as faulty equipment leading to unsalvageable misplaced products etc. The two most important limitations in the study are the lack of negotiation power of the retailer on wholesale price and the study does not account for any other contract besides wholesale price. In real-world supply chains, wholesale price is a small portion of what the negotiations are based on and retailers usually have a larger role in creating incentives to invest or not invest in RFID technology (Fan et al., 2015).
The dissertation is motivated by the analysis of the impact of RFID technology in several supply chains and the potential ability of the technology to address the most common problem in inventory management; inventory inaccuracy. The paper’s main concerns are, mitigation of inventory inaccuracies using RFID technology, evaluation of optimal solutions for cost sharing, address the strengths and weaknesses of RFID technology as a whole, and the potential improvements that lead to structural reengineering in retail industry supply chains. There are several important studies that were presented in the dissertation for the reader to evaluate the impact of RFID technology in various scenarios; (i) Information inaccuracy in inventory systems: stock loss and stockout by Kang and Gerwshin (2005), (ii) Inventory Record Inaccuracy, Double Marginalization, and RFID Adoption by H. Sebastian Heese (2007), (iii)A literature review on the impact of RFID technologies on supply chain management by Sarac et al., (2010) and (iv) Impact of RFID technology on supply chain decisions with inventory inaccuracies by Fan et al., (2015).
In the beginning of the paper, background information (section 1.1) and historical development of RFID technology (section 2.1.2) are presented as well as the key issues in inventory management (section 2.2.1). The background information presents the current environment of the inventory management and supply chains in several businesses. It has been concluded that contrary to popular belief, retailers holding physical inventory have been prone to inventory inaccuracies for many decades (Kang & Gerswhin, 2005). Information systems holding inventory records experience inventory inaccuracies are presented to allow the reader to understand the impact of inventory inaccuracies to supply chains. Based on the background information, it can be concluded that supply chains have been plagued with inventory inaccuracies that have accumulatively cost businesses all over the world billions of dollars in monetary and non-monetary assets (Bednarz, et al. 2003).
The historical development of RFID technology was also presented in section II.I.II to provide the reader a brief overview of how the technology came about. Based on literary reviews and the research conducted for this dissertation, RFID technology has been mentioned multiple times in countless academic studies (see Table 1) as one the key to answering the most important obstacle in inventory management; inventory inaccuracies. Before analysing RFID technology, the dissertation has presented different types of inventory inaccuracies to understand how RFID technology help improve inventory management and controls. The most common inventory inaccuracies are errors in transactions, shrinkage (stockloss), inventory misplacement, and supply errors according to Table 1 (Sarac et al., 2015). Each inventory inaccuracy causes a rift to expand between inventory records and physical inventory which can inevitably cost businesses millions of dollars when left undetected (Kang &Gershwin 2005).
Each study was presented to provide examples of different types of supply chains, specifically centralized and decentralized supply chains, experiencing various types of inventory inaccuracies such as shrinkage (stock loss) and misplacement of inventory. The first conclusion based on the first study analysed in this dissertation, “Information inaccuracy in inventory systems: stock loss and stockout” by Kang and Gerswhin (2005), is that untreated stock loss within inventory records can significantly disrupt inventory flow. The study by Kang &Gershwin (2005) presented in section in 184.108.40.206 used simulations (Q,R policy, stochastic and deterministic models) to conclude that untreated stock loss can cause severe out-of-stock periods and loss sales if the business is left unaware or does not system in place to identity and mitigate discrepancies between their inventory information systems and actual inventory on-hand. Al though the conclusions state that the sophisticated technology isn’t necessary to mitigate inventory discrepancies, Auto identification systems such as RFID technology can significantly improve inventory flow within retail supply chains especially when the supply chain is in a lean environment where lead-times are shorter (Kang & Gershwin, 2005).
For further analysis of the impact of RFID technology in supply chain and inventory management, the study by Heese (2007) “Inventory Record Inaccuracy, Double Marginalization, and RFID Adoption” was presented in section 3.1.2 The study observed an integrated and a decentralized supply chain with and without RFID implementation, as well as optimal ordering quantities and wholesale contracts, and the optimal cost threshold of profitability when adopting RFID technology. Using a simple supply chain model, the study has provided several conclusions that help understand supply chains with inventory inaccuracies with and without RFID technology, and cost-benefit ratio on RFID adoption. In an integrated supply chain under inventory inaccuracies without RFID, the lower the level of inventory inaccuracies, the lower the level of the optimal order quantity and vice versa. This occurs because supply chains must compensate using safety stock to be able to minimize the effects of stock-outs. In a decentralized supply chain, RFID technology is more beneficial when there are inventory inaccuracies but the cost of implementation will be higher. Also, the benefits of RFID technology are higher in a decentralized supply chain because it helps minimize inflation in stocking quantities by optimizing the order quantity level for all parties involved. RFID mitigates the short and long term negative effects of double marginalization. This occurs because RFID technology streamlines inventory management processes based on real-time and accurate information. (Heese, 2007). In an event of inventory discrepancies occurring due to shrinkage or inventory misplacement, the study suggests that RFID technology is a recommended method to minimize its negative effects on business assets.
To be able to present multiple studies about the potential benefits of RFID technology in supply chain in the limited time allotted for this dissertation, the third study “A literature review on the impact of RFID technologies on supply chain management” by Sarac et al., 2015) is presented for analysis and evaluation of the system. The literature review analysed more than 40 different surveys (Table 1) to determine the most common causes of inventory inaccuracy along with 20+ different analytical models (Table 3), and 17 simulation analyses(Table 4). Sarac et al., (2010) concluded based on their literature review of various surveys, models and simulations, RFID technology can optimize supply chains because RFID technology provides real-time visibility on physical inventory. RFID can also improve inventory flow by streamlining purchase order management with correct forecast planning using the data gathered from the RFID tags. This will allow business to monitor consumer demands, sales, and other valuable trends. RFID can also decrease inventory loss, help reengineer important processes, and reprioritize supply chain objectives. (Sarac et al., 2010)
The literature review by Sarac et. al., (2010) also concluded that before adopting RFID technology, it is important to assess the environment of the business, expertise in the industry, known constraints, main priorities, and understanding of the overall objective of the business. RFID technology might potentially answer the problem of inventory inaccuracies in supply chain management, but it is also important to understand that RFID technology needs further research and international standardization.
The last study presented is Fan et al., (2015), “Impact of RFID technology on supply chain decisions with inventory inaccuracies”, and the study further improves the credibility of the benefits of RFID technology in supply chain with inventory inaccuracies. The study by Fan et al., (2015) investigated centralized and decentralized supply chains with and without RFID technology under shrinkage and misplacement. It has been concluded that before adopting RFID technology in a centralized supply chain, the business must evaluate the investment cost for RFID tags, readers, and other equipment, and the level of shrinkage in the supply chain to understand the profit margins of the business. The sensitivity of the manufacturer and the retailer on the benefits of the RFID technology depends on who has more influence on the other. RFID technology is acknowledged as technology that can minimize the effects of shrinkage and misplacement due to the inventory transparency it provides and its optimization in supply chain processes.
The questionnaire in section 5 is based on an interview with a current operations manager for a consumer soft goods company based in New York City. The company transitioned from a small to a medium size company within several years and holds a significant amount of inventory. Based on the interview, a number of issues has been raised that have caused the supply chain to experience a significant number of out-of-stocks leading to costly airfreights, and thousands of dollars lost on unavailable products. The inventory record used is an excel file that has been sent in the beginning of the day and is used throughout the day leaving the inventory prone to incorrect information. RFID tags has also been mandated by their customers such as Macy’s and Saks 5th Ave.
In conclusion, RFID technology has potential benefits that can greatly improve supply chain and inventory management. Inventory inaccuracies in supply chain are mitigated by the provision of real-time information on inventory by different levels of RFID tagging. In several scenarios presented in this dissertation, it can be concluded that RFID technology improves inventory flow because it allows businesses to gather valuable information from effective supply chain processes such as improved forecast planning, accurate inventory records, and aligned communication policies throughout the supply chain. RFID technology also does not necessarily have to replace the barcode system but it should rather be seen as an improvement to the current norms of product identification. However, it is very important to assess the environment of the industry the business belongs to, the key objectives of the business and costs/benefits of equipment and implementation before adopting RFID technology. Furthermore, deployment of RFID systems will not always minimize inventory inaccuracies in inventory information systems without proper planning. The technology holds potential on fixing the most important problem in inventory supply chain management; inventory inaccuracies. It is recommended that RFID technology manufacturers improve the lifespan of the tags at an affordable price to improve the products value. Further research must be conducted on various privacy policies, cost optimization procedures, improvement on equipment, and the international standardization of RFID policies to greatly improve the reliability of the RFID technology in supply chain management.
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