Safety Stock Research Articles

THE FORECASTING OF RAW MATERIAL INVENTORY IN SUPPORT OF THE CONTINUITY PRODUCTION PROCESS

This study aims to calculate the prediction of raw material inventory, the Economic Order Quantity (EOQ), safety stock, and reorder point in support of the continuity production process at a fence manufacturer, CV. Moderen Arsiteknis in Kupang city. Data were analyzed from records of the period 2013–2017 that consist of the annual demand of a product in quantity per unit of time (D), product order cost (S), unit cost (C), holding cost per unit as a fraction of product cost (H), and lead time (L). It is calculated from the forecasting of raw material demand and then computed the Economic Order Quantity (EOQ), safety stock, and reorder point for the next 3 years (2018-2020). The computation of demand forecasts, EOQ, safety stock, and reorder points is intended to smooth the continuity of the production process, reduce the risk of raw material shortages, and minimize the ordering cost and holding cost in CV. Modern Arsiteknis was discussed in the results section.
 Keywords: Forecasting; Economic Order Quantity; Safety Stock; Re-Order Point

Managing material shortages in project supply chains: Inventories, time buffers, and supplier flexibility

We consider a two‐stage project supply chain with a downstream project firm producing an engineer‐to‐order (ETO) complex product or a make‐to‐order (MTO), low‐volume, customized industrial product as a project, and an upstream contract supplier supplying a key material to the project. The project faces two uncertainties: project activity time uncertainty and material consumption uncertainty, which may be positively or negatively correlated. In anticipation of these uncertainties, the project firm has to carefully decide its promised project due date to its project customer, against which harsh penalties will be assessed, and his material order quantity to commit to the contract supplier in advance. In most practical settings, project firms order from contracted suppliers via a flexible wholesale price contract consisting of a discounted advance order price and a risk‐premium adjusted expedite order price. The discounted advance order price encourages the project firm to take more inventory risk in the supply chain, and the expedite order price incentivizes the supplier to bear more inventory risk by carrying safety stock in excess of the project firm's advance material order. We formulate an optimization model that solves the project firm's project due date and material order problem, which takes into account the supplier's strategic reaction to the project firm's material order under the flexible wholesale price contract. We show that for MTO projects, risk‐sharing with suppliers on project materials is less important to the project firm, with the project firm assuming ownership of all material inventory in the channel and setting a deliberate project due date being the key. On the other hand, for ETO projects, risk‐sharing with contracted suppliers assumes critical importance. Project firms managing ETO projects should fully exploit the flexibility in the material supply contract to optimally drive the supplier's safety stock level and set the project due date reflecting the shared risk in the supply chain.

Analisa Perencanaan Dan Pengendalian Persediaan Bahan Baku Kasur Busa Dengan Metode Eoq (Economic Order Quantity) Pada Pt. Kurnia Persada Mitra Mandiri

This study aims to analyze the planning and control of raw material inventory at PT. Kurnia Persada Mitra Mandiri. The analysis was performed using the EOQ (Economic Order Quantity) method. This analysis technique consists of reviewing the reorder point, safety stock, and total annual inventory cost. The results show that by using the EOQ method, the company can find out how many times raw materials are purchased and in the quantity how many times raw material purchases are made, know how much minimum stock is needed to be on guard, determine the time to reorder raw materials, and know the cost. The results showed that by using the EOQ method the company could generate more optimal profits compared to conventional methods. Furthermore, the research results also show that with the application of EOQ, companies can make savings on raw material inventory costs, namely in 2018 amounting to IDR 19.092.034 and in 2019 of IDR 21.053.480. In the end, this research is expected to provide insights for companies to use the EOQ method sustainably so that the process of planning and controlling raw materials is better.

ANALYSIS OF INVENTORY CONTROL OF RAW MATERIALS FOR OYSTER MUSHROOMS PLANTING MEDIA IN UMKM AQSHA GUNUNG LINGKAS URBAN VILLAGE, EAST TARAKAN

UMKM Aqsha is a Small and Medium Enterprise that produces oyster mushrooms in Tarakan City. In the implementation process, the inventory for oyster mushrooms has yet to use the calculation method of EOQ analysis. In this case, there might be a media shortage of raw planting materials. The objectives of the research were to (1) describe the system of controlling the inventory for oyster mushrooms planting media raw materials based on actual conditions at UMKM Aqsha, (2) analyze the system of controlling the inventory for oyster mushrooms planting media raw materials using economic order quantity analysis, buying frequency, safety stock, reorder point and maximum inventory. The technique of taking informants was conducted by selecting the key informants, namely business owners and workers who know the information needed in the research. The analysis method used economic order quantity analysis, buying frequency, safety stock, reorder point and maximum inventory. The results of the research showed that the inventory control of UMKM Aqsha required all three raw materials totaling 3,345 kg in a year, with a one-time order quantity for the three raw materials totaling 1,115 kg. The inventory control implemented by UMKM Aqsha was not optimal yet and also has not yet implemented a reorder point. So that it was not possible to prevent a shortage of the three raw materials during the production process. EOQ analysis was given an optimum order for all three materials with 1,655.9 kg of raw materials, no safety stock for all three materials, a reorder point for all three materials with 526,17 kg of raw materials, and for the maximum inventory for all three materials with 1655.9 kg of raw materials.

Inventory Management with Demand Forecast for Eyeglass Lenses Using The Time Series Method at An Optical Store

In the healthcare sector, supply chain management is one of the most important elements since in the logistics of medical devices and pharmaceutical products, patient satisfaction is the main focus in efforts to improve service quality. One of the problems that often occurs in the optical supply chain is inventory control. The optical store is one of the microenterprises engaged in optometric health services. The enclosed supply chain is a three-echelon model, where the store is at the second level. The process of ordering lenses at the store from suppliers is not carried out based on predicted demand. The determination of the safety stock amount and the reorder point also still has a fairly low accuracy there. This is indicated by overstock and stock-out situations that still occur frequently in this company. Overstock causes the product to be damaged because it has been stored for too long and stock out causes lost sales. To solve the problem in this research, the prediction of future demand is overcome by using several time series methods, such as cyclical models, cyclical trend models, and ARIMA models. Forecasting result validation is implemented by calculating the calculation of errors using MAPE, MAD, and MSE then it was found that the forecasting model chosen to predict the demand for the lenses is a cyclical trend model. The result of the demand forecasting and safety stock size calculation with 3 service levels are used as input to determine the reorder point. After observing the condition of the company and the targets set by the company, the calculation results with a service level of 90% is the most possible to be implemented.

Analysis of Inventory Control of Perishable Goods with Capital Constraints and Warehouse Capacity Using the Lagrange EOQ Method (Case Study UD. XYZ)

Inventory control is a company policy in managing goods in order to optimize the number of orders and minimize inventory costs. The object of this research is PT XYZ in Gresik city which produces tempeh and tofu. Several raw materials are needed in the production process, one of which is soybeans. As the main raw material for making tempeh and tofu, soybeans are perishable goods. Previously, the company used a method based on past usage data in controlling its inventory, resulting in bloated inventory costs and a buildup of raw materials in the warehouse. Therefore, researchers need a method that is economical and takes into account the limitations of the company. The Lagrange EOQ method is a model that measures the order quantity by looking at one or more restrictions. The results of the Lagrange EOQ method get an order quantity of 20 sacks of soybeans with an order frequency of 27 times a year, a total inventory cost of Rp. 665,575, an ROP of 12 sacks and a safety stock of 10 sacks.

Using the kanban system as an effective tool for organizing the transportation of dairy raw materials

The paper considers approaches to providing the enterprise with the required raw materials or semi-finished products. The general scheme of the milk raw material transportation cycle was analyzed. According to one approach, the supply system of raw materials can be represented by three constants, based on which several of their relations can be established, allowing us to describe the supply system much better. It is emphasized that the total duration of the cycle for each supplier is individual and depends on the demand indicator and the volume of the batch of the product or raw material. However, each product or raw material supplier's different cycle times do not allow them to be consolidated to build a stable delivery route. It is essential to achieve the required delivery frequency with maximum vehicle loading. The need to use the " heijunka board" to organize the efficient operation of routes for the transportation of dairy raw materials by the enterprise's employees was analyzed. Such a tool allows one to visualize dairy raw materials' transportation routes and ensure explicit control. For this, a heijunka board and supplier kanban cards are used, which form a graphic representation of transport routes in the corresponding time interval. Policy directions for determining the frequency of transportation of raw materials or semi-finished products are highlighted. It is proved that the optimal order policy must satisfy the zero-order property, and the time between orders can be calculated based on the amount of stock in the warehouse and the speed of their use, which will correspond to the demand indicator d and will reach zero after f orders. The kanban system allows optimal results in combination with the heizunk method, which balances the delivery time of raw materials or products as much as possible. Several models for the analysis of the heizunk system are considered. The common feature of these methods is the search for the optimal size of the buffer stock to ensure the maximum efficiency of production facilities while minimizing losses. The total number of kanbans for the system is decisive because this indicator determines the effectiveness of their adaptation to changes in production conditions. Keywords: kanban, system, heizunk method, loss minimization, order.

Political aspects of ‘buffer stock’ employment: a reconsideration

AbstractAdvocates of Job Guarantee (JG) or Employer of Last Resort (ELR) schemes have suggested that if the state provides ‘buffer stock’ employment to workers displaced from private employment, then full employment can be maintained over the course of the business cycle. Kalecki was sceptical about the prospects for maintaining full employment in capitalist economies, without fundamental institutional change that would alleviate certain political constraints. We argue that in and of themselves, JG/ELR schemes do not create the fundamental institutional change required to address Kalecki’s concerns and so ensure that full employment becomes achievable as a permanent state.

Multi-Level Site Selection of Mobile Emergency Logistics Considering Safety Stocks

With the increasing frequency of emergencies in recent years, the emergency response capacity of the emergency management system needs to be improved. Based on safety stock strategy, this paper proposes a multilevel siting model on the topic of mobile emergency response. We modeled the emergency response needs during emergencies by incorporating the population distribution of each region. The uncertainty of emergencies is modeled by aggregating the frequency of crises in each region over the past 20 years. The site selection model minimizes contingency logistics costs that include transshipment, deployment, inventory, and safety stock costs. In this paper, the IA (Immune Algorithm) is optimized to solve the constructed emergency site selection model. The experiments on the model were carried out with data from the area of Chongqing, Sichuan Province. The number of logistics centers and distribution storage warehouses was tested. The influence of safety stock strategy on the total cost of emergency logistics was analyzed. The research results found that the cost of safety stock is negatively related to the cost of transshipment. In addition, the total cost of emergency logistics has a lower bound. Adding distribution and storage warehouses does not further reduce the total emergency logistics cost.

Demand forecasting under lost sales stock policies

Demand forecasting is a crucial task within supply chain management. Stock control policies are directly affected by the precision of probabilistic demand forecasts. For instance, safety stocks and reorder points are based on those forecasts. However, forecasting and replenishment policies have typically been studied separately. In this work, we explore the influence of inventory assumptions on the selection of the forecasting model. In particular, we consider when the stock policy follows a lost sales context and the demand is estimated by means of sales data. In that case, forecasting models should use censored demand estimations. Unfortunately, the literature about censored demand forecasting remains very limited, without an accepted general solution for this problem. In this work, we bridge that gap by proposing the Tobit Kalman filter (TKF). To the best of our knowledge, this is the first time that the TKF has been applied to supply chain demand forecasting, and this approach may represent a general solution for lost sales contexts. The TKF is compared with a previous ad hoc censored demand forecasting solution that is based on single exponential smoothing. In addition, we show the performance of the TKF when dealing with trends where ad hoc approaches are not available for use as benchmarks. To express the potential benefits of the proposed approach in terms of costs and the service level, a newsvendor stock policy is employed. Simulated demand data and a case study are used to illustrate the significant advantages of the proposed tool.

ANALISIS PERSEDIAAN PAKAN TERNAK PADA USAHA KECIL MENENGAH TANI RAYA

Inventory management is an important aspect for good planning in business activities. The application of inventory management in it is a primary need if there is a problem with the supply of raw materials, all operational activities will be disrupted, the problem in this study is that there are often empty P304C laying quail stocks, so many consumers complain. Predicting demand accurately is very difficult because Tani Raya cannot predict consumer desires, so it must carefully plan the inventory so that it is not too large and not too small. this study used the EOQ method. The purpose of this study is to analyze and determine the control of feed inventory of p304c laying quails using the Economy Order Quantity method in SME tani raya. The results obtained by the optimal frequency of purchases are carried out 12 times a year with a total purchase of 14,000 kg, with a safety stock of 1,514 kg. Reordering is carried out when the inventory of goods remains 14, 514 kg or 14, 500 kg. the calculated EOQ method produces a total cost of Rp. 2,509,976 while the conventional method is Rp. 7,539,873, with a difference of Rp. 5,029,897.

Inventory Cost Reduction with Economic Order Quantity for Filter Spare Part in Aircraft Filling Depot

Filter is one of the spare parts playing an important role in maintaining the quality of aviation fuel. Filter replacement is increasingly being carried out when the frequency of aviation fuel distribution is higher. Therefore, it is necessary to control the filter level of inventory. This research aimed to design filter ordering schemes by Economic Order Quantity (EOQ) and to reduce the inventory cost for filter in aircraft filling depot. This research was conducted in one of aircraft filling depot in Indonesia. The data regarding filter demand, lead time, ordering cost, and carrying cost were collected from the depot’s documents. Several steps were conducted to achieve the purposes of the research including classifying filter category by ABC method, calculating optimal order quantity, order frequency, safety stock, reorder point, and inventory cost. The inventory cost calculated by EOQ was then compared to the actual inventory cost incurred in the depot to determine the inventory cost reduction. The implementation of EOQ enabled the depot to reduce its inventory cost by Rp8.348.848,20 or there was a 73,22 percent inventory cost reduction.. The EOQ used in this research was adapted to the difficulties of the depot to predict the demand of filters. The probabilistic EOQ used in this research was expected to be the contribution from this research since this method tended to be used in the uncertainty condition. Based on this method, the safety stock was calculated as a way to reduce the uncertainty demand and the risk of filter shortage.

Demand management using responsive pricing and product variety to counter supply chain disruptions

We consider a retailer that offers multiple variants of two brands, all of which are substitutable, within a single product category. Due to supply disruptions, the retailer may not be able to always offer either or both brands. To mitigate potential loss in demand due to unavailability of one brand, the retailer may choose the product variety strategically and/or adjust the price of the available brand. The goal of this paper is to compare the relative impact of these two levers of demand management in the face of supply disruptions. To that end, we develop and analyze a model of a retailer buying from two brands (suppliers) subject to random supply disruptions. The retailer’s customer demand depends on price and product variety, and their impact on customer choice is captured through the nested logit model. The model also takes into account fixed design and operational costs associated with product variety. Our analysis reveals that strategic choice of product variety yields most of the benefit; price is a largely ineffective lever. We also show that when the supply of one brand is disrupted, the optimal price for the other brand is lower than when both brands are available, provided the outside option is equally or less affected by the disruption. However, even if the outside option is affected more, this result may not necessarily reverse. Finally, even though responsive pricing does not improve the profit substantially, it may reduce safety stock requirements.

Penentuan Order Quantity Bahan Baku Pupuk Bersubsidi Jenis Npk Menggunakan Metode EOQ Di Pt. XYZ

Fertilizer has an important role in supporting the productivity of food crops. The Indonesian government provides subsidized fertilizers in an effort to support the fulfillment of national food needs. The number of subsidized fertilizer needs targeted by the government increases every year. Therefore, appropriate inventory planning is needed to realize the subsidized fertilizer production target that has been set by the government. The type of NPK fertilizer is one of the concerns because this type of subsidized fertilizer has a high demand rate, but its production figure is still far from the realization target. So that in this study the author aims to conduct a comparative analysis of inventory with the policies set by the company, namely Minimum-maximum with the Economic Order Quantity (EOQ) method. The EOQ method considers several costs, such as holding costs, raw material prices, and ordering costs. There are several outputs produced by the authors in this study, such as the frequency of orders, safety stock, reorder points, and total inventory costs. With this policy, the total cost of raw material inventory that must be spent for the manufacture of NPK fertilizer is Rp 4,257,606,170. And by using the EOQ method, it can save the company's total inventory cost of Rp. 121,368,688 or 2.77%.

A STUDY ON INVENTORY MANAGEMENT” AT MULTITEK AUTO PARTS IN DODDABALLAPUR.

The study on inventory management at Multitek Auto Parts addresses the critical importance of efficient inventory management practices within the automotive parts industry. Multitek Auto Parts, a prominent player in this sector, faces challenges in maintaining an optimal balance between supply and demand while minimizing costs and ensuring customer satisfaction. This research delves into the various strategies employed by Multitek Auto Parts to manage their inventory effectively, considering factors like demand forecasting, procurement methods, stock control techniques, and technology integration. The study not only explores the company's successes and best practices but also highlights potential areas for improvement. By analyzing the inventory management practices at Multitek Auto Parts, this study contributes valuable insights to both academic literature and industry professionals, shedding light on the intricacies of inventory optimization in a competitive automotive parts market. Keywords: Inventory management, Supply chain, Optimization, Inventory control, Demand forecasting, Stock levels, Ordering policies, Reorder point, Safety stock, Just-in-time (JIT),MEconomic order quantity (EOQ) etc.

Pentingnya Perencanaan dan Pengendalian Persediaan Bahan Baku Paving Dengan Metode Economic Order Quantity (EOQ) Untuk Optimalisasi Laba

This study aims to determine optimal raw material purchasing planning using the EOQ (Economic Order Quantity) approach at the Somber Berkah Sukosari Dagangan Madiun Regency company and to provide input regarding planning and controlling raw material inventory so that it has the potential to increase profit efficiency in the company. This study uses a quantitative descriptive method. The descriptive analysis technique used to analyze data regarding the problem of planning and controlling raw materials to optimize company profits is to use the EOQ (Economic Order Quantity), TIC (Total Inventory Cost), Safety Stock, Reorder Point, MI (Maximum Inventory) methods. From the research results it is known that the purchase of raw materials using the EOQ method total raw material inventory is less than using the method used by the company today. Besides, the frequency of purchasing raw materials using the EOQ method is smaller than using the company's method. In addition, there are also safety stocks, reorder points and MI (Maximum Inventory) that have been calculated, so that they can anticipate excess or shortage of raw material supplies. Therefore the EOQ method is very important to be applied in companies in order to achieve more optimal company profits.

Analysis of Supply Quantity Control of Argon Gas Raw Material At PT XY

The background in this research is that there is no method used to manage and control the quantity of raw material supplies at PT XY. This situation causes problems in ordering raw materials so that ordering costs and costs for storage will not be optimal. The purpose of this study was to determine the effect of applying the EOQ method to the total cost of raw material inventory at PT. XY. Raw material inventory costs can be minimized by applying the EOQ (Economic Order Quantity) method. This method can show the economic order quantity, optimal purchase frequency, time to reorder/ROP (Re-Order Point), and the amount of safety stock. Data collection was carried out using documentation techniques related to observation inventory documents and interviews with several informants, for data analysis using EOQ by calculating total inventory cost, ROP, reorder frequency and safety stock. The results of calculations and data analysis using the EOQ method show that the total cost of inventory is lower than the company's actual method.

Smart food grain storage system using Internet of Things (IoT): A Review

India is one of the largest producers of food grains in the world. The country has a diverse agricultural sector that produces a wide range of crops, including rice, wheat, maize, pulses (such as lentils and chickpeas), and oilseeds. Rice and wheat are considered essential for ensuring food security in India. India has an extensive network of food grain storage infrastructure to cater to its significant agricultural production. The storage infrastructure in India is primarily managed by the Food Corporation of India (FCI), state government agencies, and private sector entities. Some of food grain storage infrastructure in India are warehouses, covered storage structures (silos), mandi storage facilities (temporarily store grains) and strategic reserve (buffer stock for food security). Private sector entities are increasingly investing in the modern storage facilities including temperature-controlled warehouses and automated storage systems, to improve storage capacity and reduce post-harvest losses. India faces challenges in effectively managing and maintaining the quality of stored food grains. Issues such as inadequate storage capacity, insufficient maintenance, lack of proper pest control measures, and logistical constraints contribute to post-harvest losses. The government and other stakeholders are continuously working on improving storage infrastructure and implementing technological solutions to address these challenges that tiggers for spoilage, mold growth, insect infestation and excessive drying. The real time monitoring and controlling of these factor during the storage period is a cumbersome task and needs advanced techniques. In this aspect Internet of Things (IoT) offers numerous benefits to food grain storage systems including real-time monitoring, early warning systems, optimal environmental conditioning, energy efficiency, inventory management, traceability and predictive analytics. By leveraging IoT technology, the industry can improve storage practices, reduce losses, ensure food safety, and enhance the overall efficiency of grain storage operations.

B-297 Effortless and Streamlined Workflow for Absolute Quantitation of Therapeutic Monoclonal Antibodies Using Promise Proteomics mAbXmise Kits and TSQ Altis Plus Mass Spectrometer

Abstract Background Laboratories continuously seek improved productivity and efficacy for clinical testing, ultimately impacting the turn-around time and sample throughput. Various efforts have been made including rapid and high-throughput testing, automation, and high-end instrumentation. This also applies to therapeutic drug monitoring (TDM) of therapeutic monoclonal antibodies (mAbs). In particular, mass spectrometry (MS) has gained significant popularity in clinical laboratories for TDM of mAbs due to its great versatility to measure such complex biological proteins qualitatively and quantitatively. Here we present the streamlined workflow for the absolute quantitation of therapeutic mAbs using the Promise Proteomics mAbXmise kits and the Thermo Scientific™ TSQ Altis™ Plus mass spectrometer. The mAbXmise kit is the first commercial ready-to-use kit that offers all the necessary reagents for the LC-MS/MS assay including the stable-isotope labeled (SIL) proteins of the target mAbs (SIL-mAbs). The TSQ Altis™ Plus mass spectrometer is the latest generation of the TSQ MS series, offering superior acquisition speeds, sensitivity, selectivity, and robustness for routine and high-volume targeted protein quantitation. Methods The experimental workflow followed the instructions provided by Promise Proteomics with minor modifications (refer to instructions manual—https://customer.mabxmise.com). The kits used in this study include pre-coated plates with a full-length SIL-mAb corresponding to each target mAb sequence as internal standards with purity >95% and isotopic corporation >98%. Thus, the ITDM1 kit contains 2 SIL-mAbs and the OTDM1 kit contains 7 SIL-mAbs pre-coated in each plate. The kits also provide buffer stocks, reagents, 6 calibration standards including zero, and 2 QC controls. Each kit provides 12 strips capable of 96 sample preparation. The calibrators and QC samples were added to the mAbXmise plate and subjected to immunocapture followed by trypsin digestion. LC-MS/MS was performed using a Thermo Scientific™ Vanquish™ Flex UHPLC system hyphenated to TSQ Altis™ Plus mass spectrometer. Results Highly comparable results were observed across six replicates for both OTDM1 and ITDM1 kits with R2 values >0.99 and % RSD of peak areas of peptides <15. After confirming the complete sample preparation of 96 samples, an evaluation of LC-MS analytical performance was performed. The results show great linearity with R2 > 0.998 over measured calibration concentration points for all the OTDM1 and ITDM1 target peptides, respectively. Also, the data support the reproducible LC-MS measurement of the entire plate providing % RSD <10. The accuracy of QC samples was determined to be between 94 and 103% for OTDM1 peptides with a precision of <7% CV and between 95 and 107 % for ITDM peptides with a precision of <9% CV. The response of CAL1 (LLOQ) was 5 times higher than CAL0 for all the target peptides with accuracy between 96 and 112% and precision of <11% CV. Additionally, extremely reproducible retention times were observed from all SIL-mAb peptides with RT difference ±0.03 min during the evaluation. Conclusion The workflow tested in this report generated sensitive and robust data with high confidence, emphasizing the capability of MS-based TDM of mAbs as routine testing.

Text-Based Measure of Supply Chain Risk Exposure

Using textual analysis techniques, including seeded word embedding and bag-of-words-based content analysis, I develop a firm-level measure of supply chain risk exposure from a novel source of unstructured data—the discussion between managers and equity analysts on supply chain-related topics during firms’ quarterly earnings conference calls. I validate the measure by showing that (1) the measure exhibits intuitive variations over time and across firms, successfully capturing both routine and systematic supply chain risk events; and (2) the measure is about risk exposure, as it significantly correlates with realized and options-implied stock return volatility, even after controlling for well-known aggregate risk measures. I then demonstrate that the measure is specifically indicative of the supply chain component of risk exposure. (3) Consistent with theoretical predictions, firms facing higher supply chain risks have higher inventory buffers, particularly in raw materials and intermediate inputs, increased cash holdings in lieu of investments, and significantly lower trade credit received from suppliers. Moreover, (4) during unexpected risk episodes, such as the Tohoku earthquake, firms with higher ex ante risk exposure have worse operating and financial performance. These results indicate that the text-based measure provides a credible quantification of firm-level exposure to supply chain risks and can thus be reliably utilized as outcome or explanatory variables in empirical supply chain research. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4927 .