Nikolay Osadchiy is an Associate Professor of Information Systems & Operations Management at Emory University's Goizueta Business School. His research interests are in supply chain management, where he studies productivity, risk, and resiliency in supply networks, and in revenue management where he studies the impact of behavioral regularities on pricing. He has published in the leading academic journals including Management Science, Operations Research, Manufacturing and Service Operations Management, and Production and Operations Management. He serves as a Senior Editor at Production and Operations Management. Nikolay's practice-focused work has been published in Harvard Business Review and MIT Sloan Management Review. He regularly contributes to the media commenting on the current issues and developments in supply chains.
Nikolay has taught Supply Chain Management and Process and Systems Management courses in the BBA, MBA, and Professional MBA programs, Supply Chain Analytics in the MSBA program, and an Operations Management seminar in the PhD program. He holds a PhD in Operations Management from the New York University Stern School of Business.
Education
New York University Leonard N. Stern School of Business
PhD
Operations Management
2010
New York University Leonard N. Stern School of Business
MPhil
Operations Management
2008
Areas of Expertise
Supply Networks
Supply Chain Management
Risk and Resilience
Empirical Methods in Operations Management
Operations-Finance Interface
Revenue Management
Publications
Trade Credit and Customer Portfolio Approach to Managing Cash Flow Variability
Manufacturing and Service Operations Management
2025-05-20
Cash flow variability is driven by operational decisions and influences operating performance and valuation. Despite this and the early role that operations management scholarship had on cash flow management theory, the prevailing approaches for managing cash flow variability focus on financial remedies. Our research extends this set of remedies by proposing customer portfolio management and selective trade credit as operational hedges for reducing cash flow variability. We empirically validate our proposal by studying a causal relationship between new customer acquisitions and cash-flow variability using a large database of customer-supplier relationships that we join with quarterly financial reports. We strengthen the inferences from this analysis by assembling random samples of customers for each firm in our study and show that the firms’ actual customer portfolios yield lower cash variability compared with the counterfactual sets of randomly sampled customers. Using aggregate and link-level trade credit data, we show that trade credit harmonization is associated with reduced cash flow variability. Our analysis shows that firms can reduce their cash variability by (i) pursuing customers with desirable order patterns that offset the cash flow variability from serving legacy customers and (ii) selectively offering customers trade credit that harmonizes payment terms in the customer portfolio.
Outsourcing as a Risk Management Mechanism for Domestic Manufacturing Capacity Investment
Foundations and Trends® in Technology, Information and Operations Management:
2024-08-01
We propose two perspectives on the shift from U.S. domestic manufacturing to Asia in 1990–2011: production cost arbitrage and the management of supply-demand mismatch. In our model, a firm facing demand uncertainty decides between investing in domestic or overseas production capacity. The model predicts greater investment overseas when the cost arbitrage is high, switching cost is low, demand volatility is high, and the systematic risk in demand is above a certain threshold. Empirically, we observe strong support for the cost arbitrage motive in 1990–2000 and the risk management motive in 2001–2011, i.e., after China’s entry into the WTO. We estimate that investing into risk mitigation could have saved more than 400,000 U.S. manufacturing jobs.
Inventory Productivity and Stock Returns in Manufacturing Networks
Manufacturing and Service Operations Management
2023
We provide a novel, supply network-based perspective on inventory productivity and incentives for its improvement. Using data from 2003 to 2019, we find that inventory productivity is lower materially and statistically for firms located upstream in the supply network, and higher for high degree and more central firms. Firms with high inventory productivity show high equity valuations and abnormal returns, with both valuations and abnormal returns amplified for upstream, low degree, and peripheral firms. Moreover, the difference in valuations and abnormal returns between best and worst performing firms is greater upstream, suggesting that financial markets offer outsized rewards for improving inventory productivity to upstream firms. We show that the information about firm’s upstreamness and centrality in the supply network is a valuable predictor of its inventory productivity and financial performance. Our methods for evaluating upstreamness are useful for that purpose. For operations managers and firm executives, our results highlight strong incentives for inventory productivity improvement upstream in the supply network. For investors, we show that supply network position data can sharpen inventory-based arbitrage opportunities.
Sourcing for online marketplaces with demand and price uncertainty
Production and Operations Management
2023
Our paper is motivated by a manufacturer that sells a seasonal product through multiple retailers competing on an online marketplace, such as the Amazon marketplace. Demand and selling price uncertainty are key features of the online marketplace. Sourcing choices are differentiated by cost and available lead times—delaying shortens the lead time which is more expensive but yields more accurate information about future selling price and demand. Thus, ahead of the season, each retailer faces a continuous-time decision problem about when to place an order with the manufacturer and in what quantity. The manufacturer is interested in knowing the ordering pattern of the retailers in order to plan production. We consider two sourcing strategies varying in the flexibility of order timing: an optimal precommitted ordering time strategy and an optimal time-flexible ordering strategy. We prove that the former is optimal when the selling price is constant and the latter when the selling price is uncertain. We show that time-flexible ordering can be mutually beneficial for the retailer and the manufacturer in a wide range of scenarios and that the manufacturer can favorably influence order timing by adjusting its wholesale price trajectory. The predictions of our model are consistent with the experience of a large U.S. manufacturer that motivated our study.
Supply chain disruptions in the last decade have generated lots of recommendations for companies to map their supply chains, identify sources of the most costly risks, and then take steps to mitigate them. But a study of industries’ supply chains for semiconductors reveals that doing so is enormously challenging. The study found that these networks are vast, dense, and dynamic.
“The costs of demand variability can put you out of business.” That blunt assessment, recently offered to us by the director of sales and operations planning at a Fortune 500 company, reflects what managers already know: Peaks in demand can drive high overtime costs, stockouts, and lost sales, while slowdowns leave capacity idle and increase excess inventory. The impact on customer service levels — not to mention the bottom line — can be significant. But how can companies best manage this variability, especially when deciding which potential new customers to target?
We offer a new network perspective on one of the central topics in operations management—the bullwhip effect (BWE). The topic has both practical and scholarly implications. We start with an observation: the variability of orders placed to suppliers is larger than the variability of sales to customers for most firms, yet the aggregate demand variability felt by suppliers upstream does not amplify commensurably. We hypothesize that changes to the supplier’s customer base can smooth out its aggregate demand. We test the hypothesis with a data set that tracks the evolution of supply relationships over time. We show that the effect of customer base management extends beyond the statistical benefits of aggregation. In particular, both the formation and the dissolution of customer-supplier relationships are associated with the smoothing of the aggregate demand experienced by suppliers. This provides fresh insight into how firms may leverage their customer-supplier relationships to mitigate the impact of the BWE.
This chapter reviews historical and contemporary research in economics, operations management, and finance that adopts a network perspective for modeling interactions between agents. It argues that incorporating extended network characteristics in the analysis can yield unique insights compared to the analysis done at the level of dyads or local neighborhoods. The chapter explains how new network-based models contribute to the academic debate and advance our understanding of supply network drivers of performance and risk. This includes a discussion on the structural configuration of a firm’s interconnected portfolio of upstream supplier and downstream customer relationships and its role in influencing financial and operational performance as well as its innovation.
Systematic Risk in Supply Chain Networks
Management Science
2016
Industrial production output is generally correlated with the state of the economy. Nonetheless, during times of economic downturn, some industries take the biggest hit, whereas at times of economic boom they reap most benefits. To provide insight into this phenomenon, we map supply networks of industries and firms and investigate how the supply network structure mediates the effect of economy on industry or firm sales...
Behavioral Anomalies in Consumer Wait-or-Buy Decisions and Their Implications for Markdown Management
Operations Research
2016
A decision to buy an item at a regular price or wait for a possible markdown involves a multi-dimensional trade-off between the value of the item, the delay in getting it, the likelihood of getting it and the magnitude of the price discount. Such trade-offs are prone to behavioral anomalies by which human decision makers deviate from the discounted expected utility model.
Are Patients Patient? The Role of Time to Appointment in Patient Flow
Production and Operations Management
2016
The current state of outpatient healthcare delivery is characterized by capacity shortages and long waits for appointments. Yet a substantial fraction of valuable doctors’ capacity is wasted due to no-shows. In this paper, we examine the effect of wait to appointment on patient flow, specifically on a patient’s decision to schedule an appointment, and subsequently arrive to it. These two decisions may be dependent, because appointments are more likely to be scheduled by patients who are more patient and are thereby more likely to show-up. To estimate the effect of wait on these two decisions, we introduce the willingness to wait (WTW), an unobservable variable that affects both bookings and arrivals for appointments. Using data from a large healthcare system, we estimate WTW with a state of the art non-parametric method. The WTW in turn allows us to estimate the effect of wait on no-shows. We observe that the effect of increased wait on the likelihood of no-show is disproportionately greater among patients with low WTW. Thus, although reducing the wait to appointment will enable a provider to capture more patient bookings, the effects of wait time on capacity utilization can be non-monotone. Contrary to the previously reported findings, our results suggest that increasing wait can sometimes be beneficial for reducing no-shows.
Sales forecasting with financial indicators and experts' input
Production and Operations Management
2013
We present a method for forecasting sales using financial market information and test this method on annual data for US public retailers. Our method is motivated by the permanent income hypothesis in economics, which states that the amount of consumer spending and the mix of spending between discretionary and necessity items depend on the returns achieved on equity portfolios held by consumers.
Selling with binding reservations in the presence of strategic consumers
Management Science
2010
We analyze a revenue management problem in which a seller endowed with an initial inventory operates a selling with binding reservations scheme. Upon arrival, each consumer, trying to maximize his own utility, must decide either to buy at the full price and get the item immediately or to place a nonwithdrawable reservation at a discount price and wait until the end of the sales season where the leftover units are allocated according to first-come-first-serve priority...
Upstream or downstream thinking? What’s the best way for suppliers to go mainstream and reach the most customers?
You might have heard of the beer distribution game.
The idea is that a group of participants enact a four-stage supply chain scenario. Some take on the role of those at the point of origin in the supply chain – the upstream agents: manufacturers and distributors. Others role-play the downstream agents at the other end of the chain – the distributors and end-customers: in this case, let’s say the bar owners and beer drinkers. The goal is simple. All you have to do is produce, deliver and sell the beer to your customers, while keeping your costs on back orders and inventory to a minimum.
This should be easy enough, in theory. The basic rules of economics suggest that customer demand dictates supply. In practice, however, things can get a little skewed. And this disconnect can happen fast.
For a start, players have limited information. They can only see what’s in front of them – bits of paper with order numbers. And as they start to share this information with each other, all kinds of coordination issues arise. Things start to go wrong. Customer demand for X or Y kegs of beer is imperfectly relayed to the bar owner retailer, who in turn passes it on the other players upstream, but makes mistakes in doing so. The result is a kind of Chinese Whispers where confusion reigns, poor decisions are made about stock, too much or too little beer is manufactured or supplied. You end up with increased costs in the supply chain, and, not to mention thirsty beer drinkers.
The beer game is just that – a game. But it represents a problem that is all too familiar to suppliers in most industries and sectors. It’s called the Bullwhip effect, and it’s a conundrum.
“The Bullwhip effect is a real challenge for suppliers in every industry,” said Nikolay Osadchiy, associate professor of Information Systems & Operations Management at Goizueta Business School. “Because demand information gets distorted along the chain, suppliers can see a lot of volatility at their end which can translate into more inventory and drives up costs. It’s a really pressing issue that needs to be addressed.” Osadchiy and his colleagues Bill Schmidt from Cornell University and Jing Wu from the Chinese University of Hong Kong got to work researching the idea.
First, they modeled a supply network based on 15 years of data from publicly traded companies across the globe. Second, they determined the ‘upstreamness’ that different firms had – or the positions they occupy – within that network. And third, they examined the demand distortion within each firm and measured demand variability across the different layers of the network to determine how they affect each other. The results of their work were all captured in the article attached below – the information was quite compelling and will greatly assist businesses as they plan their way through and after a globe-shifting event like COVID-19.
It’s interesting material for sure – and if you are a journalist looking to know more about supply chains and how businesses will need to adapt in order to survive post-pandemic, then let our experts help with your questions and coverage.
Nikolay Osadchiy is an Associate Professor of Information Systems & Operations Management at Emory University's Goizueta Business School. He is an acclaimed expert in the areas of supply chain management and how supply networks affect risk and operational performance. Nikolay is available to speak with media regarding this topic – simply click on his icon to arrange an interview today.
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1 min
Forecasting sales using financial stock market data
Firms use many kinds of data for forecasting future sales—one of the key activities in the management of a business—and combine various methods in order to utilize different types of information. A recent study by Nikolay Osadchiy, assistant professor of information systems and operations management; Vishal Gaur (Cornell); and Sridhar Seshadri (UT Austin) focuses on financial stock market data in developing a new methodology for firm-level sales forecasting, testing it against standard benchmarks such as forecasts from equity analysts and time-series methods. Applying their method to the forecast of total annual sales for US public retail firms, the researchers find their market-based approach achieves an average 15 percent reduction in forecasting error compared with more typical forecasting methods. Their model, they write, can also be applied to hedging operational risk with financial instruments.
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1 min
Markdown Management and Shopping Behavior
Consumers face the trade-off of immediately paying tag price for an item or waiting for a time when it might be marked down but out of stock. In new research, Nikolay Osadchiy, assistant professor of information systems & operations management, Manel Baucells (U of Virginia), and Anton Ovchinnikov (Queen’s U) argue that retailers can better optimize markdowns by paying more attention to this particular type of consumer behavior. The researchers approach the consumer waitor-buy decision as a “multidimensional trade-off between the delay in getting an item, the likelihood of getting it, and the magnitude of the price discount.” Those dimensions need not be independent; for example, the consumer patience (or sensitivity to delay) could depend on the magnitude of markdown. By optimizing the model, they find that retailers can substantially increase revenues by offering larger markdowns than the current state of the art suggests. In the experiments involving business school students as well as Amazon Mturk participants, which is an on-demand, scalable workforce, the trio found that the expected revenue gains are between 1.5% and 2%.
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In the News
Georgia warehouses say they see the impact on tariffs, so could it trickle down to consumers?
WSBTV tv
2025-05-08
US ports are also feeling the effect.
“The number of docks at the ports of LA declined roughly 40%. And we expect to see a similar decline in East Coast ports in the coming weeks,” Emory Professor Nikolay Osadchiy said.
Osadchiy said the tariffs have reduced demand to bring in new products and led to some ships canceling trips or skipping ports.
McDonald’s and GM Boast Positive Q4 Earnings to End 2022 on a High Note
MarketScale online
2023-02-07
Financial markets have been doing well recently, and there are several factors explaining that in my opinion. First, supply chain pressures are easing and trade flows are starting to normalize, so that’s definitely great news, and markets typically react well to supply chains working smoothly.
A sign of the economic times: Ships lined up at Savannah port
The Atlanta Journal-Constitution online
2021-09-29
“We used to have an efficient system where everything on the supply chain was synchronized,” said Nikolay Osadchiy, an associate professor who teaches supply chain management at Emory’s Goizueta Business School. “Right now, it’s not predictable at all.”
Research from Nikolay Osadchiy, assistant professor of information systems and operations management at Goizueta Business School, highlights how the decision to purchase an item at regular price or wait for a possible markdown involves a multi-step mental process and that this process is predictable.
Emory Professor Nikolay Osadchiy on Science Behind Retail Markdowns
The Dana Barrett Show (WAFS) (Wall Street Business Network) radio
2016-07-14
During the first hour, we were joined by Nikolay Osadchiy, Assistant Professor at the Department of Information Systems and Operations Management of the Emory University Goizueta Business School. Professor Osadchiy explained the science behind retail markdowns and discussed consumer behavior.
For example, faculty can leverage social media tools like Twitter, Google Docs, and public blogs to extend classroom discussion beyond physical walls. Nikolay Osadchiy, assistant professor of information systems and operations management, has launched just such a blog, providing an online forum for students to share opinions on current business news.
"I have a two-fold approach to the use of technology in teaching," he explains. "The first part focuses on enhancing in-class learning. For example, I post spreadsheets for systems simulation and forecasting online before class so students can follow along on their laptops during class discussion. The second part, learning reinforcement, involves things like uploading video recordings that go over complicated concepts we've discussed in class. Students find them very helpful."...
