Nikolay Osadchiy

Associate Professor of Information Systems & Operations Management Emory University, Goizueta Business School

  • Atlanta GA

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Biography

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

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.

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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.

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The Right Way to Mix and Match Your Customers

MIT Sloan Management Review

2021

“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?

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Research Spotlight

3 min

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.

Nikolay Osadchiy

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. Source:

Nikolay Osadchiy

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%. Source:

Nikolay Osadchiy
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In the News

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.

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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.”

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Customer Focused Retail Strategy

IEDP Developing Leaders  online

2016-07-28

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.

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