Santiago Gallino

Santiago Gallino
  • Assistant Professor of Operations, Information and Decisions

Contact Information

  • office Address:

    3730 Walnut Street
    547 Jon M. Huntsman Hall
    Philadelphia, PA 19104

Research Interests: Empirical Operations Management, Retail Management

Overview

Santiago Gallino is an Assistant Professor at the OID Departament. He is interested in operations management challenges in the retail industry. Santiago studies both omni-channel integration and store execution issues in retail. In his research, he uses field data and econometric tools to study existing operational practices as well as potential operational improvements.

Before joining Wharton, Santiago worked at the Tuck School of Business at Dartmouth.

Santiago holds a PhD in Operations and Information Management and a Master’s in Statistics from the University of Pennsylvania where he was a Fulbright Scholar, an MBA from IAE Business School, and a degree in Electrical Engineering from Universidad de Buenos Aires.

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Research

  • Dawson Kaaua, Santiago Gallino, Christian Terwiesch, S Mehta (Working), The Impact of Waiting Location on Customer Satisfaction: An Empirical Analysis of Preoperative Patient Flow.

  • Santiago Gallino and Dawson Kaaua (Work In Progress), How May I Help You? Inferring Service Quality from a Server’s Personal Details.

  • David Bell, Santiago Gallino, Antonio (Toni) Moreno-Garcia (Forthcoming), Customer Supercharging in Experience-Centric Channels.

    Abstract: We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and test our thesis using data from a digital-first men’s apparel retailer and a pioneer of the so-called “Zero Inventory Store” (ZIS) format—a small footprint, experience- centric retail location which carries no inventory for immediate fulfillment, but fulfils orders via e-commerce. Using a risk-set matching approach, we calibrate our estimates on customers who are “treated”, i.e., have a ZIS experience, and matched with identical customers who shop online only. We find that post the ZIS experience, customers spend more, shop at a higher velocity, and are less likely to return items. The positive impact on returns is doubly virtuous as it is more pronounced for more tactile, higher-priced items, thus mitigating a key pain point of online retail. Furthermore, the ZIS shopping experience aids product discovery and brand attachment, causing sales to become more diffuse over a larger number of categories. Finally, we demonstrate that our results are robust to self-selection and potentially confounding effects of unobservable factors on the matched pairs of customers. Implications for retailing practice, including for legacy, offline-first retailers, are discussed.

  • Marshall L. Fisher, Santiago Gallino, Jiaqi (Joseph) Xu (2019), The Value of Rapid Delivery in Omnichannel Retailing, Journal of Marketing Research.

    Abstract: The authors study how faster delivery in the online channel affects sales within and across channels in omnichannel retailing. The authors leverage a quasi-experiment involving the opening of a new distribution center by a U.S. apparel retailer, which resulted in unannounced faster deliveries to western states through its online channel. Using a difference-in-differences approach, the authors show that online store sales increased on average by 1.45% per business day reduction in delivery time, from a baseline of seven business days. The authors also find a positive spillover effect to the retailer’s offline stores. These effects increase gradually in the short to medium term as the result of higher order count. The authors identify two main drivers of the observed effect: customer learning through service interactions with the retailer, and existing brand presence in terms of online store penetration rate and offline store presence. Customers with less online store experience are more responsive to faster deliveries in the short term, while experienced online store customers are more responsive in the long term.

  • Bob Batt and Santiago Gallino (2019), Finding a Needle in a Haystack: The Effects of Searching and Learning on Pick-worker Performance, Management Science.

    Abstract: The rise in online and multichannel retailing has pushed retailers to give increased attention to their order fulfillment operations. We study "chaotic storage" fulfillment systems in which dissimilar items are stored together in a single location. This necessitates a searching task as part of the picking process, which has not been previously studied. We show that pick times increase by as much as 16% as the searching task becomes more difficult. However, the deleterious effect of searching decreases with pick worker experience. Using simulation, we show that pick times can be improved by incorporating distance, bin density, and picker experience into pick assignments and pick routing. Through properly combining the details of the task and the workers, order fulfillment productivity can be increased by approximately 5%.

  • Santiago Gallino, Nil Karacaoglu, Antonio (Toni) Moreno-Garcia (Under Review), Why Retailers Should Care about Net Neutrality: The Impact of Website Performance on Online Retail.

    Abstract: The share of e-commerce sales is rapidly increasing and so are the associated losses generated by website outages and slow websites. We leverage novel retail and website performance data to investigate the impact of website performance on online sales. This question is especially relevant in the current regulatory environment, given the ongoing policy debates around net-neutrality. Using two different research designs---panel data with fixed effects and generalized synthetic control with elastic net---we estimate sizable adverse effects of website speed slowdowns on online sales, especially in the mobile channel. Our results show that decreases in website performance make customers less likely to place an order and undermine retailers' quest to turn website traffic into sales. The findings have important implications for the net neutrality debate and retailers' website design decisions, specifically the selection of third-party content providers and the customized design of mobile and desktop channels.

  • Gérard Cachon, Santiago Gallino, Jiaqi (Joseph) Xu, Free Shipping Is Not Free: A Data-Driven Model to Design Free-Shipping Threshold Policies.

    Abstract: Online retailers often offer free shipping threshold policies: customers who purchase more than a threshold amount are not charged an additional fee for shipping. This paper provides a data-driven analytical model to (i) assess the profitability of a retailer’s current shipping threshold policy and (ii) identify the best freeshipping threshold policy for a retailer. The model is estimated from actual transaction and product return data. The model explicitly accounts for changes in customer shopping behavior due to a free shipping threshold, including strategically adding items to a shopping basket to receive free shipping, which we call orderpadding, and the subsequent adjustment in product return decisions. Roughly speaking, according to our model, a retailer that offers a free shipping threshold policy should set the threshold slightly abovethe average shopping basket amount. We calibrate our model to data from an online apparel retailer and determine that its decision to offer a lower free shipping threshold reduced its profitability considerably.This result is robust to a number of assumptions regarding the impact on long-run sales and possible price adjustments. We conclude that free shipping threshold policies are profitable only under a limited set of restrictive conditions.

  • Marshall L. Fisher, Santiago Gallino, Serguei Netessine, Does Online Training Work in Retail?.

    Abstract: A knowledgeable retail sales associate (SA) can explain the features of available product variants and give the customer sufficient confidence in her choice or suggest alternatives so that she becomes willing to purchase. Although it is plausible that increasing an SA’s product knowledge will increase sales, training is not costless and turnover is high in retail, so most retailers provide little or no training. Thus, an important question is how much, if at all, does training increase an SA’s sales productivity? To answer this question, we partnered with Experticity, a firm that provides online, self-guided training modules for retail SAs, and Dillard’s, a leading department store chain whose more than 50,000 SAs had access to the Experticity modules. We assembled a data set of the training history and sales productivity of Dillard’s associates over a two-year period. We found that as SAs engaged in training over time, their sales rate increased by 1.8 percent for every online module taken, which is a much higher benefit than the direct or indirect costs associated with this training. We also found that willingness to engage in voluntary training was an indicator of raw talent; those SAs who engaged in training were 20 percent more productive prior to any training and 46 percent more productive after training than those who took no training. Surprisingly, brand-specific training did not significantly affect the sales of the focal brand but did improve overall sales of all brands. Our evidence of successful online learning may be of general interest given that, to date, analysis of massive open online courses has shown poor engagement by participants and questionable outcomes.

  • Marshall L. Fisher, Santiago Gallino, Serguei Netessine, Setting Retail Staffing Levels: A Methodology Validated with Implementation.

    Abstract: We describe a three-step process that a retailer can use to set retail store sales staff levels. First, use historical data on revenue and planned and actual staffing levels by store to estimate how revenue varies with the staffing level at each store. We disentangle the endogeneity between revenue and staffing levels by focusing on randomly occurring deviations between planned and actual labor. Second, using historical analysis as a guide, we validate these results by changing the staffing levels in a few test stores. Finally, we implement the results chain-wide and measure the impact. We describe the successful deployment of this process with a large specialty retailer. We find that 1) the implementation validates predictions of the historical analysis, including the use of the variation between planned staffing and actual staffing as an exogenous shock, 2) implementation in 168 stores over a 6-month period produces a 4.5% revenue increase and a nearly $7.4 million annual profit increase, after accounting for the cost of the additional labor, and 3) the impact of staffing level on revenue varies greatly by store, and therefore staffing levels should also vary, with more sales staff relative to revenue assigned to those stores where sales staff have the greatest impact on revenue. Specifically, we found the largest impact of store labor in stores with the largest average basket sizes, located in regions with good growth potential, facing certain competitors (e.g., Wal-Mart), and run by long-serving managers.

  • Gérard Cachon, Santiago Gallino, Marcelo Olivares (2018), Does Adding Inventory Increase Sales? Evidence of a Scarcity Effect in U.S. Automobile Dealerships, Management Science.

    Abstract: What is the relationship between inventory and sales? Clearly, inventory could increase sales: expanding inventory creates more choice (options, colors, etc.) and might signal a popular/desirable product. Or, inventory might encourage a consumer to continue her search (e.g., on the theory that she can return if nothing better is found), thereby decreasing sales (a scarcity effect). We seek to identify these effects in U.S. automobile sales. Our primary research challenge is the endogenous relationship between inventory and sales — e.g., dealers influence their inventory in anticipation of demand. Hence, our estimation strategy relies on weather shocks at upstream production facilities to create exogenous variation in downstream dealership inventory. We find that the impact of adding a vehicle of a particular model to a dealer’s lot depends on which cars the dealer already has. If the added vehicle expands the available set of sub-models (e.g., adding a four-door among a set that is exclusively two-door), then sales increase. But if the added vehicle is of the same sub-model as an existing vehicle, then sales actually decrease. Hence, expanding variety across sub-models should be the first priority when adding inventory—adding inventory within a sub-model is actually detrimental. In fact, given how vehicles were allocated to dealerships in practice, we find that adding inventory actually lowered sales. However, our data indicate that there could be a substantial benefit from the implementation of a “maximizes variety, minimize duplication” allocation strategy: sales increase by 4.4 percent without changing the number of vehicles at each dealership, and a 5.2 percent is possible if inventory is allowed to decrease by 2.8 percent (and no more than 10 percent at any one dealer).

Teaching

OIDD101 – INTRODUCTION TO OIDD

OIDD 101 explores a variety of common quantitative modeling problems that arise frequently in business settings, and discusses how they can be formally modeled and solved with a combination of business insight and computer-based tools. The key topics covered include capacity management, service operations, inventory control, structured decision making, constrained optimization and simulation. This course teaches how to model complex business situations and how to master tools to improve business performance. The goal is to provide a set of foundational skills useful for future coursework atWharton as well as providing an overview of problems and techniques that characterize disciplines that comprise Operations and Information Management.

Past Courses

  • OIDD101 - INTRODUCTION TO OIDD

    OIDD 101 explores a variety of common quantitative modeling problems that arise frequently in business settings, and discusses how they can be formally modeled and solved with a combination of business insight and computer-based tools. The key topics covered include capacity management, service operations, inventory control, structured decision making, constrained optimization and simulation. This course teaches how to model complex business situations and how to master tools to improve business performance. The goal is to provide a set of foundational skills useful for future coursework atWharton as well as providing an overview of problems and techniques that characterize disciplines that comprise Operations and Information Management.

Activity

Latest Research

Dawson Kaaua, Santiago Gallino, Christian Terwiesch, S Mehta (Working), The Impact of Waiting Location on Customer Satisfaction: An Empirical Analysis of Preoperative Patient Flow.
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In the News

Can the ‘Supercharged’ Consumer Save Retail?

Digital retailers can reap significant financial benefits from opening physical stores, according to new research from Wharton and Harvard.

Knowledge @ Wharton - 2019/09/5
All News