Smart Pricing: Linking Pricing Decisions with Operational Insights

The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field.supply chain management;inventory;capacity;dynamic pricing;operations-marketing interface

Smart Pricing: Linking Pricing Decisions with Operational Insights

The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field

Inventory Model with Seasonal Demand: A Specific Application to Haute Couture

In the stochastic multiperiod inventory problem, a vast majority of the literature deals with demand volume uncertainty. Other dimensions of uncertainty have generally been overlooked. In this paper, we develop a newsboy formulation for the aggregate multiperiod inventory problem intended for products of short sales season and without replenishments. A distinguishing characteristic of our formulation is that it takes a time dimension of demand uncertainty into account. The proposed model is particularly suitable for applications in haute couture, i.e., high fashion industry. The model determines the time of switching primary sales effort from one season to the next as well as optimal order quantity for each season with the objective of maximizing expected profit over the planning horizon. We also derive the optimality conditions for the time of switching primary sales effort and order quantity. Furthermore, we show that if time uncertainty and volume uncertainty are independent, order quantity becomes the main decision over the interval of the primary selling season. Finally, we demonstrate that the results from the two-season case can be directly extended to the multi-season case and the limited resource multiple-item case

Markdown Budgets for Retail Buyers: Help or Hindrance?

For many retailers, markdown decisions are taken by retail buyers whose compensation is based on sales revenue so their objective is to maximize it through the season. This implies that the buyers' objectives are not perfectly aligned with the overall profitability the firm. Many retailers set markdown budgets prior to the season to control margin erosion and increase profitability. Markdown budget constrains the buyers on the amount of discounts that they can apply on a given inventory of merchandise and sets a limit on the dollar value of markdowns for the season. While markdown budgets may be useful in preventing excessive discounts, they can have a detrimental effect on the buyers' ability to respond to poor market and remove distressed inventory. We investigate the effectiveness of this practice in aligning the incentives of buyers with that of the firm, and provide guidance on how these budgets should be established ahead of time. We consider a firm with a fixed inventory of a seasonable item, and a single chance to mark the price down. The retailer knows only the demand distribution at the beginning of the season, but the market information is revealed during the season to the buyer. We first characterize the buyer's markdown policy and understand the circumstances under which this can be different from the retailer's markdown policy. We use our model to determine the optimal markdown budget and quantify its effectiveness considering different factors such as the level of demand uncertainty, initial markup, and market's responsiveness to markdowns. © 2017 Production and Operations Management Societ

Implementation of the Newsvendor Model with Clearance Pricing: How to (and How Not to) Estimate a Salvage Value

The newsvendor model is designed to decide how much of a product to order when the product is to be sold over a short selling season with stochastic demand and there are no additional opportunities to replenish inventory. There are many practical situations that reasonably conform to those assumptions, but the traditional newsvendor model also assumes a fixed salvage value: all inventory left over at the end of the season is sold off at a fixed per-unit price. The fixed salvage value assumption is questionable when a clearance price is rationally chosen in response to the events observed during the selling season: a deep discount should be taken if there is plenty of inventory remaining at the end of the season, whereas a shallow discount is appropriate for a product with higher than expected demand. This paper solves for the optimal order quantity in the newsvendor model, assuming rational clearance pricing. We then study the performance of the traditional newsvendor model. The key to effective implementation of the traditional newsvendor model is choosing an appropriate fixed salvage value. (We show that an optimal order quantity cannot be generally achieved by merely enhancing the traditional newsvendor model to include a nonlinear salvage value function.) We demonstrate that several intuitive methods for estimating the salvage value can lead to an excessively large order quantity and a substantial profit loss. Even though the traditional model can result in poor performance, the model seems as if it is working correctly: the order quantity chosen is optimal given the salvage value inputted to the model, and the observed salvage value given the chosen order quantity equals the inputted one. We discuss how to estimate a salvage value that leads the traditional newsvendor model to the optimal or near-optimal order quantity. Our results highlight the importance of understanding how a model can interact with its own inputs: when inputs to a model are influenced by the decisions of the model, care is needed to appreciate how that interaction influences the decisions recommended by the model and how the model’s inputs should be estimated

Solving Practical Dynamic Pricing Problems with Limited Demand Information

Dynamic pricing problems have received considerable attention in the operations management literature in the last two decades. Most of the work has focused on structural results and managerial insights using stylized models without considering business rules and issues commonly encountered in practice. While these models do provide general, high-level guidelines for managers in practice, they may not be able to generate satisfactory solutions to practical problems in which business norms and constraints have to be incorporated. In addition, most of the existing models assume full knowledge about the underlying demand distribution. However, demand information can be very limited for many products in practice, particularly, for products with short life-cycles (e.g., fashion products). In this dissertation, we focus on dynamic pricing models that involve selling a fixed amount of initial inventory over a fixed time horizon without inventory replenishment. This class of dynamic pricing models have a wide application in a variety of industries. Within this class, we study two specific dynamic pricing problems with commonly-encountered business rules and issues where there is limited demand information. Our objective is to develop satisfactory solution approaches for solving practically sized problems and derive managerial insights. This dissertation consists of three parts. We first present a survey of existing pricing models that involve one or multiple sellers selling one or multiple products, each with a given initial inventory, over a fixed time horizon without inventory replenishment. This particular class of dynamic pricing problems have received substantial attention in the operations management literature in recent years. We classify existing models into several different classes, present a detailed review on the problems in each class, and identify possible directions for future research. We then study a markdown pricing problem that involves a single product and multiple stores. Joint inventory allocation and pricing decisions have to be made over time subject to a set of business rules. We discretize the demand distribution and employ a scenario tree to model demand correlation across time periods and among the stores. The problem is formulated as a MIP and a Lagrangian relaxation approach is proposed to solve it. Extensive numerical experiments demonstrate that the solution approach is capable of generating close-to-optimal solutions in a short computational time. Finally, we study a general dynamic pricing problem for a single store that involves two substitutable products. We consider both the price-driven substitution and inventory-driven substitution of the two products, and investigate their impacts on the optimal pricing decisions. We assume that little demand information is known and propose a robust optimization model to formulate the problem. We develop a dynamic programming solution approach. Due to the complexity of the DP formulation, a fully polynomial time approximation scheme is developed that guarantees a proven near optimal solution in a manageable computational time for practically sized problems. A variety of managerial insights are discussed

Locating outsourced and offshored production based on supply chain strategy: Findings from Swedish fashion/trend apparel companies

Bakgrund: En stor utmaning inom klädindustrin är att kombinera produkters korta livscykler med de komplexa försörjningskedjornas långa ledtider. Följaktligen finns det ett antal supply chain-strategier som hanterar utmaningen olika: kostnadseffektiva, responsiva och resultatdrivna som fokuserar på ett större antal aspekter. Dessa olika strategier lokaliserar outsourcad och offshorad produktion olika för att hantera utmaningarna. Utvecklingen i lågkostnadsländer har utvecklat supply chain-strategier och beslutet för lokalisering. Syfte: Följande syfte har formulerats för examensarbetet: ”Analysera vilka faktorer svenska klädföretag finner viktiga när de lokaliserar outsourcad och offshorad produktion i Europa och Asien, samt hur dess företagsstrategi och supply chain-strategi matchar”. Ett antal forskningsfrågor har också uppformats för ytterligare förståelse. - Hur kategoriserar svenska klädföretag sina produkter och används kostnadseffektiva samt responsiva försörjningskedjor för respektive kategori? - Hur påverkar valet av supply chain-strategi de olika faktorerna? - Hur har utvecklingen i lågkostnadsländer påverkat svenska klädföretags lokaliseringsval för outsourcad och offshorad produktion? Metod: Metoden använd för studien är inspirerad av Yins (2004) multipla fallstudie metod. För att kunna svara på syftet och forskningsfrågorna till detta examensarbete har en intervjuguide tagits fram, vilken var underlag för genomförandet av fem mer djupgående analyser av svenska klädföretag. Då det finns ett stort antal företag i den svenska klädbranschen bör därför inte resultatet av de genomförda intervjuerna ses som ett enhetligt resultat för hela branschen, utan bör istället ge en indikation på hur företag inom branschen resonerar kring dessa frågor. De givna svaren från respektive intervju jämfördes först med det utformade teoretiska ramverket, för att sedan följas upp med en avslutande jämförelse företagen emellan för att på så sätt kunna urskilja eventuella mönster. Det utvecklade teoretiska ramverket är primärt baserat på Chopra och Meindls (2004) Network Design Decision Framework. Författarnas ramverk används för att kunna avgöra lokalisering av produktion baserat på: konkurrensstrategi, supply chain-strategi och ett antal faktorer. Detta ramverk kompletterades sedan med supply chain-strategi teori av Fisher (1997) och ytterligare faktorer som forskarna fann intressanta för studien. Slutsatser: Vår undersökning visade att alla fem företag kategoriserar sina produkter. Däremot är det enbart de större företagen, som bedriver egen detaljhandels verksamhet, som har olika supply chain-strategier för dess produktkategorier. De större företagen erhåller hela risken i dess supply chain själva. Dessa företag använder sig av en kostnadseffektiv strategi för dess första orders och en responsiv strategi för dess andra orders. De mindre företagen använder sig istället av en grosshandlarförsäljningsmodell (tillverkning mot order), vilket innebär att de inte själva behöver ta någon risk. Detta medför att de mindre företagen därmed inte behöver samma nivå av matchning dess respektive strategier emellan. Generellt är det samma faktorer som är viktiga för samtliga fem företag gällande val av lokalisering, däremot skiljer sig ledtid och kostnad mellan stora och mindre företag. Slutsatsen är att mindre företag, med dess grosshandlarförsäljningsmodell, inte behöver reducera kostnaden och vara responsiva i samma utsträckning som de större företagen med den egna detaljhandelsmodellen. De gemensamma faktorerna företagen emellan är viktiga oavsett om produktionen är lokaliserad i Europa eller Asien, detta då företagen vill standardisera sin produktion i så stor utsträckning som möjligt och därmed försäkra sig om att samma nivå på kvalitet och passform m.m. uppnås. Alla deltagande företag har erfarit utvecklingen i lågkostnadsländer och har därför börjat se över alternativa lokaliseringar för dess nuvarande produktion.Background: One of the main challenges in the fashion apparel industry is combining the products short lifetimes with the complex supply chains and long lead-times. There are thus several different types of supply chains that compete differently: the physically efficient, the market responsive and the outcome-driven supply chain. These supply chains locate outsourced and offshored production differently to manage the challenges. The development in Asian low cost countries has implied higher wages and manufacturing costs. This development has affected the supply chains and decisions of where to locate production. Purpose: The formulated purpose for this master thesis is: “Analyze factors Swedish fashion apparel companies find important when locating their outsourced and offshored production in Europe and Asia, and its alignment with their competitive strategy and supply chain strategy”. A number of research questions were also formulated to get a more thorough understanding. - How do Swedish fashion apparel companies’ categorize their products, and are efficient or responsive supply chain strategies established for each category? - How does the choice of supply chain strategy affect the factors? - How has the development in LCC affected Swedish fashion apparel companies’ choice of locating production? Method: The methodology of this thesis is inspired by the multiple case study method (Yin, 2004). To answer the purpose and research questions of this thesis an interview guide was designed to conduct in depth interviews with five Swedish fashion apparel companies. As there are a large number of Swedish fashion apparel companies the outcome of the interviews should not be considered as a representative sample. Instead they should provide an indication of how companies reason regarding the questions. The answers from each interview were first compared to the established theoretical framework and then followed by cross-case patterning. The established framework is primarily based on Chopra and Meindl’s (2004) Network Design Decision Framework. The authors’ framework is used for determining location for production based on: competitive strategy, supply chain strategy, and a number of factors. This model was complemented with additional theory regarding supply chain strategies from Fisher (1997) and other factors that the researchers found interesting. Conclusions: Our investigation showed that all five companies categorize their products, however it is only the larger companies with their own retail business who have different supply chain strategies for their categories. The larger companies bear the risk in the supply chain themselves and thus they have a cost-efficient supply chain for first orders and a market responsive supply chain for second orders. The smaller companies use a wholesale model (make-to-order) and thus don’t take any risk, consequently they don’t need the same level of alignment between their strategies. Generally the same factors are important for all five companies when selecting location, however the lead-time and cost factor differ among the smaller and larger companies. The conclusion being that the smaller companies with their wholesale business models don’t need to reduce costs and be responsive compared to the larger companies with their own retail. The same factors are important regardless if production is located in Europe or Asia as the companies want to standardize production and ensure the same level of quality, fit etc. All case companies have experienced the development in LCC and are thus reviewing alternative locations

Coordination of inventory distribution & price markdowns for clearance sales at Zara

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 83-86).There is an essential need in the retail industry, of integrating inventory planning and pricing strategies. In the fast-fashion world of retail, inventory is treated as a perishable item leading to short selling periods. It is a common practice for retailers to liquidate unsold merchandise via clearance markdown policies. Joint marketing and production decisions are important and challenging in retailing. Clearance sales depend on the pricing, seasonal effects, and the assortment of goods available to the customer. Errors in inventory distribution and clearance pricing result in loss of potential revenue or excess inventory to be salvaged. In the case of Spanish-based retailer Zara, thirteen percent of annual revenues are attributed to clearance sales. To maximize these revenues a supply chain tool is designed to facilitate the inventory distribution decisions for the clearance season while considering price markdowns. A two part linear optimization model considers the demand forecast, pricing decisions, and logistic costs in determining the allocation of excess inventory. The business case is very similar to other retailers where revenues need to be maximized. However, Zara's business model and vertically integrated supply chain makes this case very unique. In a forecast error comparison test, the proposed solution improved the forecast error from 8 to 4 percent in respect to the current forecast process.by Orietta Parra Verdugo.S.M.M.B.A