Peter C. Bell earned BA and MA degrees from Oxford University and MBA and PhD degrees at the Graduate School of Business, the University of Chicago, and is a Professor Emeritus of Management Science at Ivey.
He serves as a consultant to corporations, hospitals, small businesses, charities, and government agencies in the areas of competitiveness, pricing, analytics, and operations.
Bell's research interests include using management science/operations research to create competitive advantage, pricing and revenue management, business decision-making, competing with analytics, Excel modelling, and statistical analysis.
In the community, Bell is a Past-President of the Nor'West Optimist Club of London, and was formerly President and Chairman of the Board of Meals-on-Wheels London. In his spare time, he plays golf, and collects and restores classic British motorcycles.
Teaching
Competing with Analytics: Executive MBA core course
Business Analytics: undergraduate and MBA program core
Management Science for Competitive Advantage: BA senior elective
Executive (short courses) in Business Analytics, Management Science, Business Statistics, and Pricing and Revenue Management
Abstract: The Whistler-Blackcomb (WB) Mega Day Challenge requires a skier to ride all 24 lifts at the resort in a single day. Among over two million skiers annually at WB, only 313 completed the challenge in fourteen months following the introduction of a system that tracks lift use by skier. Apart from the physical challenge, the difficulty is to find a route that matches one’s skill level while accounting for variable lift opening and closing times. brbr We use data from WB’s radio-frequency identification (RFID) ticketing system to estimate ski times between lifts for skiers of various skill levels. We then formulate and solve the problem by a combined, iterative integer programming and heuristic approach, up to the highest feasible skier skill level. The problem’s distinctive features preclude use of known solution methods for similar problems, so we use a practical, staged solution approach. brbr Our results include a recommended route that enables the greatest number of skiers, roughly the fastest quartile, to achieve the challenge. We also provide a benchmark, that skiers who can ski a particular common run in 12 minutes or less, should be able to complete the challenge. In three months following communication of our recommended solution, the rate at which Mega Days were successfully completed increased by two-thirds from the previous seven skiing months.
Abstract: Supply chain decision-making processes that are not tightly integrated with marketing decisions may well be costing the firm twice. First, this will promote poor operations level decisions and second, this may provide management with a view of their firm that will lead to inappropriate strategic decisions. The motivation of this paper is to explore the relationships between decision-making at various levels within the firm and, in particular, the relationship between the firm’s strategic and operations decision making. Using the case of a manufacturer managing a supply chain we show that increasing revenues may not increase profits and cutting costs may also reduce profits. We also show that the strategic or tactical view of the firm, and consequently the quality of the firm’s strategic and tactical decisions, can be highly dependent on how the firm makes low-level marketing and supply chain decisions. Our results illustrate the significant benefit available to manufacturers who can successfully and tightly integrate production, logistics, and marketing decision making. Such integration will improve operations level decisions and also provide an improved platform for tactical and strategic decisions.
Abstract: We examine a revenue-enhancing opportunity for perishable products that face demand uncertainty with fixed capacity and limited product options, and where customers have distinct preferences in product selection. We use an airline as an example of such products in this paper. An airline provides several product options for customers, as it operates multiple flights between the same origin-destination at different times of the same day. We consider customers with a strong preference for a specific flight and introduce a segment of customers who are flexible with their travel plans and have no specific flight preference on that day. We find that under some circumstances, the airline offering the flexible ticket to attract price-sensitive, flexible customers will enhance revenues. We investigate the optimal number of seats to reserve from the flights for the various fare classes and the fare for the flexible ticket. The implications of this research for the product with market disruption are also discussed.
Abstract: Recently, Kim and Bell (2011) developed a revenue managemnent pricing model with price-driven substitution. The authors considered production decisions under unlimited production capacity and investigated the impact of price-driven substitution on a firm's pricing and production decisions. The authors modeled the consumer demands for each market segment as linear additive demand function based on exogenous variables, where demand substitution occurred as a function of price differences between the two products. In this article, we extend this work to examine the impact of a production capacity constraint on the firm's joint pricing and inventory decisions. Based on this extended model, we investigate the impact of price-driven substitution on a firm's pricing and production decisions where there is a limit on total capacity. We show how revenue managers should adjust prices and production levels to take into account price-driven substitution under a capacity constraint setting. Both deterministic and stochastic models are developed, and the impact of price-driven substitution and a capacity constraint on the optimal prices, production levels, and revenues is illustrated.
Abstract: There has been much written on the topic of competing with analytics or creating a competitive advantage through analytics but there has been less written about how the firm can sustain an advantage created through analytics. There is an active market for analytics both domestically and offshore with the result that most analytics can be easily replicated. This article reports results from research following analytics applications over many years and describes five analytics strategies firms have used to extend the competitive advantage that they have achieved through their use of analytics.
Abstract: Lease expiration management (LEM) in the apartment industry aims to control the number of lease expirations and thus achieve maximal revenue growth. We examine rental rate strategies in the context of LEM for apartment buildings that offer a single lease term and face demand uncertainty. We show that the building may incur a significant revenue loss if it fails to account for LEM in the determination of the rental rate. We also show that the use of LEM is a compromise approach between a limited optimization, where no future demand information is available, and a global optimization, where complete future demand information is available. We show that the use of LEM can enhance the apartment building's revenue by as much as 8% when the desired number of expirations and associated costs are appropriately estimated. Numerical examples are included to illustrate the major results derived from our models and the impact on the apartment's revenue of sensitivity to the desired number of expirations and associated costs.
Abstract: The surge of interest in big data has led to growing demand for analytics teams. A strong analytics team can help a company become more efficient and improve overall competitiveness. Companies with superior data analytics capabilities have found ways to build long-term advantages. FedEx, for example, has for years used its team of analytics professionals to create and maintain a competitive advantage through enhanced revenues and lower costs, while one of the factors that has helped Wal-Mart become one of the world’s largest and most successful retailers is the strength of its analytics. Assembling analytics teams, however, is difficult. For one thing, many companies lack the in-house knowledge and experience needed to put together an analytics team. What’s more, the labor market for analytics professionals has grown increasingly tight. Fortune recently reported, Online help-wanted ads for data analysis mavens have shot up 46% since April 2011, and 246% since April 2009, to over 31,000 openings now, according to job-market trackers. The shortage of analystsparticularly those capable of developing and leading world-class teams that can enable a company to create a competitive advantage from its data and analyticsis driving organizations to consider outsourcing their analytics activities. However, choosing analytics providers and structuring effective working relationships that deliver value requires managers to have a clear understanding of what they’re looking for and the potential risks.
Abstract: We examine a supply chain in which a manufacturer supplies a single product to a retailer who faces two forms of customer returns. We compare the impact of these two forms of customer returns on the decisions and profits of the manufacturer and the retailer under various types of channel interaction: Manufacturer Stackelberg (MS), Vertical Nash (VN), and Retailer Stackelberg (RS). We find that when the level of customer returns that are proportional to quantity sold is extremely high, the retailer prefers the MS rather than the RS channel interaction. We also examine the impact of the asymmetric customer returns information on the decisions of the manufacturer and the retailer and on profits under MS and VN channel interactions. We show that in the MS case, the retailer can decide whether or not to share customer returns information with its manufacturer without knowing the manufacturer's estimates of customer returns and in the VN case, both the retailer and the manufacturer can decide whether or not to shareacquire the information based on observation of the other's behavior. The issues of sharing this information are also discussed.
Abstract: Market segmentation is a key strategic element in the practice of revenue management (RM). After being identified, market segments should be kept separate to prevent demand spillover from high priced segments to low priced segments and the associated revenue loss. Tools to restrict customer migration across segments are referred to as fences’. This paper represents one of the initial efforts to organise the characteristics of fences and to extend the research to more general RM settings. We first present a general picture of fencing in the world of RM and discuss business issues related to the segmentation process, segmentation enforcement and the implementation of fencing in RM. Next, we provide a survey of segmentation variables and use them to develop the discussion of the corresponding fences in the practice of RM. We categorise fences based on purchase patterns, product characteristics and customer characteristics, and lay out a taxonomy, and provide examples using the taxonomy. We suggest that management can look at their particular business situation and decide whether or not fencing is applicable. If fencing is essential, the manager must consider each of the elements listed in the taxonomy and then decide which descriptor best fits the situation. The next step is to choose the optimal fencing decisions (that is, price, inventory and cost devoted to fences) and apply them to the situation in order to improve the firm's financial results.
Abstract: The objective of this article is to lay out the fundamental concepts that make up the field known within operations research (OR) as revenue management (RM). Five basic ideas (overbooking, differential pricing, product protection, planned upgrades, and short-selling) and their variants provide the conceptual foundations of the practice of RM and motivate OR research in RM. Understanding these concepts will provide an understanding of the practice of RM and the RM algorithms in use today, and will also help to understand some of the new business practices that we see appearing every day.
Abstract: Products returned by customers are common in the retail industry and result in costs to both the supplier and the retailer. In practice, retailers implement returns policies that may give customers a full, partial, or no refund for returned products. In this paper, we examine how a firm that faces customer returns can enhance profit by using different customer returns policies, full-refund and no-returns, as a device to segment its market into a dual-channel structure. We also show the impact of customer returns on the firm's pricing and ordering decisions, as well as on the firm's profit in such a dual-channel structure.
Abstract: In this paper, we examine how customer returns influence the retailer's ordering decision, the manufacturer's wholesale price decision, and the profits of the manufacturer and the retailer, in a single-period, stochastic demand (newsvendor) setting. When the manufacturer is a Stackelberg leader and the retailer is the follower, we also examine how to contract a buyback policy, where the manufacturer buys back both unsold inventory and customer-returned products, so that both the manufacturer and the retailer are more profitable than if they operate independently. We also show how this work can be generalized to the case of multiple retailers.
Abstract: We investigate a decentralized supply chain that consists of a manufacturer and a retailer where the retailer simultaneously determines the retail price and order quantity while experiencing customer returns and price dependent stochastic demand. We propose an agreement between the manufacturer and the retailer that includes two buyback prices, one for unsold inventory and a second for customer returns, and show that this type of easy-to-implement agreement can achieve perfect supply chain coordination and be a win-win for both manufacturer and retailer when a complementary profit-sharing agreement is included.
Abstract: Firms may produce a variety of generally similar products or may practice 'scientific pricing' or revenue management where the firm will offer similar or somewhat differentiated products in multiple market segments at different prices. Whenever generally similar products are available, the demand for the products is linked through the ability of the customer to substitute one product for another. One widely known type of demand substitution is referred to as inventory-driven substitution where a customer will substitute for a product that is out of stock by buying a similar product. A second type of substitution occurs as a response to price-differences when a customer substitutes a less expensive product for a similar higher priced product. As firms use dynamic pricing to match demand with inventory or capacity while maximizing revenue or contribution, there is a need to take into account the fact that the creation of price differences between market segments will motivate customers to try to switch from higher priced segments to lower priced segments leading to price-driven product substitution. If the firms' price behavior leads to stockouts, inventory-driven product substitution may also occur. Both these effects will impact the firms' price and production capacity decisions. In this paper, we consider the impact of price-driven substitution on a firm's pricing and production capacity decisions for a single period, when the firm sells to multiple market segments. We show that revenue managers and supply chain coordinators should adapt product prices in each market segment and order quantities to take into account substitution by customers and the costs of supplying product to each market. We develop both deterministic and stochastic models with substitution as a result of price-differences. We investigate the impact of the symmetrical and asymmetrical demand substitution on optimal prices, production levels and revenue or contribution and the impact of changes in the production cost on the optimal solutions.
Abstract: This paper evaluates the simultaneous determination of price and inventory replenishment when a firm faces demand from distinct market segments. A firm utilizes fences, such as advance or nonrefundable payment, to maintain separation of its market segments however, fences are imperfect and allow a degree of demand leakage from the higher-priced to the lower-priced market segment. We investigate the optimal structure of joint price and inventory decisions with fencing, and demonstrate that more segments is not necessarily better, especially when demand uncertainty is high in the presence of lost sales. We also show the impact of imperfect fences on the firm's profitability, and evaluate how fencing costs affect the optimal fencing decision.
Awarded L. W. Tapp Prize for MBA teaching 2010 by MBA students.
Awarded Ivey prize for teaching innovation, 2009
Award of Merit for outstanding service to the Operational Research profession: Canadian Operational Research Society, 2007
Elected a Fellow of the Institute for Operations Research and the Management Sciences 2006.
Awarded the INFORMS prize for teaching the practice of operations research and management science, San Francisco, 2005.
Experience
Elected Chair of the Franz Edelman Prize Committee for the 2013 and 2014 competitions.
Elected Vice-President and President Elect of the College on the Practice of Management Science within the Institute for Operations Research and the Management Sciences 2011-15.
Treasurer of the International Federation of Operational Research societies 2007-14.
Founding Editor-in-Chief, International Transactions in Operational Research, (1993-2000) and acting EIC 2006-07
International editorial advisory board, Journal of the Operational Research Society (1999- )
Editorial Board, Omega: The International Journal of Management Science (1994 - )
Associate Editor, INFOR (1990 - )
Vice President, International Activities, INFORMS (2002-2006)
President, International Federation of Operational Research Societies (1995-97)
North American Vice-President, International Federation of Operational Research Societies (1989-91)
The Institute of Management Sciences: elected Member of the 1991-1993 Council
President, Canadian Operational Research Society (1985-86) (Vice-President 1984-85)
Visiting Professor, London Business School (UK)
President, Canadian Operational Research Society (1985-86) (Vice-President 1984-85)
Visiting Professor, London Business School (UK)
Visiting fellow, Warwick Business School (UK)
C-I-L Distinguished Lecturer, Wilfrid Laurier University
Chevron Distinguished Visiting Professor, Simon Fraser University
Research/Course Development
Management Science/Operations Research: A Strategic Perspective, SouthWestern Publishing, Cincinnati, Ohio 1999. (Available in Chinese translation, 2001)
Analytics for Managers (with G. Zaric), Routledge Publishing, New York, NY, 2012
Author or coauthor of 16 books, more than 80 articles, and more than 120 cases.