Volatility in the Consumer Packaged Goods Industry — A Simulation Based Study

Abstract

Abstract. The volatility in a CPG market is modelled using a bottom up simulation approach and validated against disaggregated supermarket transactions data. The simulation uses independent agents, each agent representing unique households in the data. A simple behavioural model incorporates household preferences for product attributes, prices and promotions. Our validation strategy tests the model predictions at both macro and micro levels. At the macro level, the model is validated against out of sample evolution of market shares while at the micro level, household level choice of individual products and product attribute combinations are used. The model captures the volatility in terms of market share of brands and flavours -with the direction of change being more accurately predicted than the magnitude. At the micro level, we achieve a reasonable degree of prediction accuracy of household level SKU choice and a substantially higher accuracy for attribute choice. We found that product size to be the most difficult to predict among all attributes.

Modelling of Consumer Goods Markets

“…Additionally, the chapter also provides an example of how such models can be used to "explore the future", with their ability to incorporate "what-if" scenario building techniques. This chapter is based on Sengupta and Glavin (2013) and Sengupta and Glavin (2010), and introduces the models and methods used in both, and extends them by illustrating how radical changes in the market (such as new product introductions) can be modeled robustly using computational methods.…”

“…al., 2001;Blattenberg & Wisniewski, 1989). However, the presence of a wide variation in tastes and preferences amongst a reasonably large and demographically varied consumer population is also a key factor leading to the noisy character (Allenby & Rossi, 1998;Sengupta & Glavin, 2010;Sengupta & Glavin, 2012). Such markets do not lend themselves easily to traditional statistical and econometric analysis.…”

“…CPG markets have been extensively studied in the mainstream literature, but in spite of exhibiting many characteristics of a complex system, have only recently been brought within the purview of complex systems analysis (North et. al., 2009;Sengupta & Glavin, 2010;Rand & Rust, 2011). This paper builds a behavioral model of consumer choice, which is then incorporated within a multi-agent simulation framework to illustrate the accuracy and usefulness of such an approach in predicting market phenomena.…”

“…Our earlier work, specifically Sengupta and Glavin (2010) focused on developing a theoretical model of behavior, which took into account the heterogeneity in tastes within the consumer population and illustrated the link between this heterogeneity and the resultant volatility in overall market shares of brands and specific product characteristics. In order to carry out this analysis, the authors developed a rigorous methodology which focused on out of sample predictions of both macro level market share movements and micro level household level choices.…”

“…However, the behavioral model presented in Sengupta and Glavin (2010) was restricted at a simple level where agents made rational ordinal utility based choiceswhere the utility function depended solely on prices, product characteristics and individuals' preferences towards these characteristics. This restrictive utilitarian nature of the choice algorithm was intentional as the focus was establishing a validation methodology which is able to capture the volatile dynamics of the market and subsequently, illustrate the link with agent level heterogeneity.…”