Forecasting Lumpy Demand

Best Practices in Forecasting Lumpy Demand

Torey Payne

Liberty University

BUSI 620 Sec B04

October 10, 2014

* Best Practices in Forecasting Lumpy Demand

Introduction

Managers are challenged in trying to manage the risk or uncertainty associated with the decisions they make on a daily basis. These decisions include production planning, inventory management, marketing budgeting, compensation programs, and myriad other decisions which impact the growth of the firm. All of these decisions are heavily reliant on a reliable economic forecast in order to understand the future demand for the firm’s products or services. Forecasting can be both art and science and requires a macroeconomic understanding of general market conditions as well as detailed analysis of the firm’s historical sales and future marketing strategy (Salvatore, 2012). Forecasting methods are varied and range from simple to highly sophisticated models based on massive amounts data and interrelationships. Firms who fail at accurately forecasting their businesses will risk missing financial targets and could negatively impact customer satisfaction. Firms with fluctuating demand will have an especially difficult time developing the appropriate forecasting methods.

This purpose of this research paper is to provide an analysis of the literature pertaining to forecasting and specifically forecasting in firms whom experience lumpy demand. Lumpy demand exists in many manufacturing and service industries including heavy machinery, automotive, and spare parts (Gutierreza, Solis, and Mukhopadhyay, 2008). Accurately forecasting lumpy businesses is especially challenging and therefore this author has formulated the following research questions to explore throughout this paper. First, what are the challenges associated with generating accurate forecasts? Second, what are the commonly used methods for forecasting lumpy businesses and their deficiencies?

Challenges with Accurate...