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Introduction
Forecasting principles are applied by companies to predict sales for a certain industry during a selected period with the focus on firms’ share in these sales depending on tendencies in the market. Dr. Pepper Snapple Group is a company that produces soft drinks, and it is one of the leaders in the beverage market of the United States. This company uses sales forecasts actively to determine production volumes for different periods and regions of the country (Lombardo, 2018). The purpose of this paper is to analyze the impacts of Dr. Pepper’s sales forecasts on other forecasts, explain the role of exogenous factors in forecasting, and assess prerequisites of good forecasts in the process.
Identifying the Sales Forecast
In 2017, Dr. Pepper increased its net sales to $6.7 billion that indicated a 3.9% rise in comparison with the previous year. A sales forecast predicted such increases because of focusing on developing an attractive product and package mix for customers and improving an advertising campaign. The company addressed the forecasted changes in sales with the focus on the 1% rise in the sales volume and the 3% rise in the bottler case sales volume in comparison to 2016 (“Dr. Pepper’s (DPS) Q4 earnings,” 2018). To predict certain outcomes based on forecasting, the company’s leaders chose a causal model to determine the number of bottles to produce depending on market trends and changes in customers’ demands.
Analyzing the Impact of the Sales Forecast on Other Forecasts
For Dr. Pepper and other firms, sales forecasts directly influence setting the budget for a year. Thus, sales forecasts determine volumes or resources and materials to be ordered from suppliers and labor to be hired additionally. If sales forecasts are not appropriate, a firm can face significant losses and waste resources. Overhead costs depend on sales forecasts because different sales volumes influence expenses associated with supplies, advertising, taxes, and insurance among others (Merigo, Palacios-Marques, & Ribeiro-Navarrete, 2015). Cash receipts and disbursements also depend on sales forecasts because unachieved goals regarding sales influence the amount of cash available for a firm’s operations.
Exogenous Factors and Prerequisites of a Good Sales Forecast
To develop sales forecasts, managers should aware of such exogenous factors as the country’s GDP, market and industry trends, inflation and unemployment rates, and interest rates trends among others. If economic conditions in the country, which are analyzed concerning GDP, are negative, this aspect influences consumers’ buying capacity and sales. Market and industry trends accentuate consumers’ interest in the product and changes in prices. Inflation and unemployment rates are also important factors to impact consumers’ readiness to improve their purchasing of a certain product (Trapero, Kourentzes, & Fildes, 2015). Interest rates trends influence sales mostly internally. From this perspective, the prerequisites of an appropriate sales forecast include the analysis of economic conditions in the country, market and industry tendencies, a company’s previous market share, the position of competitors, advertising and promotion results, changes in set prices, and studies on market trends (Kolassa, 2016). All this information is important to forecast sales while paying attention to the factors that can influence alterations in consumer behavior.
Conclusion
Sales forecasts are important for firms to determine what volumes of products to manufacture and what revenues to expect. If these forecasts are formulated inappropriately or are not based on the analysis of previous sales, it is possible to expect increasing costs and losses. Therefore, it is necessary to understand how sales forecasts influence other aspects of a company’s operations and its sales strategy, recognize factors that can influence purchasing trends, and become aware of prerequisites of an effective forecast.
References
Dr. Pepper’s (DPS) Q4 earnings meet, revenues lag estimates. (2018). Web.
Kolassa, S. (2016). Evaluating predictive count data distributions in retail sales forecasting. International Journal of Forecasting, 32(3), 788-803.
Lombardo, C. (2018). Dr. Pepper Snapple’s sales are flat as it plans for the Keurig merger.The Wall Street Journal. Web.
Merigo, J. M., Palacios-Marques, D., & Ribeiro-Navarrete, B. (2015). Aggregation systems for sales forecasting. Journal of Business Research, 68(11), 2299-2304.
Trapero, J. R., Kourentzes, N., & Fildes, R. (2015). On the identification of sales forecasting models in the presence of promotions. Journal of the Operational Research Society, 66(2), 299-307.
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