Optimizing Sales and Marketing Activities in the Industrial Gas Industry
MetadataShow full item record
Marketing and sales comprise an important part of a company's core processes. We study this core component in a very large corporation in the industrial gas industry. This company has thousands of employees worldwide involved in sales and marketing activities. This dissertation develops mathematical tools for the company's top managers to better utilize this large workforce. Our study includes two parts. In the first part, we develop a framework via a sequence of mathematical models to address sales force optimization within the company's packaged gas (cylinder) business. In particular, our sequence of models determines: (a) the optimal number of visits to each of the existing customers with the goal of retaining them; (b) the optimal number of employees with different kinds of skills for satisfying the workload obtained using model (a) and including the time to hunt for new customers; and (c) the optimal way of providing the workforce calculated in part (b) (i.e., optimal strategies for hiring, relocation or dismissal of the current workforce). In the second part of the study, we develop a logistic regression model for predicting the probability of retaining a current account or winning a new account. This part of the study has been developed for the company's bulk gas (liquid) business. Moreover, we develop solution algorithms for those models developed in the dissertation which are not easily solved by commercial software. We then run the models on the company's real data, and make our conclusions based on the obtained results.