Chapter 7. Informing Pharmaceutical Sales and Marketing
Six Sigma is often positioned as a project-based approach. Certainly using identifiable and well-defined projects aligns well with approaches to managing change, and change management can be an important aspect in spreading the use of data within a company. But insofar as Visual Six Sigma makes data analysis lean, it has an important role to play within companies whose operations and organizations do not or cannot support the traditional project infrastructure, as well as for projects that by their nature do not require a formal structure. This scenario looks at one such project set in one such company.
Pharma Inc. is a pharmaceutical firm that markets drugs addressing several therapeutic areas. Rick Fincham is a recently hired sales manager who is responsible for U.K. operations. Although Rick is very experienced in sales, he is still learning about how Pharma Inc.'s sales operations run and perform.
Executive management perceives that Pharma Inc. has lost ground recently. Consequently, Rick has been asked to look into the recent performance of his sales force. Specifically, Rick has been asked to:
Verify the claims of the marketing group that a limited promotion for Pharma Inc.'s major product, run from May through December 2008, was very successful.
Determine whether there are regional differences in performance relative to sales of Pharma Inc.'s major product.
However, Rick also sees this as an opportunity to learn more about what happens in the field.
To answer the questions posed above, Rick downloads company data on the monthly performance of the sales representatives for May through December 2008. The data table is large, containing 95,864 rows and 16 columns. The data consist of a number of nominal demographic variables, as well as a few continuous and ordinal variables. The number of prescriptions for Pharma Inc.'s product written by physicians is the major Y of interest.
Rick's data are typical of large observational data sets. As such, Rick first spends some time assessing and dealing with the quality of the data. He moves on to obtain a better understanding of the deployment of his sales force using a bubble plot to display the location of the practices visited and their associated sales representatives. In answering the questions posed to him, Rick uses summary tables, oneway analyses with comparison circles, regression plots, and even an animated bubble plot.
Rick finds that the promotion was indeed successful. He identifies regional differences. He also uncovers what seems to be an uncanny and suspicious adherence to an unstated operational rule that each physician should be visited once per month.
The upshot of his single-handed analysis is that he can easily answer the questions posed by the executive management, using results and arguments supported by data and informed by visual displays that make it easy for him to get his points across. In addition, Rick uncovers a number of interesting facts that will help him to manage and deploy his sales force more effectively in the future.
Had Rick simply used a spreadsheet, by far the most common tool used for such analyses, he would not have arrived at his conclusions so quickly, if at all. He certainly would have struggled to construct informative graphical displays and to apply appropriate statistical techniques, and it is very likely that he would not have noticed the one-visit-per-month behavior. In short, it is probable that the useful new insights that Rick obtained from his quick visual analysis would not have been gained.
The platforms and options that Rick employs are listed in Exhibit 7.1. The data sets that he uses are available at http://support.sas.com/visualsixsigma. Rick would really enjoy your company as he explores his sales data set. You might be able to uncover some information that he overlooked. Give it a try!
Figure 7.1. Platforms and Options Illustrated in This Case Study
