Where there is power, there is resistance.
At the other end of the analytics spectrum from Google, consider a large drug maker that employed me at the end of the century. I won’t name it here, but you can view my LinkedIn profile if you must know. I call it Beneke Pharmaceuticals in this chapter; I also changed the names of all of the people who worked with me at the company.
At Beneke, I split my time between its HR and IT departments. Half of my responsibilities entailed supporting a global PeopleSoft implementation. To this end, I traveled to Latin America quite a bit. When not working on this project, I worked in more traditional HR capacities such as compensation and recruiting.
About midway through my tenure at Beneke, my friend and colleague Lori swung by my cubicle and asked for my help. As someone with a traditional HR background, she was, by her own admission, “numerically challenged.” This normally didn’t concern her, but things had suddenly changed. Her manager, the fortyish head of college recruiting whom we’ll call Tom, had given her a very quantitative project. Tom asked Lori to evaluate Beneke’s MBA recruiting efforts. Specifically, he wanted answers to the following questions: