Reference no: EM13969837
CEO Brett was conducting a quarterly review of oper- ations with his top-management team. One of the sub- jects he introduced, as well as informing the participants in advance of the meeting, was what the company was doing with its powerful new analytics. Brett explained that he was already aware of how advanced analytics, or Big Data, was helping make good decisions in mar- keting and selling many of its consumer products. He continued: "At the moment, I would like to review what we are doing with analytics to help us do a better job of managing operations and human resources. We are pay- ing large sums of money to collect and analyze data, but what's the payoff?"
Kevin, the manufacturing vice president, said that some new machine analytics were providing precise data about when to schedule maintenance on machines, including the optimal time to lubricate machines with hundreds of parts. Brett replied, "Not very impressive.
You and your staff were doing a good job maintain- ing complex machinery before we hired the analytics consultants."
Melissa, the vice president of information technol- ogy, explained that recent advances in analyzing vast amounts of data have provided her and her staff with a ton of facts about employee use of computers, the Inter- net, and mobile devices provided by the company. Me- lissa said, "We can now tell you which websites our em- ployees visit, when they visit the sites, how much time they spend sending and receiving e-mails, and which employees receive the most e-mails. We even know which employees use our IT equipment after hours and on vacation." Brett responded, "And in what way are these data telling us anything useful for operating the company more efficiently?"
Sandra, the HR vice president, explained that the HR department was getting a lot of information for HR 99 analytics. She said, "We have a precise picture of which employees are using which benefits, and which employ- ees are most likely thinking about retiring or quitting. We have even developed a data set of which employees are the most likely to participate in company training, or participate in MOOC [massive open online course], and who is most likely to have to take care of an elderly parent." Brett responded, "Sandra, you have put us in the realm of Big Brother. But why should our company care? Why do we really need information about which employees are most likely to participate in training? When they ask us for training, and we ask them to par- ticipate in training, then we will have the information we need."
After shaking his head for a few seconds, Brett said, "Maybe I'm a little dense. But will somebody give me a clear explanation of how our investment in Big Data is doing anything but making our consultants happy?"
1. What advice can you offer Kevin, Melissa, and San- dra to better impress Brett about the usefulness of analytics and Big Data at the company?
2. What advice can you offer Brett to help him be more realistic about the use of Big Data at the company?
3. What, if any, ethical issues are involved in this case?