Problem
I. What is big data?
i. What is big data in the context of manufacturing? (Why are there opportunities to leverage big data in the context of manufacturing? Why hasn't it been more widely deployed in manufacturing contexts as it has in marketing contexts?)
ii. What are the opportunities that big data provides in manufacturing? (How could it be deployed in manufacturing? What are some of its uses in various manufacturing contexts? That is, think beyond Dow and chemical manufacturing.)
II. Is the chemical industry amenable to the deployment of enterprise manufacturing intelligence (EMI)?
(What present characteristics of the chemical industry indicate that leveraging the capabilities of EMI would be helpful? Are there any changes occurring in the chemical industry that indicate EMI would be more helpful or less helpful going forward? Are there any industry characteristics, present or emerging, that could be cited as demonstrating that the usefulness of EMI in the chemical industry is limited? What is the one specific issue with Dow's position in the industry that might impede employees appreciating/accepting the usefulness of EMI?)
III. What are the metrics by which Dow could measure the return on investment of EMI? (In addition to various tangible metrics, also provide some intangible metrics as discussed in the case, but not along the lines of the use of "blue dollars" at Energizer as discussed in class. That approach is simply trying to equate intangible metrics into real returns which is terribly misguided and fraught with problems. Mention the intangible metrics and discuss how they could help move the company forward, but do not try to convert them into "hard" dollar returns.)