Reference no: EM131210950
1. Complete the readings, then reflect critically on How Google Works in the light of the other readings. What are some key elements of Google's culture, and how do they relate to elements of culture mentioned in "How Innovative is Your Company's Culture?" and "GE and the Culture of Analytics"? What about Google's culture might translate well to other environments, and what would be challenging? Would it be a good idea for all companies to have a culture like Google's? Consider which elements of the Google culture could be relevant to your small group assignment.
In this discussion, I will be looking for evidence that you are able to relate the elements of culture discussed in the readings and begin forming your own framework of the key elements of organizational culture. Your individual participation will be assessed according to the level of your engagement in the discussion space and your ability to translate and synthesize content from the readings and your peers.
• Eric Schmidt and Jonathan Rosenberg, How Google Works, Grand Central Publishing, Introduction and Culture, pp. 1-66 (66 pp.)
• Jay Rao and Joseph Weintraub, "How Innovative is Your Company's Culture ," MIT Sloan Management Review, 54:3 Spring 2013, pp. 29-37 (9 pp.)
• Philip Kim, "GE and the Culture of Analytics ," MIT Sloan Management Review, Spring 2014 55:3, pp. 1-4 (4 pp.)
2. Tell a couple of stories that describe how analytics have been used to make a positive difference for in an organization. Your stories can be based your own experiences, case studies, journal or newspaper articles, etc. Below you will find the sort of thing that I might use because I am familiar with the particular journal, but don't feel that you have to use these articles (although feel free to) or this journal.
• Ahire, S. L., Malhotra, M. K., & Jensen, J. B. (2015). Carton-Mix Optimization for Walmart.com Distribution Centers. Interfaces 45(4):, 341-357.
• Elsner, R., Krafft, M., &Huchzermeier, A. (2003). Optimizing Rhenania's Mail-Order Business ThroughDynamic Multilevel Modeling (DMLM). Interfaces 33(1):, 50-66.
• Körpeoglu, E., Kurtz, Z., Kilinç-Karzan, F., Kekre, S., &Basu, P. A. (2014). Business Analytics Assists Transitioning TraditionalMedicine to Telemedicine at Virtual Radiologic. Interfaces 44(4):, 393-410.
• Tandon, R., Chakraborty, A., Srinivasan, G., Shroff, M., Abdullah, A., Shamasundar, B., . . . Dhore, P. (2013). Hewlett Packard: Delivering Profitable Growth for. Interfaces 43(1):, 48-61.
• Yelland, P. M., Kim, S., &Stratulate, R. (2010). A Bayesian Model for Sales Forecasting at SunMicrosystems. Interfaces 40(2), 118-129.