Sign Up Now
Get instant access to over 1 million+ study documents
OR
Already registered? click here to login
By creating your account, you agree to our terms of service, privacy policy and student honor code.
Big Data
Many companies are making use of big data to give themselves competitive advantage. Tesla is a good example of this. Tesla installed its Autopilot self-driving system on its cars in late 2015, even though the system is not activated. But what it has done is allowed the company to collect data on 1.3 billion miles of driving. This in turn "allows Tesla's engineers to fine-tune the algorithms that control its cars' active-safety systems," the basis of fully autonomous driving (Edelstein, 2016). Other car companies are working towards self-driving cars, but are doing it without the benefit of this enormous data set, which means that Tesla should in theory enjoy a technological competitive advantage with its self-driving cars (Edelstein, 2016).
The implementation of this big data is a work in progress. It will take years, and in theory the implementation should remain ongoing even once Tesla's cars are fully autonomous. The company is pursuing this project with an eye to gaining competitive advantage. It will be able to develop better self-driving cars, safer and more effective, than those of its competitors. When self-driving cars arrive on the market there will be intense competition...
It is possible that a larger competitor that sells more cars in a year can overcome this, but with self-driving cars not more than a year or two away from fully autonomous capability, competitors may not be able to make up the data gap on Tesla until market positioning has already been established.
Another company that makes ample use of big data is IBM, and they are using it in an entirely different way. IBM is leveraging the trendiness of big data in business to help sell its technology solutions. While companies look to the firms they admire -- Google, Tesla, Apple -- that make substantial use of big data, there is a whole industry of other companies that are willing to build around the drive towards data acquisition, and make supporting data acquisition, storage and retrieval a…
References
Edelstein, S. (2016) Tesla's autonomous-car efforts use big data no other carmaker has. Green Car Reports. Retrieved February 21, 2017 from http://www.greencarreports.com/news/1108065_teslas-autonomous-car-efforts-use-big-data-no-other-carmaker-has
Versace, C. (2014). Talking big data and analytics with IBM. Forbes. Retrieved February 21, 2017 from http://www.forbes.com/sites/chrisversace/2014/04/01/talking-big-data-and-analytics-with-ibm/#7a0f0f974aa7
Big Data Shopping Big data is a relatively recent concept in the marketing world, that describes the process of analyzing massive data sets to unearth trends. The data sets are so large that it would be almost impossible to find such trends without high-powered analytical technology. Big data has been facilitated by the ability to gather massive amounts of information about consumer profiles and shopping trends. The primarily facilitators of big
875). Often success introduces complacency, rigidity, and over confidence that eventually erode a firm's capability and product relevance. Arie de Geus (1997) identified four main traits for a successful firm; the first is the ability to change with a changing environment (Lovas & Ghoshal, 2000, p.875). A successful firm is capable of creating community vision, purpose, and personality, and it is able to develop and maintain working relationships. Lastly, a
Introduction Big data has become one of the most important aspects of supply chain management. The concept of big data refers to the massive data sets that are generated when millions of individual activities are tracked. These data sets are processed to yield insights that help inform managerial decision-making. Supply chains in particular have leveraged big data because companies have been able to develop technology to not only capture hundreds of
Market Analysis The third principle, that markets that don't exist can't be analyzed, reminds managers that assessing the effects of disruptive technologies is often counter-intuitive to good management practice. Many companies require the development of a business case and a business plan for new products. This approach is generally very successful when applied to sustaining technological innovations, because the market is well-known; however, when companies apply this strategy to new, emerging
P&G's free cash flow growth rate is also superior to Gillette's, but the productivity of the free cash flow is inferior. The addition of Gillette is expected to increase P&G's bottom line. 4. The price paid by Procter and Gamble to purchase Gillette seems rather high, but the investment is expected to return in the form of increased sales and cost reductions. The 20% premium is appropriate as it is
Zaslavsky is the leader of the Semantic Data Management Science Area (SMSA). He has published more than 300 publications on science and technology. Perera has vast experience in computing and technology as he is a member of the Commonwealth Scientific and Industrial Research Organization alongside publishing numerous journals. Georgakopoulos is the Director of Information Engineering Laboratory. He has published over 100 journals on issues related to science and technology