Why are companies unsure/skeptical on how to proceed with "Big Data"?
Answer: Although organizations are increasingly becoming aware of the power that “Big Data” has or can bring, they are still unsure how to use it in their situation. They feel their organization is not ready. One of more of the three scenarios is possible. Companies may have a lot of data but they fail to read or decipher it correctly. Perhaps these companies invested in data warehousing and other such programs mindlessly without verying whether it matches their requirements. Also perhaps they find the current analytics models too complex to read and understand and therefore don’t trust the results or insights such models draw.
What are the mutually supportive capabilities that the authors recommend for fully exploiting data analytics
Answer: The authors suggest three mutually supportive capabilities; (a) Ability to identify/combine/manage data from multiple sources (b) Ability to build predictive and optimization models using this data (c) Willingness of the organization to make transformations based on the findings from this data.
What are the inherent risks with any modelling exercise?
Answer: The inherent risk with modeling exercise is that the designed model may turn out to be so complex that it is no longer practical to be used. A model based on too many input parameters or giving out too complex a solution or view could be just impractical.
How did the company (the case discussed in the paper) avoid the common pain points that caused the failure of early CRM and other Big data implementations?
Answer: Many implementations of big data and analytics failed because they weren’t in sync with the company’s day-to-day processes and decision making norms.
This company (the case discussed here) wanted to optimize it’s advertising expenditure by coming up with a data-based model. Unfortunately the field managers never believed or trusted did model and...
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