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Posts tagged ‘mu sigma’

28
May

Data Science and Analytics Outsourcing – Vendors, Models, Steps


feldframework_whyData-driven business processes are not a nice-to-have but a need-to-have capability today. So, if you’re an executive, manager, or team leader, one of your toughest assignments is managing and organizing your analytics and reporting initiative.

The days of business as usual are over.  Data generation costs are falling everyday.  The cost of collection and storage is also falling.  The speed of insight-to-action business requirement is increasing.  Systems of Record, Systems of Engagement, Systems of Insight are being transformed with consumerization and digital.

With this tsunami of data and new applications, the bottleneck is clearly shifting from transaction processing to Analytics & Insight-driven “sense-and-respond” Action. This slide from IBM’s Investor Briefing summarizes the data-driven transformation underway in most businesses.

datadrivers

Better/Faster/Cheaper Analytics Execution

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18
Mar

Making Money on Predictive Analytics – Tools, Consulting and Content


Here are just a few examples of analytics at work

  • Target predicts customer pregnancy from shopping behavior, thus identifying prospects to contact with offers related to the needs of a newborn’s parents.
  • Tesco (UK) annually issues 100 million personalized coupons at grocery cash registers across 13 countries. Predictive analytics increased redemption rates by a factor of 3.6.
  • Netflix predicts which movies you will like based on what you watched.
  • Life insurance companies can predicts the likelihood an elderly insurance policy holder will die within 18 months in order to trigger end-of-life counseling.
  • Con Edison predicts energy distribution cable failure, updating risk levels that are displayed on operators’ screens three times an hour in New York City.

Now you are interested.  So what about your organization. Do you have the right toolset, dataset, skillset and mindset for analytics? Do you want to enable end users to get access to their data without having to go through intermediaries?

The challenge facing managers in every industry is not trivial… how do you effectively derive insights from the deluge of data? How do you structure and execute analytics programs (Infrastructure + Applications + Business Insights) with limited budgets?

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