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DATA4000 Introduction to Business Analytics - Kaplan Business School

Your Task
Complete Parts A to C below by the due date. Consider the rubric at the end of the assignment for guidance on structure and content.

Assessment Description
You are to read case studies provided and answer questions in relation to the content, analytics theory and potential analytics professionals required for solving the business problems at hand.

Part A: Case Study Analysis

Instructions: Read the following case study:

GE Power: Big Data, Machine learning And ‘The Internet of Energy'
Based on this case study discuss:
a) The industry to which analytics has been applied
b) The business problem to be solved
c) The type of analytics used, and how it was used to address that business problem
d) The main challenge(s) of using this type of analytics to achieve a business objective
e) Recommendations regarding how to assist stakeholders adapt to the changes outlined in the article.

Part B: The Role of Analytics in Solving Business Problems (300-400 words)

Instructions: Describe one type of analytics (from Workshop 1) and evaluate how it could be used as part of a solution to a business problem with reference to ONE real-world case study of your own choosing.

Part C: Developing and Sourcing Analytics Capabilities (600-800 words)

Instructions: You are the Chief Analytics Officer for Telefonica, the largest telecommunications company in South East Asia and Latin America. The organization is undergoing significant transformations; it is scaling back operations in existing low revenue segments and ramping up investments in next generation products and services - 5G, cloud computing and Software as a Service (SaaS). Telefonica is keen to develop its data and analytics capabilities. This includes using technology for product innovation and for developing a large contingent of knowledge workers.

To prepare management for these changes, you have been asked review Accenture's report (see link below) and publish a short report that addresses the following key points:

1. How do we best ingrain analytics into our decision-making processes? (pages 5 - 6)

2. How do we organize and coordinate analytics capabilities across the organization? (pages 7 - 10)

3. How should we source, train and deploy analytics talent? (pages 11 - 13)