Introduction

Sprint has nearly 54 million customers and offers a host of products for consumers, businesses and government. The company recently began using analytics tools to try to make sense of the mountains of data created by Sprint network users on a daily basis. With approximately 70,000 employees worldwide and nearly $27 billion in annual revenues, Sprint is widely recognized for developing, engineering and deploying state-of-the-art network technologies, including the United States' first nationwide all-digital, fiber-optic network and an award-winning Tier 1 Internet backbone. Sprint provides local voice and data services in 18 states and operates the largest 100-percent digital, nationwide wireless network in the United States.

The decision to focus our project on Sprint was based on a couple of factors. Sprint is currently the 3rd largest telecom operator in USA and with the recent take over by SoftBank the prospects to grow look promising. This provides a clear opportunity to help the business grow using analytics. Secondly because of our connections in the company we were able to get more information on Sprint’s analytics strategy and future plans.

Recommendations

Sprint Telecom is part of an industry, which is one of the largest providers of data in the world. Sprint’s initial big data steps have been in the right direction. They have successfully used their current data sets for quick profits and short-term results. It is now time to take the jump by acquiring or building necessary skills to carry out the initiative on a larger scale.

The current issue with Sprint is that it works more as a telecom, Internet provider rather then a data company. The company sells handsets and minutes of usage. To maximize profits through analytics Sprint needs to have a more data scientific approach.

Sprint needs to implement its continuous