Case Synopsis: The case describes General Electric’s transformation from an industrial manufacturer to an industrial analytics giant. It opens in 2009 when CEO Jeff Immelt decides that GE, a hardware maker, needs to be more capable in software. The narrative traces his early efforts to consolidate and coordin

Managerial Economics
Digitization of an Industrial Giant: GE Takes on the Industrial Analytics”

Each student is required to submit a detailed written report on the “Digitization of an Industrial Giant: GE Takes on the Industrial Analytics” case study (Reference no. 317-0237-1).

Case Synopsis:

The case describes General Electric’s transformation from an industrial manufacturer to an industrial analytics giant. It opens in 2009 when CEO Jeff Immelt decides that GE, a hardware maker, needs to be more capable in software. The narrative traces his early efforts to consolidate and coordinate software capabilities in a central unit (GE Software Center) headed by Bill Ruh in Silicon Valley.

It documents the realization of the potential for big data and analytics for customers to which GE has sold industrial equipment for decades. Opportunities related to ‘predictive maintenance’ seem attractive given the significant economic costs of unplanned maintenance and repair for GE customers.

Equipment optimization through analytics also has the potential to increase their margins, especially for those that face increased competition and lack pricing power. As GE roars down the runway to becoming the leading player in the digitization of industry, the question is can it reach the critical speed to break free of the tarmac and sustain flight?

Case Assignment Questions:

1. Considering the five stages of analytical progress proposed by Davenport et al (2010), evaluate the current status of GE.

2. How GE positioned in relation to its software rivals such as SAP? Better or worse? Why?

3. Discuss the critical factors for an analytics project? Why is GE pursuing industrial analytics? And what are the challenges that GE faces?

4. What are the suggestions that you would give to GE to grow its analytics business?

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