Information and Knowledge Management

Case Study Knowledge Management at GE

About GE: GE (NYSE: GE) is the worlds leading Digital Industrial Company, transforming industries through software-defined machines and solutions that are connected, responsive, and predictive. With a worldwide presence across in than 180 countries and a workforce of more than 300,000 employees, GEs revenue for 2017 amounted to over $122 billion.

Knowledge Management At GE, our knowledge sharing program was re-created as an enterprise-wide KM Strategy and began implementation in early 2016. In just over two years, we have designed and launched 160+ global communities for our engineering staff and others across GE businesses (130K members). Our focus is on tacit knowledge exchange for GEs engineering workforce. Within a year, we expect to grow to about 200 communities that engage about 175,000 employees in both our primary and supporting roles to our 45K+ engineers. This is the foundation of our KM approach working within and across businesses to connect employees and drive business value.

Daniel Ranta is accountable for GE-wide vision and strategy for Knowledge Sharing (KS) implementation that builds on work being done in other businesses across GE with a focus on connecting people, both internal and external, to leverage our collective GE expertise. He has 25+ years of experience in KM strategy, collaboration, content management, portal design, social networking, and measuring business results. He says, we pride ourselves on listening to our customers and being agile and fast with our continuous improvement efforts.

Knowledge management and big data One of the critical challenges with integrating AI into industrial applications today is around digitizing human knowledge in a way that machines can mimic a human's ability to reason, make decisions and work more productively with their peers. It requires a combination of human ingenuity and advanced AI that can draw upon the vast volumes of expert domain knowledge that humans have produced over millennia.

To enable machines to capture and benefit from this domain expertise, GE Research uses semantic web technology to model, digitize, reason and learn from human knowledge. In addition, we draw upon deep domain expertise in natural language processing and text mining to extract knowledge from unstructured sources, and our expertise in Big Data and cloud computing technologies to simplify the management of data and accelerate analytics.

With these capabilities at work at GE Research, we often reduce run times from days or months to just minutes or hours.

Required :

Analyse GEs KM systems. Apply the following themes in your analysis: Knowledge application systems; Knowledge discovery systems; Knowledge-sharing systems.

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How the question should be answered :

Analyse the case study and be able to identify where different kinds of knowledge systems have been used and for what purpose at GEs KM systems. With proper analysis of the case study, you will identify the following knowledge management systems. Your purpose is to analyse them and below might be a starting point.

1. Knowledge application systems define and describe AI systems. Definitions for AI range from: systems that act like humans, systems that think like humans, systems that think rationally, to systems that act rationally.
2. Knowledge discovery systems - The technologies that enable the discovery of new knowledge uncover the relationships from explicit information. Discovery through 1. Synthesis of new knowledge through socialisation with other knowledgeable persons; and 2. Discovery by finding interesting patterns in observations, typically embodied in explicit data.
3. Knowledge sharing systems- Knowledge sharing systems: Knowledge sharing systems can be described as systems that enable members of an organisation to acquire tacit and explicit knowledge from each other.