Knowledge Management Revolution: Driving Efficiency with MyGPT in Mechanical Engineering
The Challenge: Information Overload and Productivity Losses
In today’s world, information overload and the difficulty of finding the right data are major contributors to negative work environments, lowering productivity and increasing employee frustration. Losses directly or indirectly caused by information overload are estimated to reach $650 billion globally each year—a figure equivalent to Switzerland’s GDP in 2015.
So, what can be done?
- 17. October. 2024
Patrick Ratheiser
CEO & Founder
Karin Schnedlitz
Content Managerin
The Daily Struggle for Information: A Glimpse into the Reality of Knowledge Management
In the controlling department of a mechanical engineering company, productivity losses due to information overload and searching for the right data are all too familiar. A significant amount of time is consumed by locating relevant documents scattered across intranet wikis, email attachments, and up-to-date data from external systems—often leaving employees uncertain whether the information they need even exists.
The company’s traditional approach to knowledge management has focused on centralizing and organizing information as much as possible. While this has simplified collaboration and knowledge sharing among employees, it’s far from optimal. Information is frequently outdated or incomplete, and the system heavily relies on manual input and maintenance.
New Approaches in Knowledge Management: The Innovative Solution MyGPT
A new initiative is generating excitement: To transform knowledge management within the company, the solution MyGPT from Leftshift One is being introduced.
MyGPT is a customizable, enterprise-specific version of ChatGPT that securely integrates all internal company data. To ensure a smooth rollout across the organization, the controlling department is given early access for testing. The team welcomes this opportunity and is eager to familiarize themselves with the key concepts and features.
Technology Serving Efficiency: How MyGPT Works
MyGPT Sets New Standards in Knowledge Management Across Two Key Categories:
1.   Explicit knowledge, already available in digital form within the company.
2.    Implicit knowledge, held by employees and not yet documented.
On a technical level, explicit knowledge is indexed through an enterprise search and made available on demand. The beauty of it is that internal company knowledge is delivered via a large language model (LLM) in a natural conversation with MyGPT—just like ChatGPT provides general facts. A key advantage is the reliable citation of sources, which boosts confidence in the answers provided.
Implicit knowledge cannot initially be captured by MyGPT. When employees ask a question that MyGPT cannot answer, a “Human Handover” occurs. An experienced employee responds, and previously implicit knowledge is digitized, transforming it into explicit knowledge that will be available to all employees through MyGPT in the future.
Two additional features of MyGPT are particularly noteworthy. First, there’s the Strict Mode, which prevents hallucinations. Unlike ChatGPT, which may sometimes provide incorrect yet convincing answers, MyGPT’s Strict Mode ensures that responses are strictly based on the information in the cited sources. Lastly, custom-built plugins allow MyGPT to integrate up-to-date external knowledge as well.
From Theory to Practice: A Test Run with MyGPT
The goal for the MyGPT test phase is clear: drastically reduce the time spent searching for information without compromising on quality or relevance. This boosts productivity and allows employees to focus on more important tasks for the company.
With access to MyGPT, the first use case is utilizing Strict Mode to make a natural language request regarding internal controlling guidelines—information needed to create a quarterly report. The response includes a complete list of relevant policies, along with a linked source to the original document for further reference.
To further challenge MyGPT, the next task involves a specific, speculative question related to the company’s environmental goals. The MyGPT interface immediately notifies the user that, due to Strict Mode, no response can be generated as the available information is too sparse. However, it is also evident that another employee from the CSR department has already been assigned to address the question.
More Time for What Matters: How MyGPT Boosts Productivity
To identify current industry trends in mechanical engineering for the quarterly report, using a plugin is ideal. External sources are connected in seconds and utilized to provide the necessary information. Based on this, MyGPT generates a summary of key insights that can be used for the report. Upon completing this task, the previously asked question about environmental goals has also been answered and is now available to all employees through MyGPT.
In the past, these tasks would have required time-consuming research across various systems or consultation with colleagues, and the requirements would not have been as easily describable in natural language. The first test in the controlling department of the mechanical engineering company was a success, and productivity is expected to increase steadily with continued use of MyGPT.
Security and Reliability: MyGPT and the Partnership with Leftshift One
In addition to the outstanding solution, the successful collaboration between the company and Leftshift One has been a key factor in their success. Data privacy, in particular, was a top priority and has been effectively addressed through MyGPT’s secure environment, which prevents data retraining by LLM providers. For production data, there’s even the option to use an open-source LLM hosted within the company’s own data center, ensuring that no data is exposed externally.
The Future of Knowledge Management: Step into the World of MyGPT
In terms of individual employee productivity, an increase of 25-30% is expected with MyGPT. Additionally, the company’s collective productivity will rise, as anonymous cluster analyses of requests made to MyGPT provide leadership with real-time insights into what topics are occupying employees. With Leftshift One as a partner in the world of generative AI, the company is well-equipped to usher in the future of knowledge management.
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Sources:
1 Springer Link (2018), Information overload in the information age: a review of the literature from business administration, business psychology, and related disciplines with a bibliometric approach and framework development, https://link.springer.com/article/10.1007/s40685-018-0069-zTake advantage of generative AI in your business now.
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