The knowledge residing in organizations is a source of competitive advantage in the management of companies. Many companies, however, fail to fully share and make use of those resources. ABeam Consulting takes advantage of its broad insight around the utilization of data and its track record and know-how in making use of generative AI to contribute to enhancing and streamlining client businesses by building effective knowledge management frameworks (Knowledge CoEs).
Generative AI-enabled knowledge management enhancement support service - ABeam Knowledge CoE solution
Solution
Supporting the creation of frameworks for utilizing cross-organizational knowledge by taking advantage of generative AI
Background
Appropriate in-house knowledge management is now an even more pressing need with the emergence of generative AI
In a rapidly changing business environment, it is critical for companies to make effective use of the knowledge they hold in order to make the right decisions.
Generative AI, which has grown more effective over recent years, has particular strengths in processing and outputting textual information. By feeding it in-house knowledge, it can be expected to prove useful in a variety of applications, from simple summarization to outputting suggestions from the combination of multiple documents.
Suitable aggregation and management of in-house knowledge documents is needed to get the most out of such generative AI technology and to promote the use of knowledge across the company.
On the other hand, while departments (corporate planning, IT, investment planning and other departments) that gather knowledge from across their entire organizations aggregate and make use of valuable in-house information on a daily basis, many organizations fail to appropriately manage these resources and make continuous and company-wide use of them.
Challenges
If they are to take advantage of cross-organizational knowledge, companies need frameworks to appropriately aggregate and manage knowledge, and to serve the knowledge in a user-friendly manner
Pitfalls
- Knowledge holders do not share their knowledge for reasons including a lack of platforms, organizations or rules for the management of knowledge, or awareness around the utilization of knowledge failing to have permeated the organization
- Companies fail to manage data appropriately for lack of data management insight (excesses and deficiencies of necessary data arising, inability to ensure the accuracy and timeliness of data, potential users limited by excessive authorization controls etc.)
- Utilization of knowledge by users does not advance due to low usability (low searchability, difficulty in interpretation etc.)
Approach
Based on its insight into promoting the use of data across a wide variety of industries, ABeam Consulting provides end-to-end support for everything from designing strategies for promoting knowledge sharing, to building “Knowledge CoEs” that possess features including “knowledge aggregation DBs” that collate knowledge in a single place, and “knowledge interpretation assistants” that help make broader use of knowledge.
Key features
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Formulating effective strategies based in an extensive consulting track record
ABeam Consulting formulates the optimal knowledge management strategy to address each of its clients’ organizational and user challenges by taking advantage of the wealth of industry insights, experiences and methodologies it has cultivated over many years.
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Effective testing based in the wealth of insight offered by data and generative AI
Taking advantage of insights based in ABeam’s wealth of experience in data utilization and generative AI utilization projects enables the introduction of these technologies based on testing that effectively improves operations.
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End-to-end support from strategy formulation to implementation
ABeam Consulting provides side-by-side support throughout the entire process from beginning a project to business transformation by taking advantage of the insights and experience it has across all domains of data utilization.
Details
Approach to considering the construction of a Knowledge CoE
[Phase 1: Formulating a strategy]
ABeam Consulting begins by establishing the goals clients want to achieve by enhancing their knowledge management. Next, ABeam defines the work that needs to be carried out, the data systems to be used and the organizations and structures that will contribute to the project with reference to the DMBOK1 framework or other guidance.
1 Data Management Body of Knowledge
[Phase 2: Testing the use of generative AI]
ABeam Consulting tests whether the user experience defined in Phase 1 is achievable using generative AI. By getting a clearer image of the application through prototyping, ABeam evaluates the worth of the application in terms of both user testing and precision testing. ABeam is able to comparatively test multiple types of generative AI, including Azure OpenAI Service and open-source LLMs.
[Phase 3: Implementation in production]
Based on the details of what was defined up to Phase 2, ABeam Consulting builds a secure knowledge aggregation DB and generative AI-enabled knowledge interpretation assistant application. Depending on the generative AI model selected, clients can consider adopting either the provision of these applications as SaaS or through implementation in on-premise environments.
Knowledge CoE utilization case studies | Enhancing the use of investment memoranda
By repeatedly investigating and testing systems, aggregating investment memoranda from across all business units, and managing said memoranda in an easy-to-use format, with the established aims of “enhancing decision making,” “streamlining operations,” and “generating new ideas,” ABeam Consulting streamlined and enhanced all investment operations.
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