Silicon Labs is a $1 billion global leader in secure, intelligent wireless technology. The organization faced significant challenges in content usability, traceability, and findability, hindering their internal training workflows and access to critical knowledge assets.
They needed to organize hundreds of training courses and get their content chaos under control to improve training workflows, increase course usage and find critical knowledge assets to fulfill different search use cases.
They also needed to track course publishing to various downstream systems. In this webinar we will walk through how a standardized information architecture leveraged initially in the training organization will now be applied to new businesses to improve content findability for their business functions.
We will hear from Bob Power, VP of Engineering for Silicon Labs and the Earley Information Science (EIS) delivery team about how Silicon Labs addressed challenges of course and content usability, traceability, and findability by rethinking how information was managed, organized, and published from concept through development and deployment.
Course content was in DropBox and shared and personal drives that were either not widely available or well socialized. Confluence provided a way to advertise and host course content, but findability was a core issue. Several attempts at organizing their course content resulted in different organizing principles that added to the confusion of finding courses.
Previous efforts were not successful due to a lack of a formalized approach. The company recognized the need for a disciplined approach to information architecture, to address their problem of course organization and findability not only for the immediate use case for R&D training but across the enterprise including HR and Customer Training.
The key consideration was to begin with a narrow focus and develop the approach in a way that is flexible and extensible. This means that the new standardized taxonomies and content structures (metadata, security and workflow models) can be extended and applied to other parts of the business more quickly reducing overall effort and at a lower cost. Building a repeatable, sustainable yet flexible structure enables faster turnaround time, improved organizational agility, higher quality information and increased user satisfaction.
The design was also created with the future in mind – as the organization explores Large Language Models (LLMs) like ChatGPT, this same work will be necessary to train those technologies on organizational content and knowledge.
By starting with a narrow focus and scope, the project demonstrated clear success and established core content and knowledge process hygiene that other departments are lining up to also apply to their knowledge and information challenges.
To quote Bob Power “We are finding that as departments see our success, they want to emulate it. With the governance process we have in place as well as the carefully designed information models, we can extend to new applications more quickly and cost effectively. The assets from this project become increasingly valuable as they are extended and applied.”
Attendees will leave with a greater understanding of:
- Ways to explain the value of and need for information architecture design.
- How to engage leaders and department heads in the process.
- How cross functional teams can be aligned for success.
- Making the abstract (information architecture) concrete through prototyping and MVP iterations.
- How to quickly demonstrate value in a 3-month program with clear success outcomes.
We will review core concepts including the critical need for controlling knowledge and content, why content processes and architecture are important for the entire organization, typical content challenges and approaches for remediation, the mechanics of the content design (domain modeling, content structure, taxonomy, schema, metadata, tagging, etc.) and governance and decision-making processes and structures.
We will also discuss what’s next on the content and information horizon including the role of machine learning and why these approaches are needed for AI Powered applications including LLMs and ChatGPT types of information access.
Seth Earley, Founder & CEO, Earley Information Science
Bob Power, Vice President, Silicon Labs