A leading pharmaceutical company's manufacturing division is responsible for formulating, packaging, and distributing products to more than 140 markets around the world.
The division’s internal knowledge management (KM) team was working on a number of initiatives to enhance and apply a custom taxonomy to its content, search tools, and project and collaboration workspaces. With a better taxonomy, the company's scientists and engineers can more quickly find relevant content. The division’s internal knowledge management team recognized that they didn’t have the taxonomy subject matter expertise in-house and desired external assistance. They invited Iknow to prepare and deliver a taxonomy workshop to the KM team to support this effort.
The objectives of the taxonomy workshop were to provide:
- A critique of the division’s current taxonomy development roadmap,
- Guidance on creating a forward-looking taxonomy, and
- Best practices for classifying content in the pharmaceutical industry.
Preparation for the workshop started several weeks prior to the workshop date. Iknow’s initial step was to prepare and submit a data request for information about the company’s existing taxonomies, its taxonomy development plans, and use of text mining and autoclassification tools. The pharmaceutical company provided the information. In all, Iknow reviewed over a dozen documents, including:
- Current-state assessment of the division’s taxonomy development,
- Description of the major taxonomy-related initiatives for the past five years,
- The company's future-state vision for a new knowledge management KM platform, and
- Requirements documentation on the future-state KM platform.
Iknow then identified several of the division's KM team members for interviews, development a detailed interview guide, and scheduled and conducted telephone interviews to ask questions about the information in the initial data request and to gather additional information. Specifically, the interviews provided further insights about the KM landscape, user satisfaction with the current KM platform, and potential opportunities for improvement.
Based on the initial data request and the findings from the interviews, Iknow drafted an agenda for the taxonomy workshop. The agenda included the following topics:
- Assessment of the existing taxonomies
- Methodology for taxonomy creation and application, including a number of “deep dives” into the following practical aspects:
- How to apply text analysis to identify terms and concepts to include in the taxonomy
- How to harmonize taxonomies created by disparate business units, functions, and departments
- How to merge repositories that contain similar document types and subject matter
- How to apply new taxonomy terms to existing content
- How to integrate existing enterprise data into the knowledge management platform
- How to perform autoclassification incorporating taxonomy and ontology models.
- Next steps
After a few refinements to the agenda and subsequent signoff, Iknow developed the workshop presentation materials and several case study examples.
Iknow delivered the half-day workshop to the manufacturing division's KM team and other key staff. The workshop was engaging and highly interactive. The staff benefitted from seeing actual taxonomies and taxonomy-embedded applications developed by Iknow for other Iknow clients.
In addition to the workshop, Iknow prepared a sixty-page written summary report. The summary document contained highlights from the workshop, a taxonomy development roadmap, and next steps.
The workshop resulted in a set of prioritized projects designed to accelerate the company’s taxonomy development process and a set of recommendations to enhance content findability and discoverability. The workshop taught the KM team how to create a useful taxonomy. The KM team also learned how to perform text mining and clustering to understand the contents of a repository.
Based on Iknow’s expertise demonstrated during the workshop, the KM head asked Iknow to support the development of an upgraded taxonomy and the incorporation of the taxonomy in autoclassification and faceted search applications.