Imagine this: your R&D team is racing toward a critical deadline, and an unexpected technical question pops up. Jane in Boston needs to know whether a particular polymer blend has already been tested under high-humidity conditions. She’s checked the usual folders, skimmed through volumes of reports, and even pored over old email threads—yet still has no answer. Meanwhile, halfway around the world in Munich, Raj has the exact results Jane needs, meticulously documented in his lab notebook. Only he has no idea that she exists or that her question even matters.

This familiar scenario, urgent problems lingering because expertise is invisible, happens every day in large enterprises. Employees send “Does anyone know about X?” emails, ping half a dozen people in Slack, or resort to hallway cold calls, all while high-value minutes tick away. In organisations where innovation is the lifeblood, such delays compound quickly, stalling projects and eroding morale.

But it doesn’t have to be this way. By rethinking knowledge management to focus on people as much as documents, companies can connect employees to the precise expertise they need, instantly. In this post, we’ll explore why conventional document management systems fall short, outline four strategies for locating expertise, and illustrate how a platform like Phlow brings these approaches together in practice.

 

The Hidden Cost of Expertise Gaps

We often quantify “knowledge management” in terabytes of stored documents, but the true cost of not knowing who knows what shows up in lost hours and stalled innovation. According to industry research, employees can spend up to 20% of their workweek hunting for information. This time could otherwise be spent designing experiments, optimising processes, or iterating on prototypes. If an engineer spends two hours each day merely chasing down answers, that amounts to 10 full days of lost productivity per quarter.

The impact isn’t just numeric. When your team can’t quickly find the right expert, decisions get delayed, and confidence takes a hit. A project that could have shipped in six months easily stretches to nine, simply because key questions went unanswered. Moreover, employees grow frustrated when they feel bogged down by administration rather than empowered to innovate. In a knowledge-driven world, expertise blind spots become not just an annoyance, but a strategic liability.

 

Why Documents Alone Don’t Cut It

It’s tempting to believe that centralising all files in a single repository solves the knowledge problem. After all, a well-structured document management system (DMS) provides version control, access permissions, and searchable metadata. But storing information and surfacing expertise are not the same thing. Here’s why a DMS alone leaves critical gaps:

1. No Expertise Directory. Seeing “Document Author: John Doe” tells you who wrote a file, but not whether John has the deep domain knowledge you need for a new challenge.

2. Siloed Knowledge. Documents often live in departmental or regional folders. Without cross-linking, insights produced by one team remain invisible to another.

3. Static Context. A PDF can’t explain why a decision was made, what trade-offs were considered, or whose input drove a conclusion. Only the original author, or someone who was in the room, knows the nuanced backstory.

In effect, a DMS turns knowledge into digital clutter: the information exists, but employees must know exactly where to look and what to ask. The result is a constant cycle of “hunt and hope,” undermining productivity and slowing down innovation.

 

Four Strategies to Connect People and Expertise

Transitioning from document-centric to people-centric knowledge management involves blending culture, process, and technology. Here are four proven strategies:

1. Expert Profiles & Skill Taxonomy

Begin by creating a living directory of expertise. Invite each employee to maintain a profile listing their key skills, recent projects, and areas of interest. Structure these profiles around a clear taxonomy—for example, breaking down “Materials Science” into subdomains like “polymer chemistry“, “nanocomposites“, or “corrosion engineering“.

Why it works: A searchable directory transforms vague inquiries into precise queries. Instead of emailing “Anyone know about corrosion inhibitors?”, you can filter for “Materials Engineers—corrosion,” instantly surfacing the right contacts. Over time, as people update their profiles, the directory becomes richer and more accurate than any static document archive.

2. Automated Expertise Discovery

Manually populating profiles is a good start, but it rarely keeps pace with real-world changes. That’s where AI-powered analysis comes in. By scanning authored documents, tagged content, and contributions to internal forums, sophisticated platforms can infer each employee’s expertise.

Why it works: Automated discovery uncovers “hidden experts”, those who contribute valuable insights in niche areas but may not self-nominate. It also reduces administrative overhead. When AI flags that you’ve co-authored several papers on “machine learning for predictive maintenance,” it can suggest adding that skill to your profile, keeping the directory current without waiting on manual updates.

3. Communities of Practice & Q&A Forums

Expertise thrives in communities of practice, groups of like-minded professionals who share challenges and solutions. Establishing dedicated forums (digital or in-person) around topics like “Advanced Battery Materials” or “Biocompatible Polymers” encourages peer-to-peer exchange.

Why it works: These forums capture tacit knowledge, the unwritten tips and tricks that seldom make it into formal reports. When someone posts a problem and multiple experts weigh in, the entire thread becomes a living document, searchable by keywords and easily linked back to the experts who contributed. This not only democratises knowledge but also fosters a culture of collaboration.

4. Integrated Expert Finder Tools

Finally, embed “Ask an Expert” widgets directly into employees’ daily workflows, whether that’s a project management dashboard, CRM system, or intranet homepage. With a simple query interface, teams can type natural-language questions like “Who has experience with high-pressure extrusion?”

Why it works: By integrating the expert finder where work actually happens, companies eliminate the need to switch between systems. The tool surfaces the top three experts, along with links to their most relevant documents or forum posts. Employees can reach out directly or view prior Q&A threads, slashing response times from days to minutes.

 

Best Practices for Expertise Location

To maximise impact, combine these strategies with solid governance and incentives:

• Define a Clear Taxonomy. Collaborate cross-functionally to agree on skill categories that reflect real business needs, avoiding overly broad or ambiguous labels.

• Incentivise Contributions. Recognise top contributors in communities and forums. Consider peer-nominated awards or include knowledge‐sharing in performance reviews.

• Blend AI with Human Oversight. Use automated suggestions for skill updates, but empower individuals to refine and validate their own profiles.

• Measure and Iterate. Track key metrics, question-response time, forum engagement rates, directory search success, and refine processes based on real data.

With these practices in place, expertise location evolves from a one-off project into a sustaining engine of organisational learning.

 

Case in Point: How Phlow Bridges the Expertise Gap

Phlow’s Enterprise Intelligence brings these principles together on a unified platform:

1. Knowledge Graph Foundation. Phlow interlinks people, documents, and data into a semantic network, so that both content and contributors are instantly discoverable.

2. Dynamic Expert Profiling. Through continuous analysis of authored content and forum activity, Phlow builds and refreshes individual skill profiles, keeping them accurate without manual effort.

3. Embedded Expert Finder. A lightweight, context-aware interface surfaces the best experts for any query, alongside links to their most relevant insights.

4. Community Hubs. Phlow nurtures communities of practice by capturing Q&A threads, notes, lessons learned, and best practices in a central repository, ensuring that tacit knowledge is preserved and shared.

As a result, when an R&D manager asks “Who in our global organisation knows about PET recycling processes?”, Phlow doesn’t just return dusty documents, it delivers a ranked list of specialists, highlights their past contributions, and connects teams for real-time collaboration.

 

Putting It Into Action

1. Audit Your Knowledge Landscape. Map where expertise currently resides, documents, chat logs, and, most importantly, in employees’ heads.

2. Choose Your Pilot. Select one business unit or technical domain to launch your expertise-location initiative. A focused pilot yields quick insights and user feedback.

3. Deploy and Promote. Roll out expert directories, AI-driven profiling, and community forums. Communicate benefits clearly and offer training sessions.

4. Measure and Refine. Monitor usage metrics, collect user feedback, and continuously improve your taxonomy, incentives, and integrations.

5. Scale Across the Enterprise. Share success stories from the pilot, expand communities, and embed expert-finder tools into additional workflows.

By starting small and iterating, you’ll build momentum, and soon, connecting to in-house experts becomes second nature.

 

Conclusion & Next Steps

In knowledge-intensive enterprises, expertise is the most critical resource, and yet it remains remarkably hard to access. By moving beyond static file repositories and embracing people-centric knowledge strategies, you transform “Does anyone know?” into “Here’s who knows—and here’s what they’ve already shared.” That shift drives faster problem-solving, deeper collaboration, and sustained innovation.

Ready to see this in action? Book a demo today and discover how an expertise-location solution can plug your knowledge gaps and supercharge your teams.