Who Knows What? How to Find (and Prove) Expertise Inside Your Company

Every company has hidden experts—people with the knowledge to win proposals, guide projects, or mentor colleagues—but too often, they remain invisible. The real challenge isn’t a lack of expertise, it’s knowing who knows what and being able to prove it when it counts.

The quiet tax of not knowing “who knows what”

When teams can’t quickly find an internal expert, work slows down, proposals get weaker, and risk creeps into delivery. Multiple recent studies show the drag is real: Microsoft’s 2024 Work Trend Index found that 57% of people struggle to find the information they need at work and over half say they’re wasting time searching or recreating content. (Microsoft research)

APQC’s survey data (~1,000 knowledge workers) shows employees spend ~2.8 hours every week just looking for or requesting needed information, with more time lost to communication churn and unnecessary meetings—collectively “one quarter of a knowledge worker’s time” lost to productivity drains.

Vendor studies corroborate the magnitude: in large U.S. enterprises, inefficient knowledge sharing has been estimated to cost ~$47M/year in lost productivity—driven by hours waiting on colleagues or recreating existing know-how.

Back-of-the-envelope ROI: If your 1,000 knowledge workers each lose even 2.8 hours/week, that’s 2,800 hours/week. At a conservative $60/hour loaded cost, that’s $168,000/week → $8.7M/year—before considering proposal win-rates, cycle-time, or rework. [Change the employee count and their average loaded cost to compute for your company or team.]

From corporate “yellow pages” to AI expert-finders

Long before enterprise search, global firms built “corporate yellow pages”—internal directories that mapped who knew what across far-flung teams. The knowledge-management literature describes these as expertise locator systems: searchable staff lists that point you to the human with the tacit know-how you need. 

Real-world cases followed: Siemens ShareNet connected sales and marketing to experts and best practices worldwide; Xerox Eureka captured field technicians’ fixes so peers could find and reuse them—both classic examples of expertise discovery improving time-to-resolution. 

In high-reliability settings, expert-finding isn’t optional—it’s mission critical. NASA has formalized “knowledge capture and transfer” to mitigate knowledge loss during retirements and transitions, and runs agency-wide lessons-learned systems precisely so teams can find the right know-how (and the right people) when it matters. 

As we discussed recently, on the shop floor, the skills matrix made expertise visible at a glance so leaders could staff, cross-train, and maintain quality. That same visual pattern now scales to knowledge work across large global enterprises. 

What the research says about expert visibility and performance

In organizational science, teams with a strong Transactive Memory System (TMS)—i.e., a shared “map” of who knows what—perform better, coordinate faster, and adapt more effectively. Recent peer-reviewed work (2024+) continues to show TMS as a mediator of job performance and a driver of team outcomes: when people can find the right expert, they solve problems faster and with higher quality. (Read more here)

Meanwhile, the everyday drag remains substantial: multiple large-scale workplace reports put time spent searching at ~3 hours per day on average—a huge productivity sink that compounds when expertise is siloed. 

Compliance: why “provable expertise” matters

Beyond speed, many regulated frameworks expect demonstrable competence:

• ISO 9001:2015 (Clause 7.2) requires organizations to retain documented evidence of competence—which, practically, means you must know who your experts are and show proof.
• ISO 27001 (Clause 7.2) requires ensuring and evidencing competence for roles affecting the ISMS.
• SOC 2 doesn’t prescribe competence the way ISO does, but auditors evaluate Communication & Information (CC2.x) and expect role-appropriate training evidence and clear responsibilities—both helped by expert mapping and sign-off trails.

If you can prove an employee’s critical skill with an expert sign-off, that’s gold for audits, customer due diligence, and internal risk management.

But when put to practice, all of this still matters outside of compliance frameworks for workforce planning and workforce strategy. 

A practical playbook to surface and prove expertise

1. Inventory the work: Start from job architecture and competency groups; enumerate the critical skills per role. (Keep names human-readable.)
2. Make expertise visible: Use skill flags (e.g., “Expert,” or “Mentor”) and publish them where managers and proposal teams actually look.
3. Centralize discovery: One search box across skills, roles, competency groups, people, and content—rank by skill level, recency of validation, and project relevance. Also for resumes and CVs.
4. Create an expert network: Let experts opt-in to mentoring, proposal reviews, “ask me” hours—with capacity signals to avoid overload.
5. Require sign-offs for critical skills: Lightweight workflows where recognized experts validate that a colleague can perform a safety- or compliance-critical task.
6. Close the loop: Capture evidence (project artifacts, assessments, reviews, training dates, etc.). Keep an audit trail: who validated whom, when, and why. (Helps with compliance framework evidence, such ISO/SOC 2, or industry specific audits.)
7. Measure what matters: Track time-to-staff proposals, mean time-to-answer internal questions, mentor participation, % of critical roles with at least 2 experts, and audit exceptions.

Where SkillsDB fits

• Powerful search across skills, job roles, and competency groups to surface people with exactly the right expertise—fast. And, across resumes, CVs, job descriptions, or any uploaded document.
• Skill flags to clearly delineate experts (and reviewers/mentors) at the skill and job-role level, discoverable in search.
• A visual skills matrix that shows all experts for any role, group, or the entire company—ideal for staffing, succession, and competence evidence.
• Expert sign-off flows that create provable records tied to people and skills—ready for audits and customer questionnaires.

Finding experts isn’t just about efficiency—it’s about building confidence that your teams can deliver, adapt, and prove competence when it matters most. If you’d like to see how SkillsDB makes expertise easy to search, validate, and showcase, we’d be glad to walk you through it. Book a free demo.

FAQs

How does AI help me find the right expert faster?

By unifying your skills, roles, competency groups, profiles, and project artifacts into a single search index, then ranking people by skill level, validation recency, and context (e.g., similar past projects). AI can also summarize profiles and suggest alternates if an expert is at capacity.

Can an expert “game” the system by self-claiming skills?

Require expert review/sign-off for critical skills and expire validations after a period or after major tech changes. Keep audit trails for who validated whom and why. Also, corroborate with manager grading of employee skills that can be a flag for inaccurate employee claims. 

How do we avoid overloading top experts?

Use capacity signals (current load, mentoring slots) and “near-expert” alternates suggested by AI. Rotate reviews and reward participation.

What about privacy and bias?

Limit visibility of sensitive attributes; focus on skills and evidence. Review ranking features for bias; provide appeal mechanisms and human override.

How often should expertise be re-validated?

At a minimum, plan to re-validate critical skills and competencies once a year using skill surveys or assessment flows. For modern teams or fast-moving skills and competencies, consider a quarterly or bi-annual review (maybe even monthly) to keep pace with changes. 

Can we use this for mentoring and succession?

Yes—publish opt-in mentor flags, track sessions, and pair near-experts with experts. NASA’s approach emphasizes continuity before retirements—good practice for any specialized team. 

What metrics should we watch?

Time-to-staff proposals, MTTA (mean time to answer), % critical skills with ≥2 validated experts, rework rate, audit exceptions.

Does this help with ISO 9001/ISO 27001/SOC 2?

Yes. ISO 9001 Clause 7.2 requires documented evidence of competence; ISO 27001 7.2 expects competence for roles affecting the ISMS; SOC 2 auditors expect clear communication, training, and role-appropriate evidence under CC2.x. Expert sign-offs + audit trails support all three. 

What is a “corporate yellow pages” directory?

In the late 1990s, global firms built “corporate yellow pages”—simple, searchable directories of internal experts—so a proposal manager in Frankfurt could find the exact microwave-antenna specialist in Singapore. Siemens’ ShareNet and Xerox’s Eureka are classic examples: they didn’t just store documents; they helped employees find the right people behind them, improving win rates and time-to-resolution. Today’s expert-finding tools are that idea—but with modern search, signals, and audit-ready proof.

How do we prevent AI from “hallucinating” expertise?

Ground the system in first-party, governed data (your skills and validations), restrict generative answers to cited sources, and show provenance (who signed off, when). Coveo’s 2025 EX report highlights employee skepticism when AI isn’t grounded.