Find Out Who Your Knowledge Depends On Before You Have To.
The Expert Dependency Radar analyses your approved knowledge by ownership and surfaces concentration risk — so you know which people are single points of failure before they become one.
35% of your critical knowledge in one person's head is a fragile system.
Expert dependency risk is the gap between the knowledge your organization has and the number of people who hold it. When 35% of your critical knowledge belongs to one person, you have a fragile system — and you usually don't know it until that person leaves.
Knowledge concentration invisible in day-to-day operations
Teams don't feel concentration risk until it hits. Day-to-day, the expert is present and the knowledge is accessible. The vulnerability only becomes visible when they're gone.
No early warning system for succession risk
Without analysis, there is no signal that concentration is building. The Expert Dependency Radar provides that signal — updated automatically from your approved knowledge base.
Organizations discover the gap only when the expert has already left
Exit interviews, knowledge transfer meetings, and shadow periods all happen too late. The Radar lets you address concentration while you still have the option to act.
Concentration by owner. Amber at the 30% threshold.
Ownership breakdown by person
How many approved articles each knowledge owner holds — sorted by article count so the highest-dependency owners appear at the top.
Concentration percentage
What percentage of total approved knowledge each owner holds. A simple, interpretable number that converts article counts into risk signal.
Amber highlight at >30%
Any owner who holds more than 30% of total approved knowledge is highlighted in amber — a single-point-of-failure warning that prompts action.
Risk score
Computed from concentration percentage multiplied by the count of owners who exceed the single-point threshold. A relative risk indicator, not an absolute rating.
Unowned articles
Knowledge articles with no assigned owner are surfaced separately — knowledge without a steward is as risky as knowledge concentrated in one person.
Five steps from Radar to risk reduction.
- 01
Prioritize cross-training for high-concentration owners
Identify owners above 30% concentration. Their knowledge needs a second person who understands it — the Radar shows you exactly who to focus cross-training on first.
- 02
Assign owners to unowned articles
Find articles with no owner in the Radar's unowned section. Assign a responsible owner before those articles become orphaned knowledge with no one accountable for their accuracy.
- 03
Run Loss-of-Expert Simulation for at-risk owners
The Simulation models the specific article-level impact of any owner's departure — turning the Radar's concentration signal into a concrete departure plan.
- 04
Use Memory Graph for visual confirmation
The Memory Graph visualizes the same ownership structure spatially — useful for presenting concentration risk to leadership or a safety officer.
- 05
Set review cycles for high-concentration owners
High-concentration owners are also your highest-staleness risk if they become unavailable. Prioritize their articles in your review cycle scheduling.
Questions about the Expert Dependency Radar.
What does >30% concentration mean?
That one person owns more than 30% of your total approved knowledge. This creates a single point of failure — if that person leaves, 30%+ of your organizational memory is at immediate risk.
Is 30% always dangerous?
30% is a calibration signal, not a hard rule. Context matters: a 2-person team will naturally have 50% each. What matters is whether the concentration represents critical operational knowledge with no backup.
How is the risk score calculated?
It is proportional to the highest individual concentration multiplied by the count of single-point owners. It is a relative signal, not an absolute risk rating.
Find your knowledge single points of failure.
The Expert Dependency Radar is available in the Insights section. Book a demo to see it running on a real knowledge base.