Reliability is central when working with executive and organizational data. We aim to be a dependable reference, while recognizing that companies evolve constantly and accuracy requires both technology and human judgment.
Corporate leadership changes more often than it appears. On average, out of 100 senior executives, only about 60 will still be in the same role and reporting to the same manager one year later.
Keeping organizational data accurate therefore requires continuous detection, verification, and review. This is an always-on process, not a periodic update.
The scale and the challenge
Every day, our challenge is the same. Among more than 1.35 million executives we follow, we must identify the few whose roles, responsibilities, or reporting lines have actually changed, usually over 5,000. These changes are scattered across thousands of sources, signals, and conversations. Finding the ones that matter, as they happen, is what keeps the data accurate every day of the year.
Technology-driven signal detection
• Continuous monitoring of approximately 5 million selected public and professional sources
• Advanced analytics to detect leadership signals, structural changes, and potential misses
• Machine learning models trained on historical data to surface the most relevant events
• GenAI tools used to extract, normalize, and compare organizational information at scale
Relevance analysis and prioritization
• Signals are ranked using predictive models based on past organizational patterns
• The system prioritizes for our analysts what is most likely to matter
• This ensures human attention is focused where it adds the most value
Human verification at the core
• A dedicated team of 20 highly trained in-house analysts reviews prioritized changes
• Analysts validate roles, reporting lines, and organizational context
• Findings are cross-checked against multiple independent sources
• Crowdsourced inputs from over 700,000 members help surface adjustments
Direct executive confirmation when needed
• When appropriate, executives are contacted directly by email
• This allows confirmation or correction of sensitive or ambiguous changes
• It adds a level of accuracy rarely achievable through automation alone
Safety net and coverage control
• When no changes are detected, targeted human checks confirm organizational stability
• Detection coverage is continuously audited to identify blind spots
• Sources, models, and rules are adjusted when gaps or inconsistencies are found
Ten years of continuous improvement
• These workflows have been developed and refined over more than 10 years
• They rely on proprietary tools built specifically for organizational data
• Several components were developed with academic research teams, including MIT
We do not claim perfection.
We invest continuously in better models, better tools, and better processes
so that accuracy improves as organizations and data complexity increase.
Explore this section
• Compliance and permitted use
Related topics:
• REST APIs
• Company & executive data coverage
• Data delivery
Questions? Contact us.