I Wish I'd Known - Tactical & Strategic Applications of Talent Intelligence

Talent intelligence starts with a simple habit: applying design thinking to sourcing by constantly asking why. Why can't we hire? Why did we hire a hundred people? How did we get there and where do we go next? The answers only matter if the underlying data is validated rather than assumed, and a working definition of talent intelligence treats it as the metadata of talent — where people move, how their pay changes, how their careers progress, and eventually how those external signals connect to internal performance after hire.

A live walkthrough of salary research covers the gap between crowdsourced and validated data, and how to combine both:

• Self-reported compensation sites and forums that break pay into base, bonus and equity, and how easily that data can be scraped for ongoing monitoring
• H-1B visa filings, which are public and disclose exact salary ranges for sponsored roles at named companies
• SEC filings through EDGAR, including 10-K forms and proxy statements that show executive compensation, stock sales, and year-over-year pay tables at public companies
• Why current market value matters more than a candidate's original offer, since equity granted as a dollar amount at hire loses or gains real value as the stock price moves, and how sector-specific ETFs give a fast read on whether an industry's total compensation is trending up or down
• Using Excel's stock history function to pull historical share prices against scraped compensation data, producing quick comparisons of how total compensation has shifted by company, location, or date
• Timing a search around a company's financial reporting dates, since an offer made just before or after earnings can land very differently depending on where the stock sits
• Filtering by ticker and industry to spot companies whose stock has fallen sharply, since falling valuations often precede layoffs and signal where candidates may be more open to a conversation

None of this replaces the actual conversation with a candidate about what they are willing to work for, but it replaces guesswork with numbers that can be checked, and turns a spreadsheet of data points into an argument for what a role should really pay.