What do employers actually want?

What skills matter? What credentials will they trust? Can better data improve hiring? After three months investigating how hiring decisions actually get made, Ian Davidson thinks we're starting with the wrong question.

The better question is: Which decision are you trying to change?

Hiring isn't one decision. Job boards decide which opportunities people see. Applicant tracking systems decide who gets surfaced. Recruiters decide who gets a conversation. Hiring managers decide who gets the job.

Together, those decisions allocate one of hiring's scarcest resources: human attention.

And the decisions affecting the most candidates often happen when the system knows the least about them.

Episode 10 brings together insights from Allison Danielsen, Matt Plummer, Andrew Cunsolo, Jordan Franklin, Matt Charney, Brad Robinson, and James Harris.

The investigation began as a search for better signals. It became the Hiring Decision Architecture: a framework for identifying which hiring decision we're trying to improve, what information could make it better, and where to intervene.

EPISODE CHAPTERS

00:00 — What Do Employers Actually Want? Why skills and credentials may be the wrong starting point.

05:00 — What Hiring Managers Really Evaluate Motivation, potential, work ethic, learning, and what resumes miss.

12:00 — Skills-Based Hiring and the Replacement Problem What replaces degree and experience requirements?

14:00 — Application Overload, ATSs and AI Hiring What happens when employers receive 1,000 applications?

16:00 — Hiring Is an Allocation of Human Attention Why consequential decisions happen with limited candidate information.

18:00 — The “Cake Lady” and the Candidates Systems Miss A great hire who never would have survived the conventional process.

21:00 — Better Candidate and Opportunity Profiles Why resumes and job descriptions both leave out critical context.

26:00 — The Hiring Decision Architecture Start with the decision, then identify the information needed to improve it.

28:00 — Talent Marketplaces and Workforce Intelligence What if matching systems understood people's needs and constraints?

33:00 — Fix the System Before the Hiring Manager Improve the decisions determining who reaches a human.

37:00 — AI, Machine-Readable Data and Verifiable Skills Technology can use richer information without overwhelming recruiters.

40:00 — Better Talent Marketplace Matching Matching capability, potential, motivation, needs, and opportunity.

42:00 — Learning and Employment Records + Trusted Career Profile How portable, verifiable data could improve hiring decisions.

45:00 — The Demand-Side Case for Better Workforce Data Employers aren't asking for LERs. They're asking for help with 1,200 applicants.

48:00 — Which Hiring Decisions Should We Fix? Stop starting with data. Start with the decision.

Research supported by the U.S. Chamber of Commerce Foundation and T3 Innovation Network.

Explore the Hiring Decision Architecture: https://signollabs.com/hiring-decision-architecture/

Signol Labs: https://signollabs.com/

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