Talent Assessment and Development

Traditional talent assessments ask people to answer questions about themselves. The problem isn't that self-report data is useless — it's that it captures what people think about themselves, which can differ significantly from how they actually show up. Someone who scores highly on a "leadership" self-assessment may not be the person you'd want leading your next major initiative.

Conversation-based assessment captures something different: how a person thinks, how they frame problems, what they reach for when complexity is high, and how they describe their approach to real situations they've navigated.

Profile & Characterize mode

Savo's Profile & Characterize interview mode is designed for assessment contexts. Rather than asking evaluative questions, it draws out narrative — specific experiences, past decisions, how someone approached a challenge. The structured conversation follows a consistent protocol, with adaptive follow-ups based on each participant's responses. That consistency makes scores comparable across participants in a way that informal interviews or manager assessments rarely are.

What you can measure

P&C mode sessions can be designed to assess a wide range of competency and developmental dimensions, such as:

• Leadership orientation — how a person thinks about leading versus managing, and how they navigate the difference
• Problem-solving approach — how they frame complex problems, where they look for information, how they move through uncertainty
• Communication style — how they calibrate their communication to different audiences and contexts
• Learning agility — how they approach unfamiliar domains, and what they do when they don't have the answer
• Collaboration patterns — how they work with others when goals conflict or stakes are high

The specific dimensions are defined in the Signal Event, so they can be tailored to your organization's competency framework, your role requirements, or your development program goals.

Fairness and traceability

Every score links to the specific conversation passages that produced it — which means any score can be reviewed against the source material. The scoring rubric is human-authored and calibrated against reference sets. AI does not write its own scoring criteria. This matters for fairness: the instrument is designed to surface dimension-relevant evidence, not to detect demographic signals or proxy variables.

Use cases

• Selection and screening — structured assessment of candidates at scale, with scores comparable across evaluators and consistent over time
• Development planning — understanding individual strengths and growth edges with enough specificity to drive meaningful development conversations
• High-potential identification — moving beyond performance ratings to competency depth as a basis for development investment
• Succession planning — building a picture of organizational capability that org charts and performance reviews don't capture

For a deeper look at how Savo measures and scores dimensions, see Understanding Dimensions and Confidence Levels and Why They Matter.