Sourcing
Map the talent landscape before sending outreach
Talent mapping is a research step that turns a role brief into testable candidate pools. Define the capabilities, list work contexts where they develop, sample profiles across those contexts, and record what the market evidence changes. Use the map to broaden or sharpen outreach; do not treat it as a private directory of people to contact indefinitely.
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Translate the brief into signals
Convert each important capability into observable profile clues without assuming one title. Ownership of a regional rollout might appear in project descriptions, team scope, customer types, or progression. Separate strong signals from weak proxies. A keyword may locate profiles, but it rarely proves the judgment or depth the role requires.
Build several background hypotheses
List direct, adjacent, and unconventional contexts. Direct candidates may need less domain learning; adjacent candidates may bring useful methods and a broader pool; unconventional candidates require careful transfer testing. Include relevant Indian locations and approved remote possibilities based on the actual work. Do not add cities simply to make the map look comprehensive.
Sample before scaling
Review a small number of profiles in each context and note common titles, career paths, evidence, and gaps. The sample is exploratory, not a claim about an entire market. Ask the hiring manager to review examples against the scorecard rather than personal familiarity. Update search terms only after explaining what the sample taught.
Record the map as hypotheses
For every pool, write why it may fit, what evidence to seek, likely learning needs, and the next test. This keeps the map useful to another sourcer and prevents names from replacing reasoning. Respect the organisation’s data practices when recording identifiable information and contact only through appropriate processes.
- Relevant work context
- Transferable capability signal
- Likely gap to test
- Next search or conversation
Let the map challenge the brief
Illustrative example: a team assumes customer education leaders must come from software companies. Sampling shows that professional training organisations contain people who build curricula, manage instructors, and measure adoption, though their product context differs. The team adds this adjacent pool and creates an interview probe for learning unfamiliar products. The map broadens evidence without lowering the outcome bar.
Decide when mapping is enough
Stop when the team has several credible pools, understands the main tradeoffs, and can write relevant messages. Endless mapping delays real conversations and creates false certainty from profiles alone. Reopen the research only when outreach reveals a wrong assumption, a pool is exhausted, or the role changes. Capture those triggers before beginning outreach. Keep a visible list of search exclusions as well as included pools. For each exclusion, state whether it came from evidence, a practical constraint, or an untested belief. This prevents a narrow map from presenting itself as the whole market. Review exclusions with the hiring manager.
Next step
Sample five profiles from each of three plausible background pools and ask the hiring manager what evidence transfers, what gap remains, and why.