Position Match
Position Match is an AI-powered tool that finds the best internal candidates for any open or planned position. You describe the role, and the engine evaluates your entire talent pool — ranking employees by how well they fit the job requirements.
Step 1 — Fill in Position Details
Open Position Match from the navigation sidebar. The form in the center panel has four required fields:
| Field | What to enter |
|---|---|
| Position Name | The target job title. Start typing to see autocomplete suggestions from existing positions in the system. |
| Supervisor Position | The direct manager's current position title. Used to calibrate layer expectations. |
| Supervisor Layer | The manager's seniority layer. Select from the dropdown — see the Layer Reference below. |
| Job Description | A description of the role's responsibilities and requirements. You can write it manually or generate one automatically. |
💡 Tip: The more specific and complete your job description is, the more accurate the match results will be. Generic Job Description produce lower-quality rankings.
Step 2 — Generate a Job Description (Optional)
If you don't have a ready-made job description, TalentForge can generate one for you:
- Fill in Position Name, Supervisor Position, and Supervisor Layer.
- Click Auto - Generate.
- The system drafts a job description based on the position title and supervisor context. It draws on standard role definitions and your organization's hierarchy.
- Review and edit the generated text before proceeding. The Job Description field is fully editable.
Note: The Generate Match button remains disabled until the Job Description field contains at least 10 characters.
Step 3 — Apply Candidate Filters (Optional)
Click the Filters section to expand optional filters that narrow the candidate pool before scoring:
| Filter | Description |
|---|---|
| Age Range | Select one or more decade buckets (e.g., 30 – 39, 40 – 49). |
| Job Layer | Restrict candidates to specific seniority levels (e.g., Section Head, Department Head). |
| Min Tenure | Only include employees with at least this many years of service. |
| Max Tenure | Only include employees with at most this many years of service. |
Filters are combined — for example, selecting Layer = Department Head and Min Tenure = 5 will only evaluate Department Heads with 5 or more years at the company.
💡 Tip: Leave filters blank to evaluate your entire eligible talent pool. Filtering too aggressively on a small organization may result in too few candidates.
Step 4 — Generate Match
Click the Generate Match button at the bottom of the form. The button is enabled only when all required fields are filled.
A loading indicator appears while the engine is running ("Matching Talent..."). This typically takes a few seconds.
Reading the Results
Results appear in the right panel after matching completes.
Results Header
| Element | What it shows |
|---|---|
| Top Matches | Up to 20 best-fit candidates returned by the AI |
| Candidates ranked / evaluated | How many candidates were returned vs. the total pool that was scored |
| Position tag | The target position name shown as a label |
Pool Quality Warning
If the AI determines that fewer than 5 candidates scored 60% or above, a warning banner appears at the top of the results. This usually means the internal talent pool does not have strong matches for the role, and you may want to widen your filters or reconsider the position requirements.
Candidate Cards
Each candidate is shown as a card in a two-column grid:
| Element | What it shows |
|---|---|
| Rank | Position in the AI-ranked list (#01, #02, etc.) |
| Avatar | Photo or initials |
| Name & current position | Employee's name and their current job title |
| Fit Score | Overall match percentage |
| Match bar | Visual indicator of the fit score |
Click any card to open the candidate's detail view.
Candidate Detail View
Clicking a candidate card opens a full detail panel on the right side.
Score Breakdown
| Score | What it measures |
|---|---|
| Overall Match Score | The combined AI-assessed fit percentage |
| Experience Match | How closely the candidate's prior roles and job history align with the target position |
| Education Match | Whether the candidate's degree level and field are appropriate for the role |
| Skills Match | How many of the role's required skills the candidate already holds (shown when LinkedIn skill data is available) |
Interpreting the Overall Score:
| Score | Meaning |
|---|---|
| 80–100% | Excellent fit — minimal gap between candidate profile and role requirements |
| 60–79% | Strong candidate — specific gaps may exist; review "Why They Fit" for details |
| 40–59% | Moderate fit — notable development needed before the employee is competitive for this role |
| Below 40% | Poor fit — significant preparation required |
Why They Fit
The Why They Fit section shows the AI's written rationale for the score — explaining which aspects of the candidate's background make them a good (or partial) match for the role. Read this section to understand the reasoning beyond the numbers.
Badges
Below the score, badges show the candidate's current:
- Job layer (e.g., Section Head)
- Talent class (e.g., STAR Leaders, Growing Talent)
- Years of service
View Career Path
Click View Career Path to open the candidate's full Career Navigator page. The page opens pre-loaded with the position match fit scores so you can see the full career path in context of the target role.
History Panel
The History sidebar on the left stores your last 20 position match searches. Each entry shows the position name, supervisor context, and timestamp.
| Action | How to use it |
|---|---|
| Restore a search | Click any history entry to reload the form and results from that session |
| Delete one entry | Click the trash icon on a history row |
| Clear all history | Click the Clear All button at the bottom of the history panel |
| Toggle sidebar | Click the panel icon at the top-left to collapse/expand the history sidebar |
History is saved locally in your browser — it is not shared with other users.
Business Unit Diversity
If your account has access to multiple business units, the engine automatically prevents any single BU from dominating the top 10 results. No more than 4 candidates from the same BU will appear in the top 10 slots, ensuring the results represent talent across your full scope.
LinkedIn Data Notice
The system shows a banner if a candidate's profile is missing LinkedIn-sourced skills or work experience. Skills Match scores and keyword overlap accuracy improve significantly when LinkedIn data is available. Use the Data Enrichment module to import this data for candidates whose profiles are incomplete.
Layer Reference
| Layer | Seniority |
|---|---|
| Staff | 1 (entry level) |
| Team Leader / Specialist | 2 |
| Section Head / Sr. Specialist | 3 |
| Department Head / Expert | 4 |
| Division Head / Master Expert | 5 |
| BU / SU Head | 6 |
| Director | 7 |
| C-Level | 8 |
| President Director / CEO | 9 |
| Board Commissioner | 10 (highest) |
Common Mistakes to Avoid
- Using a vague job description — Short or generic JDs (e.g., "Manage finance") produce low-quality rankings. Add specific responsibilities, required qualifications, and domain keywords.
- Over-filtering the candidate pool — Setting both layer and tenure filters on a small BU may return too few candidates for the AI to produce a meaningful ranking.
- Ignoring the pool quality warning — A warning banner means the match quality is low. Consider relaxing filters or adjusting the job description before acting on the results.
- Not checking "Why They Fit" — The score alone does not tell the full story. Always read the AI rationale before shortlisting a candidate.