Youth Hiring Compliance Tracker

3.70

Derivation Chain

Step 1 Improving youth mandatory employment compliance rates

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Step 2 Youth hiring management tools for public institutions

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Step 3 Automating compliance documentation for hiring mandates

Problem

HR managers at public institutions (approximately 1,100 organizations) must report their youth mandatory employment compliance rate to the government annually. Manually organizing recruitment, resignation, and contract period data in Excel and calculating compliance rates consumes an average of 3-5 business days each reporting cycle. The complex eligibility criteria for edge cases—such as mid-contract resignations and contract-type conversions—lead to high error rates whenever staff turnover occurs.

Solution

A SaaS that lets users upload CSV exports from HR systems (such as Saramin HR or Douzone) to automatically classify employees against youth mandatory employment criteria, calculate compliance rates, and generate PDF reports. Includes exception-case adjudication logic, year-over-year trend analysis, and hiring gap simulation.

Target: HR team managers at public institutions and state-owned enterprises with 50-500 employees

Revenue Model: SaaS Annual Subscription at ~$44/month per organization (~59,000 KRW), with 20% discount for annual billing. Free Plan for organizations with fewer than 50 employees

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

4.0/5

M Market

3.0/5

R Realizability

4.0/5

V Validation

4.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (72%)

Tech Complexity

29.3/40

Data Availability

23.1/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (59/100)

Competition

8.0/20

Market Demand

9.4/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium] Data Pipeline [low]

Dashboard