Career Asset Structuring Workshop

3.20

Derivation Chain

Step 1 Career-based re-employment & re-entrepreneurship matching

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Step 2 The problem of not knowing how to digitally structure 20–30 years of career experience

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Step 3 The problem of not seeing a clear path for converting structured career assets into income-generating activities

Problem

When a 55-year-old director-level executive at a large corporation considers post-retirement options—re-employment, consulting, lecturing, or entrepreneurship—they first need to decompose 25–30 years of experience into 'expertise keywords.' However, most people in their 50s describe their careers only as '30 years in sales' or '25 years in production management,' unable to articulate the specific competencies within (e.g., B2B SaaS sales process design, automotive parts QC auditing, chemical plant safety management). Career coaching costs 100,000–300,000 won (~$75–$225) per session, and most offer only generic advice.

Solution

Users input their work history conversationally (company name, department, key responsibilities, achievements), and the system automatically extracts expertise keyword tags and visualizes a 'career asset map.' Based on the extracted keywords, it assesses fit across four monetization paths (re-employment, consulting/advisory, lecturing/mentoring, Solo Entrepreneur venture) and provides realistic first steps for each path. It also matches and displays anonymized transition case studies from peers with similar career backgrounds.

Target: Ages 50–58, manager-to-director level at large or mid-sized corporations, 1–3 years before retirement or recently retired, actively considering next steps

Revenue Model: Career asset map generation is Free. Monetization path detailed Report (PDF) at 9,900 won (~$7.50). 1-on-1 online career structuring session (1 hour) at 49,000 won (~$37).

Ecosystem Role: Education

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

3.0/5

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 (73%)

Tech Complexity

29.3/40

Data Availability

23.3/25

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 (56/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

7.5/15

Solo Buildability

10.0/10

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

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

Dashboard