Future Readiness Diagnostic

Every region has a demographic dividend. Almost none has the data to deploy it.

One 45-minute session per student, twice a year, in their language — turned into one comparable Future Readiness Score for every school, district and state.

Future Readiness ScoreDistrict view · Cycle 1 · illustrative
Live
67.4
+5.2 vs state
± 1.3 · 95% confidence interval
92%Profiled
4 / 38District rank
3Blocks flagged
Personality
Adaptability · wellbeing 7.2 / 10
Career
Aspiration–supply gap: 2 trades
Industry
Technical-seat alignment 78%
Learning style
Kinaesthetic 29% · visual 27%
4profilers, one 45-minute session
2×/yrcycles, on your academic calendar
7 daysfrom cycle close to dashboards
54dashboards — nine views × six scopes
§ 01 · How it works

Four profilers. One session. Every student.

Profiler 01

Personality

How students adapt and lead under change.

Profiler 02

Career

What they aspire to — with an AI-impact rating per career.

Profiler 03

Industry

Where they want to work — by sector cluster.

Profiler 04

Learning style

How they learn best — by pedagogy fit.

0 · log in5 · personality15 · career25 · industry35 · learning45 min
Any device2G is enough · works offlineClass teacher supervisesOne period per cycleStudent picks the language
§ 02 · The five-forces readiness model

Five forces decide whether students become your workforce — or someone else’s.

The diagnostic reads the leading signal at ages 13–18 — years before it shows up in employment statistics.

Your students AGES 13–18 · EVERY SCHOOL ONE COHORT A YEAR LEADING SIGNAL READ HERE · TWICE A YEAR FORCE 01 AI & automation 39% of core skills change by 2030 → LEVERS · GUIDANCE · TEACHER TRAINING FORCE 02 Sunrise industrial policy Talent is the binding constraint on every plant → LEVERS · INDUSTRY · SKILLS FORCE 03 The youth transition 1 in 5 young people NEET · 20.4% (2023) → LEVERS · GUIDANCE · EQUITY · VOCATIONAL FORCE 04 The demographic window One cohort per year passes the transition → LEVERS · BUDGET · HIGHER EDUCATION FORCE 05 Migration & mobility Talent leaves before a region knows it had it → LEVERS · MIGRATION · INDUSTRY
How to read it. Arrows are the forces acting on a region’s cohort; the dashed ring is where the diagnostic reads them, twice a year.
  • AI & automationof core skills change by 2030
    39%
  • Sunrise industrial policyis the binding constraint on every plant
    Talent
  • The youth transitionyoung people NEET · 20.4% in 2023
    1 in 5
  • The demographic windowpasses the transition every year
    One cohort
  • Migration & mobilitybefore a region knows it had it
    Talent leaves
Five decisions the model makes possible
§ 03 · From student to state

One score. Six scopes. Seven days.

Results roll up through your hierarchy exactly as it exists — nothing renamed, nothing re-entered.

  • Studentpseudonymised
  • Classteacher
  • Schoolhead teacher
  • Block / zoneblock officer
  • Districtdistrict officer
  • State / provinceministry

Every level sees the same evidence base through its own authorised lens. Every action is logged.

The Future Readiness Score

  • AI resistance
  • Industry stability
  • Adaptive personality
  • Learning agility
± confidence interval on every number9 views × 6 scopesTrend · drift · shift · anomaly
What each official sees, and decides
§ 04 · The workforce mandate

One dataset. Nine policy levers.

Evidence for all nine from the same cycle — tagged with the SDG targets it serves.

Skill development

44.488.6

Vocational education

44.444.5

Teacher training

44.c44.1

Higher education

44.388.5

Career guidance

88.688.b

Industry partnership

99.288.5

STEM gender equity

55.544.5

Migration insights

1010.288.5

Budget allocation

1616.61717.18
See five levers worked as decisions
§ 05 · Sustainable Development Goals

Leading indicators for the goals you already report against.

Census-scale evidence, disaggregated by sex, age and location — years before the official indicator moves.

4
Quality education4.4 · 4.5 · 4.c
5
Gender equality5.5 · 5.b
8
Decent work8.5 · 8.6 · 8.b
9
Industry & innovation9.2 · 9.5
10
Reduced inequalities10.2
16
Strong institutions16.6
17
Timely data17.18
The full target-by-target crosswalk
§ 06 · AI-ready for the sunrise economy

Find the students wired for tomorrow’s industries — first.

Every aspired career carries an AI-impact rating. Every district gets a sunrise-affinity read. One chart shows where to act.

0% 20% 40% 60% 80% 0 25 50 75 100 ACCELERATE build sunrise pipelines now REDIRECT affinity is there; aspirations point at exposed jobs SUSTAIN stable — keep measuring INTERVENE FIRST guidance + reskilling priority A B C D E F G H I J K L Share of aspirations pointed at high-AI-exposure occupations → Sunrise-sector affinity index →
The AI-readiness quadrant. Illustrative — districts plotted by AI exposure of aspirations against sunrise-sector affinity. Real values come from your first cycle.
Capacity 01AI-complementary capacities

Adaptability, learning agility, interpersonal and hands-on orientation.

Capacity 02Exposure of aspirations

What share of a cohort’s ambitions point at automatable work.

Capacity 03Sunrise-sector affinity

The pipeline an investment-promotion team can put in a pitch.

Semiconductors & electronicsGreen energy & hydrogenEV & batteryAI · data · digitalAgritech & food processingBiotech & pharmaAdvanced manufacturing+ your region’s own
§ 07 · Implementation

A statewide baseline in 12 weeks.

Weeks 1–2Setup & pilot

One district, ~50 schools, first 5,000 students.

Weeks 3–6District

Full rollout; first dashboards live.

Weeks 7–10Multi-district

Five representative districts.

Weeks 11–12Baseline report

Score, action plans, cabinet brief.

Then twice a year30-day windowDashboards in 7 daysAnnual evidence series
§ 08 · How to start

Three things start a first cycle.

Everything else — devices, training, processing, dashboards, the report — is covered by the programme.

01

Department sign-off

An MoU covering data sharing, privacy and pilot-district selection.

02

Pilot district nomination

One district, representative across rural/urban and gender ratios.

03

Read-only roster access

Your existing rosters, so we sync on day one — no new identity records.

Funded by CSR or philanthropy — zero cost to the exchequerDevelopment-partner programmesDirect procurement
Get started

See your region’s students the way a workforce planner needs to.

A 45-minute briefing: a live dashboard, the 12-week plan, and what a first cycle in your region would look like.

Any languageAny hierarchySDG-mapped evidenceAnalytics first