Workforce Analysis

Example report · illustrative data

The method

ONE ENGINE

This report turns live UK labour-market signals into decision-ready insight at role level. It quantifies hiring friction, exposure to AI redesign and pay positioning across every role in scope, then prioritises the response: source, retain, reskill or relocate.

The same engine runs on three inputs, the external market, your internal workforce, or competitor hiring. The input changes; the analysis does not.

Data foundation. Built on free and official UK sources: job-advert volume and advertised pay (Adzuna), earnings by occupation and region (ONS ASHE via Nomis), AI exposure (ONS GAISI index mapped to SOC), supply and diversity (ONS Annual Population Survey), skills and adjacency (Nesta Open Jobs Observatory). Figures shown here are illustrative sample data for layout review.

Executive summary

THE HEADLINE

Bottom line:

AI exposure is moderate overall but concentrated in software, data and cloud roles, exactly where hiring is hardest. That overlap, not raw scarcity, is the strategically significant finding: these roles cannot be cheaply backfilled externally and the work itself is being reshaped. The response is proactive, reskill internally and source in deeper regional pools before attrition creates irreversible gaps.

Where to act

RECOMMENDED ACTIONS

Protect critical capability

Ring-fence skilled operational and engineering roles (DoH ≥ 8, AI < 25) with targeted retention and succession before institutional knowledge walks.

Reskill in cloud, data & cyber

Build internal pathways into roles with AI ≥ 50 and DoH ≥ 8 that external hiring alone cannot fill. Service desk is the clearest feeder.

Source in deep regional pools

Focus net-new hiring in Leeds, Manchester, Glasgow and Belfast where supply per role is 5-9x London and competition is manageable.

Realign pay where it bites

Where internal pay sits >10% below market for DoH ≥ 8 roles, adjust bands. Prioritise London cloud and cyber first.

AI exposure

AI IMPACT DISTRIBUTION

Roles by AI Impact band (ONS GAISI mapped to SOC). Gold line is the UK market baseline.

Key insight: The distribution is left-shifted versus the market, reflecting a large operational and field footprint. But the combined 50-69 bands sit above the market average, an above-average concentration of high-exposure digital roles that warrant task-level analysis and structured reskilling.

The decision map

AI IMPACT vs DIFFICULTY TO HIRE

Each point is a role. Thresholds: AI Impact 30 (vertical), DoH 8 (horizontal).

Key insight: Population sits in all four zones. Protect (top-left) holds skilled operational roles. Reskill (top-right) holds transformation-critical cloud, data and cyber roles. Recruit (bottom-left) is abundant, addressable hiring. Resize & Automate (bottom-right) is where AI tooling can absorb volume in admin and contact-centre work.

Location landscape

UK MARKET BY CITY

Median values per city. Bubble size is candidates per role (supply depth).

Key insight: The landscape splits cleanly. London, Cambridge and Reading combine high DoH with thin pools, these need retention, reward and selective relocation. Northern and devolved-nation hubs (Leeds, Manchester, Glasgow, Belfast) offer multiples more candidates per role and should anchor growth, sourcing and reskilling.

Location	Roles	Median DoH	Median AI	CPR	Median pay	Risk

Deep dive

ROLE SPOTLIGHT

Location	Candidates	Postings	CPR	Avg pay	AI	DoH

Key findings: London and Edinburgh are uniformly tight (CPR 3-5). For functionally identical work, Leeds and Belfast offer 3-4x the candidate availability at 25-38% lower pay. For greenfield platform capacity these regional hubs are the clear winners, and the strongest case for building internally rather than buying in London.

Build, not buy

RESKILLING PATHWAYS

Strategic read: Moving service-desk talent into higher-AI roles is not contradictory. It is how Albion builds internal supply for roles that are mission-critical, externally scarce and being reshaped by AI rather than eliminated by it.

Pay positioning

INTERNAL vs MARKET

Internal base pay (vertical) vs market mid-point (horizontal). The diagonal is parity. Demo values normalised to £.

Key insight: Median pay gap is . The widest under-market gaps cluster in cloud, data and cyber in London, Cambridge and Reading, precisely the high-AI, high-DoH roles where external hiring is already near-impossible. Below-market pay there compounds the problem and escalates retention risk.

Order of magnitude

ILLUSTRATIVE VALUE

Read this correctly: these are directional scenarios showing the scale of value the engine can inform. They are not finance-ready commitments and should be pressure-tested against productivity, redeployment and change-cost assumptions.

What happens next

SAME ENGINE, YOUR DATA

This demo uses illustrative data. The real value appears when the engine is pointed at the client’s internal workforce, their live hiring activity, and their competitor market, to build a live quarterly workforce-risk view.