MASON WILHELM × 1805 Driven by Saigan

Intelligence-Led
Leadership Advisory

A multi-agentic, data-led approach to provide a readily consumable information layer on decades of top-tier search experience.

When combined with our insight and specialist market knowledge, the result becomes a true intelligence-led leadership advisory service.

Where we get the call

Click into the situation that matches the conversation you're having.

01

High-Stakes Appointments

When a single appointment shapes the next strategic chapter — and the Board needs to see the entire mapped market, not just the shortlisted names.
Open
02

Market Intelligence

When the question is people-shaped — how does our ELT compare, where will the next CFO come from, who's vulnerable across the sector — and the answer has to be the whole leadership market, not anecdote.
Open
03

Top-Team Succession

When the next CEO-1 conversation is 12–36 months out, not 0–6 — and the bench needs to be visible, benchmarked, and refreshable rather than improvised under pressure.
Open
04

Dynamic Assessment

When an organisation needs a dynamic data driven assessment of a leadership team, more than just individual reports. It can visualise the culture, operating rhythm and how the team's shape aligns to its strategy.
Open
The Engine

Driven by Saigan

One proprietary intelligence platform beneath all four. A single data lake, multi-agentic processing, microservice connectivity to global research — the synchronous interface between data and advisory.

How it works
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Situation Showing It Example ↩ Home
Situation · 04

When the team needs to be seen, not asserted

The combined leadership team appointed with data-led evidence and insight — not on negotiation, nor on inherited evaluations carried over from either prior organisation. A digital, real-time view of team dynamics, quantified in the platform's architecture rather than asserted in a deck. Equally true when a portfolio of companies is being consolidated under a single operating model.

What's at stake

The first ninety days set the tone for everything that follows. Retention decisions, culture decisions, structural decisions — all of them benefit from the same evidence base, applied identically to every leader in scope.

Two ELTs to One ELT — cohort competency radar comparing the full cohort against the modelled future ELT, with cognitive, psychometric, competence and motivation read-outs beneath.
Two ELTs → One ELT — when two leadership teams combine, every leader is measured against the same framework. Each radar maps a team's collective strength across eight executive competencies: at left, the full combined cohort (24 leaders); at right, the modelled future ELT (12) drawn from it. The four panels beneath show how cognitive, psychometric, competence and motivation scores shift from the current cohort to the modelled team.

Where traditional integration relies on inherited evaluations and the politics of who-knows-whom, this turns the combined team into a single live data set — every leader visible against the same metrics, every relativity quantified, every scenario modellable on the fly. The Board sees the team as a system, not a stack of CVs.

Where this gets called in

  • A fresh evaluation of existing leadership team — a capability and cultural assessment of an existing team, potentially going through transformation.
  • M&A — calibrate the combined ELT before naming it. Defensible at the board table; fair across both prior teams.
  • Multi-entity consolidation — bringing a portfolio of operating companies under a single leadership model. One framework, applied across all entities and geographies.
  • Post-acquisition integration — talent retention decisions in the first ninety days. Who to invest in, who to exit, where to bring outside hires — on evidence, not impression.
  • JV consolidation — when joint-venture leadership has to integrate into the parent without losing the people who made it work.
Assessment · Primary Search · External Gaps Engine
← Top-Team Succession Next · Showing It → Hub →
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Situation · 04 · Showing It

Four domains. One integrated view of every leader.

Each executive evaluated across the four domains where leadership effectiveness, fit and potential actually live — cognitive, psychometric, competence and motivation. A dynamic team assessment and modelling exercise to visualise every eventuality. Triangulated through dedicated instruments plus a structured competency interview. Two consultants in every conversation.

Domain 01
Experience
Track record — roles held, scale managed, outcomes delivered. External referencing + structured CV analysis + STAR interview.
Domain 02
Competence
Behaviour against 20 universal competencies, role-calibrated. SHL OPQ32 UCR + STAR interview, two consultants.
Domain 03
Motivation
18 motivational dimensions across Energy, Synergy, Intrinsic and Extrinsic factors. SHL MQ.M5.
Domain 04
Potential
Cognitive horsepower plus personality predictors of stretch. SHL Verify Interactive + OPQ32 32-dimension profile.

Four stages, one process — ten weeks

Wks 1–2
Cognitive
Inductive · numerical · deductive
Wks 3–4
Psychometric
OPQ32 · MQ.M5
Wks 5–7
Interviews
STAR · two consultants
Wks 8–9
Synthesis
Individual + cohort + dashboard
Week 10
Board Report
Evidence-led recommendations

The cohort, on one page

Dynamic, not static. The whole leadership team in a single live view — segmentable, scenario-modellable, refreshable as the organisation evolves.

  • Heatmap relativities across psychometric and cognitive metrics.
  • Filterable segmentation — legacy entity, function, geography, gender, potential.
  • "What if?" modelling — impact of losing a key leader or bringing one in.
  • Combination planning — design the future-state ELT against the data, not the org chart inherited from a prior chapter.
  • Two parallel reports per executive — a development-oriented report for them, a deployment-decision report for the Board.
Cohort assessment dashboard — top-left: Personality (OPQ32) stem scores across Relationships With People and Thinking Style. Top-right: Motivation (MQ.M5) standardised-score spider web across Energy, Synergy, Intrinsic and Extrinsic drivers. Bottom-left: Competency (UCF) likelihood scores across Leading, Supporting, Interacting, Analysing, Creating and Organising. Bottom-right: Motivational drivers, highlights and weaker substrates per executive.
Cohort Spider Web (OPQ Competency) — personality, motivation, competency and drivers, on one page.

v2 note: this is the page that needs to feel like a live platform. Today it's a flat capture; the next iteration links out to a recorded demo or embeds a slider between filtered/unfiltered states.

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Situation · 04 · Example

Leadership calibration across a multi-entity merger

Anonymised. A consolidated leadership team built on evidence rather than on the politics of either prior organisation — across multiple business units and geographies, on one framework, in twelve weeks.

Integration & Merger Multi-Entity Multi-Geography Day-100 Decisions

The brief

Combine the executive teams of two legacy organisations — and their underlying business units across multiple geographies — into a single future-state ELT. No inherited evaluations. No "this is how we did it on our side". One assessment framework, applied identically to every leader at the top two levels.

The approach

Four domains, four stages, twelve weeks. Two consultants per interview: one with deep market expertise, one with assessment specialisation. Same instruments, same scales, same competency framework — across every executive in scope, regardless of which legacy organisation they sat in.

The outcome

  • Defensible appointments — every seat backed by the same evidence, in the same format, comparable across both legacy teams.
  • Retention & development plans for the leaders not selected for the future-state team but critical short-to-medium term.
  • CEO-2 pipeline identified for longer-term succession — investment going where it returns.
  • Live enterprise dashboard for the Board, refreshable post-Day-100 as the new team begins operating.
Anonymised leadership calibration across a multi-entity merger: legacy entities A, B and C assessed through one framework, with calibrated leader IDs, fit scores, risk levels and future-state ELT recommendations.
Leadership calibration across a multi-entity merger — anonymised cohort view, common framework and future-state slate.

When the decision has to be defensible, start with the evidence.

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Situation Showing It Example ↩ Home
Situation · 03

When the next CEO-1 conversation is 12–36 months out

Succession is a relationship, not an event. Reactive succession is expensive and limits options. Proactive succession is a continuous mapping engagement that turns "we've got someone in mind" into a benchmarked, refreshable bench — internal and external — that the Board can interrogate.

What's at stake

The people two and three steps below the CEO matter as much as the CEO — and a list of names in a deck isn't a succession strategy. The Board needs to see the live universe, with internal candidates benchmarked against external reality, and the early signals when the external benchmark moves.

Live Succession Map — four CEO-1 seats (CFO, COO, CTO, CHRO) each shown with internal bench candidates ranked by readiness and external benchmarks alongside. Status indicators show readiness, tenure curve and flight risk.
Live Succession Map — every CEO-1 seat, internal bench and external benchmark side by side. Refreshable.

Where this gets called in

  • CEO-1 readiness — internal candidates benchmarked against the external universe. Quantified, not asserted.
  • CEO-2 pipeline mapping — the bench two layers down. Where it's deep, where it's thin, where to invest.
  • Emergency-transition contingency — the named alternates the Board would turn to in the first 48 hours of an unplanned exit.
  • Capability-shift succession — when the next chapter requires skills the current bench wasn't built for (digital, capital markets, geographic expansion).
Succession · Primary Assessment · Bench Eval Engine
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Situation · 03 · Showing It

The succession universe, continuously mapped

Where the executives in your succession universe came from, where they're going, how stable they are, and who you've never spoken to but should.

Three pillars of intelligence

Pillar 01
Talent Flow & Origin
Executive movement across industries and geographies, mapped over time. Surface under-utilised pools; prevent recycling the same names.
Pillar 02
Predictive Risk Scoring
Career-history, tenure and inflection-point analysis. Scores "gettability" of external targets; identifies internal flight risk.
Pillar 03
Performance Benchmarking
Aggregate-data benchmarking against market standards for capability, experience and compensation.

What the dashboard reveals

  • Talent flows — who hires from whom, in your sector and adjacent ones. The pipelines you already use; the ones you don't.
  • Flight-risk distribution — across your peer set, who is statistically overdue a move. A market signal, not a single profile.
  • Stability profile — Embedded · Settled · Settling · Watch · Flight Risk — sorted by at-risk concentration.
  • Origin profile — how much of your sector's leadership came from within it, and what that means for who to look at next.
  • Continuous, refreshable — not a quarterly anxiety. The map updates as the market moves.

Stability, by company

An aggregate read of the peer set — surfaces which competitors are about to lose senior leaders, and where the talent will land when they do. "The biggest succession event waiting to happen sometimes sits next door."

Executive Stability dashboard — top-left: stacked horizontal bars by AREIT showing the Embedded / Settled / Settling / Watch / Flight Risk distribution per company. Top-right: stability distribution donut across the full cohort (1,247 executives). Bottom-left: company tenure distribution histogram. Bottom-right: average tenure by AREIT bar chart with peer overlay.
Executive Stability Dashboard — stability bands, tenure curves and flight-risk concentration across the peer set.
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Situation · 03 · Example

Continuous succession mapping in practice

Anonymised. A 24-month engagement mapping the leadership universe for an integrated business preparing for a sequence of CEO-1 transitions.

Top-Team Succession Continuous Mapping Strategic Pivot

The brief

An ELT whose dominant career origin sat heavily inside its own sector — perfectly adapted to the last decade, increasingly mismatched against the platform the business was becoming. The question wasn't who comes next, it was where do they come from.

What the mapping revealed

  • The two largest internal feeder organisations shared the same operating heritage — the leadership pipeline was narrower than the org chart suggested.
  • The closest peer had already done what the brief implied — a template for diversification, half its leaders hired from outside the sector.
  • The capability the next chapter required sat in adjacent industries the firm had never recruited from.
Career Origin Mix dashboard — top: headline mix (AREIT Origin 42%, Property/RE 14%, Financial Svcs 6%, Non-Property 23%, Female 26%, 14 layers). Below: origin distribution donut, origin-by-function stacked bars across executive roles, and origin mix by AREIT showing each peer company's career-origin breakdown.
Career Origin Mix — where the leadership came from, by peer and by function.

The outcome

A live succession map refreshed quarterly. A named pipeline against every CEO-1 seat. A target list for proactive outreach before roles became live — and the early signals when an external target's tenure curve flagged "movable".

← Showing It Hub Dynamic Assessment →
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Situation · 01

When one appointment shapes the next strategic chapter

A defensible shortlist — built on the entire mapped market, not the seven names you see on a shortlist. AI underpins the research; partner judgement runs the conversation. The resulting advice is enriched by insights.

What's at stake

The Board doesn't want to hear "we know everyone in this space." It wants to see the evidence behind every name on the shortlist — and the names that didn't make it, and why. The search firms that built their reputation on the curated seven are quietly being displaced by the ones who can show the whole map.

Brief → Universe → Shortlist — funnel schematic showing the brief defined by function, sector, company calibre, leadership scale and cultural fit, expanding into a mapped universe of candidates (high-risk/high-reward, adjacent, direct peer), and narrowing to an evidence-backed shortlist.
Brief → Universe → Shortlist — the brief at the top, the mapped market in the middle, the evidence-backed shortlist at the bottom.

Where this gets called in

  • Strategy pivots / transformation – when organisations think differently, make pivots and embark on bold moves. They need to understand the market, available talent, unique talent pools.
  • New geographies — operating at pace in markets where the firm has no incumbent network. The methodology travels.
  • Low-coverage sectors — when the talent you need sits outside your traditional hiring pool, and identifying them requires deep research across sectors that don't overlap with your usual network.
  • Capability-shift appointments — when the next role is meaningfully different from the last one; the platform mitigates pattern-matching to the prior incumbent.
  • Time-pressured exec hires — when the research phase normally takes months and the business needs a defensible shortlist in weeks.
Search · Primary Assessment · For the Chosen One Engine
← Hub Next · Showing It → Hub →
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Situation · 01 · Showing It

From brief to shortlist — visible at every step

The agent UI, the likelihood curve, the results grid, the platform beneath them. Sequential, transparent, calibrated.

What clients see, week to week

Clients should not have to wait for the final shortlist to understand the work. The process is visible as it develops: brief calibration, mapped universe, scoring logic, coverage and evidence.

From brief to shortlist — a calibrated search strategy directing an orchestrated agent workforce that scrutinises, examines and compiles research, surfacing candidates beyond those already known to us.
From brief to shortlist — calibration, market mapping, scoring and evidence in one inspectable workflow.

The point is transparency without clutter. Each name has a reason, each gap has a status, and the final recommendation lands with enough context to be defended at the board table.

  • Scoping & scales calibrated to the brief — agreed before the research starts.
  • Live longlist dashboard — tier-banded, 5-dimension scored (functional fit · industry · company calibre · leadership scale · cultural fit).
  • Match reasoning in plain English — why each candidate ranks where they do.
  • Coverage grid — what we've spoken to, what we haven't, and why.
  • Weekly status update — short-form, refreshable.
  • Final shortlist evidence pack, defensible at the board table.
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Situation · 01 · Example

Cross-border senior appointment, on the same brief, in any market

Anonymised. Two engagements — one in Egypt, one in Australia — same methodology, same evidence pack, same pace. Geography is a variable, not a constraint.

High-Stakes Appointment Cross-Border Low-Coverage Market Pace + Fidelity

The brief

A senior appointment in a market with limited traditional search infrastructure. Candidates needed to be sourced internationally, scored consistently, and presented to the Board on the same evidence base any domestic hire would receive.

The approach

  • The semantic search engine surfaced the international universe — across geographies that don't overlap with traditional regional networks.
  • Scales calibrated to the brief, applied consistently to every candidate.
  • Weekly status updates kept the client embedded in the research, not on the outside of it.
  • Final shortlist landed with the same evidence pack a domestic appointment would receive.
Coverage Grid + Evidence Pack — 1,247 companies mapped across Industrials, Financials, Consumer, Technology, Energy and Healthcare, colour-coded by status (not yet contacted · attempted · spoken to · shortlist). Below: a shortlist evidence card showing 5-dimension scoring (functional fit · industry · company calibre · leadership scale · cultural fit) with a tier 1 candidate summary.
Coverage Grid + Evidence Pack — who we spoke to, who we didn't, and the evidence behind every shortlisted name.
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Situation Showing It Example ↩ Home
Situation · 02

When the question is people-shaped

"How does our ELT compare?" · "What skillsets are required to fulfil our future strategy?" · "Where will the next CFO come from?" · "Who's vulnerable across the sector?" Strategic questions that need the whole mapped leadership market for an answer — not anecdote, not the same seven names, not a generic sector report.

What's at stake

The Board's biggest people questions sit upstream of search. Before the role is open, the answer to "where will they come from?" shapes strategy. Before a competitor moves, the signal that an executive is "gettable" changes the conversation. This is the layer above the appointment — the leadership market understood as a system.

Peer ELT Comparison — executive leadership structures across four diversified Australian property groups (Harbourview LRE, Stonebridge, Aurelia Property Group, Summit Property Partners). Top: role pills colour-coded by category. Below: comparative intelligence (gender diversity, average tenure, flight-risk indicators, dominant career origin) and career-origin commentary per peer.
Peer ELT Comparison — four peers, side by side, on one framework.

This is not generic sector intelligence — that's a Gartner conversation. This is leadership intelligence: the people, the movements, the benchmarks, the structural patterns.

Where this gets called in

  • Competitive ELT benchmarking — how the leadership team compares to peers, structurally and stylistically. The evidence behind board-level talent reviews. How that aligns to strategy.
  • Sector leadership mapping — who's who, who's where, who came from where, who's overdue a move. Before the role exists.
  • Talent-flow analysis — the pipelines and pathways into a sector or function. Whose pool you can fish in; whose pool you're being fished from. Shapes how, and where you might go for future hires.
  • Board talent-strategy reviews — the people-shaped evidence behind structural and strategic decisions.
Engine · Primary Succession · Origin Data Search · Universe
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Situation · 02 · Showing It

The whole leadership market, on one page

Mapped, benchmarked, refreshable. Every senior leader across the peer set — career origins, tenure, stability scoring, flight risk — filterable by entity, function, geography and gender.

What it shows

  • ELT structural comparison — where peers have seats your team doesn't (and vice versa). The structural signal beneath the headline numbers.
  • Career origin profile — what proportion of each peer's leadership came from within the sector vs adjacent industries vs entirely outside.
  • Talent flow Sankey — who hires from whom, with thickness indicating volume of executive movement.
  • Stability distribution — Embedded · Settled · Settling · Watch · Flight Risk across the peer set, sorted by at-risk concentration.
  • Comparative intelligence table — ELT size, gender diversity, tenure, flight-risk scores, dominant career origins side by side.

And what it's not

This isn't a Gartner report. It isn't sector economics or industry forecasts. It's leadership-shaped intelligence — the people who lead the businesses in the sector, the patterns of their careers, the structural choices their organisations have made.

The same platform that powers Search and Succession produces this — refreshable, filterable, and as deep as the brief demands.

Cross-segment talent flows — Sankey diagram showing which segments executives came from (left) and which segments they're in now (right). Below: Industry Origin → Retail Segment Sankey showing which adjacent industries executives came from before joining the retail segment.
Cross-Segment Talent Flows — where executives came from, where they ended up; volume by ribbon thickness.
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Situation · 02 · Example

ELT benchmarking for a strategic pivot

Anonymised. An integrated business preparing to scale beyond its traditional operating model needed to know whether its leadership pipeline matched its destination — and how it sat against peers who had already made the shift.

ELT Benchmarking Peer Mapping Pre-Strategy Diagnostic

The brief

The business was rotating its capital allocation away from its historical engine and toward platform-style growth. The Board needed to understand whether the leadership structure reflected where the business had been, or where it was going.

What the mapping produced

  • 112 senior executives mapped across 12 peer organisations — career origins, tenure, stability scoring, flight risk, function.
  • Peer ELT structural comparison — surfacing where the client's team mirrored peers, where it diverged, and which divergences mattered.
  • Career origin diagnostic — the client's leadership came overwhelmingly from within the sector; the closest peer who had already made the strategic pivot drew half its team from outside.
  • Forward target list — named executives in adjacent industries who fit the capability profile the pivot required.
Comparative intelligence table showing peer ELT benchmarking across size, diversity, tenure, flight risk and career origin.
Comparative Intelligence Table — ELT size, gender diversity, average tenure, flight risk and dominant career origin, peer by peer.

Why it mattered

The Board moved from "we need to be more diverse in our hiring" to "here are the three sectors we should be hiring from, and here are the names already on the move." Strategy became actionable people-strategy in a single engagement.

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Overview Architecture Why It Matters ↩ Home
The Engine · Overview

Driven by Saigan

One proprietary platform beneath all four situations. Not an appendix — what the firm is built on. The same intelligence layer flows through Integration, Succession, Appointments and Market Intelligence, which is why the work is consistent, evidenced and refreshable.

From data to advice — the flow

Stage 01
Data
Continuously enriched from primary sources — career history, references, public filings. Depth, currency and provenance over headline count.
Stage 02
Information
Structured, deduplicated, semantically embedded. Queryable in natural language; joinable across people · companies · engagements.
Stage 03
Insight
40+ specialised agents. Brief-calibrated scoring. Benchmark layers. Synthesis across cognitive, psychometric and interview evidence.
Stage 04
Advice
Partner-led narrative. Defensible at the board table. The art remains human; the science is now AI-augmented.

What makes it different

  • A single data lake — every engagement adds to it; every engagement benefits from it. No re-mapping the universe each time.
  • Synchronous interface between data, insight and advisory. Microservice connectivity to global research. Live, not batch.
  • Multi-agentic processing — specialised agents do the discoverable work so the partner spends time on the human end of the call.
  • Built, owned and refined in-house since 2024. Not a wrapper around a third party.
← Dynamic Assessment Next · Architecture → Hub →
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Overview Architecture Why It Matters ↩ Home
The Engine · Architecture

Inputs → Engine → Deliverables

Three layers. Four engine components. One coherent process from brief to board pack.

Three-layer architecture diagram showing inputs, engine components and deliverables.
Three-Layer Architecture Diagram — inputs, core engine components and downstream deliverables in one view.

Four engine components

Component 01
Cultivation Database
The structured memory of every conversation the firm has had — continuously enriched from primary sources, queryable in seconds.
Component 02
AI Workforce
40+ specialised agents — enrichment, normalisation, classification, scoring. Continuous, not on-demand.
Component 03
Brief Matcher
5-dimension scoring against the mapped market: functional fit · industry · company calibre · leadership scale · cultural fit.
Component 04
Reporting Engine
Client-designed updates and outcomes. Live dashboards today; QR-linked content, podcasts and written long-form as the capture layer evolves. Two-mode output throughout: development-oriented and deployment-decision.
← Engine Overview Next · Why It Matters → Hub →
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Overview Architecture Why It Matters ↩ Home
The Engine · Why It Matters

AI underpinning high-quality search

Not data for data's sake. Not AI for AI's sake. The science of search is now AI-augmented; the art remains human. Partner-led judgement, on evidenced ground.

Trust earned, not asserted

Search firms have long claimed trust by virtue of being known. The reputational shortcut goes: "they're well-known, so the seven names they bring are the right seven." That worked when nobody could see the rest of the market. It doesn't work now.

v2 note (Jack): is there a more eloquent way of saying this rather than taking a shot at the big firms?

We don't claim trust — we show it. We share the methodology, the evidence trail and the rejected names alongside the chosen ones. Real trust is built on a truthful set of data, with partner-led judgement layered on top of facts, not just opinion. Then opinion, on top of facts.

Where this lands

  • Speed without sacrificing fidelity — research that traditionally took months, compressed to weeks; final judgement preserved.
  • Defensibility at the board table — every recommendation footnoted to evidence the Board can interrogate.
  • Continuity across engagements — the cohort you mapped last year informs the search you run this year.
  • A compounding advantage — every engagement makes the next one better-evidenced.

Data. Information. Insight. Advice.

The flow that turns a query into a decision the Board can defend.

When the decision has to be defensible, start with the evidence.

Closing-page candidates: partner contact strip · QR code to live HTML hub · podcast version link (per meeting).

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