Not marketing.
An emerging body of research.
R7 is grounded in published academic research, validated through 200+ enterprise implementations, and currently undergoing structured empirical study in collaboration with Prof. Felix Oberholzer-Gee, Professor at Harvard Business School.
The Core Hypothesis
R7's central proposition is that two metrics predict business performance with greater precision than any traditional HR measurement:
Revenue Hypothesis
Revenue ∝ Customer Acquisition ∝ % A-Players in Critical Roles Acquired. A-Players in revenue and market-facing roles bring knowledge and innovation that drive customer acquisition.
Profit Hypothesis
Profit ∝ Customer Retention ∝ A-Player Tenure in Critical Roles. A-Players who stay know the company DNA deeply — they drive customer retention, operational excellence, and compounding value.
This hypothesis is supported by converging evidence from 200+ implementations and is being validated through a large-scale empirical study across organizations in Asia-Pacific.
Academic Foundation
R7's measurement architecture draws on established academic research across multiple disciplines:
| Research | Finding | R7 Application |
|---|---|---|
| Aguinis & O'Boyle (2012) | High performers generate 400% more in standard roles, 800% in complex ones. Performance follows power-law, not normal distribution. | Validates the A-Player thesis: the difference between an A and B Player is not marginal — it is multiplicative. |
| Huselid, Beatty & Becker (2005) | Strategic workforce differentiation — not all roles have equal impact. 15–20% of roles drive disproportionate value. | Validates role criticality segmentation (Critical/Standard/Support) and the 15-60-25 distribution. |
| Sackett et al. (2022) | Corrected GMA validity from 0.51 to 0.31. Job knowledge (r=0.40) and structured interviews (r=0.42) are stronger predictors. | SF34 predictive validity coefficients and assessment method recommendations. |
| Miller (1956) / Dunbar (1992) | Working memory limited to 7±2 chunks. Stable social relationships capped at ~150. | Validates the Institutionalization Thesis: at enterprise scale (500+ employees), manual talent management produces systematically worse outcomes. |
| Oberholzer-Gee (2021) | Value Stick framework: competitive advantage through raising customer willingness-to-pay and lowering employee willingness-to-sell. Making work more attractive lowers WTS without competing on compensation. | R7's role-relative measurement architecture provides the infrastructure for systematic WTS reduction — matching employees to roles where they excel increases intrinsic satisfaction, creating talent market differentiation independent of compensation. |
Extending the Value Stick into Talent Markets
In Better, Simpler Strategy, Prof. Felix Oberholzer-Gee argues that firms create competitive advantage through two mechanisms: raising customer willingness-to-pay and lowering employee willingness-to-sell. The customer side of this equation has mature measurement infrastructure — decades of CRM systems, NPS scores, journey analytics, and revenue attribution models. The employee side does not.
This asymmetry creates a specific research question: can systematic talent measurement infrastructure enable organizations to lower employee willingness-to-sell through better role-person fit, rather than through compensation? When employees are matched to roles where they consistently exceed expectations, intrinsic satisfaction rises — reducing the compensation premium required to retain them. This is the mechanism Oberholzer-Gee identifies as the most sustainable form of WTS reduction: making work itself more attractive, rather than paying more for unattractive work.
R7's measurement architecture — tracking talent quality, conversion rates, and retention across seven lifecycle stages — provides the empirical infrastructure to test this hypothesis at scale.
Prof. Oberholzer-Gee, Andreas Andresen Professor of Business Administration at Harvard Business School, serves as research advisor to this validation program, bringing the strategic theory lens to R7's practitioner-developed methodology.
The current research focuses on a large-scale empirical study across organizations in Asia-Pacific, examining how talent management maturity correlates with EVP distinctiveness and talent market outcomes. A research survey instrument has been co-developed with Prof. Oberholzer-Gee to capture this relationship at the construct level.
This work extends Oberholzer-Gee's Value Stick into a domain where measurement has been conspicuously absent, and connects R7's practitioner evidence to established competitive strategy theory.
The Research Program: Two Streams
Stream 1: EVP & Talent Market Differentiation
Research advisor: Prof. Felix Oberholzer-Gee
Question: Does systematic talent measurement infrastructure enable organizations to build differentiated EVPs that lower employee willingness-to-sell?
Method: Large-scale cross-sectional survey of senior HR leaders across industries and geographies in Asia-Pacific. Survey instrument co-developed with Prof. Oberholzer-Gee.
Theoretical foundation: Value Stick framework (Oberholzer-Gee, 2021), strategic workforce differentiation (Huselid, Beatty & Becker, 2005), experience goods and EVP credibility.
Status: Survey instrument finalized. Data collection forthcoming.
Stream 2: A-Player Concentration & Business Performance
Research program: Independent R7 research
Hypothesis: Higher concentration of A-Players in Critical Roles correlates with revenue growth (via customer acquisition), and longer A-Player tenure in Critical Roles correlates with profit growth (via customer retention).
Method: Longitudinal implementation data from R7 deployments. Phase-gate measurements at M6, M12, M18, and M24+ correlated with organizational financial performance.
Theoretical foundation: Performance distribution theory (Aguinis & O'Boyle, 2012), cognitive science of measurement at scale (Miller, 1956; Dunbar, 1992), supply chain yield optimization.
Status: Prospective data collection underway across active implementations.
Practitioner Evidence (2010–2026)
200+ enterprise HCM implementations across APAC — technology, manufacturing, financial services, professional services, healthcare. Observed patterns in how organizations transition from activity-based to outcome-based talent metrics.
Research Advisory Collaboration
Prof. Felix Oberholzer-Gee serves as research advisor to R7's empirical validation program. The collaboration focuses on examining how systematic talent measurement infrastructure enables organizations to build differentiated employment propositions — extending Oberholzer-Gee's Value Stick framework into talent markets.
Empirical Validation Study
Structured study targeting organizations across Asia-Pacific. Phase 1: 8–12 warm organizations. Administer SF34 assessment, classify A/B/C at 12 months, correlate Recruit predictions with Rate outcomes. Outputs: criterion validity per SF, optimal weighting model, differential validity by role criticality, cross-cultural validation.
The Institutionalization Thesis
R7 introduces a critical evaluation criterion — the Sustainability Test:
When the answer is no — and cognitive science demonstrates it is no for any organization exceeding ~500 employees — HRTech becomes existential infrastructure rather than discretionary tooling. Performance calibration for a team of 10 requires processing 50+ data points, far exceeding Miller's Law limits. Cross-unit talent decisions exceed Dunbar's Number for stable relationships. Manual processes produce systematically worse outcomes at scale.
This reframes HRTech investment from "nice to have" efficiency tooling to "necessary infrastructure" for sustained business outcomes — the same way ERP is necessary infrastructure for manufacturing supply chains.
Participate in the Research
We are actively seeking organizations to participate in the empirical validation study. Participants receive a full R7 diagnostic and talent classification valued at $75K–$150K consulting equivalent.
Express Interest