Overview
What this research program is and why it exists. The frame the rest of the work hangs on.
The Fourth & Two research program
Fourth & TwoforthcomingForthcoming — research arc to be designed.
research / arc / decision-support
When the answer exists on a range, how do you make it executable for a decision-maker? Monte Carlo simulation, formal Value-of-Information analysis, regression-based surrogate calculators, scenario modeling at population scale, and the principal-issues framing that names the load-bearing measurement set every decision actually rests on.
Why this matters
The portable claim — what this arc lets you understand outside the surface domain.
The headline question executives bring to a planning cycle is rarely 'what is the answer' — it is 'what is the range of plausible answers, and how confident can I commit before more is known.' This arc is the methodological spine for any forced-choice point where the population, the inputs, or the future are themselves uncertain. Fourth & Two applies it to fantasy decisions; the People Analytics Platform applies it to compensation; the principal-issues thesis names why most domains fail to do this at all.
Spans
Products this arc cuts through. Each application is sometimes the lead empirical apparatus, sometimes the funding/data-collection platform.
In the magazine
Editorial pieces from principal-issues that draw on this arc.
A slide shows a single confident effect; the data only said "about" so, on a sample thin enough to cover both transformative and noise — and the decision gets made on a number a good week of data from reversing. The answer was never the product; the error bar is. Decision theory settled it sixty years ago: information is worth only what it changes about the decision in front of you (value of information), so the question isn't "what's the answer" but "how much certainty does this decision deserve, and what would it cost to get it." Certainty is a dial with a posted price — and telling a customer when more analysis isn't worth buying is what proves it isn't a sales tactic.
Ask three comp pros whether one company's Senior Engineer equals another's Staff Engineer and you get three defended, uncheckable answers — leveling is an argument, every time, because work has no shared reference. Pantone fixed exactly this for color in 1963: own the reference everyone maps into, not the ink, and give it coordinates so difference becomes a computed number. Jobs can carry coordinates too — kept in separate spaces, honest enough to say “no confident match,” frozen in editions. The irony that opens the market: the survey houses copyright and enforce their structures, which fences them permanently out of the neutral position none of them can occupy — and universal math locates their jobs without ever storing their codes. We own the universal structure; licensed crosswalks stay client-side. Never pull an Adobe.
The job is the primary key of the economy of work: you compare pay, plan hiring, audit representation, and map careers by job — yet in nearly every dataset it's free text two companies fill in differently and no one reconciles. The market chased skills (the attribute) and skipped the job (the entity they attach to). Governments built the codes coarse-but-open; the survey houses built them rich-but-locked; nobody built the canonical architecture that's both. Get the job right — function × level, synthesized to map every source — and pay, skills, supply/demand, representation, and careers all compose onto it. The hilltop went unclaimed because the path up was labeled boring.
Drill-down — full arc surface
Cross-product. Source application shown on each entry.
Overview
What this research program is and why it exists. The frame the rest of the work hangs on.
Forthcoming — research arc to be designed.
Methodology
How the work is done — instruments, protocols, the standards each report inherits.
Reports
The actual research findings — phased results, research-question briefs, applied analyses.
The headline thread — load-bearing analytics, the structure-first pipeline, and the value stack (Employee Lifetime Value → activation → Net Activated Value → opportunity), demonstrated live on a compensation command center running structured synthetic data.
Companion to the thesis — the compensation theory underneath the value stack. Why pay is three kinds of value (external, internal, personal) reconciled into one number, and how an errant value equation becomes an attraction, activation, and attrition problem.
Anticipated thread — Monte Carlo decision support, principal-issues-set framing.
Audience tiers
The same headline research surfaced four ways: peer-review, engineering, general audience, product.
Bibliography
Field positioning — formal references and literature maps grounding the research threads.
Preregistrations & protocols
Studies and intervention protocols filed before execution.