PA Instruments
The measurement & decision primitives
A is one composable measurement or decision primitive, exposed as a single standalone tool. They are the ingredients: each does one thing well, statelessly, and can be called on its own or wired together. The toolbox's products — the meals a buyer meets — are built by composing them.
The ingredients
Thirteen instruments across five spokes today. Each links to its spoke's explainer.
Preference Modeler
explainer →MaxDiff — generate
Build a deterministic set of best/worst choice tasks from a list of items.
preference-modeler.maxdiff.generate
MaxDiff — score
Turn best/worst responses into per-item and per-variable preference weights.
preference-modeler.maxdiff.score
Present↔future gap
Score the gap between where something is today and where you want it — the change intent.
preference-modeler.present-future
Performance Validity
explainer →Rater alignment
Measure how closely raters converge, item by item, on the same target.
performance-validity.alignment
Directional alignment
Score a leader's alignment with those above, below, and beside them.
performance-validity.directional-alignment
Calculus
explainer →Distribution fit
Fit a statistical distribution to a sample and report how well it actually matches.
calculus.distribution-fit
Importance reconcile
Reconcile what people say matters against what the data implies matters.
calculus.importance-reconcile
Forecasting
explainer →Interval scoring
Grade past interval estimates against what actually happened — coverage and sharpness.
forecasting.interval-scoring
Bayesian combine
Merge several independent estimates of one quantity into a single calibrated posterior.
forecasting.bayesian-combine
Measurement recommend
Given a thing to measure and your constraints, recommend how to measure it.
forecasting.measurement-recommend
Measurement catalog
The menu of available measurement methods and the ranges they produce.
forecasting.measurement-catalog
Factor Models
explainer →Analytics plan
Rank models by priority relevance, then order measurement by value of information.
factor-models.analytics-plan
Empirical importance
Derive each item's importance from the variance of its observed outcomes.
factor-models.empirical-importance
Two instruments worth naming for what they unlock: (only gather data that would change the decision) and (merge many estimates into one calibrated answer). The preference instruments use and capture; the fit instrument reports .
Composed into products
The same instruments, wired together over typed contracts, become the products a buyer actually meets.
AnyComp
The compensation decision OS — composes preference + value-of-information instruments.
Leadership Index
Manager epistemic quality — composes alignment + interval-scoring instruments.
Analytics-Plan Generator
Priorities into a value-ranked measurement plan — composes preference + forecasting instruments.