WSCM-Lite: A Practitioner-Ready Implementation of the Weak Signal Cultivation Model

TL;DR

WSCM-Lite is a simplified, spreadsheet-compatible implementation of the Weak Signal Cultivation Model that maintains core tracking capabilities while reducing complexity and computational requirements.

Contribution

It introduces a lookup-table based version of WSCM that reproduces key behaviors without exponential functions or free parameters, enhancing accessibility.

Findings

WSCM-Lite replicates the full model's coordinate trajectories within 0.01 units.

It triggers escalation within two sessions, matching the full model's behavior.

Sensitivity analysis shows stability under +/-30% parameter variation.

Abstract

The Weak Signal Cultivation Model (WSCM) provides a mathematically rigorous framework for tracking frontline risk signals across a two-dimensional coordinate field using 15 equations and 16 tunable parameters. While this specification is designed for eventual software implementation, its computational requirements create an adoption barrier for organizations whose available infrastructure is a spreadsheet. This paper introduces WSCM-Lite, a lookup-table implementation that reproduces the full WSCM's coordinate trajectories within 0.01 field units while eliminating all exponential functions, state-dependent tracking, and free parameters. The simplification replaces continuous recency weighting with a four-row lookup table and removes consensus momentum and reversal amplification entirely, reducing the specification to seven formulas and five hardcoded constants. A 26-session worked example using the Gas Fumes signal from the parent paper demonstrates that WSCM-Lite traverses the same four-region path (Question Marks --> Lit Fuses --> Owls --> Sleeping Cats --> Question Marks) and triggers SMS escalation within two sessions of the full model. Five additional scenarios validate boundary behavior, and a sensitivity analysis confirms stability under +/-30% gap threshold variation. An accompanying Excel simulator and supplementary materials are publicly available at https://github.com/emmgonai/wscm-lite.