Skilled financial planning: the cost of translating ideas into action

This work uses GOMS models to predict error rates and mental times for translating financial concepts into equations in two widely used interface representations, and concludes that interfaces having the keyword representation are far superior.

Abstract

We use GOMS models to predict error rates and mental times for translating financial concepts into equations in two widely used interface representations. The first of these, common to spreadsheet packages, is characterized by non-mnemonic naming and absolute referencing of variables. The second, common to non-procedural command-driven software, is characterized by mnemonic naming conventions and relative referencing of variables. These predictions were tested in an experiment using experienced financial analysts. Although the interface that allows mnemonic and relative names (called keyword) takes longer overall, it produces seventy-five percent fewer simple errors and requires less mental effort. Given the overall serious cost of errors in financial models, we conclude that interfaces having the keyword representation are far superior.