#1:  Modelling the ROI of High Cost HR Initiatives (2002).
1. An intervention is defined as any HR initiative which seeks to intervene in the day-to-day functioning of employees and their work.
2. If money, time, or effort is expended on any activity within a business, then, unless that business is a charity, there should be a firm expectation that the expenditure can be assessed for its eventual return (profit) – expressed monetarily as a Return on Investment (ROI).
3. ROI modelling is defined to be the entire and complete costing of an HR intervention, taken together with an explicit detailing of the process of “how and when” the benefits of such an intervention are to be realised by a company.

This paper shows how the cost of implementing the Gallup Workplace Audit may be critically evaluated in terms calculating of the likelihood of making or losing money as a corporate-wide Gallup Audit score is increased. i.e. The question posed and answered via computational simulation is "what are the odds of a company making or losing money as a result of an increase in score from 36 (average) to something higher". The paper may be downloaded as a pdf file here (1Mb).

7th July, 2006: I will be updating this paper soon with the advent of my new "Correlation Visualizer" and change-score ROI "effect calculator" program, which will allow users to calculate these kinds of odds/effect outcomes over the score range of any kind of test, given the relationship between a test and a criterion outcome is known.

#2:   The Use of Standardized-Normatively Scaled Scores within a Performance-Oriented Selection Process (August 2006)
Two questions are asked in this paper:

Q1. When a test publisher/employer/recruiter begins using a psychometric test scale as part of a selection process, where a particular score on a scale is required to be used as a threshold for a “minimum likely performance/literacy standard” or “filter” for applicants, the first question they face is “which score should be used as the “threshold”?
Short answer: The response requires a clear choice to be made, between setting a threshold subjectively or using an empirical evidence-based approach. Arguments are made for each approach, concluding that an empirically informed decision is all but mandatory except in exceptional circumstances.

Q2. Should raw or normatively-interpreted scores be used in selection settings? That is, should an employer use the raw scale score to represent a magnitude of some attribute for a candidate, or instead, re-express the score relative to a normative set of scores provided by a homogenous group of individuals (whether “general population” or some specific subgroup)?
Short answer: From some detailed “closely-matching-reality” data simulation work, there is clearly no justification whatsoever for using transformed scaled scores such as stens, T-Scores, stanines etc. in a performance-oriented selection process, except where the norms are properly representative, substantive in constituent number, and remain static (i.e. are not cumulatively updated or “bootstrapped”).

This is a fairly hefty19-page whitepaper - with some substantive exemplar analyses and argument, explaining why the use of transformed scores is not recommended for work in selection settings where a cut-score or threshold is being used as a pre-screen.

It is downloadable here (660k) as a pdf file.