Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation

An accurate assessment of human capital or labor force variation in organizations is predicated upon collecting error-free data. When organizations report imprecise human capital or labor force data, problematic data analytic issues arise because the application of frequency-based indices of variat...

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Main Author: Salomon Alcocer Guajardo
Format: Article
Language:English
Published: IJMADA 2025-02-01
Series:International Journal of Management and Data Analytics
Subjects:
Online Access:https://ijmada.com/index.php/ijmada/article/view/65
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author Salomon Alcocer Guajardo
author_facet Salomon Alcocer Guajardo
author_sort Salomon Alcocer Guajardo
collection DOAJ
description An accurate assessment of human capital or labor force variation in organizations is predicated upon collecting error-free data. When organizations report imprecise human capital or labor force data, problematic data analytic issues arise because the application of frequency-based indices of variation obtain questionable measures of variation. This article addresses the assessment of vertical pay variation in organizations with count-based indices of heterogeneity. In doing so, this article demonstrates how imprecise categorical pay dispersion data negatively impacts the ability of logarithm-, mode-, and probability-based indices of variation to obtain accurate and reliable measures of pay variation. More importantly, this article demonstrates how count-based indices of variation overcome data analytic issues presented by imprecise data reported by organizations. In demonstrating their appropriateness to assess variation in organizations, the article assesses the measurement validity and reliability of unstandardized and generalized scores of pay dispersion obtained with count-based indices. By applying count-based indices to imprecise pay dispersion data reported by New York City municipal departments, this article addresses an important data analytic issue and shows that count-based indices are a viable alternative method for assessing variation in organizations when imprecise data limit the use of logarithm-, mode-, or probability-based indices. As an alternative method to frequency-based indices of variation, count-based indices provide additional data analytic techniques for assessing how pay and other forms of variation directly or indirectly affect organizational stability and performance.
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spelling doaj-art-c3cce4440dd2486d8e64028a98c7f5d22025-08-20T02:13:56ZengIJMADAInternational Journal of Management and Data Analytics2816-93952025-02-0151Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variationSalomon Alcocer Guajardo0BizSavy An accurate assessment of human capital or labor force variation in organizations is predicated upon collecting error-free data. When organizations report imprecise human capital or labor force data, problematic data analytic issues arise because the application of frequency-based indices of variation obtain questionable measures of variation. This article addresses the assessment of vertical pay variation in organizations with count-based indices of heterogeneity. In doing so, this article demonstrates how imprecise categorical pay dispersion data negatively impacts the ability of logarithm-, mode-, and probability-based indices of variation to obtain accurate and reliable measures of pay variation. More importantly, this article demonstrates how count-based indices of variation overcome data analytic issues presented by imprecise data reported by organizations. In demonstrating their appropriateness to assess variation in organizations, the article assesses the measurement validity and reliability of unstandardized and generalized scores of pay dispersion obtained with count-based indices. By applying count-based indices to imprecise pay dispersion data reported by New York City municipal departments, this article addresses an important data analytic issue and shows that count-based indices are a viable alternative method for assessing variation in organizations when imprecise data limit the use of logarithm-, mode-, or probability-based indices. As an alternative method to frequency-based indices of variation, count-based indices provide additional data analytic techniques for assessing how pay and other forms of variation directly or indirectly affect organizational stability and performance. https://ijmada.com/index.php/ijmada/article/view/65Data analyticsDiversityGuajardo index of diversityReliabilityValidity
spellingShingle Salomon Alcocer Guajardo
Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
International Journal of Management and Data Analytics
Data analytics
Diversity
Guajardo index of diversity
Reliability
Validity
title Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
title_full Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
title_fullStr Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
title_full_unstemmed Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
title_short Assessing compensation and organizational variation with imperfect data: An application of count-based indices of variation
title_sort assessing compensation and organizational variation with imperfect data an application of count based indices of variation
topic Data analytics
Diversity
Guajardo index of diversity
Reliability
Validity
url https://ijmada.com/index.php/ijmada/article/view/65
work_keys_str_mv AT salomonalcocerguajardo assessingcompensationandorganizationalvariationwithimperfectdataanapplicationofcountbasedindicesofvariation