Purpose

The purpose of this paper is to perform a comparative analysis between the productivity metrics recommended in the literature and those that companies in the knowledge-intensive services sector use in practice.

Design/methodology/approach

To collect information, a systematic review of the literature was used, to apply virtual surveys and interviews among managers of different companies representing the sector. For data analysis, categorical optimal scales, homogeneity tests, tetrachoric correlation matrices, word clouds and association coefficients for dichotomous variables were used.

Findings

There are association patterns between the metrics used and the nature of the work performed. Despite the heterogeneity observed in the productivity metrics, categorization guidelines related to the traditional, human resources and customer-oriented approaches emerge.

Practical implications

Possible neglects using metrics aimed at valuing the intellectual capital immersed in human resources are evident, particularly in the follow-up to autonomy, knowledge management, human capital, teamwork, training and capacity building metrics, among others. Conversely, face-to-face monitoring metrics, such as absenteeism, are overvaluation.

Originality/value

The approaches and metrics discussed and the results obtained, provide information so that knowledge-intensive companies have a reference framework to identify and select useful metrics to assess the work carried out by their workforce.

中文翻译：

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知识工作背景下的生产力指标：文献与实践

目的

本文的目的是对文献中推荐的生产率指标与知识密集型服务业公司在实践中使用的指标进行比较分析。

设计/方法/方法

为了收集信息，对文献进行了系统回顾，对代表该行业的不同公司的经理进行了虚拟调查和访谈。对于数据分析，使用了分类最优尺度、同质性检验、四色相关矩阵、词云和二分类变量的关联系数。

发现

使用的指标与所执行工作的性质之间存在关联模式。尽管在生产力指标中观察到异质性，但出现了与传统、人力资源和以客户为导向的方法相关的分类指南。

实际影响

使用旨在评估人力资源中的智力资本的指标可能被忽视是显而易见的，特别是在自治、知识管理、人力资本、团队合作、培训和能力建设指标等的后续行动中。相反，面对面的监控指标，例如缺勤率，被高估了。

原创性/价值

讨论的方法和指标以及获得的结果提供了信息，以便知识密集型公司有一个参考框架来识别和选择有用的指标来评估其员工所做的工作。