Applying HR analytics to talent management

Mayo, Andrew (2018) Applying HR analytics to talent management. Strategic HR Review, 17 (5). pp. 247-254. ISSN 1475-4398 (doi:10.1108/shr-08-2018-0072)

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Abstract

Purpose
The purpose of this paper is to summarise the different areas of talent management and how HR metrics and analytics can be harnessed to make those areas more effective.
Design/methodology/approach
The paper first discusses the different definitions of “talent”. It then takes three areas for the application of metrics and analytics – data about individuals, the effectiveness and efficiency of talent processes and the extent of the supporting culture.
Findings
The definition of talent should not be confined to senior leadership only, nor be fully inclusive of every employee, but organisations need to define those individuals and groups where some specific attention will benefit the organisation; it is as important to understand the potential of all employees as it is to assess their performance; metrics should be chosen for all talent processes and related to business KPIs where possible.
Practical implications
This is a practical paper giving guidance to talent managers in organisations on how to apply and utilise people analytics.
Originality/value
This paper is based mostly on the writing, models and experience of the author.

Item Type: Article
Research Areas: A. > Business School > Leadership, Work and Organisations
Item ID: 25575
Notes on copyright: This article is © Emerald Publishing Limited 2018 and permission has been granted for this version to appear here (https://eprints.mdx.ac.uk/). Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.
This is the accepted version of the manuscript "Applying HR analytics to talent management", published in the journal "Strategic HR Review" available via the journal site at: https://doi.org/10.1108/shr-08-2018-0072
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Depositing User: Jisc Publications Router
Date Deposited: 13 Nov 2018 10:39
Last Modified: 19 Nov 2019 04:14
URI: https://eprints.mdx.ac.uk/id/eprint/25575

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