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003			SA-PMU
005			20210418124558.0
008			151117t20162016enka f b 001 0 eng d
010			_a 2015050726
040			_aCDX _beng _erda _cCDX _dIG$ _dYDXCP _dOCLCF _dBDX _dBTCTA _dIOJ _dPHUST _dFIE _dOCLCQ
019			_a919564136 _a930255124
020			_a9780749473914 _q(pbk.)
020			_a0749473916 _q(pbk.)
020			_z9780749473921 _q(ebook)
035			_a(OCoLC)944012402 _z(OCoLC)919564136 _z(OCoLC)930255124
050		4	_aHF5549 _b.E416 2016
082	0	4	_a658.30072/7 _223
100	1		_aEdwards, Martin R., _eauthor.
245	1	0	_aPredictive HR analytics : _bmastering the HR metric / _cMartin R. Edwards and Kirsten Edwards.
264		1	_aLondon : _bKoganPage, _c2016.
264		4	_c©2016
300			_axiii, 457 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"While other departments in an organization deal with profits, sales growth, and strategic planning, Human Resources (HR) is responsible for employee well-being, engagement, and staff motivation. Even though it may not be immediately obvious, the management of these duties often requires a great deal of measurement and technical skill. Predictive HR Analytics provides a clear and accessible framework to understanding and learning to work with HR analytics at an advanced level, using examples of particular predictive models, such as diversity analysis, predicting turnover, evaluating interventions, and predicting performance. When dealing with metrics, management information, and analytics, HR practitioners rarely use any advanced statistical techniques or go beyond describing the characteristics of the workforce. Authors Martin Edwards and Kirsten Edwards explain the business applications of HR predictive models; the ethics and limitations of HR analytics; how to carry out an analysis; predict turnover, performance, recruiting, and selection outcomes; and monitor the impact of interventions."-- _cProvided by publisher.
520			_a"Where other functions of an organization deal in profits, sales growth and forecasts and strategic planning, the HR function is responsible for employee well-being, engagement and motivation. Such concerns do not immediately conjure up images of technical know-how, despite the fact that in reality the management of such things may often require a lot of measurement and technical skill. Predictive HR Analytics: Mastering the HR Metric provides a clear, accessible framework with which to understand and work with HR analytics at an advanced level, taking the reader through examples of particular predictive models. When dealing with HR metrics, management information and HR analytics, HR practitioners rarely use any advanced statistical techniques to make the most of the data they have. This book will show the reader step-by-step, using simple terms, how to carry out the analysis (using the statistical package SPSS) and how to interpret the results, helping them to communicate the potential of HR analytics and get the most out of their HR function, whether they are carrying out the analysis themselves or briefing external consultants. Predictive HR Analytics: Mastering the HR Metric will help HR professionals to deliver a credible and reliable service to the businesses that they support by providing metrics on which executives will be able to make sound business decisions"-- _cProvided by publisher.
505	0		_aSection -- 01: Understanding HR analytics; Section -- 02: HR information systems and data; Section -- 03: Analysis strategies; Section -- 04: Case study 1: Diversity analytics; Section -- 05: Case study 2: Employee attitude surveys engagement and workforce perceptions; Section -- 06: Case study 3: Predicting employee turnover; Section -- 07: Case study 4: Predicting employee performance; Section -- 08: Case study 5: Recruitment and selection analytics; Section -- 09: Case study 6: Monitoring the impact of interventions; Section -- 10: Business applications: Scenario modelling and business cases; Section -- 11: More advanced HR analytic techniques; Section -- 12: Reflection on HR analytics: Usage, ethics and limitations.
650		0	_aPersonnel management _xStatistical methods.
650		7	_aPersonnel management _xStatistical methods. _2fast _0(OCoLC)fst01058842
700	1		_aEdwards, Kirsten, _eauthor.
938			_aBrodart _bBROD _n114288542
938			_aBaker and Taylor _bBTCP _nBK0017992451
938			_aCoutts Information Services _bCOUT _n32459408
938			_aYBP Library Services _bYANK _n12591084
029	1		_aAU@ _b000057438343
942			_cBOOK
994			_aZ0 _bSUPMU
948			_hNO HOLDINGS IN SUPMU - 39 OTHER HOLDINGS
596			_a1 2
999			_c8606 _d8606