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Module Reading List

People Analytics: Strategy and Practice, 2021/22, Semester 2
Xanthe Whittaker
Tutor information is taken from the Module Catalogue

*please note: module reading list is currently under revision and will be updated weekly

Seminar 1

Polzer, Jeffrey (2018) Should an algorithm tell you who to promote? Harvard Business Review, May/June: 147 – 151


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Lecture reading lists

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1. People analytics in the context of HRM

Lecture two: Key reading

Charlwood, Andy and Nigel Dias (2018) Analysing HR Analytics: How do organisations successfully build HR analytics functions? London: HR Analytics Thinktank  [You can find this underneath the lecture slides in the learning resources section].

Fink, Alexis and Keith McNulty (2018) If You Haven’t Invested in Analytics, Start Now. Here’s How.

Background reading

Angrave, David, Andy Charlwood, Ian Kirkpatrick, Mark Lawrence, Mark Stuart (2016) Why HR is Set to Fail the Big Data Challenge. Human Resource Management Journal, 26(1): 1 – 11.  

Arellano, Carla Alexander DiLeonardo, and Ignacio Felix (2017) Using People Analytics to Drive Business Performance: A Case Study. The McKinsey quarterly. , July.   

Charlwood, Andy and Kim Hoque (2017) Managing People: Understanding the Theory and Practice of Human Resources Management in Adrian Wilkinson, Steven J. Armstrong, and Michael Lounsbury (eds) The Oxford handbook of management. Oxford: OUP.

Davenport, Thomas, Jeanne Harris and Jeremy Shapiro (2010) Competing on Talent Analytics. Harvard Business Review, October.

Garvin, David (2013) How Google Sold Its Engineers on Management. Harvard business review. , December.   

Kaur, Jasmit and Alexis Fink (2017) Trends and Practices in Talent Analytics.  

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2. Ethics and people analytics

Primary reading

 O’Neil, Cathy (2016) How algorithms rule our working lives.The Guardian, September 1.

 Gal, U., Jensen, T.B. and Stein, M.K., 2020. Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics. Information and Organization30(2), p.100301.

 Loi, M., 2020. People Analytics must benefit the people. An ethical analysis of data-driven algorithmic systems in human resources management. Algorithmwatch. Available at:

 Secondary reading

 Ajunwa, I., Crawford, K. and Schultz, J., 2017. Limitless worker surveillanceCalif. L. Rev.105, p.735.

Adams-Prassl, J., 2019. What if your boss was an algorithm? Economic Incentives, Legal Challenges, and the Rise of Artificial Intelligence at WorkComp. Lab. L. & Pol'y J.41, p.123.

Bodie, M.T., Cherry, M.A., McCormick, M.L. and Tang, J., 2017. The law and policy of people analytics. U. Colo. L. Rev.88, p.961.

Mittelstadt, B.D., Allo, P., Taddeo, M., Wachter, S. and Floridi, L., 2016. The ethics of algorithms: Mapping the debate. Big Data & Society3(2), p.2053951716679679.

Tursunbayeva, A., Pagliari, C., Di Lauro, S. and Antonelli, G., 2021. The ethics of people analytics: risks, opportunities and recommendations. Personnel Review.

Weiskopf, R. and Hansen, H.K., 2022. EXPRESS: Algorithmic governmentality and the space of ethics: Examples from 'People Analytics'. Human Relations, p.00187267221075346.


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3. Employee engagement and performance

Key Reading:

Harter, J.K., Schmitt, F.L., and Hayes, T.L. (2002) Business-unit-level relationship between employee satisfaction, employee engagement and business outcomes: A meta-analysis. Journal of Applied Psychology. ISSN: 0021-9010, 87(2): 268 – 279.

C Ogbonnaya, D Valizade (2018) High performance work practices, employee outcomes and organizational performance: a 2-1-2 multilevel mediation analysis. The International Journal of Human Resource Management 29 (2), 239-259. 

Kahn, W. A. 1990. Psychological conditions of personal engagement and disengagement at work. Academy of Management journal. ISSN: 0001-4273, 33(4): 692–724.  

Roher, Julia M. (2018) ‘Thinking clearly about correlations and causation: graphical causal models and observational data.’ Advances in Methods and Practices in Psychological Science 1(1): 27 – 42.

Background reading:

Edwards, Martin and Kirsten Edwards (2016). Predictive HR analytics : mastering the HR metric ISBN: 9780749473914 (pbk.) : £29.99. London: Kogan Page. Case Study 2: Employee Attitudes Surveys – Engagement and Workforce Perceptions. pp. 144 – 189.

Garvin, David (2013) How Google Sold Its Engineers on Management. Harvard business review. ISSN: 0017-8012, December.

Lawler, E. E. (2013) ‘Engagement and performance: Old wine in a new bottle’ Forbes ISSN: 0015-6914, 9 April

Rasmussen, Thomas and Dave Ulrich (2015). Learning from practice: how HR analytics avoids being a management fad. Organizational dynamics. ISSN: 0090-2616, 44(3): 236 – 242.

Wake M, Green W (2019). Relationship between employee engagement scores and service quality ratings: analysis of the National Health Service staff survey across 97 acute NHS Trusts in England and concurrent Care Quality Commission outcomes (2012–2016) BMJ Open. doi: 10.1136/bmjopen-2018-026472


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4. Predictive Analytics in HR

Key Reading:

Charlwood, Andy and Nigel Dias (2018) Analysing HR Analytics: How do organisations successfully build HR analytics functions? London: HR Analytics Thinktank

Marritt, Andrew (2016) The Greatest Mistake for Many in People Analytics?

Background reading

Athey, Susan (2017). Beyond Prediction: Using Big Data for Policy Problems. Science, 355 (6324): 483 - 485.

Lee, Thomas, Peter Hom Marion Ebery, Junchao Li and Terence Mitchell (2017) ‘On the next decade of research in voluntary employee turnover.’ The Academy of Management perspectives. 31(3)

Rombaut, Evy and Marie-Anne Guerry (2018) ‘Predicting voluntary turnover through human resources database analysis’ Management Research Review 41(1): 96 – 112. (see link in module resources folder)


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5. People analytics and strategy execution

 Levenson, Alec (2018) 'Using Workforce Analytics to Improve Strategy Execution' Human resource management. , 57(3): 685 - 700.

Background reading

Rasmussen, Thomas and Dave Ulrich (2015) ‘Learning from practice: how HR analytics avoids being a management fad’ Organizational Dynamics, 44(3): 236 – 242.

Roher, Julia M. (2018) ‘Thinking clearly about correlations and causation: graphical causal models and observational data.’ Advances in Methods and Practices in Psychological Science 1(1): 27 – 42.


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6. From Strategy to Operations: Communicating results and managing change


Key Reading

Fernando, V., Gallardo-Gallardo (2020) 'Tacking the HR Digitalization Challenge: Key factors and barriers to HR Analytics Adoption', Competitiveness Review (July)   Hughes, M (2019) Managing change : a critical perspective, 2nd Edition, Basingstoke: CIPD. In particular chapters 10, 17 and 18  

Further Reading

Kotter, J. P. (1995) Leading Change: Why Transformation Efforts FailHarvard business review. (March-April, 1995:59-67). Cawsey, T.F., Deszca, G. and Ingols, C., 2016. Organizational change: An action-oriented toolkit (3rdedn.) Sage. Chapter 7.   Hayes, J. (2010) The Theory and Practice of Change ManagementThird Edition, London: Palgrave,Chapters 2 and 10

Hodges, J., (2021), Managing and Leading People through Organizational Change: The Theory and Practice of Sustaining Change through People. London, Kogan Page


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7. Visualising diversity and inclusion

On diversity and gender pay

Tomlinson, J., Valizade, D., Muzio, D., Charlwood, A. and Aulakh, S. (2019) ‘Privileges and penalties in the legal profession: an intersectional analysis of career progression’ British Journal of Sociology, 70 (3): 1043 – 1066.

Woodhams, C., Lupton, B. and Cowling, M. (2015) The Snowballing Penalty Effect: Multiple Disadvantage and Pay. British Journal of Management, 26(1): 63 - 77.  


Olsen, W. K., & Walby, S. 2004. Modelling Gender Pay Gaps. (EOC WORKING PAPER SERIES). Equal Opportunities Commission. Available at:

Xaquín G.V., 2017. Can we talk about the gender pay gap? The Washington Post. 26 October 2017. Available at:

Beioley, K. 2021. UK firms grapple with ethnicity pay gap reporting. Financial Times. 17 November 202. Available at:

On visualisation

Smith, Alan (2017) ‘Data mistakes and how to avoid them’ Financial Times 

Issac, Dan (2018) Visualising Pigeons and Donuts: A case study.  



 Analysing performance: Safe hospital staffing

Charlwood, A. (2018) People Analytics: A matter of life and death.  

Griffiths P, Maruotti A, Recio Saucedo A On behalf of Missed Care Study Group, et al. (2019) Nurse staffing, nursing assistants and hospital mortality: retrospective longitudinal cohort study. BMJ Quality & Safety 28:609-617.  

Marritt, Andrew (2016) The Greatest Mistake for Many in People Analytics?  

LW Schreuders, AP Bremner, E Geelhoed, J Finn (2015). The relationship between nurse staffing and inpatient complications. Journal of advanced nursing 71 (4), 800-812. 



This list was last updated on 17/03/2022