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LUBS5342M
Module Reading List

People Analytics: Strategy and Practice, 2019/20, Semester 1
Andrew Charlwood
A.Charlwood@leeds.ac.uk
Tutor information is taken from the Module Catalogue

Seminar 1. 

Polzer, Jeffrey (2018) Should an algorithm tell you who to promote? Harvard Business Review, May/June: 147 – 151 https://hbr.org/2018/02/case-study-should-an-algorithm-tell-you-who-to-promote

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Seminar 2.

Ton, Zeynip (2012) ‘Why “good jobs” are good 4 retailers’ Harvard Business Review, January, https://hbr.org/2012/01/why-good-jobs-are-good-for-retailers

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Lectures

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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. https://www.tlnt.com/if-you-havent-invested-in-analytics-start-now-heres-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. http://onlinelibrary.wiley.com/doi/10.1111/1748-8583.12090/full  

Arellano, Carla Alexander DiLeonardo, and Ignacio Felix (2017) Using People Analytics to Drive Business Performance: A Case Study. The McKinsey quarterly. , July. http://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/using-people-analytics-to-drive-business-performance-a-case-study?cid=other-eml-alt-mkq-mck-oth-1707ts&hlkid=d6579922cf3a42de9be7b9ec342e16fc&hctky=9175239&hdpid=c9f72ddd-fc7a-4a84-9456-153535153813   

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. https://hbr.org/2010/10/competing-on-talent-analytics

Garvin, David (2013) How Google Sold Its Engineers on Management. Harvard business review. , December. https://hbr.org/2013/12/how-google-sold-its-engineers-on-management   

Kaur, Jasmit and Alexis Fink (2017) Trends and Practices in Talent Analytics. http://www.siop.org/SIOP-SHRM/2017%2010_SHRM-SIOP%20Talent%20Analytics.pdf  

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2. People analytics and strategy execution

Levenson, Alec (2016) Using Workforce Analytics to Improve Strategy Execution, Center for Effective Organizations, University of Southern California. https://ceo.usc.edu/files/2017/11/G16-08675.pdf

a more recent version of this article is:

Levenson, Alec (2018) 'Using Workforce Analytics to Improve Strategy Execution' Human resource management. , 57(3): 685 - 700. https://onlinelibrary.wiley.com/doi/abs/10.1002/hrm.21850 

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. https://www.sciencedirect.com/science/article/pii/S0090261615000443

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. http://journals.sagepub.com/doi/abs/10.1177/2515245917745629

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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. , 87(2): 268 – 279. http://www.factorhappiness.at/downloads/quellen/s17_harter.pdf

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. https://www.tandfonline.com/doi/full/10.1080/09585192.2016.1146320 

Kahn, W. A. 1990. Psychological conditions of personal engagement and disengagement at work. Academy of Management journal. , 33(4): 692–724. https://engagementresearch.wikispaces.com/file/view/Kahn+(1990)_Psychological+conditions+of+personal+engagement+and+disengagement+at+work.pdf   

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. http://journals.sagepub.com/doi/abs/10.1177/2515245917745629

Background reading:

Edwards, Martin and Kirsten Edwards (2016). Predictive HR analytics : mastering the HR metric . 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. , December. https://hbr.org/2013/12/how-google-sold-its-engineers-on-management

Lawler, E. E. (2013) ‘Engagement and performance: Old wine in a new bottle’ Forbes , 9 April http://www.forbes.com/sites/edwardlawler/2013/04/09/engagement-and-performance-old-wine-in-a-new-bottle/

Rasmussen, Thomas and Dave Ulrich (2015). Learning from practice: how HR analytics avoids being a management fad. Organizational dynamics. , 44(3): 236 – 242. http://www.sciencedirect.com/science/article/pii/S0090261615000443

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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5. Analysing workforce diversity

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.  https://doi.org/10.1111/1468-4446.12375

Woodhams, C., Lupton, B. and Cowling, M. (2015) The Snowballing Penalty Effect: Multiple Disadvantage and Pay. British Journal of Management, 26(1): 63 - 77. https://doi.org/10.1111/1467-8551.12032  

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6. From Strategy to Operations: Reporting, dashboards and visualisation

Smith, Alan (2017) ‘Data mistakes and how to avoid them’ Financial Times https://www.ft.com/content/3b59f690-d129-11e7-b781-794ce08b24dc  

Issac, Dan (2018) Visualising Pigeons and Donuts: A case study. https://www.graphicinsight.org/ideas/visualising-pigeons-and-donuts-a-case-study  

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7. 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? https://www.linkedin.com/pulse/greatest-mistake-many-people-analytics-andrew-marritt/

Background reading

Athey, Susan (2017). Beyond Prediction: Using Big Data for Policy Problems. Science, 355 (6324): 483 - 485. https://science.sciencemag.org/content/355/6324/483

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)

https://www.researchgate.net/profile/Thomas_Lee60/publication/317311935_On_The_Next_Decade_of_Research_in_Voluntary_Employee_Turnover/links/5a0a9ebfaca272d40f414118/On-The-Next-Decade-of-Research-in-Voluntary-Employee-Turnover.pdf

Rombaut, Evy and Marie-Anne Guerry (2018) ‘Predicting voluntary turnover through human resources database analysis’ Management Research Review 41(1): 96 – 112.  http://www.emeraldinsight.com/eprint/VDV3GXJCHJYZ9AUTS2WR/full

Listen:

https://vimeo.com/207042665/5ed31e8793 - HR Analytics ThinkTank #2 with Kevin Dickens from Experian, speaking on predictive attrition modelling. (password 3N3N).  

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8. Change Management

Key Reading

Hughes, M (2010) Managing change : a critical perspective, 2nd Edition, Basingstoke: CIPD. In particular chapters 10, 17 and 18  Available as an Online Course Reading in Minerva 

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

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9. Safe hospital staffing

Charlwood, A. (2018) People Analytics: A matter of life and death. https://www.linkedin.com/pulse/people-analytics-matter-life-death-andy-charlwood/  

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. https://qualitysafety.bmj.com/content/28/8/609.info  

Marritt, Andrew (2016) The Greatest Mistake for Many in People Analytics? https://www.linkedin.com/pulse/greatest-mistake-many-people-analytics-andrew-marritt/  

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. https://onlinelibrary.wiley.com/doi/full/10.1111/jan.12572 

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10. Ethics and people analytics

Key Reading:

Davenport, Thomas H. (2017) When Jobs Become Commodities. MIT Sloan Management Review. July. http://sloanreview.mit.edu/article/when-jobs-become-commodities/  

Boyd, D. and Crawford, K., 2012. Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication and society. 15(5), pp.662-679.  

Background Reading:

O’Neil, Cathy (2016) How algorithms rule our working lives.The Guardian, September 1. https://www.theguardian.com/science/2016/sep/01/how-algorithms-rule-our-working-lives

Dinnen, Mervyn (2014)The Uberfication of Knowledge. https://mervyndinnen.wordpress.com/2014/12/18/the-uberfication-of-knowledge/

European Union (N.D.) General Data Protection Regulation Portal. http://www.eugdpr.org/   

Gal, Uri (2017) Why algorithms won’t necessarily lead to utopian workplaces.The Conversation, February 21st. http://theconversation.com/why-algorithms-wont-necessarily-lead-to-utopian-workplaces-73132

Galer, Susan (2017) Make Sure Your Hiring Algorithms Are Legal: Four Machine Learning Questions To Ask. https://www.forbes.com/sites/sap/2017/01/26/make-sure-your-hiring-algorithms-are-legal/#ff7050364c75

Haque, U. (2015). ‘The Asshole Factory’. Available at https://medium.com/bad-words/the-asshole-factory-71ff808d887c

Kolah, Ardi (2017) Ethics and the Processing of Employee Data. https://www.linkedin.com/pulse/ethics-processing-employee-data-ardi-kolah-ll-m?trk=hp-feed-article-title-share

Levin, Sam (2017) Accused of underpaying women, Google says it's too expensive to get wage data. The Guardian., 26th May. https://www.theguardian.com/technology/2017/may/26/google-gender-discrimination-case-salary-records

Staley, Oliver (2017) employers-are-using-sentiment-analysis-and-analyzing-your-emails-and-slack-chats-to-see-if-youre-happy-at-work.Quartzhttps://qz.com/910394/employers-are-using-sentiment-analysis-and-analyzing-your-emails-and-slack-chats-to-see-if-youre-happy-at-work/ 

This list was last updated on 09/12/2019