People Analytics
People Analytics (also known as HR Analytics or Workforce Analytics) refers to the analysis of data from human resources (human capital) in conjunction with other company data. People Analytics is based on research fields such as social psychology, motivational psychology and behavioral science as well as business intelligence, predictive analytics and big data.
Categorization and objective[edit]
People Analytics is using behavioral data to understand how people work and change how companies are managed.[1] Many decisions that affect employees and the organization are made on the basis of the personal experience of the respective decision-maker. People Analytics is designed to provide additional, tangible information in order to make decisions concerning employees, collaboration and communication in the company, hypothesis-driven and data-supported.
The field of application is very diversified, therefore People analytics is also known as workforce analytics, HR analytics, talent analytics, people insights, talent insights, colleague insights, human capital analytics, and HRIS analytics.[2] HR analytics is the application of analytics to help companies manage human resources.[3] Additionally, HR analytics has become a strategic tool in analyzing and forecasting Human related trends in the changing labor markets, using Career Analytics tools [4].
Current questions, which concern cooperation in the broadest sense, are translated into a concrete hypothesis, which is then examined using statistical methods, among other things. Questionnaire studies or quasi-experimental designs can be used for this purpose. Experiences and intuition of the management are supplemented by well-founded information in order to be able to make decisions in a more targeted and well-founded way.[5] The aim is to discern which employees to hire, which to reward or promote, what responsibilities to assign, and similar human resource problems.[6] HR analytics is becoming increasingly important to understand what kind of behavioral profiles would succeed and fail. For example, an analysis may find that individuals that fit a certain type of profile are those most likely to succeed at a particular role, making them the best employees to hire.
However, there are key differences between people analytics and HR analytics. "People Analytics solves business problems. HR Analytics solves HR problems. People Analytics looks at the work and its social organization. HR Analytics measures and integrates data about HR administrative processes," says Ben Waber, MIT Media Lab Ph.D. and CEO of Humanyze.[7] Josh Bersin, founder and principal at Bersin by Deloitte agrees that people analytics is a larger industry than HR Analytics, explaining, "… over time, I believe it doesn't even belong within HR. While it may reside in HR to begin with, over time this team takes responsible for analysis of sales productivity, turnover, retention, accidents, fraud, and even the people-issues that drive customer retention and customer satisfaction… These are all real-world business problems, not HR problems."[8]
In the context of people analytics the data can be viewed at different levels : at company level, at team or department level and at individual level. Every People Analytics project requires a clear, specific and transparent data protection policy.
Relationship to personnel controlling[edit]
In many cases, projects that become known under the People Analytics label are classic personnel controlling. However, People Analytics comprises much more than the mere presentation of data. While in personnel controlling the development of various variables is documented, people analytics focuses on the question of how the variable is influenced and how you can different aspects can be predicted.
Examples[edit]
Algorithms for behaviour prediction[edit]
Algorithms are used to predict the behavior or suitability of employees for certain tasks. For example, the company Google inc. tries to predict with its hiring algorithm which applicant has the best chance of success when hired. Despite the algorithm, however, at Google every applicant still goes through four interviews in which people decide on his or her employment [9].
Companies also use algorithms, for example, to determine the probability of an employee leaving the company [10] [11].
Employee selection and recruitment[edit]
In the area of employee selection, new aptitude diagnostic procedures are used. For example, the analysis of speech and voice is used to draw conclusions about personality traits. In the area of employee recruitment, People Analytics can be used to investigate which job portals receive the most applications or how high the quota of suitable applicants is in response to various job advertisements. There are also more and more new services for employees and applicants, e.g. for evaluating the corporate culture[12].
Age structure & demography analysis[edit]
With an age structure analysis, future scenarios about the personnel structure of a company can be developed on the basis of operational and personnel data, including implemented or planned personnel measures. The age structure analysis makes the current age structure in the company visible and shows future scenarios. It can thus be simulated where the company will be in 10, 20, 30 years under the same conditions and which varied conditions can have a meaningful influence on this development. Questions on this can be, for example: Which company/activity areas are particularly affected by ageing? Which knowledge and experience carriers will leave the company when they retire? How and when is knowledge transfer feasible? What does this mean for the recruitment and employee retention strategy, for succession planning, for employer branding?[13][14]
Employee satisfaction[edit]
Bank of America recorded fluctuation rates of 40 % in the company's own call centers. Using a people analytics program, the company found that collaboration and communication within departments correlated strongly with employee success. Bank of America changed break schedules to encourage departmental collaboration and allow time for personal communication and networking. This resulted in increased efficiency and cohesion among employees in the call center.[15]
Management staff[edit]
One of the earliest people analytics projects at Google was the Oxygen study,[8] which investigated what qualities make a good leader in a technology company. The result was a collection of eight key leadership qualities, a collection of concise original statements from employees and an internal training program.[16][17]
Analysis of employee reasons for dismissal[edit]
The analysis of reasons for dismissal in combination with demographic data and information about the job and the business area using people analytics can help to understand what keeps employees in a company and to discover opportunities to develop employees in a targeted manner. People Analytics can also be used to find out the most common characteristics of employees who stay longer in the company. It is possible to observe trends over a longer period of time.
See also[edit]
References[edit]
- ↑ lukem (2016-11-04). "People Analytics: Transforming Management with Behavioral Data". Programs for Professionals | MIT Professional Education. Retrieved 2018-04-03.
- ↑ "[VIDEO] The Difference Between People Analytics and HR Analytics". Analytics in HR. 2018-03-08. Retrieved 2018-04-03.
- ↑ Chalutz Ben-Gal, Hila (2019). "An ROI-based review of HR analytics: practical implementation tools" (PDF). Personnel Review, Vol. 48 No. 6, pp. 1429-1448.
- ↑ Sela, A., Chalutz Ben-Gal, Hila (2018). "Career Analytics: data-driven analysis of turnover and career paths in knowledge intensive firms: Google, Facebook and others" (PDF). In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE). IEEE.CS1 maint: Multiple names: authors list (link)
- ↑ Davenport, Thomas H.; Harris, Jeanne; Shapiro, Jeremy (2010-10-01). "Competing on Talent Analytics". Harvard Business Review (October 2010). ISSN 0017-8012. Retrieved 2020-04-02.
- ↑ "People analytics - University of Pennsylvania". Coursera.
- ↑ "People Analytics: MIT July 24, 2017". HR Examiner. 2017-08-02. Retrieved 2018-04-03.
- ↑ Bersin, Josh. "The Geeks Arrive In HR: People Analytics Is Here". Forbes. Retrieved 2018-04-03.
- ↑ "How Google Is Using People Analytics to Completely Reinvent HR". TLNT. 2013-02-26. Retrieved 2020-04-02.
- ↑ "Google uses maths to improve employee retention". www.hrmagazine.co.uk. Retrieved 2020-04-02.
- ↑ Waller, Rachel Emma Silverman and Nikki (2015-03-13). "The Algorithm That Tells the Boss Who Might Quit". Wall Street Journal. ISSN 0099-9660. Retrieved 2020-04-02.
- ↑ "Culture-Fit Assessments for Employers & Careers". Good&Co. Retrieved 2020-04-02.
- ↑ Strohmeier, Stefan. (13 January 2015). Human Resource Intelligence und Analytics : Grundlagen, Anbieter, Erfahrungen und Trends. Piazza, Franca. Wiesbaden. ISBN 978-3-658-03596-9. OCLC 900193783. Search this book on
- ↑ Leonardi, Paul; Contractor, Noshir (2018-11-01). "Better People Analytics". Harvard Business Review (November–December 2018). ISSN 0017-8012. Retrieved 2020-04-02.
- ↑ Waber, Ben, 1984- (2013). People analytics : how social sensing technology will transform business and what it tells us about the future of work. Upper Saddle River, N.J.: FT Press. ISBN 978-0-13-315831-1. OCLC 829445881.CS1 maint: Multiple names: authors list (link) Search this book on
- ↑ ""Oxygen" – Googles große Führungsstudie | Forum Gute Führung". 2015-09-24. Archived from the original on 2015-09-24. Retrieved 2020-04-02.
- ↑ Bryant, Adam (2011-03-12). "Google's Quest to Build a Better Boss". The New York Times. ISSN 0362-4331. Retrieved 2020-04-02.
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