People Analytics

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People analytics (from English people "people" and analytics "analytics", also: HR analytics or workforce analytics ) refers to the analysis of data from human resources (HR human capital ) in connection with other company data . People analytics are based on research fields such as social psychology , motivational psychology and behavioral sciences as well as business intelligence , predictive analytics and big data .

Goal setting

Many decisions that affect employees and the organization are made based on the personal experience of the respective decision maker. People Analytics should also provide tangible information in order to be able to make decisions that affect employees, collaboration and communication in the company, based on hypotheses and data. Therefore, People Analytics can be used under the terms workforce analysis, HR analysis, talent analysis, employee analysis, human capital analysis and HRIS analysis and in the areas of recruiting, onboarding, training & development, employee development, employee management and many other scenarios.

People Analytics sees itself as an interface technology that requires the interaction of many corporate areas: management, human resources, marketing, corporate communication, controlling, IT. Since it is mostly about personal data, the topic is subject to co-determination in German companies .

Current issues that affect cooperation in the broadest sense are translated into a concrete hypothesis , which is then examined using statistical methods, among other things . Here, questionnaire studies or quasi-experimental designs can be used. Management's experience and intuition are supplemented by well-founded information in order to be able to make more targeted and well-founded decisions.

In the context of people analytics, data can be viewed at various 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 regulation.

Especially in English, there are significant differences between the terminology People Analytics and HR Analytics "People Analytics solves business problems. HR Analytics solves HR problems. People Analytics looks at work and its social organization. HR Analytics measures and integrates administrative data HR processes, "says Ben Waber, a PhD student at the MIT Media Lab and CEO of Humanyze.

Connection to personnel controlling

In many cases, projects that are known under the People Analytics label are classic personnel controlling . However, people analytics is much more than just displaying data. While the development of various variables is documented in personnel controlling, people analytics focus on the question of how the variable is influenced.

Examples

Behavioral Prediction Algorithms

With the help of algorithms , the behavior or the suitability of employees for certain tasks can be predicted. For example, the company Google inc. Use their hiring algorithm to predict which candidate has the greatest chance of success if they are hired. Despite the algorithm, however, every applicant goes through four interviews at Google, in which people decide on their hiring.

Companies also use algorithms to determine, for example, the likelihood that an employee will leave the company.

Employee selection and recruitment

New aptitude diagnostic methods are used in the area of ​​employee selection. For example, the analysis of language and voice is used to infer personality traits. In the area of recruiting , People Analytics can be used to examine which job portals receive the most applications or how high the quota of suitable applicants for various job advertisements is.

Age structure analysis

With an age structure analysis, future scenarios about the personnel structure of a company can be developed on the basis of company and personnel data, taking into account implemented or planned personnel measures. The age structure analysis makes the current age structure in the company visible and shows future scenarios. In this way, it is possible to simulate where the company will be in 10, 20, 30 years' time under constant conditions and which varied framework conditions can have a meaningful influence on this development. Questions about this can be, for example: Which company / activity areas are particularly affected by obsolescence? Which knowledge and experience carriers leave the company and when to retire? How and when can knowledge transfer be realized? What does this mean for the recruiting and employee loyalty strategy, for succession planning, for employer branding?

Employee satisfaction

Bank of America recorded turnover rates of 40% in its own call centers. With the help of a people analytics program, the company found that collaboration and communication within the individual departments correlated strongly with the success of employees. To encourage collaboration across departments and free time for face-to-face communication and networking, Bank of America changed its break schedules. This led to an increase in efficiency in the call center and increased cohesion among employees.

Executives

One of the earliest people analytics projects at Google was the Oxygen Study, with which the company investigated the characteristics that make a good leader in a technology company. The result was a catalog of eight central leadership characteristics, a collection of concise original statements from employees and an internal training program.

Transparency in cooperation

The social intranet can also be used for people analytics, via which collaboration within the company is coordinated and communication and knowledge transfer are promoted. In addition, the metadata can be used to examine how closely corporate areas are networked, how high the level of knowledge transfer actually is (e.g. through file uploads), what the mood is in the company, where the opinion leaders or experts can be found in the company. When introducing people analytics in connection with their social intranet, for example, IBM relied on comprehensive information and transparency. An important success factor of this project were the privacy regulations developed by IBM itself:

  • Every user has access to their own data and can delete them.
  • Each user decides for himself which information he would like to share.
  • Management only receives aggregated data.

Analysis of reasons for termination

The analysis of reasons for dismissal in connection with demographic data and information on activities and company division using people analytics can help to understand what keeps employees in a company and to discover opportunities to specifically promote employees. People analytics can also be used to find out the most common characteristics of employees who stay with the company for longer. It is possible to observe trends over a longer period of time.

People analytics research at universities

Alex Pentland, director of the “Human Dynamics Laboratory” at MIT developed the idea of ​​“Social Physics”. Sensor tapes attached to the body collect information about the behavior of test subjects such as the duration of conversations, the pitch of the voice, the gestures, the speaking and listening proportion or the physical position. Based on this data, success factors for cooperation in teams are to be mapped and forecast.

Legal situation in Germany

People Analytics uses personal data , including sensitive personal data . In Germany, however, these are subject to special protection due to the Federal Data Protection Act. In addition, they are subject to codetermination duty of the council .

Legally impermissible measures do not become lawful even with the consent of the works council. The BDSG gives rise to barriers to the design and selection of data processing systems from §§3a (principle of data avoidance , anonymization and pseudonymization ), §4 para. 2 (principle of direct collection of data from the data subject), §4d para. 5 (prior checking by the data protection officer because of the sensitive data regularly affected). 6a para. 1,2 (restriction of automated individual decisions that have legal consequences for the data subject or significantly affect him) §6c (use of mobile media) and also §§4b, 4c BDSG with regard to cross-border data processing in countries outside the EU.

The analysis of business e-mails from employees has so far been permitted, as they do not fall under Section 88 of the TKG . According to the case law of the BVerfG , the protection of telecommunications secrecy ends when the message has reached the recipient.

In contrast, the free processing of personal data with query languages ​​is not permitted. It is incompatible with the right to informational self-determination , as it removes the purpose limitation of employee data and the data transparency for employees.

Biometric identification processes that not only check identity, but also allow statements to be made about the state of mind, state of health or character, are also inadmissible, as they make individuals the mere object of a process and rob them of their privacy (see also marginal number 201, §94 Rn. 39, 48 mwN)

Positioning systems that can relate movement data such. Capturing data , e.g. via GPS-supported navigation systems , RFID technology or mobile phones, are only permitted in exceptional cases with regard to personal rights (e.g. for people to enter and leave the danger areas, but never e.g. in private areas). Complete motion profiles are not permitted. The dissemination of employee health data is also prohibited.

See also

literature

  • Tracey Smith: HR Analytics: The What, Why and How…: 2013, ISBN 978-1492739166
  • Jac Fitz-enz John Mattox: Predictive Analytics for Human Resources (Wiley and SAS Business Series): 2014, ISBN 978-1118893678
  • James C. Sesil: Applying Advanced Analytics to HR Management Decisions, Pearson Education (Us): 2013, ISBN 978-0133064605
  • Gene Pease: Optimize Your Greatest Asset - Your People: How to Apply Analytics to Big Data to Improve Your Human Capital Investments, Wiley: 2015, ISBN 978-1119004387
  • Brenda L. Dietrich, Emily C. Plachy, Maureen F. Norton: Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics, IBM Press: 2014, ISBN 978-0133833034
  • Bryan Wempen: Dancing with Big Data: Conversations with the Experts, Inheritance Press LLC: 2015, ISBN 978-0982385975
  • Gene Pease Barbara Beresford, Lew Walker: Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments (Wiley and SAS Business Series): 2014
  • Jean Paul Isson, Jesse S. Harriott, Jac Fitz-enz: People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent, John Wiley & Sons: 2016, ISBN 978-1119050780

Web links

Individual evidence

  1. ↑ Thomas H. Davenport, Jeanne Harris, Jeremy Shapiro: Competing on Talent Analytics , Harvard Business Review, October 2010
  2. ↑ People Analytics: MIT July 24, 2017 | HR examiner. Retrieved April 2, 2020 (American English).
  3. ↑ Dr. John Sullivan, How Google Is Using People Analytics To Completely Reinvent HR , Ere Media, February 2013
  4. ↑ David Woods, [1]
  5. ↑ Rachel Emma Silverman and Nikki Waller [2]
  6. ↑ Stephan Strohmeier & Franca Piazza: Human Resource Intelligence and Analytics, Springer Gabler: 2015, ISBN 978-3-658-03595-2
  7. ↑ Ben Waber: People Analytics: How Social Sensing Technology Will Transform Business and What It Tells Us about the Future of Work, Financial Times Prent .: 2013, ISBN 978-0133158311
  8. ↑ "Oxygen" - Google's large leadership study ( memento of the original from September 24, 2015 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. , Forum Good Leadership: 2013 @1@ 2Template: Webachiv / IABot / www.forum-gute-fuehrung.de
  9. ↑ Melanie Petersen, People Analytics: 6 exciting use cases for data-based personnel decisions [# rp15], t3n: 2015
  10. ↑ Video: Marie Wallace: Privacy by design: humanizing analytics , TED Institute: 2014
  11. ↑ Alex "Sandy" Pentland: The New Science of Building Great Teams , Harvard Business Review: 2012
  12. ↑ Alex Pentland: Social Physics: How Good Ideas Spread-The Lessons from a New Science, Penguin Press: 2014, ISBN 978-1594205651
  13. ↑ cf. "Limits for personal data processing " - bund.online