People Analytics - Trust and Leadership in the Digital Era

Executive School of Management, Technology and Law

Executive School of Management, Technology and Law


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Who should attend

The programme is targeted towards senior-level leaders whose role is at the intercept of strategic management decision making, organizational development and technology. Roles might comprise senior-level HR managers, senior compliance officers or heads of organizational learning and development, amongst others as well as people/data analytics professionals, project managers, directors and functional heads or employee representatives.

About the course

People Analytics applications are growing in significance in the business world. This is not only in response to the changes occurring in the modern workplace in the aftermath of COVID-19. The demand is also driven by the idea that HR management decisions that are based on employee-related data are more effective and accurate than those based primarily on intuition, experience, or personal recommendation.

In everyday business, however, it quickly becomes clear that the mere collection and analysis of employee-related data is not enough. More is needed and buzzwords like “Algorithmic Discrimination”, “Taylorism 4.0”, “Data Gold Rush” or “Big Brother” vividly illustrate how People Analytics can pose a threat to employees’ work life, their unique value contribution, and the organizational culture.

In our new online programme, you will acquire a solid foundation in applied People Analytics and learn how to foster the two most important features of leadership in the digital era: digital literacy and trust.

Course Structure

The course consists of eight modules, divided into two sessions each.

Solid foundations of applied People Analytics

In the first part, we will target the question of “What is Good Evidence?”. Herein, you will be equipped with the critical root-cause thinking capabilities necessary to apply People Analytics effectively. On top of that, we will address “Good Evidence” as a matter of data and measurement quality as well as experimentation and structured piloting. Practically, you will gain insights into how you can organize employee data that already exist in your organization, and how to adapt your People Analytics function, including the intangible assets of your organization, such as engagement, trust, or leadership effectiveness. In all, these insights will help you unleash your People Analytics potential that already exists and broaden your strategic analytics focus.

Distinct leadership expertise in digital literacy and trust

In the second part, we will target “Leadership in the Digital Era”. Herein, you will be equipped with critical leadership skills and capabilities that enable you to implement People Analytics applications effectively and to engage in a vivid stakeholder engagement. Thereby, we focus on two core building blocks of leadership in the digital era: digital literacy and trust. You will learn to effectively balance technology-induced dilemmas, even those you cannot foresee but may regret once People Analytics is rolled out. Practically, you will gain insights into the changing requirements of leadership, corporate and legal governance mechanisms, and a sense of unwanted consequences for your employees. The latter bridges the gap to trust, as a critical topic to address in the People Analytics equation. Herein you will be equipped with concrete leadership tools to maintain trust in times of digital change and to succeed in your leadership role as a trusting employee champion. In all, these insights will enable you to enact People Analytics in a digitally literate way so that you fully seize data benefits without compromising on employees' needs - hence, successfully tango technology, agility, and resilience in the 21st-century.


Each week, a different facet of People Analytics will be explored. The lectures cover both academic and practical insights. The transfer sessions will consist of peer-to-peer exchanges where participants can share their experiences in applying the course knowledge and analytics to their current work.

Module 1: People Analytics – It’s not just about Data but also about Mindset!

People Analytics as a new powerful tool to enhance HR decision-making efficacy is currently on everybody’s mind. However, to unfold its full potential, decision-makers need to change their mindset and enact digital literacy and trust as prevailing principles inside the organization. Similar to what Wharton Professor Adam Grant has argued recently, decision-makers should change their mindsets from preacher, consultant, or prosecutor to a more scientific one where robust evidence complements experience and best practices in HR decision making. Digital literacy relates to critical thinking “as an attitude”, where questions like, What is the problem?, What causes the problem?, or What solutions are out there?, go into the DNA of People Analytics business practice. Trust as an enacted principle serves as an excellent template to take an employee perspective in the use of People Analytics and thus, serves as a guideline for engaging with various stakeholders and investing in human-centred designs of People Analytics applications. In this module, we invite you to change perspectives on some of your beloved management habits and help you disentangle the complexities of people issues. This will help you to target a People Analytics roadmap and enter into a strategic dialogue with your key stakeholders.

Learning Outcomes:

  • Understand the basic principles of evidence-based management to familiarize yourself with the change of mindset
  • Translate complex business challenges into root-cause relationships suitable for People Analytics practice
  • Experiment with an evidence-based mindset using concrete people issues from your business practice

*Module 2: Beyond Happy Sheets – How to Turn People Analytics Insights into Business Impact! *

Who hasn’t heard the phrase about People Analytics before: Garbage in, garbage out? People Analytics' full potential can only be exploited if the data are good. Good here does not necessarily mean only very accurate or all-encompassing (Beware of the illusion of control!) but fitting for its intended purpose. In this course, you will be equipped with a refresher on “good” social-science measurement practices that will help you to critically reflect on existing People Analytics capabilities, prepare evidence-based decisions and manage your talent life cycle. Moreover, we introduce two use cases from Nestlé’s People Analytics business practice: micro-polling and flight-risk to illustrate the bandwidth from good data collection practice to predictive modelling. Sharing best practices is aimed at supporting you in how to turn data into good predictions to drive key business decisions. This critical measurement appraisal aims to make employees trusting co-creators. You don’t want them gaming or faking your People Analytics project, otherwise, it easily happens again: garbage in, garbage out!

Learning Outcomes:

  • Understand the basic premises of social-science measurement empowering you to act as an advocate and critical sparring partner of People Analytics projects.
  • Applying the gained insights to your current People Analytics projects to improve the data that you already have.
  • Gaining first-hand business insights into best practice cases to gain quick wins from collecting the right data to analyzing them and turning the results into relevant business recommendations.

Module 3: Fail fast, but fail small: Why #Experimentability is today’s most important management resource

The COVID 19 crisis has made it clear: companies are repeatedly faced with challenges that could not have been foreseen in this way. In an increasingly digital, rapidly changing world, human behaviour is fundamentally changing. Agility and innovation are the key strategies for companies to successfully meet these challenges and changes and ensure their survival. And agility and innovation require experimentation.

"Fail fast, but fail small"- that's the motto! With the help of #Experimentability, you can quickly see what works and what doesn't. The most successful companies are those that experiment a lot. Examples include big players like Amazon, Facebook and Microsoft, which conduct thousands of experiments every year. At this point, at the latest, it should be clear why #Experimentability is so important.

This course introduces you to the world of experimentation. You will develop an understanding of the central role of experimentation in the analogue and digital world and learn about those elements necessary for good experiments. Experimentation centres on the human being, so we will also give you an introduction to the basics of behavioural economics. Relevant business cases that present examples of corporate success through #Experimentability will complete the lecture and provide you with insights into the implementation of experiments in business environments.

Learning Outcomes:

  • You will understand the impact of experimentation on business success
  • You will learn how to implement a culture of experimentation
  • You will learn which ingredients are needed to design a good experiment, and
  • benefit from our first-hand insights into best-practice cases, where we show that you can change the world (or at least a company) with #Experimentability

Module 4: Happimetrics - How Measuring Emotions with AI Increases Individual Happiness and Business Performance

Knowing what makes you happy will make you happier! Analyzing people’s communication patterns and making them self-aware by mirroring their behavior back to them in a privacy-respecting way will increase individual happiness and team performance. This course module describes the three key steps to building happiness and better performance through groupflow, starting with how to create happiness by analyzing communication, how to measure happiness, and how to optimize communication for more happiness and better teamwork by mirroring back the measurements to the individual. It is based on 20 years of research from our MIT Collaborative Innovation Networks (COIN) project on leadership, creativity, team building, and positive psychology published in over 250 peer-reviewed scientific papers and hundreds of industry and research projects our team conducted on individual and organizational creativity and performance.

Learning Outcomes

  • Understand the basic concepts of groupflow – when teams collaborate at their best through intrinsic motivation and positive stress
  • Understand how analyzing your own communication behavior through virtual mirroring increases business performance and individual satisfaction
  • Successfully use the “inovent – insight, oversight, entanglement” process to create entangled teams that work together synchronized and in harmony.

*Module 5: Implementation and Use of People Analytics from a Legal Perspective *

Our empirical studies show that data-based People Analytics Tools are being tried out and implemented very widely, but often rather mindlessly.

However, it is worthwhile for the legal department or relevant stakeholders to take a legal look at it:

What is the justification for implementing and using People Analytics Tools? Is the data processing proportionate and work-related?

Otherwise, the implementation and use of People Analytics Tools may become risky from a legal, trust and reputation perspective.

Learning Outcomes:

  • To know the legal framework relevant for People Analytics Tools
  • To pinpoint the legal issues from an employment law and a data protection law perspective
  • To recognize the legal risks related to the implementation and use of People Analytics Tools

Module 6: Robots as new bosses - Prof. Dr. Jeremias Prassl

Learning Outcomes:

  • Map key socio-technical challenges and dilemmas arising from the deployment of algorithmic management systems
  • Evaluate advantages and drawbacks of different leadership approaches
  • Understand emerging regulatory regimes across the world

Module 7: Death by the leaderboard and other follies - How to use People Analytics in a thoughtful way to drive employee outcomes

People analytics is a rapidly expanding area of people management in organizations. Collecting and analyzing complex chains of employee data holds many promises for well-informed and evidence-based workforce decisions. Yet, left unchecked, some features of People Analytics bear far more danger than meets the eye. This module focuses on addressing such potential pitfalls of People Analytics from an employee-centric perspective. It deals with the unforeseen, even adverse impact of People Analytics on employees, looks into how and with what effect certain features of People Analytics such as data collection at the individual level, data transparency, and relative comparisons might unfold unwanted side effects on collaborative and productive efforts in organizations. It also aims to provide actionable insights into how organizations might apply People Analytics to minimize its potential side effects, backed by the latest scientific evidence.

Learning Outcomes

  • Gaining insights into the potential “dark side” of People Analytics
  • Understanding how different features of People Analytics impact employee outcomes at the individual- and the team level.
  • Understanding how to use People Analytics in a balanced way to drive employee performance, well-being, and collaboration.

Module 8: You Cannot do it Without Trust - Prof. Dr. Antoinette Weibel

People Analytics and Datafication are mighty tools – however, a fool with a tool remains a fool. In the course of this programme, we have discussed how to apply People Analytics in a model-driven, inquisitive, and critical fashion. We have discussed how People Analytics can produce unwanted side effects. We have looked at new ethical questions emerging and how to handle these. What remains to be done is to understand how People Analytics and datafication feed on and are impacted by trust (trust in technology but more importantly trust in leadership and the employer). In this final module, thus, we look at three core topics about trust: a) how does the design of technology solutions affect trust, b) how can leaders mitigate new trust challenges, c) how must leadership change and d) how organizations need to shape their culture to enable a humanistic and human-centred use of People Analytics and datafication.

Learning Outcomes

  • Understand the centrality of trust for business excellence and People Analytics
  • Design technological solutions in a way that enhances or at least does not undermine trust
  • Understand a “being digital” culture that enables “machines to serve humans” and not vice versa


Antoinette Weibel

Antoinette Weibel is Professor for Human Resources Management and director of the Institute for Work and Employment Research, University of St.Gallen. Her research focuses on Human Resources, Organizational Studies and Organizational Psychology. Her recent research projects center on stakeholder ...

Anastasia Sapegina

Education 2010 - 2012: Politics and Public Administration, Master of Arts, University of Konstanz, Germany 2008 - 2009: Politics and Public Administration, Erasmus, University of Tampere, Finland 2006 - 2010: Politics and Public Administration, Bachelor of Arts, University of Konstanz, Germany ...

Jeremias Prass

Jeremias' research focuses on technology, innovation policy, and the future of work in the European Union and beyond. He is a Fellow of Magdalen College, and Deputy Director of the Institute of European and Comparative Law. Jeremias read law at Oxford, Paris, and Harvard Law School, and has held ...

Boris Dzida

Boris is known for advising employers on complex restructurings and integrating employees after M&A transactions. He is the global head of our People and Reward practice group. In particular, he advises on Germany’s data protection and privacy laws, and how these may affect plans to transfer...

Isabelle Wildhaber

Isabelle Wildhaber, LL.M., is a Full Professor for Private and Business Law at the University of St. Gallen. She is admitted to the Bar in Switzerland and to the Bar in New York First Department, having worked for Swiss and American law firms in Basel, New York and Frankfurt a.M. She has conduct...

Peter Gloor

Peter A. Gloor is a Research Scientist at the Center for Collective Intelligence at MIT’s Sloan School of Management where he leads a project exploring Collaborative Innovation Networks (COIN). He is also Founder and Chief Creative Officer of software company galaxyadvisors where he puts his acad...

Gerhard Fehr

Gerhard Fehr is an applied behavioural economist, executive behavioural designer und CEO of Fehr Advice & Partners AG. As an entrepreneur, he was the founder of one of the first business consultancies specializing in behavioural economics back in 2010. Over the last ten years, he and his tea...

Lucia Görke

Lucia Görke currently works as a Senior Data Analyst and Employee Experience Lead at Nestlé in the People Analytics department. Previously, she completed her PhD at the Graduate School of Decision Sciences at the University of Konstanz and at NYU. Thematically, she worked on how autonomous teams ...

Simon Schafheitle

Simon Schafheitle is an International Postdoctoral Research Fellow at the Chair for Human Resource Management of Antoinette Weibel at the University of St. Gallen (FAA-HSG). He received his doctorate from the University of St. Gallen in 2020 focusing on the impact of datafication technologies on ...

People Analytics - Trust and Leadership in the Digital Era at Executive School of Management, Technology and Law

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Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

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