Ludek’s Blog About People Analytics


Ludek's Blog About People Analytics

Want to maximize your impact as a leader?

leadership effectiveness
causal inference

Forget the CEO chair and become a sports coach or a politician in an autocracy instead 🙃

Adjusting priors on your “emotional radar” for smoother cross-cultural encounters

expressiveness
cross-cultural differences

On interesting research that may come in handy during summer vacations abroad.

Tracking talent moves in the (in)famous 9-box grid over time

data visualization
talent management

Crowdsourcing ideas for effective ways to visualize talent moves in the 9-box grid over time.

Happy today, richer tomorrow?

happiness research
positive psychology
life satisfaction
causal inference

☀️ As many of us now take a summer break to recharge and boost our happiness, here’s some good news: it might even pay off financially 🤑

How personality risks co-occur?

leadership risks
derailers
hogan assessment
hogan development survey
personality psychology
psychometrics
network analysis

Some highlights from exploring a larger sample of Hogan Development Survey data.

What does a typical people manager value chain look like?

people management
manager
value chain

Sharing a working draft of a people manager value chain—mapping how specific manager actions drive people outcomes, team performance, and ultimately business results. Feedback and suggestions welcome 🙂

When self-selected behavior is a blessing, not a headache

measurement
self-selection
proxy measures
employee data
behavioral data

Self-selection as a measurement opportunity?

Are you crazy enough and in the right way to fit the craziness required by your job?

job fit
career advisory
cognitive biases

Listing some key takeaways from an insightful article by Adam Mastroianni on job fit.

ONA as a tool for exploring the skill space in your company?

skills
skills-based organization
organisational network analysis
network analysis
career pathing
learning and development

As we move toward a skill-based organization at Sanofi, it prompted me to think about new opportunities for applying Organizational Network Analysis (ONA).

Using Doppelgänger for career pathing?

career pathing
causal inference

Exploring an idea around using counterfactual and hypothetical scenarios to help employees navigate their career options.

Novel way to measure leadership skills via causal inference (and AI)?

leadership
psychometrics
assessment
causality
ai
llm
ai agent

A post about a new, potentially useful method for measuring leadership skills, along with complementary findings highlighting the importance of objective, skill-based selection of future leaders.

An interactive demo of Computerized Adaptive Testing

psychometrics
item response theory
computerized adaptive testing
bayesian statistics
streamlit
python

Sharing a byproduct of my recent efforts to learn Streamlit—an interactive demo that might be useful for anyone teaching psychometrics or simply curious about how modern psychometrics (relatively speaking 😉) works.

Talk vs. Walk: Predictors of staying intentions vs. actual quitting behavior

attrition
retention
attitude-behavior gap
predictive analytics

Is there a gap between what predicts employees' stated intentions to stay with their organization and their actual quitting behavior? And if so, how big is it?

Beyond prediction: Exploiting organizational events for causal inference in people analytics

causal inference
experiments
data science
people analytics
hr analytics
python
r

Sharing an article I co-authored with Cole Napper on causal inference in people analytics.

Can a simple algorithm read your personality from your face?

personality
big five
deep neural networks
convolutional neural networks
machine learning
python
r

A post describing a small experiment on ML-based recognition of personality traits from facial photographs, inspired by an older research paper that explored the use of composite images to assess the accuracy of personality attributions to faces.

What actually makes us happier?

happiness
wellbeing
psychology
systematic review

A quick rundown of some surprising and not-so-surprising findings from a recent systematic review on how well happiness interventions work.

I’ve finally lived to see the day…

market basket analysis
machine learning
team profile analysis
motivation
mvpi
hogan assessment

... and found a People Analytics use case for market basket analysis 🛒

RWA – A go-to tool for key drivers analysis of employee survey data?

employee survey
employee listening
key drivers analysis
relative weights analysis

A brief showcase of a useful method for analyzing (not only) employee survey data.

Why do psychologists disagree—even when they use the same data and methods?

psychology
scientific thinking
cognitive styles
cognitive diversity
epistemology

About a study exploring how scientific disagreements may be shaped not only by facts, but also by researchers’ cognitive differences.

Causal insights with no code?

data literacy
causal inference
difference-in-differences
data-driven HR
evidence-based HR

Causal insights without writing a single line of code? Well… maybe. In this post, I walk through how a simplified, visual version of a method called difference-in-differences can help you better understand cause and effect—even if you're not a data scientist. Using just a BI tool and some domain knowledge, you can sometimes identify meaningful patterns that suggest whether a policy or change truly made a difference. It's not perfect, and it won't replace rigorous analysis—but in the right context, it can be a surprisingly useful starting point.

Putting the "ideal" personality for high work engagement in a broader context

work engagement
personality
meta-analysis

Ever wondered whether or how personality affects your enthusiasm at work? If yes, then keep reading. 🤓

What topics might you encounter at the SIOP 2025 conference?

siop
conference
i/o psychology
topic analysis
bertopic

A quick check of the topics covered at this year's SIOP conference.

Did the Nobel Prize put causal inference on the public radar?

causal inference
econometrics
nobel prize
segmented regression
time series data
bayesian inference
r

Applying Bayesian segmented regression analysis of interrupted time series data to Google Trends data to test the hypothesis of a positive impact of the 2021 Nobel Prize in Economics on public interest in causal inference, while accounting for changes in Google's data collection methods and seasonal variations.

How to get causal interpretation for the Employee Attrition dataset?

causality
causal ml
econml
python
employee attrition

An interesting demonstration of causal inference in the People Analytics space using the famous IBM Employee Attrition dataset.