EP020 - How to use data to refine company operations with Stefan van Tulder of Talent Data Labs
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How to use data to refine company operations with Stefan van Tulder of Talent Data Labs
About the episode
This episode focuses on data analytics and the importance of metrics for better company operations. Why should you measure how you work? What can you learn from the data? How can you use the data to refine company ops? I discuss the topic with Stefan van Tulder, founder of Talent Data Labs and co-founder of Josie App.
About the guest
Stefan is a data scientist running a variety of applications based on a core technology and data-framework developed by himself and his team. The home of his data framework is Talent Data Labs but he has many different storefronts. All storefronts are busy solving the most difficult and data-deprived HR technology problems. Currently mostly focusing on two major areas first of which being extreme workforce diversity (refugees, prisoners, people with mental disabilities) and secondly occupational health, hybrid-work, and job-related mental illnesses. He is also the co-founder of Josie App, a career scoring app.
About the host
My name is Peter Benei, founder of Anywhere Consulting. My mission is to help and inspire a community of remote leaders who can bring more autonomy, transparency, and leverage to their businesses, ultimately empowering their colleagues to be happier, more independent, and more self-conscious.
Connect with me on LinkedIn.
Want to become a guest on the show? Contact me here.
Quotes from the show
Not everyone can deal with the mental health implications of remote work. According to our data, the upper limit of possibility for remote work is 25%. So a maximum 25% of society is actually equipped to work fully remote.
Data can help us to identify errors in our system. The smaller your company is, the larger the impact is for an error. For example, imagine a toxic employee or a bad operational process. But, the bigger your company is, the larger the relevance for the same error. It has become a legacy and a trend, so fixing it from the start is important
We realize something only when we see it, which is very human. You know what you want when you see it. You know what went wrong when you see what went wrong. It's easy to point to the mistake of someone else, right? To go like, okay, obviously, right? But it's very hard to internalize it. And that's why it's so important that we keep a data-driven journey.