By Sergio Garcia Mora
Bachelor in Labour Relations and Data Mining Student
Sergio Garcia Mora is based in Argentina. For English readers, Segio recommends the book, The ROI of Human Capital by Dr. Jac. He also recommends Argentinean author Luis Maria Cravino’s book called “Medir lo importante” (Measuring the Important) and Jose Maria Saracho’s book called “Talento Organizacional”.
When I started my Career on Labour Relations at the University, and I asked my classmates why they chose this career, most of them replied “because we don’t have to deal with math and numbers”, and suffering two statistics courses along the career didn’t seem so distressing.
Thinking about this situation, one of the reasons I think this happens to people who chose “soft” careers (namely HR, Psychology) is because we hit a wall thinking how hard it is to solve an equation instead of thinking of what can I do with the information the equation provides? It might be a subtle difference, but once you know that certain “maths” may help you find answers to specific issues, the negative energy that blocked your way transforms and allows knowledge to flow.
This way of thinking doesn’t exclusively belong to HR. Last year, when I started a postgraduate course in Data Mining, every single one of my classmates asked me “Can you use Data Mining in Human Resources?” and my answer was “Of course you can!” This prejudice is established because we (HR functions) are not perceived as a data-driven area (despite that we own our employees’ information when they work in our company).
“They don’t give HR a place at the Decision Table”
How are “they” giving HR a seat at the Decision Table if we don’t speak the corporate language? And the corporate language is results. If we are not able to show our own results, how do we gain a decision-maker’s trust?
And thinking of results, it’s not necessarily just saving cost and time. We can go beyond. Looking how our HR information relates with other company data, we’ll have the opportunity to drive our efforts.
Not long ago, asking Daniel Yankelevich, a key Data Mining player in Argentina (and a person I love to listen to whenever I can), what makes a miner good, he replied with 3 things:
- Must know the company’s business.
- Programming skills.
- Must be able to turn conclusions into actions.
Ok, perhaps programming might be discouraging to HR professionals, but:
- Can we have business acumen? It’s a must.
- Can we team up with other areas to conduct the analysis? It’s a good idea.
- Can we drive conclusions into action? Yes, we can.
My suggestion is simple. Don’t get messy with math, Let’s look for relationships among data, for instance:
- Is there any relation between our communication/training/compensation actions and the quality of the company’s product?
- What profiles show more turnover?
- What are the characteristics of the frequently absent workers?
- What do top performers have in common?
When we set out to focus on what we want to achieve, “playing” with data is much simpler. There are techniques that allow us to look for relationships between variables that don’t seem to be connected, but even without getting to that sophistication level, there’s a lot of available information to match, contrast with, that we haven’t taken advantage of yet.
People make the difference
Nowadays, many companies have a phrase like people are the most valuable asset in their Mission and Vision. So, how can we measure people’s impact on company’s results? By looking for patterns in data. Not only in HR information but finance, production, sales, safety, etc. If we, the people, generate value in every company, it’s necessary that we find ways of showing the value that we produce, and how our decisions affect business’ results.
I confess that when I was deciding what career to choose, one of the most important factors was being able to work with people and not with numbers. But when I started to dig into HR data I found curious things, like I didn’t have absenteeism issues with millennials but I did with 35-40 year-old people, and millennials showed a lower turnover than X-Generation professionals. With this data I’m able to:
- Discuss ideas and preconceived concepts.
- Make better decisions.
“Working with numbers” is not taking the human aspect away from the Human Resources job. On the contrary, it allows us to be precisely “more human” by providing more accurate feedback, or replying to a complaint with more precise information than vague answers or with inconsistent answers waiting for people to get tired of arguing.
This way of thinking provided me with a whole different perspective of my career. Being able to relate data with business results allows me to separate apples from oranges, evaluate our “best practices” in order to keep the ones that bring better results, letting me save money, time and be more efficient.
That’s why I say, let’s forget about numbers and math, and start focusing on data and its relationships. That’s a great way to become a strategic partner, and gain a seat at the Decision Table.