Karen Correa, who works at the People Analytics department at Wildlife, gives us some key points of this industry.
Historically, HR has never been a department very familiar with numbers and data, and for this reason, decision-making was traditionally based on the manager’s and team’s intuition. However, despite all of their experience, using something so subjective to hire new talents, develop better internal practices, or even for conducting small-scale opinion surveys may end up compromising processes when the only available baseline is how that person “feels” about something.
At Wildlife Studios, we aim to be different. Better. Technology is the core of our company, and that’s why the market came to recognize us the adjective of “data-driven”, which we’d end up taking as our mantra.
Every one of our areas moves by and through data, quantitative and qualitative analysis that helps us create scenarios in order to anticipate the best course of action.
Obviously, people are not numbers, and intuition is still a deciding factor. However, we can use data – and we produce copious amounts of it – to establish situations that help us better understand the moment we’re in and how we should go to reach a particular objective.
That’s why, in our People Analytics division, we use data to dictate preferences of “stewarding” our company – from seeking new talents all the way to comprehend what makes a professional seek new opportunities and leave us. Wanna know how we do it? Then keep reading:
Data analysis as the guiding star for human capital
Before anything, we need to establish context: inside People Analytics, we are responsible for all data pertaining to the company’s workforce – hiring process and recruiting, onboarding, training, benefits, performance cycles, internal engagement (work satisfaction surveys), employee retention – all of these parameters end up coming our way, sooner or later.
*Wildlife’s employee journey
For example: what is the average time taken for a specific department to go through an entire hiring process? What’s the most effective channel for talent-seeking? What is the turnover rate (percent) of each area for top performers? How many of said top performers are leaving the company and why?
All this helps us to understand our own behavior when it comes to HR: we put subjective intuition aside and look at data, searching for clarity of all facts without bias, so we can make decisions based on practical knowledge cushioned by numbers. We always remember that the final call will always be human, and data is used to provide that human decision with concrete numbers, creating a more comprehensive reality of facts.
When we say “data” for HR activities, it’s not uncommon for a lot of people to glare and avoids the topic, usually saying the same thing: “people are not numbers”. In truth, the use of data in HR is so much more functional and interpretative than that, such as this: because we always had such a major focus in hiring, it was usual for us to distribute our job openings more intuitively, based on what we thought was each recruiter’s potential to deliver. However, given the seniority level of each of them and the different complexity levels for each area, sometimes, this was not the best strategy for attaining the best results.
So we dedicate ourselves to a deep analysis in order to understand the true behavior we had in the past. Through that reference in historical data, we estimated the potential and capacity for all recruiters based on the level of complexity of each opening and department. And our job is to help managers distribute better hiring necessities between their teams in the most assertive, strategic way possible.
People are not numbers (but numbers will take us to people)
Of course, there is a substantial intuitive part on talent management – that happens inside every company. Even the more engaged employees have their moments of uncertainty, and our data helps us manage – and quell – those fears. We conduct engagement surveys, ensuring that every information analyzed has its own weight and can translate reality in numbers, data crossing, and above all, for managers to get the help they need – through the numbers – to make decisions that improve the team quality of life.
Yes, through the numbers. And no, we’re not reducing employees to data.
Think of it like this: a number is just a means to a better human decision. Data is exact, but it does bring historical context – and uniting the quality part, and the amount of data is what really makes a difference. We employ data in order to eliminate uncertainties.
In other words, the number is the trigger for us to understand a scenario, but the decision on what to do with it is still human. We don’t “think”, we’re sure.
It’s easy to see why People Analytics is perceived as the point where numbers justify themselves – and this is not (entirely) untrue. However, the key point in this is how does Wildlife use said numbers to improve its “Wilders”?
The first moment where this comes into play is during recruiting phases, where, based on historical behavior data, we can determine which is the best strategy for hiring someone for a particular position, defining channels with the most significant potential on finding the best talent, always aiming to improve and optimize time consumed and energy. We also have the visibility of the average rate of “yes” and “no” – what makes a candidate accept/reject our offers – and, because of that, we can predict possible obstacles that may show at the moment we extend a proposal to the candidate.
Performance analysis is also a reality here, helping us understand how a team executes its role and how to attack the necessary chokepoints.
Most importantly, all data can be crossed so that we can get a full, 360-degree view of an employee-s journey inside Wildlife – a much richer vision, I might add.
To be “data-driven” requires a change in behavior as well as mindset: you have to use all data as a means to drive your decision-making, but this change does not happen overnight.
Our recruiting team, for instance, have access to numerous dashboards with KPIs, metrics, and data on its hiring processes. Still, if recruiters are not qualified to comprehend a red flag allotted on this or that number, thus working more strategically with a solid base on their actions, all that data will make no sense since they’re not bringing the value they’re supposed to.
Thus, we are also responsible for developing our HR team when it comes to analytical thinking, problem-solving, and data comprehension.
At Wildlife, our intense growth has yet to put us under the so-called “downtime” – that is, the moment where a company slows down and stops hiring people for a time. However, our data already allows us to have certain visibility of process improvement, which gives us many clues to look for references in the industry.
In Brazil, people analytics discussions are taking form, albeit still in a very embryonary state, so, through one of Wildlife’s key values – “We innovate with research” -, we promoted benchmark tests to understand market trends and identify where and how we can improve ourselves and our data approach.
The point is: using numbers in HR does not have the aim to “quantify” people, but to actually improve them! That is what allows us to indeed be a genuinely data-driven company.