People analytics is an important subject amongst people managers, giving us, HR professionals, the chance of having a bigger and a more strategic impact on the business and talent development. We had the opportunity to discuss with Razvan Radu, co-founder of Humano, about the importance of HR analytics. Razvan is an HR passionate, who understands humans behind numbers, helping companies making data-driven decisions and building engaged teams.
First question is about you: Tell us about yourself - who are you and how did you become your present self? How did you come up with the idea of Humano and why people analytics?
I like to think that I’m a sociologist, an HR passionate and a data driven person.
Humano was founded on the desire to change the way organizations approach people. The name comes from the association of two words: human and the abbreviation of number (no.). The text “humans behind numbers” was added as a constant reminder to all decision makers that behind all the numbers are real people.
The idea came when I realized that most of the consulting projects are consumed by technical work of getting all necessary data together for the metrics that you need in order to make recommendations. I think that time should be used more meaningfully. The idea however, became a reality when I met Elvis Apostol, my co-founder and CTO. He is an expert in finding optimal solutions to solve complex problems that companies face, excelling in ensuring the scalability and efficiency of the developed projects.
Everybody is talking about people analytics, it’s a blooming and booming subject for businesses. But it is not a totally new practice within the HR departments. How do you think people analytics is transforming the HR department?
First of all, HR professionals get to do a more meaningful and enjoyable work. It’s a work that develops them both in a professional and personal manner. People analytics gives the HR department the opportunity to directly influence the success of the organization.
Using this method combined with their people skills HR professional’s now have the opportunity to become strategic. The data and measures along with the monitoring metrics will position the HR professionals as people experts. It makes a switch from a support department to the team that can directly influence people's performance. As people experts, the HR professionals are in charge with the design of practices managers should follow in order to generate within their teams, a sustainable performance growth.
When should a company / an HR department start implementing and developing people analytics?
Yesterday, like all valuable programs. Joking. It should be a top priority. Implementing and developing people analytics means understanding the real issues within the company. Understanding is key. If you understand the roots of a problem, the solution comes naturally. I have met a lot of companies who say “People Analytics is not for us”, “we are not at the right level to even think of analytics”, “it’s rocket science” or my personal favorite: “our culture is not about tracking and labeling”. Well neither is People analytics. What this companies are saying is basically that all decisions are made based on the memory, intuition and gut feeling of the decision makers. Would you like to work for such a company? Or would you like to work for a company that is able to objectively identify and reward performance, or for a company that has an enabling culture where you can develop both personally and professionally and be successful. It’s a dangerous loop, so my advice is: Just do it! Start! Don’t wait for the perfect moment as it may never come. You will always find some other pieces of information that would be helpful. Let’s face it, your data will never be perfect or complete. And on the other hand, going from nothing to a lot of data will most probably give you analysis paralysis.
If you are asking yourself when is the time, a very good exercise is to rephrase the question to: When should I start dealing with the real problems within my company? I think we all know the answer to this question: From day one of existence.
What are the steps to successfully implementing a people analytics programme?
We use a very simple and straightforward perspective:
Step 1. Data Assessment:
a. Identify all the sources from which you can & should extract valuable data: software (Payroll, HRIS, LMS, ATS, etc.), excel files used by employees, surveys, market reports, etc.
b. Diagnose it. This means you should check for: data accuracy, completion, consistency, uniformity.
c. Create a treatment plan. Decide and describe the actions you need to take (correct, delete, collect in the future, mandatory info, etc.).
Step 2. Create a strategy designed to take you to higher levels of data collection capability and quality. If you already have one, revise it in accordance with the findings in Step 1. Include milestones, be descriptive on what data should be collected and how. Don’t forget to offer context and meaning, so explain the reasons why that data is needed. Set clear responsibilities for every job regarding data quality.
Step 3. Create a data warehouse or a data architecture that will allow you to process data in an easy manner. This is where most companies get stuck due to the lack of IT and technical expertise in the HR department. At this step you should put in place processes that extract data from the tools you now use, transform it into a uniform format and load it into the warehouse. The data in the warehouse will be the base for your dashboards and analysis.
To overcome the data warehouse challenge, you can find on the market different solutions, like automated data flows, data management feature, a library with explained metrics. With a survey module / option it becomes even more powerful.
Step 4. Upskill your HR people. Better said, create a strategy to do this, as it cannot happen overnight or in just one or two training sessions. To be able to crack data, your HR professionals need to understand people and which are the factors that determine performance, engagement or the opposite. The strategy should be towards upskilling on sociological, psychological and business know how. I need to point out the importance of knowing the business. Without understanding the industry and its challenges, how the competition differentiates and the challenges faced by every line manager in the company, you will only solve problems of marginal importance.
Bottom line you need two strategies: one for your data and another for your people.
What are the top lessons learned from a successful implementation of a people analytics programme?
I really like Jim Barksdale’s words of wisdom:
If we have data, let’s look at data. If all we have are opinions let’s go with mine.
So true. Take a closer look and you will find this approach in many situations. A lesson learned from implementing people analytics in organizations is that giving people access to data (within boundaries) creates a very healthy culture. Opinions transform into hypothesis which need to be tested on data. Line managers understand and like data and metrics. They use them in their daily business planning. If clearly explained, they will understand also the HR metrics and their usefulness. This process sparkles conversations and guess what happens? HR and line managers partner to identify and solve real problems. The relationships transform itself into a “pull in the same direction” approach and so the business and HR and acts as one team. The HR is no longer the “bad guy”, the one responsible for not giving a raise to an employee or a promotion, etc. This is due to the fact that now both parties speak the same language, have the same objectives and use the same methodology to identify the sources of problems.
Another lesson learned is that People Analytics is disruptive. Often times companies have blind spots. People Analytics will paint the picture of who you really are with good and bad. Sometimes it will make you uncomfortable and force you to rethink how to approach certain problems.
Last but not least, it’s way easier to implement People Analytics than people imagine. I would dare to say that up to a certain level applying this method is just a matter of willingness.
What are the top 3 metrics each CHRO / CPO / HRD should start her/his day with and why?
A question I get a lot but I have to answer like a good consultant: it depends. Metrics should have an objective. If I were a CHRO I would start my day with the metrics that best describe the evolution of my ongoing projects. A company can have a different range of problems or objectives that have ongoing measures. Let’s do a simple exercise and take 3 general objectives with 3 metrics to measure:
Objective 1. Diminish the turnover rate. Metrics:
1. Turnover rate on tenure categories
2. Reasons to leave
3. Performance at departure
Objective 2. Increase performance. Metrics:
1. Mapping of performance moves
2. New hire performance rate
3. Percentage of skill gaps closed
Objective 3. Improve the recruitment process. Metrics:
1. Recruitment funnel conversion
2. Source effectiveness
3. Time to fill
Going beyond the debate that the above metrics can change depending on the problems you want to fix. If you’d have to pick the 3 metrics (out of the above 9), that can give you insights about whether you’re on the right track or not, with each objective: which would you choose? Difficult, isn’t it? It gets more difficult if you want those metrics to also give you insights where to focus your attention. This is why companies are making steps towards dashboards. Three, five or even ten metrics are not enough, never were. Going back, if I were a CHRO without dashboards I would start my day finding solutions to create them.
How are these metrics different for an HRBP, for example?
The before mentioned principle applies also for the HRBP. Dashboards aligned with his objectives across the company. The HRBP should be the one that is able to understand and identify what problems keep the managers up at night. I think that HRBP’s dashboards should include metrics regarding manager’s ability to implement HR practices.
What are the top 3 metrics a recruiter has to constantly observe the evolution of and why?
1. Source effectiveness. Measuring the conversion rates for every source will allow you to focus your attention towards the channel with most chances to attract talent.
2. Time spent by candidate in every recruitment step. This metric will allow you to rapidly identify in which step is room for improvement.
3. Performance of new recruits. The effectiveness of a recruitment source should also be judged by the performance of the employees offered. It is also a very good way to understand the candidate profiles and job requirements.
How can we use people analytics in the selection process helping us to predict if a candidate is going to be successful within the role or even better, a top performer?
Doing this type of predictions usually require at least a decent level of statistical skills within the HR department or technology to assist you.
One way that should come in hand to a lot of companies is to compare the characteristics of best and worst performers. The comparison should be on employee cohorts. Based on this comparison, profiles can be made. Afterwards, different statistical actions can be taken like: testing for statistical significance, or multivariate regression. I will not get into further details as this is not a statistical course.
Predicting whether the candidate is going to be successful within the role or a top performer, a lot of information should be taken into consideration, like: job description, team skill gap analysis, top performers and worst performers psychometrics or assessments, candidate psychometrics or assessments, candidate previous experience and activity, candidate tests, referrals, etc. This type of work is usually done by AI which is able to standardize the matching between candidates experience, knowledge and skills with job requirements. Usually, AI in recruitment is helpful in the screening stage and can improve the matching. Unfortunately, AI has its downsides, as it can also learn human bias. A lot of progress was made in recent years but there is still a long way for recruitment AI to accurately predict performance. Until then, the recipe for success is the mix between recruitment software, AI, statistics on current employees, psychometrics and well trained recruiters.
What resources on HR metrics would you recommend to follow?
Our community loves everything related to learning and development. What book(s) on people analytics would you recommend for us?
I would recommend the following books:
As a final thought, people analytics is more than just a statistical analysis. Knowing how to interpret and correlate HR metrics, we can predict employees’ behaviour and have a higher and a more strategic impact on the business growth.