Human Resources Datafication (Part 1) | by Michelle Venables | Towards Data Science

Michelle Venables, Data Scientist and Machine Learning Engineer
What is the strategy that is best aligned with business activities and human capital? Human Resource (HR) strategy is the idea that sets a direction for all the key areas of HR. It is our increasing ability to use analytics to understand more about people, HR processes, and demographics. This includes activities with hiring, performance appraisals, development and compensation
As data analysts/scientists in the HR space, we would develop a strategy to tackle HR goals and insights over the entire organization. We want to start off with Data we already have within the organization starting with our current employees. This might involve strengths and job descriptions across the organization. An example of this and a good solution would be to use an interactive organizational chart.
Start by collecting everyones updated resume, continuing education history, performance appraisals, and projects completed. This gives you the ability to identify your current employees’ knowledge, skills and strengths. An interactive organizational chart can be a tool beyond the basic job descriptions and skills.
Evaluating performance reviews allows management to determine when employees are willing and able to assume additional responsibility. When employees consistently rank high then its time to take on some more challenging work. This blog is meant to describe some tips when analyzing HR strategy and activities within the firm.
There are a few KPI’s worth mentioning in the HR analytics space. The following 8 metrics are quantitatively evaluated.
Talent Retention — The ability for an organization to retain its employees. This is normally a statistical measure and sometimes thought of as an employee’s loyalty to their company.Recruiting Effectiveness — there are a couple of ways organizations measure their recruiting effectiveness. A common statisical measure can be Time to Fill, Quality of Hire, Source of Hire, etc.Employee Performance — job rating scales are a common way to evaluate performance of employees, behavioral elements such as understanding job tasks and participation in decision making.Employee Movement — when an employee transfers from one organization to another and is also called the turnover rate. Similar to assessing the retention rate.Total Rewards — this is a tool that managers or employers keep track of in order to attract, motivate and retain employees.Learning and Development — training programs allow employees to grow and succeed within an organization. It allows employees to reach a higher level of skills in knowledge within the organization. These can be evaluated and monitored with performance reviews or with rating scaled (as stated before).Diversity and Inclusion — measuring and improving ideas and creativity. Attract and attain talented people in order to form strong teams.HR-to-employee ratios — delivery of services
Talent Retention — The ability for an organization to retain its employees. This is normally a statistical measure and sometimes thought of as an employee’s loyalty to their company.
Recruiting Effectiveness — there are a couple of ways organizations measure their recruiting effectiveness. A common statisical measure can be Time to Fill, Quality of Hire, Source of Hire, etc.
Employee Performance — job rating scales are a common way to evaluate performance of employees, behavioral elements such as understanding job tasks and participation in decision making.
Employee Movement — when an employee transfers from one organization to another and is also called the turnover rate. Similar to assessing the retention rate.
Total Rewards — this is a tool that managers or employers keep track of in order to attract, motivate and retain employees.
Learning and Development — training programs allow employees to grow and succeed within an organization. It allows employees to reach a higher level of skills in knowledge within the organization. These can be evaluated and monitored with performance reviews or with rating scaled (as stated before).
Diversity and Inclusion — measuring and improving ideas and creativity. Attract and attain talented people in order to form strong teams.
HR-to-employee ratios — delivery of services
We want to collect and evaluate this data in order to define where we are as an organization in terms of HR. The culture and behaviors of employees makeup an organizations team atmosphere and it is HR’s job to build a strategy for success. I have gathered Human Resource data provided by Kaggle.com in order to show an evaluation of an organization. CLICK HERE FOR LINK
The first step of a data science project is to make sure we clean and evaluate our data. Cleaning involves dealing with null values, assessing what data is currently available to us, and using different cleansing techniques to organize the structure of our data. Big, dirty, messy, and incompatible data sources can lead to ineffective analytical models. We want to understand our data and here are a few ways on how to do that:
hr_data.shape
Our output is 300 rows by 21 columns.
hr_data.isna().sum()
Checking for NA results and learning how to deal with them. One way might be to fillna with 0:
hr_data = hr_data.fillna(0)
After some basic cleaning techniques we can start analyzing and evaluating. I personally like using Seaborn and Matplotlib in order to visualize my data. After viewing our data columns, I believe that evaluating pay_rate might be beneficial. We might even want to predict newer employees pay_rate based on performance scores, position and other characteristics! Let’s take a look on our available data before trying to solve for new employees.
chart = sns.barplot(x='performance_score', y= 'pay_rate', data=hr_data, palette='Set1', ci=None) chart.set_xticklabels(chart.get_xticklabels(),rotation=90)
Make sure to import seaborn as sns before running your line of code. What can we analyze employee pay rates?
I’d probably ask some questions about the “Needs Improvement” performance score... Why are these employees at a higher pay rate than employees that “Exceed” the employee performance scores. “Exceptional” seems accurate.
chart = sns.barplot(x = 'position', y = 'pay_rate', data=hr_data, palette='Set1', ci = None) chart.set_xticklabels(chart.get_xticklabels(),rotation=90)
Our second chart shows pay rates based on positions in the company. Obviously, President and CEO are at a higher pay_rate than other employees. The positions/pay_rates seem to be accurate as long as they align with your company’s HR strategy.
Our next plot will help with analyzing some diversity within the organization. Diversity is a KPI when evaluating our Human Resource Strategy.
Organizational diversity in the workplace refers to the total makeup of the employee workforce and the amount of diversity included. Diversity refers to differences in various defining personal traits such as age, gender, race, marital status, and many other secondary qualities.
Take a look at some of our diversity evaluation bar plots below:
It’s not much of a difference but on average males have a higher pay_rate than females.
We binned our ages based on decades in order to evaluate diversification based on age. We can see that our ages ranges are pretty diverse.
After cleaning our data and evaluating pay rate based on performance scores positions, and diversity measures you should have a good sense of what our data looks like. Before we get into our modeling you always want to clean and evaluate our data. Stay tuned for my next blog on predicting HR analytics and for references to my code click on my github link below!
Human Resources Datafication (Part 2)
HR_Project — Github link
Medium Link
References:
[1] Bizfluent. “What Is Organizational Diversity in the Workplace?” https://bizfluent.com/info-12076820-organizational-diversity-workplace.html