With the popularity of analytics and data science in various organisational departments, I saw an opportunity to expand both my HR and analytical skills into this new domain. In a sense I have been doing this “job” all the time, however I was doing it disconnected from the business. Now I am preparing myself for a new era, when my HR analytics are taken into account by senior management for decision making.
The term HR analytics (or people analytics) refers to how we use people data in analytical processes, with the aim of solving real business problems. HR has a huge role to play in improving business decisions because as a department, it administers and has access to so much key data.
Traditionally, HR has often not been viewed in the light of contributing data-based decisions, but HR analytics gives us some powerful tools to contribute with.
What is the role of HR Analytics?
Essentially, we can say that the role of HR analytics is to analyse “people problems” using data. Correct analysis can help you to answer critical questions about your organisation.
HR analytics is allowing practitioners to revolutionise the field of HR, much like how data analytics has allowed for innovations in marketing and sales. The bottom line is that HR is able to make better decisions by using data.
Presenting a business case is also made easier by having the backing of data. HR practitioners are able to present their case, then test the effectiveness of their interventions. In this way, HR analytics is helping HR to move from an operational partnership role to more of a strategic partner.
Creating strategic value goes beyond simply keeping records. The goal is to be able to form insights from the various data sources that HR has available and use that to answer key strategic questions. For example, how do you figure out attrition, retention and specific workforce planning? HR data can provide accurate predictions. Furthermore, it enables organisations to answer many other questions, such as integrating workforce and financial data to analyse talent investments compared to company results.
It can be argued that human capital is the most important asset of an organisation. HR analytics allows businesses to build up an in-depth knowledge of their staff, get better answers, and use that to build competitive advantage.
Key benefits of HR analytics
HR analytics can help you to view historic trends and create predictive models that lead to better insights for the business. Here are a few key benefits:
- Use data to better understand and deliver to worker needs. This can help improve satisfaction, and therefore retention as well
- Discover areas in the business where better efficiencies can be made. For example, perhaps there are areas that could be improved by introducing automation, or making process changes
- Discover how informal communication structures work in the organisation. Businesses may have an organisational structure on paper, but this is rarely precisely how communication works. You can discover who the central links are for sharing information and forming relationships
- Create better criteria for hiring new staff and develop a better hiring process. Analytics helps companies to determine this by finding patterns from what has happened with hiring previously, comparing characteristics such as qualifications and experience with how long the person stayed and how successful they were
- Create predictive models for analysing turnover and planning for hiring needs
- Analyse employee performance based on impartial data rather than potentially biased opinions of others
There are more key examples I could mention, but the bottom-line benefit of HR analytics is that it brings structure and integrity to key people-related decisions. In the past, we may have worked from our previous knowledge or instinct without delving into data. This certainly leaves decisions open to biases that a data-based setup can clear up.
Bringing HR and Data Science together
HR analytics essentially brings together what has traditionally been separate roles – HR expertise and data science skills. The most effective HR analytics practitioners need good HR knowledge, paired with data analysis abilities, so at this early stage, people often have to learn one or the other.
Data education for HR practitioners is a critical step for optimising their analytics abilities. My personal theory on this is simply to look for opportunities to practice and manipulate data. There are courses available online, along with practice data sets. Competitions also provide an excellent training ground.
Along with mastering basic skills, HR analytics can benefit from efforts to continuously improve. For example, an article by Rob Grey outlines how for the most part, data analysis has been backward-looking. This means HR has had a tendency to study what has already happened, however there are opportunities to be had in mastering predictive analytics. Measuring historic performance is important, but what about planning for the future?
“Monitoring KPIs and the like is tremendously valuable for showing what organisations, teams and individuals are doing well at and identifying where there is room for improvement. But how much better would it be if data analysis could also provide a reasonably reliable picture of the future and be used to inform the people-related decisions of tomorrow?”
Grey goes on to note that reaching a point where predictive analytics can effectively be used is not a simple issue. One of the key challenges for businesses is that they often either don’t have great historic data, or it is stored across many different systems, making it difficult to extract and extrapolate the data.
Another major challenge Grey points to is a lack of skills and confidence in the area of analytics within the HR department:
“This lack of confidence shows in the analytics practice in organisations; even something as fairly basic as people data reporting is not common,” says Houghton. “HR professionals globally still have to get the basics right, before they can start to predict behaviour.”
What is the role of R?
What does R have to do with all of this? You’ll often see discussions of R intertwined with HR analytics. This is because R is a premier programming language to build up data analysis skills and deeper analytics knowledge.
A thorough grasp of HR analytics requires something that will perform better than Excel. R is my own personal preference (over other potential options such as Python or SQL), but it’s also a common preference among other HR analytics practitioners. Personally, I believe it wins hands-down based on simplicity. I am a self-taught R user, and found that there are plenty of opportunities to work through courses, enter competitions and generally build up knowledge and skills using R.
R is a free, open-source program which also gives it the advantage of being a cost-effective tool to operate. One of the major advantages in my view is that there is just so much you can do with it. The data manipulation capabilities far outweigh anything you can do with an Excel spreadsheet, while it has the ability to process vast amounts of data very quickly.
R is one of those programs where you don’t have to be an “expert” on the entire thing in order to effectively make use of it. You just need to be knowledgeable enough to use it for your specific needs and goals.
You can start by learning what you need to know, when you need to know it. It’s easy to go into a rabbit hole, learning things with R that don’t necessarily have practical application for your purposes. If you stick to a focus on key business questions, it helps to guide what you need to learn.
Final thoughts
The role of HR analytics is transforming how the HR department operates. It helps to give HR a strategic seat at the table for business decision-making and ensures those decisions are based on verifiable data.
People analytics can help to answer a number of key organisational questions and importantly, help the business to gain a competitive advantage. It’s also about fairness and accountability when you look at it – it’s easier to point to decisions based on clear data than to those where opinion is the basis.
The challenge for HR overall is to upskill. Departments need to improve their analytical skills and use of tools such as R to help. Those who do so are bound to help advance the position of their organisation.