29 Jan Limitations of HR Analytics
There are many applications where HR analytics can benefit a company. A previous blog post has shown that at HR analytics can bring at least 10 positive effects if implemented in the right way. However, the use of data analytics in the HR department has some limitations. For one, Big Data in HR is not always obvious. Another limitation can be the mindset of the people working with the data and algorithms. A third and important limitation is the data privacy and readiness of the data for analysis. In this article, we will focus on the limitations of HR analytics and how you can overcome these limitations.
Data Availability Limitation
HR analytics is only useful when data is both available and correct. When data is not available or the quality of the data is poor, analytics will not render the right results. This can lead to incorrect insights and conclusions. Deriving business decisions from these insights can be devastating for a company. Although you would like to have a 360-degree employee view to make better business decisions, this is not the reality. Information about your employees is not as abundant as customer data. Companies do not collect data collected on their employees very frequently. In most cases companies take one or two employee surveys a year. And it is not even always mandatory to participate in these surveys. The data points collected on an employee can therefore be an issue.
Also, data collected on employees are not always found in one database. In most cases information about employees is scattered around different databases. This makes it difficult to get the full employee view. Besides the low amount of data points per employee, the number of employees can also be a limitation. You can imagine that companies do not have millions of employees. Making use of Big Data is therefore not very applicable.
How To Overcome This Data Availability Limitation
HR can still act on the data that is available to them. For most HR departments the challenge is (simply) to use data at all. Even without a lot of data, insights can be drawn and business decisions can be derived. For HR departments, it helps a lot to work with IT and get a feeling where all the (hidden) data is. The IT department can also help with consolidating the different data sets, so it can be used for HR analytics.
If there are not enough data points for your employees within your company, turning to the web for more information can be helpful. Historical employee information on LinkedIn can enrich your current view of each employee. Furthermore, information like salaries in the market can give you a better feeling of what your employees might receive from your competitors. This information can be very helpful in shaping your 360-degree employee view.
All HR decisions should be informed by data and analytics. This is the mindset that HR employees should have. With this mindset HR analytics can thrive and deliver useful results. However, this mindset is not always present.
Not surprisingly, HR culture is people-centric and focused on human relations. By nature, individual humans behave unpredictably. Only with a lot of data, patterns can be identified and predictions can be made. Because of the unpredictability of human beings, HR employees are not always convinced that the mathematical techniques can describe human behavior. A lot of the doubt comes from a lack of understanding of statistics and data analytics, which prevents them to ask the right questions. This in turn can lead to a self-fulfilling prophecy: I do not think HR analytics will work and therefore it does not.
It is true that statistics and data analytics are be complex. Doing HR analytics in the right way involves collecting the right data from the right sources, understanding and running different algorithms and explaining this to the business in the easiest possible way.
How To Overcome This Mindset Limitation
HR employees can start with building their analytics skills. This will help them with understanding the most important features of HR analytics. Building your analytics skill does not necessarily mean becoming a world-class data scientist. It is not necessary to become the most analytical person in the world, but it helps to know what data should be stored and collected in order to build a good analysis. Platforms like Emplysight take the difficult programming- and visualization parts away, so focusing on the big picture is sufficient enough.
Starting with building analytical skills can be a bit overwhelming. Where should you start? What are the most important things to know? What should I know as a HR professional? Emplysight helps HR professionals with starting their analytical journeys. Workshops and sessions can be hold to get you started. Contact us to get to know more about this.
Data Privacy Limitation
Data privacy is taking over the headlines. And as news articles about privacy are often negative, it can be hard for HR professionals to start with analytics. Nobody wants to risk the privacy of their employees. And with all the technical possibilities, employees can (and should) ask which data points from them is stored and if this safely done.
In Europe, the General Data Protection Regulation (GDPR) will be enforced on 25 May 2018. The GDPR is a regulation by which the European Parliament, the Council of the European Union and the European Commission intend to strengthen and unify data protection for all individuals within the EU. If companies do not comply with these laws, they can expect heavy fines. Companies will need to obtain consent to process employee data. They also will need to map and audit the following:
- Employee data that is stored;
- Where the data is stored;
- Where the data is send to;
- How the data is processed.
How To Overcome This Data Privacy Limitation
Although data privacy can be overwhelming, there is no need to feel terrified about using HR analytics. There are clear rules and laws and following these rules will make sure that you always stay on the right side of privacy. It is very important to start with asking yourself why you need certain information. If this information is necessary, ask for permission from your employees and show what the information is used for. And last but certainly not least, use anonymized an aggregated data for your analysis. This will make sure that there is no privacy sensitive information used in the analysis and nothing can be traced to a certain individual.
As shown in this blog post, there are limitations of HR analytics. However, these limitations can be overcome with the help of Emplysight.
Emplysight was founded to give you better insight in your employees. The company aims to use both simple analytics as more advanced predictive analytics, such as machine learning and Artificial Intelligence, to help organizations get a better understanding of their employees. Emplysight helps all HR departments, wherever they are in their analytical journey.