20 Feb The HR Analytics Journey
It can be hard to start with HR Analytics within the company. As discussed in a previous blog, there are some limitations to HR Analytics. These include for instance data availability. However, it is very important to start small with your HR Analytics journey and to slowly expand your horizon. This article shows how you can start with your HR Analytics journey.
First, the barriers
When starting an HR Analytics journey, the barriers will first come up. You would like to have access to the data and know which data to look at. Besides that, you would like to analyze the data in a correct way, which can become quite difficult if you would like to do the more advanced analyses. Sure, there are machine learning programs like R and Python that can do this, but those are programming languages and the typical HR employee will not have advanced programming skills.
Where to start the HR Analytics journey
Having access to the data is very important, but it is not necessary to have access to all possible HR data, from recruiting till retiring. You want to pick a project that will have the biggest impact on the business. This can be for instance predicting which employees will likely leave your company and trying to lower this in the future by taking action. Another project could be discovering absenteeism factors and trying to mitigate those.
If it is possible to calculate the Return On Investment (ROI), there is even more reason to start with the project. This only holds true if the ROI is positive of course. By having a positive ROI for the project you want to start, other departments can see which benefits HR Analytics (and the HR department in general) can bring to the company. However, do not be discouraged when a ROI for a project can not be calculated. In some cases it is just very hard to come up with all the benefits a project can bring to the company. In that case it is important to list all the benefits of the project, so everyone knows what the project will bring the company (or the HR department).
The four areas of your HR Analytics journey
When a project is chosen, you can divide the HR Analytics journey into four main areas, namely Discovery, Data, Analysis and Storytelling. In the chapters below we will deep-dive into each of these areas.
During the Discovery stage, you want to understand the business problem. If you can link it to a financial outcome it is even better. An example would be that you would like to increase the retention of your best employees in the Sales department. By retaining your good Sales employees, you save yourself recruitment costs and training costs for the new Sales employees. Another big business outcome would be that you will maintain your Sales revenue, which would most certainly decline when your best employees leave.
When the particular business problem is defined, you can start looking at the data. It is not necessary to have all the data of your employees. As you have defined your business problem, it is important to see which data supports the business problem and the potential outcome. It is therefore crucial to have defined a business problem and a scope. Otherwise, you will not know which data to look for and will try collecting all the HR data that is available within the company. This is in almost all cases doomed to fail.
The data could be scattered around different databases or could be in a lot of Excel files. You would like to have the data in one central place, so more insights can be drawn from the data. This may take some action as data from different files could have different formats .When the data is collected, you can start optimizing the data. Relabeling and bucketing certain data are part of this optimization step.
During this step you should also look at the legal aspect, as some HR data is highly sensitive and collecting certain data is not legally possible.
When the correct data is collected and optimized, you can start with the analysis phase. This can be done in a lot of different ways. Doing the analysis should of course be linked to the business problem you are trying to solve. If the business problem is that too many employees are leaving the company, you could start analyzing the drivers behind employees that leave the firm. This could be through interactive dashboarding so patterns and insights can be found or using machine learning to see what the machine thinks what the drivers are for employees leaving. For other problems where you have to look at more unstructured data from your employees, like plain text, you could for instance use Natural Language Processing (NLP) to discover certain patterns. This could for instance be used to analyze what the sentiment is of a certain e-mail.
Once you analyzed the data and found the insights you are looking for, you have to take action. This is where storytelling becomes important, as you have to show the colleagues around you what you saw in the data and what the next best steps are. Storytelling becomes easier when the data is visualized, so make sure that what you have seen and found in the data gets visualized. When you have convinced your colleagues with your beautiful visualizations and the explanation that comes with it, the next best steps should be laid out so your company can tackle the business problem.
When telling the story, make sure that you know your audience. The way you want to tell the story to the CEO will be very different compared to the story you will hold in front of the CHRO.
So, the key take-away is to start small. Try to find a business problem you want to solve and collect the data that helps you solve this problem, instead of trying to throw all HR data in one system and looking for insights. When the data is collected do the analysis and visualize it, so telling the story to your colleagues will become much easier. And last, but certainly not least, take action based on your insights.
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.