Data and analytics help aligning HR strategy with the organization’s business goals. It is widely recognized that the people within an organization are one of its most valuable assets. Artificial intelligence and machine learning are enabling human resource officers to use data and analytics to assist them in making decisions regarding the people they manage. Ideally, companies will use tech driven intelligence and data analytics in the sourcing and hiring process, all the way through the individual’s career journey within the business.
Using AI and data analytics enables companies to make decisions in real time. This is naturally more cost effective and contributes to the overall agility of the organization. When using AI, decisions regarding the performance of employees can be made immediately and organizations do not have to wait for quarter year progress and performance reviews.
According to Michigan State University there are five ways in which HR and management teams are using data and analytics to increase the performance of organizations.
- Measuring Performance
Businesses and organizations can use data and analytics as well as AI to determine performance targets for employees. These benchmarks can be used to train and encourage current, new and future employees to understand these requirements and the impact they have on their job role. The data collected not only serves to benefit the organization, but it can also be used to help guide the individual in question. Areas that are looked at include not only professional performance, but also all over wellness and energy. Data obtained from top performers can be used to understand the process better and establish what is needed in order to complete the job objectives more efficiently. This can also contribute to training processes and increasing the efficiency thereof.
- Informing salary decisions and promotions
By utilizing data, employers can observe and monitor the rate at which promotions and raises are given to employees. Using data also means that the key factors driving raises and promotions can be identified and observed. Is it more ethical to promote a junior that made a big sale recently, or the senior employee that consistently delivers quality performance? By using AI algorithms managers are supported in their decisions.
- Understanding Attrition and Increasing Retention
Performance based data and analytics can indicate and predict which employees might be at higher risk of leaving the company. It also serves to capture information that tells us what factors cause or contribute to attrition. Sometimes underlying factors like a manager’s interpersonal communication style can affect attrition more than money does. When you are aware of the variables impacting on your staff, you are able to adjust these to increase your staff’s performance, or to identify the problem areas. Understanding these variables also means that you are able to evaluate your recruitment and training processes.
- Examining Employee Engagement
Employee engagement is a very important metric that businesses and organizations need to be aware of and use to their benefit. This data is often gathered by using external parties to conduct surveys. However, with the technologies available today, businesses and organizations can easily conduct these surveys in house. When this is done in house, the surveys can be shorter as well as more frequent. AI tools help gain immediate insights in these surveys. Gamification can also be used to get the required information from the employees.
- Measuring Employee Development and Learning Outcomes
Successful training programmes help businesses to reach their business goals. Rather than ask the participants what they thought of the training programme, a business should shift its focus to measure the employees understanding of the training programme. The employees’ whole training process should be observed, measured and tracked. By recording this data, the business can see how effective every part of the training process is, as well as how the training process can be improved in the right areas.
In the core of data analysis is defining the right questions. Only then can it be evaluated which kind of data is needed, and from which sources. The selected data can then be collected, combined, cleaned and analyzed. It is this process that eventually creates insight.
When you have insight into how your employees’ function and why they do what they do, you are able to provide them with a better work environment fit. Having a good work-environment fit will contribute to their employee satisfaction and this has only positive consequences.