What is HR Analytics and Data-Driven Recruiting?

Recruitment of employees has become the last line of adoption of analytics in business practices. Other tasks, such as marketing, manufacturing, finance and accounting, have learned how to use automation, sophisticated analytics, and big data to improve information quality, facilitate data collection and assist in better decision making. Recruiters, however, apparently resisted this trend for many years (Martin R Edwards,2019).

In the coming years, data-driven recruitment has the potential to transform the human resources industry. It is being accelerated by the cloud-based computing solution, more sophisticated software and the overall digitalization of the modern organization. Many forward-looking organizations are now implementing the fundamental steps towards total cloud integration. Cloud computing is the movement of data and software from internal (local) to external (remote) servers and hard drives. In three years, cloud computing is projected to raise $ 331 billion in market revenue. Information technology (IT) experts believe that the software will be almost completely separated from the hardware in the future, with an increasing number of applications stored on remote servers rather than on the user's own local hard drive. This change in storage location offers several key advantages, including increased cyber security and a unification of end-user experiences. There are additional benefits for organizations that implement cloud-based storage systems (Dan C.Marinesu,2013).The ability to centralize data from various sources through the cloud will allow companies to create substantial databases. The information extracted from these databases can be used for predictive analysis of target markets, consumer behavior and business trends, which gives companies a clear competitive advantage. With continuous advances in low-power processors and other chip technologies, companies can optimize investments and scale operations continuously, generating higher revenues, higher profit margins and greater operational agility. Another factor is the speed at which data travels across devices. Combined, these advances will allow companies to create larger applications and use their data in more complex ways.

"The dirty and good HR department is changing in the past. The geeks have arrived.
The outdated human resources department is changing. The geeks have arrived. Today, for the first time in the fifteen years that I have been an analyst, human resources departments are taking analytics seriously. And I mean seriously.”-Human resources expert Josh Bersin.

Today, Artificial Intelligence is a well-known topic that is broadly discussed in technology and business circles. Many industry experts and analysts argue that AI or machine learning is the future, but if we look around, we are convinced that it is not the future, it is the present. With the advancement of technology, we are already connected to AI in one way or another, be it Siri, Watson or Alexa. Siri is one of the most popular personal assistants offered by Apple on iPhone and iPad. The friendly voice activated assistant interacts with the user in a daily routine. She helps us find information, get directions, send messages, make voice calls, open applications and add events to the calendar.

Siri uses machine learning technology to get more intelligent and able to understand natural language questions and requests. Without a doubt, it is one of the most emblematic examples of gadget machine learning skills.

Netflix needs no introduction: it is a very popular content on demand service that uses predictive technology to offer recommendations based on reaction, interests, choices and consumer behavior. The technology examines a series of records to recommend movies based on your previous tastes and reactions.

It is getting smarter with each passing year. The only drawback of this technology is that small films go unnoticed while large films grow and spread on the platform. But as I wrote before, it is still improving and learning to be smarter.

Data-based recruitment encompasses the technologies and techniques used to analyze a large group of talents and identify candidates with the right skills and the right mindset to help the organization achieve its objectives. Applied well, it helps companies find employees who will fit into the corporate culture and become strong team players (Lyndon Sundmark,2017).

According to a recent LinkedIn report, data-based recruitment allows recruiters to
1.Ask the right questions.
2. Browse a large group of candidate data.
3. Analyze the results
The results are proven; Xerox used algorithm-based recruitment to decrease its dropout rate in its call centers by 20 percent. And these "people analysis" can lead organizations to recruit more productive workers. For example, Apple's best developer is more than nine times more productive than an average worker in a competing technology company. The best sales associate in Nordstrom generates more than eight times more revenue than an average seller in a competing store.

Other benefits of data-based recruitment include:

1. Improved workflows.
2. Almost immediate access to records and metrics.
3. Job search in real time.
4. Predictive analysis.

Part of what makes data-based recruitment successful is that it leverages a group of talents that can be used as a pipeline to identify candidates and reduce options until only the most suitable candidates remain. One of the challenges is to make data collection consistent: paper resumes are passed and candidates should be encouraged to submit their application through a portal on the organization's website. This eliminates the need to analyze individual resumes and enter data manually.

Bersin says there are two reasons for the urgency of adopting data-based recruitment:

1. It facilitates the use of the systems.

2. It improves the accuracy of the database used for people analysis and decision making.

In the Bersin report, 73 percent of organizations seeking updates said they want integrated data and analysis to be part of their new systems. Two-thirds of respondents said they are looking for a cloud-based solution.

The data-based hiring process is where human resources professionals / recruiters take advantage of the useful knowledge of the data, tangible facts and statistics to make solid and informed hiring decisions, from the creation of hiring plans to the selection of candidates. The advantages of Data-driven hiring process are Removing guesswork from hiring and forecasting, Better quality of hires, Reducing the time and cost to hire, ensure personalized and seamless candidate experiences and Removing bias from hiring and improving diversity &inclusion.

The disadvantages of Data-driven hiring process are if the algorithms used in the data-based approach reflect human biases and preconceived notions, then we may be automating human biases, Wrong/ irrelevant/ poor quality data, Recruiters lack data and analytics skills, Too much focus on the quantitative insights and Data is not translated into decisions (Rubert Morrison,2015).