Data-Driven Recruitment Process that makes for next-level Hiring

Data has changed the game of business and how! A recent report by International Data Corporation shows that organizations are managing about 57% of data in motion on a continuous basis. Data science is becoming key to business processes, helping organizations to make informed decisions based on the collected information and analyzed data. Data-backed insights are a godsend and organizations are turning to data to make business decisions and become data-driven.

Transforming your business into a data driven recruitment machine demands a major cultural shift in work ethics and environment. The first step towards a successful working model is to lead by example. An executive sponsorship can help you set expectations for everyone to adopt a data-driven mindset for making decisions at every level. Once you have instilled a discipline of relying on data for innovation, change and strategies—it becomes easier to explore the full potential of a data-driven approach. So, first and foremost, start at the top for any change.

Another important step that can help an organization to understand the data-driven approach is to make data available for the decision makers. Famously known as data democratization, it removes gatekeeping, and improves efficiency and productivity within the organization. It helps in optimum utilization of data as you shift the ownership of data analytics solely from IT to all decision makers involved.

Now that the decision makers have their data, it is important for them to understand how to read, interpret and use it for making profitable decisions for the business at every level. Adopting a work culture based on data requires all the employees to talk about data, visualize its impact and present analytical decisions based on the interpreted information. This is where data literacy and acumen sessions come to play. Investing in various data literacy training sessions (as per hierarchy requirements) can go a long way to build a data-driven culture in your workplace.

Furthermore, investing in apt technology and talent can help you build a data-driven organization. Where the right tools and technology plays a crucial role in extracting and providing accurate, clean and easily accessible information for a data-driven organization, hiring data visionaries can give you an advantage to work with employees that are willing and capable to adapt to an analytical approach for making decisions.

Taking hiring to the next level with data driven recruitment

Using analytics and data to find the best possible candidate for a role in an organization is called data-driven recruitment. Data based talent acquisition can help you overcome the basic challenges of hiring, making it an efficient and a less time consuming process.

From analyzing the skills of candidates to making an informed hiring, data smoothens the creases at every stage of recruitment. It includes minimum manual search efforts and hiring decisions made on gut-feel, mitigating guesswork and making decisions more objective.

A Career Builder study reflected, nearly three in four employers (74 percent) were affected by a bad hire. A majority of these hires were made due to manual screening errors. Where 32% employers took a chance on a “nice person”, 30% were pressured to fill the role quickly and 29% had a hard time finding the right candidate for the role.

A good or bad hire will have an impact on the bottom line of a business. According to a LinkedIn report, an efficient sales associate at Nordstrom brought in over eight times more revenue to the business than a general sales associate. Proving that programs and tools can only bring a structure to the framework of an organization, but it is the people working on them that drive the change.

A highly engaged workforce will be more dedicated to make your business thrive and thus, data plays an important role in making recruitment decisions. Data can also help organizations improve their vacancy and recruitment strategies. As per a Global Recruiting Trends report from 2018, 50% of hiring professionals had already started using data analytics as a part of their hiring strategy.

Equipped with the required data, you can also improve succession planning, predicting potential job openings and gaps in a team before they actually occur—giving the HR department optimal time to fill a position when it opens up.

Adopting data-driven hiring practices

To make the most out of the recruitment process, organizations must put these data driven hiring practices in place:

Maintaining a data-driven mindset for Hiring

Manually screening resumes is process heavy and can result in gut-driven hiring. Committing to data for the process can resolve both these issues. Training the HR team for basic data analysis skills can encourage them to take important hiring decisions based on significant data rather than intuition.

Identifying challenges & KPIs in Hiring

Once an HR team starts identifying the issues in their hiring process and track progress towards their goals, they can choose required metrics and fields they need to work upon in hiring the right candidate. These recruiting metrics can measure cost per hire, time taken to hire a resource, a candidate’s experience score and current job acceptance rates of an organization.

Building candidate profiles based on current team strengths & gaps

An organization can collect important data from their existing employees and teams. Identifying skills and representational gaps in the workforce can help an organization build an ideal profile for a candidate for open roles.

Using Resume screening tools

Resume screening tools can help organizations to sift through thousands of resumes automatically. Powered by AI filters, these tools can match resumes to profiles built by the organization. They are beneficial as they save time and help teams find candidates that match the parameters set by them for a role.

An organization can reap the benefits of data and collected information once they have a data-driven culture in place. The transition requires discipline and patience. However, once an organization becomes truly data-driven, it can drive innovation and lead the market with ease, without being subjected to personal bias.