News And Advice

Insights, tips and news for job seekers and employers.

Is Algorithmic HR Right for Your Dallas Company?

Since a recession likely will occur in 2023, many companies are preparing now. This includes deciding which employees to lay off to reduce labor costs.

Because HR is strategically involved in making high-level labor decisions, most professionals use software, algorithms, and data analytics to develop actionable insights and recommendations. This information cannot be determined through instinct or intuition alone.

However, not all HR professionals are entirely confident their technology will make unbiased recommendations. They use bad or wrong data or poorly understand its use, resulting in lower-quality recommendations.

As a result, many HR professionals have reservations about making layoff decisions based solely on the technology’s recommendations. Therefore, these professionals combine technology with other methods to make more educated decisions.

Learn more to determine whether algorithmic HR suits your Dallas company.

Data and Algorithms Are Replacing Instinct

Additional leadership responsibilities and the availability of more advanced tools encourage HR professionals to rely on technology to make decisions. This can be much more effective than relying only on instinct.

Using data and algorithms helps HR make decisions based on evidence. HR professionals can use data to explain why a decision was made and what makes the recommendations compelling. This minimizes the impact of unconscious biases and fears on the decision-making process.

Incorrectly using data and algorithms can lead to mistakes that impact employees’ livelihoods and the company’s future. As a result, data and algorithms should be combined with other methods to make business decisions.

Algorithms Can Make Poor Recommendations

Many HR professionals hesitate to use data and algorithms alone to make decisions. For instance, many HR departments cannot provide enough labor data to make accurate recommendations. Also, because algorithms do not consider context, they often produce poor recommendations.

For instance, assume a company has to lay off employees, and HR uses performance data to make these decisions. Employees with the poorest performance grades become the top candidates to be laid off.

Of course, these employees may not provide enough value to the organization. However, there may be other reasons for their poor performance grades.

For instance, these employees could have biased managers who gave bad reviews. Or, the employees might lack adequate resources or support to complete their work effectively. Or, the organization might not be tracking the right metrics to evaluate employee performance accurately. Therefore, using poor performance grades to determine who gets laid off can lead to ineffective recommendations.

Use Best Practices to Make HR Decisions

Combining the right approach, data, and platform helps uncover opportunities to cut costs:

  • Consider objective data rather than subjective data.
  • Include your short-term and long-term business goals.
  • Audit your data to ensure it is accurate and complete.
  • Ask questions to find out how black box algorithms make recommendations to ensure they are bias-free and adequately weighted.
  • Consider reduced work hours, job sharing, or talking with employees about early retirement rather than laying off employees.

Need Help to Make Hiring Decisions?

Partner with High Profile for help with sourcing candidates and making hiring decisions. Begin the process today.