Technology has made the HR domain a bit more manageable than it was. From sourcing a candidate to onboarding an employee, time and effort is an integral part of business growth. It is a crucial investment. HR leaders would agree that matching a candidate to organizational parameters takes constant grind and the right mindset towards the candidates.

One of the earliest known examples of payroll, dating back to around 3,000 BC, is a pay stub showing workers being paid in beer rations. Less than 100 years ago, some companies paid employees in company scrip. During the company scrip days, workers would find themselves in a less-than-ideal cycle of debt due to fees and the high prices of goods, as portrayed in the song Sixteen Tons by Tennessee Ernie Ford.

Productivity can be affect Employees are an asset for company growth and investing in such tools nurtures employee loyaltyed by work environment, training & career development opportunities, HR processes, pay structure, overall wellness, and tech advancements. With so many factors impacting how employees stay productive, it can be overwhelming to track it.

In today’s competitive job market, attracting top talent to your organization is more important than ever. But with so many candidates vying for the same roles, how do you ensure that you’re hiring the best possible candidates? The answer lies in predictive hiring, a method that uses data and analytics to identify candidates with the highest potential for success in a given role.

According to the Gartner 2023 CIO and Technology Executive Survey—which included 2,203 CIO respondents in 81 countries and all major industries—cybersecurity was a primary focus for the year, with 66% indicating increased investments in cyber and information security. Exploits like malware, phishing scams, and other viruses affect everyone, from local family businesses to large corporations. Hackers commit cyberattacks daily, so companies of all sizes must prioritize cybersecurity and invest in measures to protect their data and systems.