The cost of the inactive employees during the night shift: Securing workforce spend with AI video analytics.

Warehousing, manufacturing and construction sites need 24/7 working shifts to efficiently carry out their operations in order to achieve meaningful financial targets. This is why companies pay higher salaries for night shift employees in these industries. But can you really monitor their output?

On paper, it might seem employees work with no damages, no errors and no complaints being recorded. The attendance tracker confirms the clock-ins/outs and the payroll keeps stacking the salary each month. This leads business owners to think that workers efficiently cover their work. But this is where hidden cracks start showing up.

First, the daytime shift employees notice that they start work where they left off yesterday, meaning night shift employees haven’t contributed their part. The hours of forensic search through CCTV show night-shift employees hiding in surveillance blind spots. By the time these cracks open up, the payroll has already paid inactive night shift employees a hefty salary each month without work being done.

Where the System Breaks: The Blind Spots of Overnight Labour Management

This is the reality business owners have to deal with in today's world. The traditional CCTV’s and supervisors cannot provide efficient surveillance on night shift workers due to physical and technological limitations. Once workers get used to the premises, they get to know when and where the blind spots of the surveillance systems are to sleep, check out, smoke and perform prolonged tasks. Supervisors keep tracking a limited number of employees through CCTVs as security guards, neglecting broader managerial work. This ends up in a spiral where operations stop completely and revenue just leaks through payroll.

Traditional CCTV System vs Modern AI Video Analytics

Traditional CCTV	Modern AI Video Analytics
Cannot analyse footage. Clocked in and out means employees have worked.	Actively detect employees in the premises, while analysing their movement.
Doesn’t notify the supervisor, just a storage full of video records you have to manually check.	Proactively notify the supervisor when employees show unusual prolonged stillness or if the entire zone is empty during working hours.
Forensic searches take forever.	Instant forensic search. Matter of time you search for an incident. (For example, to find a tall man in yellow attire. You have to type it in words and the AI will instantly provide footage of a tall man in yellow attire by searching through the entire video.)
Delayed Visibility: Labour leakage is only realized after monthly payroll budgets blow out.	Immediate Visibility: Labour efficiency is monitored in real-time, allowing managers to course- correct proactively before payroll budgets are exceeded.

Recovering Lost Revenue with AI Future Vision

Payroll leakage due to night shift employee inactivity is not a new problem; every industry has been through the pain, but with new technology, each era’s creative and strategic approach to the solution is different. In the era of AI, traditional reactive surveillance has no chance of providing a meaningful solution to this problem. Smart leaders don't get stuck in a legacy mindset; they pioneer tomorrow's businesses. To stop paying for unproductive employees, switch to AI video analytics today.

FAQ

1. Can AI video analytics prevent night shift payroll leakage? 

Yes, modern AI video analytic software eliminates traditional attendance tracking and monitors employees' every movement, allowing the software to determine if the employee really contributed with meaningful effort, rather than just clocking in/out. The major mechanism that allows AI video analytics to determine if employees are working or not is intelligent computer vision. This technology helps to differentiate between just clocking in/out and actually working, eliminating payroll leakage on night shift employees.

2. Do companies need better cameras for AI video analytics or does it just work on the existing CCTV system?

The modern AI video analytic systems have plug-and-play mechanisms, meaning you can instantly integrate the AI software into the existing CCTV setup and equip surveillance with intelligence. This saves the entire cost of implementing new infrastructure, such as new cameras, expensive wiring or aesthetic wire coverings, making it highly cost-effective.

3. Which industries suffer the most from unmonitored night shift workers?

Warehousing, manufacturing and construction sites suffer the most from hidden overnight labour leakages. This is because these businesses have to deliver their project on time or conduct their operation 24/7 to provide customers value. Without any monitoring, these businesses can be easily exploited by night shift employees. 

4. Is AI video analytics better than CCTV?

AI video analytics is far ahead of CCTVs due to its unmatched intelligence features. AI video analytics can intelligently differentiate between employees just hanging around from really working. It can identify floors and spaces that are empty, which should have work going on. Under any scenario, if it identifies anomalies, it can directly notify supervisors before any incident happens, which makes it proactive in design when compared to CCTV, which is reactive. It completely removes the 5-to-6-hour forensic search time that CCTVs had; it’s only a matter of time before someone suggests a small hint of the situation for AI to analyse hours of footage to cut straight forward to the scene in seconds.