There’s an interesting but often overlooked difference in the way the costs of different inputs in the manufacturing process are measured.
On one hand, there’s the cost of parts, materials and other physical resources. The price of each of them is clear, right down to the piece, pound, meter or whatever unit of measure applies. Whoever’s running the plant or production line knows exactly how much it costs to buy another bag, barrel or box and how many units of output they can turn that cost into. The cost per job or order can be calculated precisely when it’s time to box everything up and deliver—it’s just simple math.
But that kind of precision is rarely demanded for the other, often larger, cost input in manufacturing. Labor costing remains more art than science for too many operations. Here, the calculations rarely go beyond anything more sophisticated than multiplying the hourly labor rate by the number of hours worked and adding things like payroll taxes and various benefits. There’s nothing about how much time was actually spent on a particular job, any downtime that may have occurred or anything apart from the fact that a given worker was physically present in a facility for eight hours.
And it’s on the basis of this model—full of estimates, guesswork and assumptions—that crucial decisions about margins, pricing policies and profitability are made.
Doesn’t something seem a bit off here?
The conventional system for measuring labor inputs is an old-school time clock. Punching in and out has been the default method for registering work time for over a century. But when you really think about it, time clocks are only good for telling you when a given worker started and finished a shift—there’s nothing about who did a certain job, what exactly what they did and where the work was done.
When you dive deeper, you can see more drawbacks of relying of time clocks for labor costing. All of them contribute to the challenge of accurate labor job costing, which is critical to calculating margins per order and, by extension, setting reasonable pricing policies.
Time clocks and the cards they stamp are inaccurate, reflecting when employees punched in and out and not necessarily when they started and stopped working. Employees often forget to record when they started or finished a shift. Time cards don’t reflect when someone left a workstation or for how long. They don’t tell you anything about how much time was spent, for example, looking for tools, on breaks or simply idle for whatever reason.
This lack of insight makes cost optimization impossible, since time cards don’t show activities that generate costs but should be minimized or eliminated. In short, time cards really only tell employers how much their labor costs are but not exactly what they’re paying for.
This just isn’t good enough for the demands of today’s business landscape.
IoT solutions have brought cost transparency to various aspects of manufacturing by digitizing workflows and creating visual representations of processes, employee movements, bottlenecks and other areas that were previously difficult to optimize. Now, with the tracking and analytical capabilities of IoT applications, it’s possible to get accurate insights into not only how much time employees spend on the factory floor, but exactly how that time is spent. That means costs can be assigned to specific segments of any process, thus enabling true labor costing structures that better inform larger business decisions and strategies.
Where time cards simply show what time they were punched and not when an employee began or finished working, IoT solutions detect precisely when workers entered or exited specific areas in a facility. There is no need to remember to clock in or out since that obligation is lifted from employees and their presence is recorded automatically.
With IoT, inactive time can be detected and the cause of the inactivity identified. Inefficient distribution of production inputs or physical workflows, awkward spatial arrangement of plant resources, bottlenecks in any process—they can all be more easily recognized when employees can be tracked at scale. This is something even the best and most attentive management team cannot achieve with simple observation alone.
Being able to monitor all movements in real time means gaining a smooth, automated and transparent view of what’s happening on the factory floor. It’s also error and cheat-proof, providing a reliable record of who was where and when. It’s all saved in the application as well, so historical comparisons can be made and improvements tracked.
IoT solutions make job costing easy and transparent while also highlighting areas for improvement. So not only can labor inputs be measured as precisely as material inputs in manufacturing, but efficiencies can be gained by ironing out small wrinkles in the process that are often invisible to the naked eye.
And again, on top of the obvious business benefits of cost transparency and optimized processes, accurate job costing provides a better foundation for crucial decisions about pricing policies and preserving necessary margins. A clear picture of what each job costs, alerts to opportunities to boost productivity and the elimination of estimates when it comes to setting your prices—what else do you need?