Improving Overall Labour Effectiveness — a practical guide for manufacturers
If you read my last article you’re likely up to speed on why it’s essential to minimise machine downtime, and are now familiar with the steps to easily mitigate it yourself. (If you haven’t yet, don’t worry — you can read it here if you’re interested). This article will continue where we started, and give you even more of an insight into optimising productivity across the factory as a whole — including the most valuable asset of all: your people.
Downtime is expensive — arguably the single biggest contributor to production and profitability losses — costing UK manufacturers a whopping £180bn a year. As you know, downtime is literally whenever a machine is ‘down’ — that means sitting idle or not producing anything.
Aside from machines, the main thing you don’t want sitting idle however — is your workforce.
With Internet of Things (IoT) devices and industry 4.0 technology now readily available to manufacturers, it’s not difficult to envision how plugging into machines and monitoring them will keep you on top of downtime and performance. What’s tricker to envision is how you do the same for your staff. For most manufacturers there is an information gap when it comes to monitoring and optimising labour outputs, with factories mainly relying on site managers to manually track breaks and time in stations. Unsurprisingly, managers can’t be everywhere at once — so labour productivity quickly falls through the cracks.
The metric to measure staff downtime and productivity is called Overall Labour Effectiveness (OLE).
To be specific:
“Overall Labor Effectiveness is a key performance indicator (KPI) that measures the utilisation, performance and quality of the work force and its impact on productivity.”
- Manish Sharma, Lead Azure Architect & Data Analytics Engineer
OLE expands on the ideas of Overall Equipment Effectiveness (OEE) by quantifying, diagnosing, and predicting not only the performance of the workforce and its influence on production, but the connection between employees and the resources needed to expand production. Manufacturers that can quantify these factors — and optimise them — can achieve significant advances in productivity — ThingTrax customers for instance have seen OLE improvements of 35% or more, while reducing downtime by up to 70%.
Quantifying OLE comes down to three different outputs: availability, performance, and quality.
1 — Availability
Availability, according to the Cambridge dictionary, is “the fact of someone being free to work” — i.e. they are ready and available to do their job, and continue production in the factory. Breaking availability down further, there are three key factors which affect it: absenteeism, scheduling and indirect time. The manufacturers who understand and monitor these factors will have the best chance of controlling them, improving factory output and profitability.
ABSENTEEISM is a major factor in determining and meeting production deadlines and benchmarks. With most factories hiring 20 to 90 employees, keeping track of excused and unexcused absences, illness, and other issues of availability can quickly become overwhelming for shift managers. Ensuring a system is in place to automatically track workers checking in and out, and notifying managers when employees are missing from their stations, makes it easy for manufacturers to quickly resolve staffing issues caused by absenteeism; mitigating delays to production in real-time. A step further to this is actively preventing other workers from getting sick in the future, and this can be done through the same check in/out system, which — in the case of ThingTrax — can also check worker temperatures as they enter and leave the work site, deny entry to those with a fever, and contact trace automatically to warn other employees who may have been exposed and keep them safe.
Unfortunately accidents can and do happen at work, and while these may cause absenteeism too — it’s most important of all that manufacturers do everything they can to keep their employees safe and well at the workplace. ThingTrax can tap into Closed-Circuit Television Cameras (CCTV) and using Artificial Intelligence (AI), can actually detect breaches in Personal Protective Equipment (PPE) in real time and automatically send notifications to site managers to resolve the issue immediately. This gets workers back to their stations right away, eliminating availability and absentee issues before they happen, while making the station safer and guaranteeing workers make it home in one piece to their families.
SCHEDULING the right employees at the right time — every time — directly impacts production levels. Factories with specialised equipment often need employees with special certifications that are highly skilled in order to operate it. Matching these employees with the right machine and booking them on the right job at the right time is a logistical challenge typically handled by the Planning department. Getting this wrong can mean an unskilled or unqualified worker attempting to operate a machine they don’t know how to use, and this will lead to significant delays to production. Much worse than that, this puts the worker at serious risk of injury or even death in the wrong circumstances. While you might be able to trust Planners to do a good job of this, the reality is that manufacturing is a constantly moving process. As unplanned downtime and other delays arise, changes to schedules occur and human error emerges when trying to schedule the right worker for the job. Fortunately, platforms like ThingTrax have your back on this, and only ever allocate workers to jobs they are qualified to be on with no human error. This is managed through an operator skills matrix — that streamlines the allocation of workers to jobs based on their qualifications.
Foresight into scheduling is equally important, as the further in advance you can plan, the more prepared you will be to complete the job effectively. Despite this, the vast majority of manufacturers only ever plan shifts two weeks in advance, leaving very little time to restructure the schedule for jobs, machines and workers when things inevitably change. With ThingTrax, Planners are able to schedule jobs up to six months in advance, leaving ample room for changes to be accounted for, and scheduling to be adapted easilyway ahead of time.
INDIRECT TIME is the last factor affecting availability, and is defined by material delays, shift changeovers, idle time, and machine downtime which all contribute to a breakdown in the production process. Most of this is covered in our step-by-step guide to reducing downtime, however it’s important to note the direct impact that workers have on these delays, and that systems which minimise the time spent away from their stations will undoubtedly improve factory output.
At ThingTrax, we can actually tap into CCTV across the entire factory or fixed cameras at machine or manual work stations and use the video data to notify managers if zones on the factory floor are unmanned for longer than a set period of time or if machines are unmanned where they should have an operator present. Facial recognition software can even inform the manager exactly who is missing from their station so there’s no more scrambling around trying to find the right worker for the right job and get them back where they’re supposed to be as fast as possible. Conversely, indirect time can also be caused by too many workers crowding zones in a factory. This too can be monitored by sensors that create infrared heat maps of the factory floor to detect spikes in heat caused by congestion (or fire, if hot enough) and notify managers to redirect staff for a safer and more productive work environment.
Analyzing these three factors can help manufacturers develop attendance, leave, and absence management policies, in addition to scheduling deliveries of materials and products to keep the production chain moving. Examining OLE data may prompt a manufacturer to hire temporary help to account for seasonal or unpredictable demand — or schedule proper lead time for the arrival of materials so workers don’t leave their stations to obtain the materials themselves.
2 — Performance
Like any workplace, monitoring your employees performance is the best way to detect and award exceptional workers, and address or cut underperforming staff. For manufacturers, performance is typically measured by how long it takes for a worker to produce and deliver a product. Without a system in place to quantify performance however, it’s almost impossible to attribute success or failure to a specific worker. ThingTrax uses AI to track and analyse shift times, break times, absenteeism, production speed and quality output; and output this into easy-to-interpret reports which make staffing decisions for managers simple. Most of this data is captured by existing CCTV or sensors across the factory floor, that use facial recognition and timers to monitor staff.
3 — Quality
The final OLE output is quality, and this comes into play if employees are following instructions and processes, and using tools properly. When they know staff are properly trained, supervisors can focus attention on producing a quality product, while avoiding high levels of rework and waste. Again with so many employees, worker skills and qualifications are hard to keep track of, but are so important to both quality output and worker wellbeing. Learning new skills that will improve their lives is one of the 5 key motivators in the workplace, even ahead of payment and compensation. ThingTrax deeply encourages upskilling and training workers in order to continuously improve output and morale across the factory, and our employee skills matrix will automatically notify managers when training for workers is due. This results in an extremely high caliber of operator and this is reflected in a quality product.
The key result of OLE is the ability to show the cause and effect of workforce factors in relation to profitability. Workforce performance through availability, performance, and quality — when managed correctly — can reveal how investments in training, root cause insights, and predictive measures within the workforce can increase both the profitability and output of a factory while improving employee wellbeing. If you’d like to learn how to improve OLE in your factory, get in touch with our team today.
