Capacity Constraints: A Definition With Solutions

When one limitation of a manufacturer’s operational processes slows down the entire production line, that single restriction can have far-ranging consequences. Known colloquially as bottlenecks, such capacity constraints can arise from a range of issues, from a lack of raw materials or labor to poorly designed facilities that impede workflows. Whatever the source, capacity constraints curb overall output and cause extended lead times and missed market opportunities. Read on to understand why it’s important for profit-driven manufacturers to identify capacity constraints and what can be done to limit their impact when they’re found.

What Are Capacity Constraints?

Capacity constraints are limitations on resources or speed of work during the manufacturing process that hold up overall operational output. The hallmark of capacity constraints is that certain processes run more slowly than others and sometimes even cause temporary halts to production.

Capacity constraints can curb maximum output because production can’t outrun the slowest steps in the process. This is why high-performing manufacturers consistently endeavor to identify all bottlenecks and work to either improve performance or optimize scheduling around these constraints.

Key Takeaways

• Capacity constraints are bottlenecks occurring in stages of operational activity that cause those stages to be slower than others.
• Capacity constraints are the weakest links in operations that limit overall production output.
• Left unmanaged, capacity constraints often lead to missed delivery deadlines, high operational costs, and customer dissatisfaction.
• Effective management of capacity constraints is a core competency of manufacturing that serves to improve operational efficiency and profitability.

Capacity Constraints Explained

Capacity constraints are best explained by Goldratt’s Theory of Constraints, a business management framework that recommends continually identifying the most critical limiting factor that keeps an organization from achieving its goals, and then systematically addressing that constraint to improve overall performance. Developed by Eliyahu M. Goldratt in the 1980s, the theory contends that every system has at least one weakest-link constraint that holds it back from peak performance and that focusing improvements on these constraints can yield the most performance gains.

Capacity constraints can be found across many different operational models and industries. For example, construction firms building houses may face labor constraints in the form of specialty trade availability when their project has to be halted to wait for an electrician or a plumber before it can progress. In manufacturing, where the impact of capacity constraints is arguably felt the most acutely, the resulting slowdowns and restrictions can have extensive ripple effects across a company’s production line—and, ultimately, its bottom line. These bottlenecks can be caused by a range of factors, including equipment and labor constraints, supply chain disruptions, poorly designed production lines, and regulatory requirements. They often result in excessive delivery delays, the inability to consistently meet customer demand, inventory discrepancies, and rising operational costs. As one measure of their impact, some Yale economic researchers contend that supply chain bottlenecks have been responsible for half of the inflationary pressures of recent years.

Addressing capacity constraints is a continuous improvement effort for manufacturers and a core part of such methodologies as Six Sigma and lean manufacturing. Fixing a bottleneck in one area will often draw attention to inefficiencies elsewhere that then become the next constraints to be addressed. To understand how this works, let’s examine the constraints affecting a theoretical smart device manufacturer that has production lines comprising multiple stages, from component assembly to final packaging.

• Single-machine constraint: Early on, the manufacturer noticed that circuit board soldering was slower at processing items than other stations and work was piling up in its queue. This single-machine bottleneck was the company’s biggest capacity constraint, so they addressed it by upgrading equipment.
• Labor constraint: Once that constraint was eliminated, a new challenge came to the forefront. The quality control team was having a hard time hiring skilled technicians, causing delays in final inspections. By implementing improvements to the quality control workflow and adding automation, the company was able to speed up the efficiency of its quality checks.
• Raw material constraint: But then, an external factor reared its head to cause yet another constraint. A global shortage of microchips was restricting the availability of critical device components and slowing down production, shifting the capacity constraint focus to supply chain management and procurement efforts. And, inevitably, there will be a new bottleneck to address in its stead.

This example is admittedly simplistic, as most manufacturers have multiple bottlenecks to contend with at once, and they’re often interconnected. But the central principle is the same: Manufacturers must address capacity constraints as quickly and completely as possible, because they’ll inevitably impact their competitiveness, business performance, and profitability. Leaving bottlenecks to linger can increase costs, reduce output volume and quality, and create missed market opportunities.

Types of Capacity Constraints

The types of capacity constraints that can slow production and limit overall output vary greatly across manufacturing verticals, individual business models, and types of production lines. However, they tend to fall into three main categories.

• Physical capacity constraints:

  Physical capacity constraints are restrictions or shortcomings in a company’s physical infrastructure that limit its production capabilities. For example, an aerospace manufacturer struggling to keep up with demand may find that its increasingly complex production processes are causing space constraints across its facility, as airplanes make their way down the line. In this case, the facility’s layout may not have been optimized for increased demand and additional stages of production, which ended up limiting material flow and causing delays. Reconfiguring the manufacturing footprint and implementing workflow management tools could potentially resolve these physical capacity constraints. In another example, a food packaging manufacturer may be experiencing slowdowns because of aging machinery that’s breaking down frequently and causing unplanned downtime. In this case, an investment in new machinery could alleviate this bottleneck and improve the company’s ability to meet customer demand.

• Resource capacity constraints:

  Resource capacity constraints occur when a business doesn’t have enough materials, labor, or other inputs to keep up with production or service demands. For example, a maker of specialty pastries and bread could face significant resource capacity constraints in the aftermath of an avian flu outbreak, due to a drastic shortage in eggs. Even with state-of-the-art commercial baking equipment and ample staff, the manufacturer would need to slow down production or reduce its volume of egg-rich baked goods to account for this constraint. Likewise, a metal fabrication firm could feel the sting of a resource capacity constraint if faced with a shortage of skilled welders, resulting in delayed shipments as welding stations hold up production workflows dependent on this work.

• Time capacity constraints:

  Time capacity constraints happen when the scheduled time to complete a process or task turns out not to be enough to meet demand. These constraints can be caused by inefficient scheduling, delays in supporting workflows, limitations in operating hours, seasonal demand fluctuations, and regulatory burdens. Consider a pharmaceutical company that must follow strict regulatory protocols concerning quality control testing. If the company mishandles scheduling and overbooks testing equipment, that equipment could be unavailable when it’s needed for critical batches as they’re processed through the production line. This delay in testing could potentially throw off packaging and shipping schedules.

Causes of Capacity Constraints

Understanding the root causes of capacity constraints can help businesses identify weaknesses in their infrastructure and planning that could potentially trigger bottlenecks. By proactively addressing these issues, companies can optimize operations with improved scheduling, strong forecasting, technology upgrades, and vendor diversification to stay ahead of constraints. The following are some of the most common causes.

• Demand volatility:

  Unpredictable spikes in demand can cause significant capacity constraints if manufacturers are unable to scale up production quickly. A classic example of this is represented by the manufacturing bottlenecks that occurred in the consumer package goods industry in the midst of the panic-buying toilet paper crisis that arose during the COVID-19 pandemic. Manufacturers can sometimes be a victim of their own success in this regard. For example, a small craft brewery that wins an award for a beer that involves several specialty brewing stages may not be able to keep up with the resulting surge in demand if its limited production capacity for that product can’t handle it.

• Poor planning and forecasting:

  When companies don’t engage in capacity planning to accurately predict demand—or the resource requirements needed to fulfill it—they often encounter capacity restraints. For example, a consumer electronics company that makes a new smart device that goes viral on social media could underestimate its popularity. The result: component shortages that cause production delays and extended stockouts, causing the company to miss out on a market opportunity. Similarly, a fashion manufacturer might overestimate the appeal of a seasonal line, which generates excess inventory that takes up warehouse space and delays efforts to build up inventory for more popular product lines.

• Loss of resources:

  Loss of resources precipitated by supply chain disruptions, labor shortages, or natural disasters can trigger significant bottlenecks in manufacturing, especially when businesses don’t have contingency strategies in place, such as resource diversification and sufficient safety stock of both finished and raw materials. One example of loss of resources is the ripple effect caused by the global semiconductor shortage that began in 2020. That supply chain disruption wound up creating significant bottlenecks for automotive manufacturers that depended on those chips to make cars—some companies even had to halt production for a period of time to wait for their supply chains to catch up. It’s situations like these that have driven some 28% of U.S. manufacturers to invest in new technologies to improve operational and supply chain resilience.

• External factors:

  Whether they stem from geopolitical events, weather disruptions, regulation changes, or shifting economic conditions, external factors are a common culprit behind capacity constraints. For example, consider what happens to a furniture manufacturer reliant on imported timber when a trade war restricts the flow of lumber into its warehouses as a result of an export ban from the timber’s country of origin. This could potentially limit the raw materials available for the company’s production lines, creating backlogs that prevent it from meeting order demand in a timely fashion.

• Outdated technology:

  Aging equipment and legacy software can slow down workflows and increase unplanned production downtime. The delays from tech-related capacity constraints can cause serious consequences for a business whose competitors have increased their capacity and manufacturing agility through infrastructure updates. These consequences include impeded order fulfillment and increased operational costs.

Impacts of Capacity Constraints

Bottlenecks can have far-reaching effects, derailing a company’s operational efficiency, customer satisfaction, and financial performance. Here are some examples of the fallout that can occur from both ongoing and intermittent capacity constraints.

• Delays in production: No matter the cause or type of capacity constraint, bottlenecks inevitably trigger delays in production that can create a chain reaction across a single production line or an entire business and its supply chain. When such resources as machinery, labor, or materials are insufficient, production timelines must be extended, resulting in missed deadlines and potential customer dissatisfaction.
• Increased operational costs: Capacity constraints can significantly impact operational costs and manufacturing overhead, particularly when a business must enact expensive remedies to maintain output. For example, a company facing time capacity constraints may need to implement more costly overtime shifts. Or constraints caused by raw material shortages might push a business to seek out more expensive sources of materials. These increased operational costs add up over time and eventually erode profit margins.
• Lost sales and revenue: When capacity constraints impact a manufacturer’s timely output, customers will inevitably tire of waiting for it to resolve stockouts or deliver overdue ordered items. They’ll eventually look for an alternative vendor, resulting in immediate loss of sales and degraded long-term revenue as customers grow more loyal to the competition. These situations can create a downward spiral as a manufacturer starts to miss earnings forecasts and is unable to keep up on infrastructure upgrades that would prevent future bottlenecks.
• Longer lead times: Limitations caused by capacity constraints can slow down order fulfillment and delivery timelines. Not only is this frustrating for customers, but extended lead times can also create other operational challenges. For example, when work-in-process stalls at bottleneck points, manufacturers will have to contend with higher inventory holding costs and logistical concerns derived from added storage burdens.
• Increased waste: Capacity constraints can result in inefficiencies that create significant waste of both materials and labor. Bottlenecks may result in higher rates of defective products or material spoilage. Additionally, specialized labor downstream from a bottleneck might sit idle at times, waiting for constraints that happen before them in the production line to resolve.
• Service unavailability: Some of the costliest bottlenecks are those that cause unplanned downtime and extreme delays to production. A breakdown of a piece of aging equipment can halt production, and a shortage of specialty labor along the line could slow down a station significantly—especially if several key employees are out at the same time.
• Reduced employee satisfaction: As the impact of capacity restraints spreads across a manufacturing company, employees are often placed under added stress and pressure to meet unrealistic output targets. For instance, employees charged with implementing a process facing a labor-related constraint might be asked to work longer shifts and endure greater scrutiny from their bosses. Meanwhile, employees working on a process downstream from a bottleneck could be asked to deal with an unpredictable feast-or-famine flow of work that leaves them contending with both boredom and stress on the job.

Best Practices for Managing Capacity Constraints

Effective management of capacity constraints stands as a core competency for manufacturers seeking to optimize operations and profitability. The following are some of the most important best practices for eliminating and adjusting to bottlenecks.

1. Remove Process Bottlenecks

   One of the most important best practices for managing capacity constraints is removing process bottlenecks that slow down operations. The first step in implementing this practice is identifying where these process choke points exist. High-performance manufacturers often accomplish this by embracing real-time data monitoring and other methods, such as value stream mapping, that can visualize production flows and pinpoint where excessive lead times or inventory buildup are occurring. Once constraints are identified, the action needed to fix or mitigate them can vary. For instance, it might involve upgrading machinery or adding manufacturing automation to increase throughput. Or, it could involve reorganizing plan layouts or altering shift schedules.

2. Adopt Lean Principles

   Lean principles that minimize waste and optimize operational processes will often proactively address the root causes behind costly bottlenecks. The lean philosophy of Total Productive Maintenance, for example, fosters a culture of proactive equipment care that will significantly reduce constraints related to machine downtime. And the lean principle of continuous flow focuses on intentional organization and scheduling of production processes to be sure work moves smoothly from one stage to the next with minimal time waste. This level of intentionality can eliminate process bottlenecks and create supportive workarounds for constraints caused by external factors outside a manufacturer’s control.

3. Eliminate Waste

   Lean manufacturing philosophies dictate that manufacturers deal with eight major types of waste: motion, overprocessing, downtime, overproduction, transport, excess inventory, defects, and untapped talent. All are closely tied to capacity constraints, either as a cause or effect—and, in some instances, both. By focusing on reducing manufacturing waste, companies will ultimately optimize their existing capacity, typically busting bottlenecks as they work on these waste-oriented improvement efforts. Some common ways to cut down on waste include improving supplier management, synchronizing workflow scheduling, and bringing greater discipline to inventory management.

4. Improve Forecasting and Planning

   Accurate forecasting and planning are essential for minimizing the impact of capacity constraints. Manufacturers that get this right can align their production and raw material procurement with market needs and tune expected resources to meet demand—even in the face of external factors, such as supply chain disruptions and changing regulations that can cause unavoidable bottlenecks. One of the most effective ways to improve forecasting is by using data analytics and machine learning tools that leverage historical sales data, production line data, market trends, and competitive analysis to accurately predict—and plan for—both demand and material requirements in advance of expected market fluctuations and seasonal trends.

5. Use Predictive Maintenance Technology

   Predictive maintenance technology can reduce the likelihood of unplanned bottlenecks caused by equipment-related slowdowns and downtime. By employing a proactive approach that uses a combination of Internet of Things (IoT) sensors, real-time monitoring data, and machine learning algorithms, manufacturers can be alerted to potential issues before machinery shuts down. IoT sensors help keep tabs on equipment performance as well as other variables, such as temperature, pressure, and vibration. By employing algorithms tailored to track how key variables shift as equipment nears failure or requires maintenance, alerts can be generated well before performance issues arise. In some cases, maintenance scheduling can even be automated, ensuring timely intervention.

6. Cross-Train Employees to Handle Demand Fluctuations

   Targeted cross-training can help businesses maintain productivity during peak seasons or unforeseen demand spikes. With so many capacity constraints interconnected with labor and skillset availability, manufacturers that effectively equip their workers to perform multiple roles can buffer themselves from potential bottlenecks. This strategy is effective for production teams that need to cover shifts when key employees are absent, or that need more people to help out temporarily overloaded departments. Cross-training has significant follow-on benefits, as well, as cross-trained teams tend to collaborate better and employees feel more valued and engaged.

7. Invest in More Effective Technology

   Upgrading production line equipment and related software is essential for breaking down bottlenecks, but there’s also a number of other supporting tech investments that can help manufacturers better manage capacity constraints. For example, manufacturing automation technology can speed up slow processes that previously constrained output. Capacity planning software can perform complex supply and demand performance analyses, as well as asset performance tracking and scenario planning that provide clearer views of present and future capacity. Finally, enterprise resource planning (ERP) systems allow manufacturers to centralize and make accessible most of the data needed to more effectively identify and manage bottlenecks, including those affecting workflows, inventory levels, and supply chain relationships.

Examples of Capacity Constraints in Production

Capacity constraints rear their heads in every manufacturing specialty, across all stages of production. The following are a few theoretical examples of how constraints could play out, along with what a manufacturer could do to address them.

• Physical space limitations: A manufacturer whose toy becomes the hot gift during holiday season needs to figure out how to deal with a huge spike in growth. However, it finds that a lack of floor space is making it difficult to expand production or store work-in-process inventory, which is accumulating near workstations and slowing down workflows. The toy manufacturer may need to optimize factory floor layouts, consider new storage solutions, or even outsource early steps in production to free up space and scale production.
• Supply chain disruptions: A smart-device manufacturer has to halt production frequently because of unexpected delays in receiving semiconductor components that lead to missed delivery deadlines. This manufacturer may need to diversify its supplier base to reduce its dependency on a single source and implement safety stock planning and predictive analytics to anticipate shortages and proactively plan procurement strategies.
• Skilled labor shortages: A precision engineering firm is unable to meet demand during its busy periods because of a lack of skilled machinists qualified to operate its specialized equipment. These expensive machines are often idle during critical production periods. The company may need to implement cross-training of existing employees to qualify them to use advanced equipment when demand spikes.
• Data processing constraints: A manufacturing plant’s data processing system struggles to handle the high volume of real-time sensor data from multiple production lines. This capacity constraint is delaying the analysis of critical metrics, such as machine performance and defect rates, leading to slower decision-making and bottlenecks in the production process. To address this, the manufacturer could upgrade its data processing infrastructure, implement edge computing to preprocess data locally, or adopt scalable cloud-based analytics solutions to manage the data load more effectively.

Enable More Production Uptime With NetSuite ERP

Manufacturers seeking to optimize their operational efficiency and minimize downtime find NetSuite ERP a powerful tool to support their efforts. NetSuite’s unified, cloud-based platform helps businesses manage and mitigate the impact of capacity constraints by bundling advanced planning, monitoring, and automation capabilities to level up capacity planning, shop floor visibility, and end-to-end inventory management. When integrated with NetSuite’s centralized financials, supply chain management, and production planning tools, NetSuite ERP becomes a single-source of truth for manufacturers seeking to identify and eliminate bottlenecks.

Eliminating bottlenecks from the production process is a pivotal activity for modern manufacturers. Supported by strategies, such as Goldratt’s Theory of Constraints and lean manufacturing principles, as well as advanced technologies, including ERP systems and data-driven predictive maintenance, manufacturers can tackle capacity constraints to improve their overall output and position themselves for long-term profitability. Doing so will help them meet customer demand and quickly adapt to market conditions without compromising on quality.

Capacity Constraints FAQs

What are the risks of capacity constraints?

The risks of capacity constraints include increased lead times, missed opportunities, increased operational costs, and lost revenue.

Is a capacity constraint different from a bottleneck?

These terms are used nearly synonymously, although there are some nuances. Though all capacity constraints are considered bottlenecks, not all bottlenecks are capacity constraints. Sometimes they’re just short-term issues that cause a temporary slowdown or stoppage in production.

What is Goldratt’s Theory of Constraints?

Goldratt’s Theory of Constraints is a management philosophy and methodology focused on continually identifying system constraints and either prioritizing activities around them or taking action to eliminate them.