MSE

Article / Updated 10-06-2022

Material requirements planning (MRP) led to the development of enterprise resource planning (ERP). As the name implies, ERP integrates an entire company into one information system that operates on real-time data it receives from throughout the organization. The shared database ensures that every location and department can access the most reliable and up-to-date information. An ERP system incorporates many operations management topics, including process design and management, aggregate planning, capacity and inventory management, scheduling, quality control, and project management. An ERP system has many advantages, but beware of the silver bullet perception. ERP systems require significant investments, including purchasing the system and then implementing and maintaining it. Many companies underestimate the amount of time and money involved with implementing and maintaining an ERP system. We recommend the following steps for implementing a successful ERP system: Assess your needs. Do you really need such a sophisticated system? The system itself won’t fix all the problems of an organization. Often, some process re-engineering and communication across the organization can do the trick, and you can handle data management in a much simpler and inexpensive way. Many world-class manufacturing and service operations use relatively simple, unsophisticated systems to manage their ERP needs. Fix your processes. Implementing an ERP system won’t fix broken, inefficient processes. Before investing in an ERP system, evaluate and, if needed, redesign your processes. Acquire and verify consistent data. When you begin populating an ERP system with data, remember that the outputs are only as good as the data going in. If different departments are operating on different sets of data — say, sales data in one department is different from sales data in another — then the software system isn’t going to produce accurate data for the company. Customize your software. ERP vendors offer highly standardized software, typically with optimized modules for particular industries. One of the major concerns companies have about implementing an ERP system is that it locks the company into standardized processes. This inhibits process innovation within a company because deviating from the ERP’s process ends up requiring many software work-arounds. When setting up an ERP, make sure the system can accommodate process improvements from Step 2 and not force you into the standard processes that have been built into its software. When customizing software to accommodate an improved process, be sure your competitors don’t get ahold of the same programs and eliminate any competitive advantage you’ve gained. Train your employees. Employees must understand the purpose of the system and how to input data and interpret the reports that the system generates. Continuously improve your processes. Continuous improvement is the heartbeat of all successful companies, and changing processes almost certainly involves modifications to ERP software. Many companies find themselves locked into their current processes to avoid the time and money needed to update their software. Avoid stagnation by developing a good relationship with your software provider.

Cheat Sheet / Updated 02-17-2022

In business, operations management is the development, execution, and maintenance of effective processes — whether used continuously for the production and delivery of goods or services or for the one-time execution of a major project. Some mathematical formulas come in handy to keep business operations running as smoothly as possible, from managing inventory to estimating the time and cost of a special project.

Article / Updated 09-27-2021

Managing inventory is an important way for a business to manage variations in demand. Inventory can provide a means to manage demand fluctuation so that process capacity and resource utilization are kept steady and used most efficiently. Of course, maintaining an inventory isn't cost-free or risk-free, because inventory represents tied-up cash and storage costs and comes with the risk that the inventory will spoil or become obsolete. In the case of bank or restaurant customers, if they have to wait in a line too long, the risk is a lost customer. Following are some formulas for the three most common inventory policies that companies use to try to minimize their risk: Newsvendor inventory policy Continuous review inventory policy Periodic review inventory policy Newsvendor inventory policy The newsvendor policy is often also called single period inventory management. As the name implies, the business has one shot to purchase the inventory that it believes it will need to meet customer demand. This policy is typically used for seasonal items, such as swimsuits and snowblowers. Let μ = expected demand, σ = standard deviation of demand, Q = an order quantity, ES = expected sales, ELS = expected lost sales, ELI = expected leftover inventory, = the cost of understocking one item, and = the cost of overstocking one item. Newsvendor optimal order quantity is Q such that: Continuous review inventory policy In a continuous review inventory policy, you continually monitor your inventory and order a fixed quantity every time your inventory level reaches a preset quantity. The fixed quantity is often called the economic order quantity (EOQ) because it's the quantity that minimizes your total inventory costs. You place an order for the EOQ whenever your inventory level reaches the set reorder point (ROP). To calculate the EOQ and ROP, use the following equations. Let D = annual demand for the product, S = setup cost to place one order, H = holding cost to keep one item in inventory for a year, SS = safety stock, and z = the z value for the desired service level. ROP = (Average Demand * Average Delivery Lead Time) + Safety Stock Periodic review inventory policy In some cases, it's impractical to continuously monitor inventory levels, and a business may choose to periodically monitor. In this policy, the firm sets a certain time (T) to check inventory levels. At this time, the company orders inventory to bring levels up to a target inventory (TI). The company typically sets the T based on its operations and calculates the TI based on this T using the following equation: TI = Average Demand * (Average Lead Time + T) + SS Where SS is calculated as:

Article / Updated 04-11-2017

In many organizations, managers need to be aware of resources that perform more than one operation in a process or are shared across processes. For example, a receptionist in a doctor’s office not only greets patients but also collects payment and schedules future appointments. Similarly, a product designer may design more than one type of merchandise in a given time period for different brands. Analyzing these situations requires special care because they affect process performance metrics. Assignment of a resource to more than one operation Assigning a resource to more than one operation in a process can be a smart way to help balance the line so that each person or machine has approximately the same work content. Work content is the total time a resource spends working on one flow unit, or one part that goes through the entire process. This structure can increase resource utilization without creating an overproduction dilemma. But when assigning resources to multiple operations, you want to be sure to avoid resource conflicts. When calculating a resource’s cycle time — the time a resource takes to process one flow unit — you must account for everything that each resource does in the process. Often, this includes multiple operations. Considering each resource’s total work time is important when identifying bottlenecks. Consider a situation in which individual clerks perform multiple operations: Clerk 1 performs OP1 and OP5; his cycle time is 18 minutes (6 + 12). Clerk 2 performs OP2 and OP4; her cycle time is 15 minutes (10 + 5). Clerks 3 and 4 both perform OP3, and each has a cycle time of 20 minutes. Clerk 5 performs OP6 with a cycle time of 15 minutes. If you analyze the process without noticing that operations share resources, you may conclude that the bottleneck is Clerk 5 performing OP6 with a cycle time of 15 minutes. Or maybe you’d peg Clerks 3 and 4 at OP3 as the bottleneck; but they don’t represent the smallest capacity or the longest cycle time because the cycle time for the resources at OP3 is really 10 minutes — you have two resources in parallel. The actual bottleneck of the process is Clerk 1 because he performs both OP1 and OP5 and has the longest cycle time of 18 minutes. When assigning resources, you need to verify that, given current demand, you aren’t creating any resource conflicts. Resource conflicts arise when a resource must do two or more operations on different flow units at the same time. For example, a receptionist at a doctor’s office can’t check in one patient at the same time he is scheduling a future appointment for another; this is a resource conflict. A resource conflict would exist if Clerk 1 has to perform OP1 on a new customer at the same time he needs to perform OP5 on a different customer. Because of the potential for resource conflicts, sharing resources often increases the time a flow unit spends in the process. Allocate resources to more than one process A single resource may be assigned to perform one or more operations in more than one process. When this happens, analyzing the performance of a particular process becomes tricky. Here are some important questions to ask when you’re evaluating a process that uses a resource that also works on other processes: Is the resource a bottleneck in any of the individual processes in which it performs? If the resource is the bottleneck in an individual process even if the resource was dedicated exclusively to that individual process, then you have a serious issue. The resource is limiting production in a process, so any additional activities it performs in other processes further limits the capacity of that first process. How much total work content does the resource perform across all the processes? The resource may not be the bottleneck in any individual process but may actually be a bottleneck given its activities across all processes in which it performs. If this occurs, then the resource may make one process wait while it performs an activity in another process. Do you need to adjust your material release policy? If a resource becomes a bottleneck because of its shared activities, then you may need to adjust the material release policy of all processes the resource works in to reflect the new bottleneck. Scheduling is critical when resources are shared among processes. You must schedule the processes in a way that doesn’t create resource conflicts.

Article / Updated 04-11-2017

Unlike processes, you don’t perform projects over and over again; they’re usually one-time efforts. The metrics of success for any operations management project depends on the objectives that the project is intended to meet. Yet many project leaders spend too little time before launching a project figuring out what they want to achieve. In some cases, this failure is a matter of interest; other times it’s a lack of resources. When initiating a project, you need to figure out ahead of time what needs to be done, how much it’s likely to cost, what kind of time frame the effort requires, and how you can track the project’s progress toward its goals. These criteria may be helpful for launching a project plan. Projects are generally evaluated against four criteria: Scope: What exactly is the project supposed to accomplish in terms of goals and deliverables? And, maybe more important, what is it not trying to accomplish? Timing: How long will it take to complete the project? Cost: How much money will it cost to finish the project? Quality: What does the project need to do well to achieve its goals? Prioritize criteria How important each of these criteria is to a particular project depends on the project. If you’re planning the construction of a new stadium for the Olympics, missing the deadline by a week is a disaster. If you’re planning the construction of a new playground by volunteers in a neighborhood park, missing the deadline by a week isn’t such a big deal. (After all, you get what you pay for!) Similarly, missing the cost budget for an Olympic stadium by 50 percent may not be disastrous. For example, the Sydney Opera House is considered one of the great architectural wonders of the 20th century and is a UNESCO World Heritage Site. Its original budget was $7 million. When completed, it ended up costing approximately $100 million. Thus, it was over budget by a factor of 14 times. While many complained about the overruns at the time, there was no rioting in the streets. On the other hand, overshooting the budget of a playground by a factor of 14 times just couldn’t happen because the project would be abandoned if costs ballooned to this degree. More important, you may never be invited to another neighborhood block party! Quality is different from cost and timing. For starters, it’s not as easy to measure. Yet its impression is usually longer lasting. For example, Australia has mostly forgotten its cost and timing issues with the Sydney Opera House, yet it constantly trumpets the quality of the structure in terms of beauty and acoustics. Moreover, missing quality targets, such as falling masonry in a tunnel project, can literally kill people. Even smaller issues, like a persistent leaking in a roof, can sour clients on a project because, unlike late completion or cost overruns, poor quality continues to haunt the client on an ongoing basis — long after the project is completed. The point is that people often worry about cost and timing more than quality in the short run, but in the long run, quality becomes much more important. We’re not suggesting that you plan on missing any of your project’s goals or success criteria. But realistically, if you have to trade off one criterion for another, be very clear which of them is more important, and be aware that this answer may be different in the long term versus the short term. The interaction of factors Bear in mind that the four factors for success (scope, timing, cost, and quality) interact and trade off against one another. For example, you can usually speed up a project if you’re willing to spend money on overtime and extra personnel. Similarly, you can always skimp on quality or scope to reduce cost or accelerate timing. The project pyramid shows the interrelationships among scope, cost, timing, and quality. For example, if you’re willing to give up on building that third wing to your Hollywood mansion, your project costs are likely to go down. One of the major jobs of the project manager is to juggle these four project success factors over the entire lifetime of the project. At the start of a project, its cost, timing, and quality are estimates. Some folks argue that the reason many projects are late or over budget is because upfront estimates are too optimistic. Though this is certainly true in many cases, a reason that estimates are done poorly is because not enough effort was spent planning out the goals of the project. Thus, planning and goals are tightly interlinked.

Article / Updated 04-10-2017

An aggregate plan provides the road map for business operations; it translates corporate strategy into a plan that can be implemented on the plant floor or on the front-line of service. For companies that sell physical products, this map details the production process. For service-based companies, the aggregate map identifies staffing levels and other resources needed to accommodate customer demand. Put together a plan The operations planning process starts at the corporate level with a strategic plan for the company. The overarching corporate strategy guides the aggregate operations plan. The purpose of the aggregate plan is to match the firm’s capacity with anticipated customer demand to ensure that the company is utilizing its available capacity to best meet anticipated demand. An aggregate plan requires two sets of information: Strategic capacity plan: A capacity plan emerges from the corporate strategic plan and provides aggregate planners with details on current and future capacity levels. Forecast of anticipated demand: The demand forecast provides an overview on how much product the facility needs to manufacture in the coming months to satisfy anticipated customer demand. In their general form, aggregate plans deal with the total demand. They typically don’t focus on individual models or items. For example, when allocating space in a grocery store, the aggregate plan would indicate a certain amount of space to be used for breakfast cereals, but the plan wouldn’t address how much shelf space each type or brand of cereal gets. In some cases, the plan may allocate a specific amount of space to a particular manufacturer, such as Kellogg’s, but this is usually as specific as it gets. The end product of aggregate planning is the production plan, which guides the development of a master schedule (MS), which informs detailed schedules for operations. The master schedule Based on the production plan, facility personnel (such as a retail store manager) create a detailed schedule to give specific direction on what to do when to employees who are actually doing the work or providing the service. The master schedule shows the quantity and timing for a specific product to be delivered to customers over a specific period of time, but it doesn’t show how many products actually need to be produced because the demanded products can be provided using inventory in some cases. The master schedule and inventory levels provide information for the master production schedule, which communicates how many units need to be produced at a given time. For example, a computer manufacturer’s production plan may show that the company forecasts sales of 1,200 portable computers in September, 1,500 in October, and 1,700 in November. But it doesn’t give any information about what quantity of each model is needed. The master schedule shows how many of each model is needed and when it needs to be produced. Getting to the specifics of the master schedule can be difficult. Breaking a production plan into the number of specific models to produce isn’t always easy. Because disaggregate forecasts are less accurate than aggregate forecasts, it’s often difficult to predict what actual models the customer will desire. You must take care when developing the forecast. Because short-term forecasts are typically more accurate than long-term forecasts, the longer you can delay making the line item (model) forecast, the better off everyone will be. When creating a master schedule, follow a structured method.

Article / Updated 04-10-2017

In a process, some operations can process multiple flow units at a time and others can’t, so it’s important to analyze the operation batch size to maximize the total system’s capacity. To accommodate other operations in a process, a particular operation’s batch size may be lower than its maximum possible output. By definition, no setup time is required between operation batches. In this analysis, assume that the operation batch size is the same as the transfer batch size, meaning that the units processed in any one cycle of an operation move on to the next operation as a batch at the same time. Here are the general steps for determining optimal batch size to maximize process capacity: Determine the capacity of each resource for different batch sizes. Calculate the capacity for several batch sizes, including the minimum and maximum allowable size. Determine whether the bottleneck changes from one resource to another. The bottleneck may shift if some resources have the same cycle time regardless of batch size and others have changing cycle times based on batch size. The operation’s cycle time is for a batch of parts, not just a single unit. Determine the batch size that causes the bottleneck to change. In general, this occurs when the capacity of the original bottleneck equals that of the new bottleneck. Note the capacity of each resource for various batch sizes: Resource 1 mixes the ingredients and prepares the pans for the oven. This resource can mix up to 3 cakes in 5 minutes, but he doesn’t necessarily need to make 3 at a time. Making only 1 or 2 still takes him 5 minutes. After preparing the cakes for the oven, Resource 1 places them in a holding area (WIP), where they wait for the oven to become available. Resource 2 (the oven) takes 30 minutes to bake a batch of cakes, no matter how many cakes are in the oven. The oven can hold 12 pans (maximum operation batch size is 12), and all the cakes must be put in the oven at the same time. After the 30-minute bake time, Resource 3 removes the cakes from the oven and places them on cooling racks. Doing so takes her 10 seconds per cake. Resource 3 isn’t the bottleneck in this process because she needs only 2 minutes to process the maximum batch size of 12. Each cake must cool at least 15 minutes before moving on to Resource 4, who removes each cake from the cooling rack, takes it out of the pan, brushes a glaze over the warm cake, and boxes it — at a pace of 6 minutes per cake. Cooling is an operation and not a WIP because Resource 4 can’t decorate a hot cake. The batch size in this process can range from 1 to 12 cakes, the capacity of the oven. The chosen batch size determines the process capacity and flow time. Comparing the capacity of each resource as batch size increases, the oven remains the bottleneck until batch size reaches 5 cakes. At this size, Resource 4 also becomes a bottleneck, and Resource 2 and 4 have a capacity of 10 cakes per hour. When the batch size exceeds 5, Resource 4 becomes the sole bottleneck — cakes will back up because cakes arrive faster at Resource 4than she can process them. The optimal batch size is 5 cakes; this is where both Resources 2 and 4 have the same capacity. When choosing the batch size, metrics other than system capacity may influence your decision. For example, the rush order flow time increases as batch size increases. If a smaller flow time is important to your customers, then you may want to reduce the batch size. Likewise, quality expectations can also influence batch size. In the cake example, if the batch size is 5, then the last cake will wait an additional 24 minutes beyond the 15-minute cool time before Resource 4 can decorate it. If this additional time allows the cake to cool too much for the glaze to spread, then you may have to reduce the batch size.

Article / Updated 04-10-2017

The transfer batch size refers to the number of units in operations management that move as a group from operation to operation. On a process map, the transfer action is represented as an operation even though it doesn’t add value to the end product because the step is necessary for the parts to move through the process. Here is a process that utilizes transfer batches. The process consists of three operators and one driver. The driver performs both of the transfer operations. In this process map, each operation has its own waiting station for work in process (WIP). Each operation uses WIP as an input and outputs WIP to a different location. For example, OP1 processes parts into WIP1, and OP2 pulls parts to work on from WIP2. When WIP1 reaches the transfer batch size, it moves and becomes WIP2. The following steps are useful when establishing transfer batch sizes: Determine the bottleneck of the process, assuming a transfer batch size of one. Initially, don’t worry about the resources used for transporting the batches from operation to operation. The amount of time these resources are utilized depends on the number of trips they have to make. As the batch size increases, they make fewer trips. Decide on your material release policy, or how fast you allow parts to enter the process. If you’re lucky and demand exceeds capacity, you’ll operate at the speed of the bottleneck to prevent overproduction. If demand is less than capacity, you’ll operate at the rate of demand. Also, consider seasonal demand, when you may want to produce more than current demand indicates. Assume that demand is greater than capacity and that parts enter the process at the rate of 300 units per hour. Figure out the capacity (trips per hour) of your transportation resources. In the example, moving a batch of parts from operation to operation takes 2 minutes. This means that the driver can make 30 trips per hour. Because there’s only one driver, he must divide his time between two transfer points. The number of transfers at each point doesn’t necessarily need to be the same. Determine the minimum batch size that the transportation resources can accommodate. Assuming that you maintain the same transfer batch size throughout the process, the driver can make up to 15 (30 ÷ 2) transfers per hour at each transfer point. Because 300 parts are released into the system per hour, the minimum batch size that the driver can process is 20 parts (300 ÷ 15). A smaller batch size requires more transfers and exceeds the capacity of the driver. Set the batch size to meet your operational objectives. When choosing batch sizes, you must consider many factors, such as operator work patterns, desired inventory levels, the time it takes to get through the process, facility layout, and traffic patterns within your facility. Not all the transfer batches in a process have to be the same size. Resource utilization Small batch sizes tend to smooth the workload of an operation. If 15 batches of 20 units enter the system every hour — meaning that a batch arrives at OP1 every 4 minutes (60 minutes ÷ 15 batches) — then Operator 1 works for 2.4 minutes (60 ÷ 500) to process the batch. He then waits for 1.6 minutes for the next batch to arrive to him. This means Operator 1 works for 2.4 minutes out of every 4 minutes, or 60% of the time. On the other hand, large batch sizes generate longer continuous active periods followed by longer continuous inactive periods. If the batch size is 300 per hour and all the units arrive at the same time, Operator 1 works for 36 minutes to process all the parts and is then inactive for the rest of the hour, until the next batch of 300 units arrives to him. The operator’s utilization remains at 60%, but he now has larger blocks of working time and downtime. Flow time Small batch sizes reduce the time for a batch of parts to get through a system. For example, OP1 and OP3 each requires 2.4 minutes to process 20 parts; OP2 can process a part every 0.2 minutes, taking 4 minutes to process 20 parts. Summing the time the batch spends at each operation and adding 4 minutes for the two transfers, a batch of 20 units takes 12.8 minutes to process from start to finish, not including any wait times if they exist. Conversely, large batch sizes increase the time a batch spends in the process. A batch of 300 parts goes through the process in 136 minutes: 36 minutes + 2 minutes + 60 minutes + 2 minutes + 36 minutes. Facility traffic and inventory storage Small batch sizes usually create more traffic in a facility because more transfers occur. In some situations, this may be dangerous and undesirable. Small batch sizes result in less wait time for an individual part, which results in less WIP inventory.

Article / Updated 04-10-2017

With a critical path diagram complete, you can calculate a timing estimate for your operations project. Follow these steps to perform a forward pass analysis, which defines the earliest start times and earliest finish times for each activity. This also identifies the earliest finish time for the project as a whole. Begin by writing the earliest start (ES) time (which is customarily 0) in the upper-left corner of the start node. Add the duration of the start node (0 days) to determine the earliest finish (EF) time for the start node and mark it in the upper-right corner of the node. That is, EF = ES + Duration. All the activities that can begin right away (activities with no predecessors) have an ES time of 0 because they are successors to the start node. B’s ES time is 0, as noted in the upper-left corner. The duration of this activity is 21, which means that B’s EF Time = ES Time + Duration = 0 + 21 days = 21 days. This information is noted in the upper-right corner of the activity’s node. Subsequent activities, operations with a predecessor, have an ES time that’s equal to the earliest finish time of its predecessor. This means that Activity C’s ES is 21. Its duration is 7, so C’s EF time is 28. If an activity has two predecessors, then its ES is the later of the two predecessor’s EF times. Activity F has two predecessors, B and C, with earliest finish times of 21 and 28, respectively. So F’s ES is 28. Its EF time is 28 + 0.5 = 28.5 days. Continue noting the ES and EF times for all the activities on the diagram. Note an EF time on the End node. The EF time, 31.2 days, is the minimum time needed to complete the project.

Article / Updated 04-10-2017

Few things are more disruptive to operations management than poor quality. Poor quality has a negative impact on all your process metrics. You will need to know how to manage your process given the current quality levels. Poor quality wastes resources in three ways: By producing the bad part in the first place By having to “fix” the bad part (often called rework) By having to find bad parts before they progress in the process or, in the worst case, before they’re sold to a customer When you find defects in a product, you can either fix what’s wrong or scrap the product. If you discard the product, you waste the time and materials that went into the product. If you attempt to fix the defect, you must use resources on the rework that could be used making additional products. You can handle rework in two ways: You can establish a separate process to handle the defective products or place them back in the main process that created them and correct the defect. Put rework back in the process that created it Sometimes, when a defective product is discovered, it’s repaired/fixed by the resource that created it and then placed back into the process where the defect occurred. In this process, a customer enters the system, and a receptionist greets him. He then waits for one of the three accountants. After an accountant completes his tax return, one of the two auditors checks it for accuracy. If the return is correct, the customer pays the receptionist, who prepared his bill while the return was being processed and audited. If returns aren’t defective, then the accountants and the receptionist have a cycle time of 8 minutes and a capacity of 7.5 clients per hour. The system bottleneck (slowest resource) is the auditors, who have a cycle time of 9 minutes, giving them a capacity to process 6.67 customers per hour. If the auditors discover that 20% of the returns have a mistake, then the return goes back to an accountant (not necessarily the one who initially worked on the return). The accountant spends an additional 24 minutes correcting the return, and the auditor must spend an additional 4 minutes rechecking it for accuracy. Assume that the return is correct the first time through the rework cycle. To analyze this process when rework is involved, the first thing you must do is calculate the new cycle times for the accountants and the auditors. To do this, you want to calculate the cycle time for a part that requires rework and the cycle time of a good part. You can then take a weighted average to obtain a new average cycle time. In the example, the accountant spends a total of 24 minutes on a good return and 48 minutes on a return requiring rework (24 minutes the first time plus an additional 24 minutes to fix the return). With 20% of the returns requiring rework, the new average cycle time is 28.8. With three accountants, the cycle time of the activity is 9.6 minutes. Similarly, an auditor spends 18 minutes on a good return and 22 minutes (18 minutes plus 4 minutes for rework) on a return requiring rework, giving a new average cycle time of 18.8 minutes. With two auditors, the cycle time of the activity is 9.4 minutes. A danger of the rework cycle is that the bottleneck of the process may change. If your bottleneck changes without your realizing it, you’ll try to optimize the wrong resource and won’t see any process improvement as a result of your efforts. In this example, the accountants are now the bottleneck, and the process now has a capacity of 6.25 clients per hour. Because of the rework, the process capacity is reduced by 0.42 clients per hour, or 3.36 per 8-hour day. Assuming a 5-day work week, this means that, over the 6 weeks before April 15, which is the peak time for income tax filing, the firm would lose capacity of more than 100 clients. That adds up to a lot of money lost over a short period of time. How to pull rework out of the main process Placing a defective part back into the main process is often hard, if not impossible. For example, consider an automobile assembly line. Moving a defective auto and placing it back on the line for repair would be extremely disruptive and costly. Usually, a company uses resources other than the main line resources to correct quality problems. This creates a lot of waste for the organization. You need not only additional resources but also additional space and equipment to process the defective part. In the example involving tax returns, placing defective returns back into the process is easy, but you could also handle them off the main process flow. You could hire additional personnel dedicated to handle rework or assign one of the main line accountants and auditors to perform rework as well. The latter option would mean using resources across multiple processes, which may create a problem of its own.