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Running the Operation: Balancing Efficiency and Customer Value
Principles of Management · Chapter 5: Modern Management PerspectivesSection 5.3 · lesson 21 of 11715 min · free with a free account
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In this lesson
Balancing efficiency and customer value.
- Define operations management and its decision areas
- Explain the trade-offs between competitive priorities
- Find the bottleneck in a described process
- Explain what makes service operations different
Transcript
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Modern Management Perspectives
Running the Operation
The quantitative school asks how to model a decision. Operations management asks something more hands-on. How should the process that produces an organization's goods and services be designed, and run? In this section we'll define operations management, and the transformation model beneath every operation. We'll cover its eight decision areas, and the five competitive priorities an operation is judged on. We'll look at a live debate about whether those priorities must trade against each other. Then three ideas with real practical bite. Order winners, the link between utilization and waiting, and the bottleneck. We'll finish with what makes service operations different, and why inventory is both a buffer and a cost. Running through all of it is one theme. Operations is where an organization's priorities become a customer's experience.
Definition
Every Organization Has an Operation
Operations management is the design and control of a process. Specifically, the process that converts inputs into the goods and services an organization delivers. The definition is deliberately broad, and the breadth makes a point. Every organization has an operation. That includes service organizations, and non-profits that never touch a physical production line. A hospital converts patient arrivals, clinical staff time, and medical supplies into completed treatments. A university converts enrolled students, faculty time, and course materials into completed instruction. Both face the same underlying decisions as a factory floor manager. Every operation can be described with one transformation model. Inputs, meaning labor, materials, capital, and information, enter a process that converts them into outputs. The outputs are the finished goods or delivered services the organization exists to produce. And feedback carries information about the outputs, and about how well the process performed, back into the system. The model works at any scale, from one workstation to a whole organization. It's the same logic behind the systems perspective in Subchapter five point four.
Decision Areas
8 Recurring Operations Decisions
Operations decisions cluster into eight recurring areas. Process design determines how work actually flows through the operation. Capacity determines how much the operation can produce in a given period. Location determines where the operation is physically sited. Layout determines how equipment, workstations, and people are arranged inside a facility. Supply chain decisions determine how materials and components move from suppliers into the operation. Inventory decisions determine how much stock to hold, and when to replenish it. That connects directly to the inventory models named in Subchapter five point two. Scheduling determines the timing and sequence of work. And quality decisions set the standards the operation holds itself to, and how it checks it's meeting them. Quality returns as its own topic in Subchapter five point six.
Competitive Priorities
5 Ways an Operation Is Judged
An operation is generally judged against five competitive priorities. Cost means producing at the lowest achievable expense. Quality means meeting or exceeding a defined standard, consistently. Delivery speed is how quickly an order is fulfilled once placed. Delivery reliability is different. It's how consistently the operation meets the delivery time it promised. And flexibility is how readily the operation adapts to changes in volume, product mix, or specification. The conventional trade-off proposition says no operation can maximize all five at once. Pursuing very low cost typically means giving up some flexibility. Pursuing very high flexibility typically means giving up some cost efficiency. The reason is practical. The equipment, staffing, and process choices that best serve one priority are often not the ones that serve another. Notice that speed and reliability are separate priorities. Fast but unpredictable is not the same as reliable.
A Live Debate
Trade Off, or Enable?
There is a genuine counter-argument, and it deserves to be stated at its strongest. Some operations researchers argue that improving one priority can, under the right conditions, enable another, rather than trade against it. Take quality. A quality improvement that reduces defects can also reduce cost, because fewer defective units mean less wasted material and rework. Or take reliability. A redesign that improves reliability can also improve speed, because less time goes to recovering from missed commitments. This is a live debate in the field, not a settled question. So we'll present both positions, and declare no winner. The strict trade-off view captures a real constraint, and it holds in many settings. It holds especially in the short run, with fixed equipment and staffing. The mutual-enablement view captures a real possibility, and it holds in other settings. It holds especially when a redesign changes the underlying process, rather than reallocating existing resources inside it. So the useful question isn't which view is right. It's whether you are reshuffling resources inside a fixed process, or changing the process itself.
Setting Priorities
Order Qualifiers and Order Winners
A practical way to set priorities among the five is to separate order qualifiers from order winners. An order qualifier is a priority a customer expects as a baseline, just to consider buying. Fall below it, and the organization isn't even a candidate. An order winner is the specific priority that decides which competitor, among those that qualify, actually wins the business. Picture a customer shopping for a commodity component. Quality might be the qualifier. Every credible supplier must meet a minimum defect rate, just to be considered. Price might be the order winner, deciding which qualifying supplier gets the order. Confusing the two is a common and costly operational mistake. An organization invests heavily to exceed a qualifier customers already take for granted, and underinvests in the actual order winner. The excess investment wins nothing extra.
Table 5.3.1
What Supports Each Priority, and What It Costs
Table five point three point one links each priority to the decision that supports it, and the priority it most often trades against. This is the conventional trade-off view. Cost is supported by a standardized process, high utilization, and large batch sizes. It trades against flexibility, because standardization resists rapid change. Quality is supported by tighter process control, and more inspection or in-process checks. It trades against cost or delivery speed, because extra control steps take time and resources. Delivery speed is supported by extra capacity held in reserve, and shorter production runs. It trades against cost, because idle reserve capacity is expensive. Delivery reliability is supported by buffer time in schedules, and redundant supply sources. It trades against cost too, since buffers and redundancy both carry direct expense. Flexibility is supported by general-purpose equipment, cross-trained staff, and smaller batches. It trades against cost, because general-purpose capability is usually less efficient per unit.
Process Types
Volume and Variety Decide the Process
Operations fall along a spectrum of process types, set by the relationship between volume and variety. At one end is the project process. It produces a single, often unique output, through a largely unrepeated sequence of activities. Very low volume, very high variety. Think of constructing a custom building. A job shop handles a wide variety of distinct orders, in low to moderate volume. Its equipment and staff are organized flexibly around whatever job arrives next, as in a specialty machine shop. A batch process produces a defined quantity of one product, then switches to a batch of another. That suits moderate volume and moderate variety, like a bakery producing different runs through the day. A line process arranges equipment in a fixed sequence, for a narrow range of similar products at high volume. An automobile assembly line is the classic case. And a continuous flow process runs a single, largely undifferentiated output, continuously, at very high volume and very low variety. A chemical refinery, for example. The key point is that the right process type follows from where the operation sits on the volume-variety spectrum. It is not a matter of preference, independent of that spectrum.
Capacity And Utilization
Why Running Flat Out Backfires
Capacity is the maximum output rate an operation can sustain. Utilization is the share of that available capacity actually being used. Now a genuinely counter-intuitive relationship. As utilization climbs toward its maximum, waiting time inside the system tends to rise sharply, not smoothly. That's especially true once utilization pushes past a fairly high threshold. The reason is variability. Real arrivals and real processing times are rarely perfectly steady. At very high utilization, there is almost no spare capacity left to absorb an ordinary fluctuation. So the fluctuation turns immediately into a queue. That's why an operation run slightly below its theoretical maximum is often more reliable, in practice, than one run at its absolute limit. Spare capacity can look like waste on paper. In practice, it is what absorbs the bumps.
Figure 5.3.1
The Bottleneck Sets the Pace
The bottleneck is the stage in a multi-stage process with the lowest capacity. The principle that follows is direct. The output of the whole process equals the output of its bottleneck, however much capacity other stages have. Here is a four-stage process at a fictional manufacturer, with illustrative hourly capacities. Stage one runs at one hundred twenty units an hour. Stage two at ninety. Stage three at one hundred fifty. Stage four at one hundred ten. Stage two is the bottleneck, so the whole process produces ninety units an hour. Now meet Renzo, the manager in a composite case built around this process. Concerned about throughput, he approved a significant investment in faster equipment for Stage four, the final stage. The equipment performed exactly as promised. Stage four's capacity rose to two hundred units an hour. Renzo watched the output figures closely for weeks. To his genuine surprise, they had not moved at all. The process was still producing ninety units an hour. Renzo had improved a real stage, just not the process's actual constraint. Stage four now simply sat further below its own ceiling than before. The number that mattered was the rate at which Stage two could pass work forward. That was still ninety. So effort aimed anywhere except the current bottleneck adds nothing to overall output, until the bottleneck itself is addressed. Before investing, find the constraint.
Service Operations
What Makes Services Different
Service operations differ from goods-producing operations in three characteristic ways. The first is simultaneity of production and consumption. A service is typically produced and consumed at the same moment. A manufactured good can be made today and used later. A haircut cannot be produced in advance, and stored for a customer who hasn't arrived. The second is customer participation. The customer is often present inside the process itself, not just receiving its finished output. So the customer's own behavior becomes part of what the operation has to manage. The third is intangibility. A service cannot be physically inspected before delivery, the way a manufactured good can be inspected before it ships. That makes quality control in services a fundamentally different problem from quality control on a production line. Put together, these mean a service operation's mistakes tend to reach the customer directly.
Inventory And The Customer
Buffer, Cost, and Customer Experience
Inventory deserves its own attention, because it is both a buffer and a cost, at the same time. That dual nature is the whole reason inventory decisions are genuinely difficult, rather than obvious. As a buffer, inventory absorbs variability, in demand, in supply, and in processing time. It protects the operation and its customers from the direct impact of that variability. As a cost, inventory ties up capital, takes storage space, and risks obsolescence or spoilage the longer it sits. So the reasoning for holding less, where an operation can safely manage it, follows from that second side. Every unit held is capital that could work elsewhere, and a risk of becoming worth less, or worthless, before it's used. Finally, notice where every decision in this section ends up. It reaches the customer. A layout decision affects how quickly an order moves through a facility. A capacity decision affects whether a customer waits. A quality decision affects whether what they receive works as promised. So operations is never purely a back-office concern. It's where an organization's stated priorities actually become a customer's experience. Next, Subchapter five point four widens the lens to systems theory, and the organization as an interdependent whole.
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