Kristen’s Cookie Company (Operations Case Study)
Kristen’s cookie operation shows how task times, worker availability, and oven capacity shape customer wait and production rate. The listed steps take 27 minutes when done one after another, but that is not the same as the time between finished orders when work overlaps. The key is to map each resource, calculate its workload, and then test realistic ways to improve flow.
A small cookie business can feel simple until orders arrive close together. Then the worker may be mixing one batch while another waits for the oven, or packing cookies while a new customer is ready to order. Even routine equipment wear and tear could affect operations over time, but this case gives no repair or downtime data. The analysis should not treat those costs as known.
I approach the case by separating three ideas: lead time, the time one order takes from start to finish; labor content, the active work a person must do; and capacity, the most the operation can produce in a given period. Confusing these measures can lead to poor staffing or equipment choices.
Case Overview, Operating Assumptions & Process Flow
This section sets out the cookie-order steps and the assumptions needed to analyze them. The case lists each task’s duration, but it does not specify order size, tray capacity, worker count, or whether the oven, cooling space, and packing area can be used at the same time. Those details must be stated before drawing firm conclusions.
The listed process is:
Take order → Wash and mix ingredients → Spoon cookies onto tray → Bake → Remove cookies → Cool → Pack → Accept payment
| Activity | Time | Baseline resource or role |
|---|---|---|
| Take order | 1 min | Worker |
| Wash and mix ingredients | 6 min | Worker |
| Spoon cookies onto tray | 2 min | Worker |
| Bake | 9 min | Oven |
| Remove cookies | 1 min | Worker |
| Cool | 5 min | Waiting time; space needs are unknown |
| Pack | 2 min | Worker |
| Accept payment | 1 min | Worker |
For a clear baseline, I assume one order uses one tray, one worker performs all active tasks, and the oven holds one tray at a time. I also assume cooling does not occupy the oven and that the worker can do other tasks during baking and cooling. If any of those assumptions is wrong, the results change.
Why the first order takes 27 minutes
Adding all listed times gives 27 minutes: 1 + 6 + 2 + 9 + 1 + 5 + 2 + 1. That is the elapsed time for one order if every activity happens in sequence and nothing overlaps.
It is not automatically the wait for every customer. Once production is underway, the worker may prepare a later order while the first tray bakes or cools. In that case, the first order’s 27-minute baseline and the time between completed orders are different measures.
The listed active worker tasks total 13 minutes: taking the order, mixing, spooning, removing cookies, packing, and accepting payment. Baking takes 9 minutes of oven time, while cooling takes 5 minutes of elapsed time. Keep those resource demands separate.
Key takeaway: Use 27 minutes as the sequential baseline, not as the automatic production interval.
Process Capacity, Bottlenecks & Order Requirements
Capacity is the most an operation or resource can produce in a set period under stated conditions. A bottleneck is the resource with the lowest capacity, which limits the whole process. Here, the worker and oven have different workloads, so compare each one’s capacity rather than relying on the 27-minute total.
Resource workload and capacity
For a resource with a fixed amount of time available, calculate capacity as available minutes ÷ minutes needed per order. The table uses 60 available minutes per hour and assumes one order requires one tray. It does not include breaks, cleaning beyond the listed task, equipment downtime, or demand gaps.
| Resource | Work per order | Capacity calculation | Baseline capacity |
|---|---|---|---|
| Worker, active tasks | 13 min | 60 ÷ 13 | About 4.62 orders/hour |
| Oven, baking only | 9 min | 60 ÷ 9 | About 6.67 trays/hour |
| Cooling time | 5 min elapsed | Not enough information | Cannot calculate |
On these assumptions, the worker is the likely bottleneck: the worker can complete fewer orders per hour than the oven can bake trays. The process’s theoretical capacity is therefore about 4.62 orders per hour, not 60 ÷ 27. This is a model result, not a promise of actual output. It assumes tasks can be scheduled without extra delays and that one order equals one tray.
There is an important oven detail to check. The case states that baking takes 9 minutes, but it does not say whether the oven remains unavailable during the 1-minute removal task. If it does, oven workload becomes 10 minutes per order, so its capacity is 60 ÷ 10 = 6 trays per hour. The worker still appears to be the bottleneck under the baseline assumptions, but the capacity gap is smaller.
Utilization, throughput, and customer wait
Throughput is the number of completed orders in a period. Utilization is the share of a resource’s available time used to meet demand. If demand is 3 orders per hour, for example, worker utilization against the 4.62-order theoretical capacity is about 65%: 3 ÷ 4.62. This is an illustration, not a demand figure supplied by the case.
Actual throughput cannot exceed the bottleneck capacity. It may be lower if orders arrive unevenly, the worker must pause, or cooling and packing space is limited. Customer wait can also rise when several orders arrive together, even when average demand is below capacity. That is why queue and arrival data matter.
To improve the estimate, record: – Orders and trays per order, including any orders that need more than one tray. – Order arrival times and promised pickup times. – Worker time spent on each task, including cleaning or customer service. – Whether oven loading, removal, or cooling blocks a resource. – Breaks, equipment downtime, and available cooling or packing space.
Key takeaway: The worker is the bottleneck in the stated baseline, but demand and resource details are needed to predict real output and wait times.
Scheduling Choices, Academic Analysis & Student Learning
Scheduling decides when each task begins and which resource performs it. For this case, the useful comparison is not “27 minutes versus a faster number.” It is how different schedules affect the first order, later orders, worker workload, and customer wait under stated assumptions.
Compare practical operating choices
| Operating choice | Likely effect | What to check before using it |
|---|---|---|
| Do each order fully in sequence | Easy to manage; first-order baseline is 27 minutes | Whether customers can accept the resulting wait |
| Prepare the next order during baking | Uses oven time for other work; may reduce gaps between completed orders | Worker task timing, oven handoff, and order mix |
| Separate customer/payment tasks from production | May reduce interruptions to mixing and packing | Whether another person is available and the extra labor cost |
| Add oven capacity | Helps only if oven capacity limits output | Demand, tray capacity, oven cost, space, and current bottleneck |
| Batch similar tasks | Could reduce repeated setup, but may delay a particular order | Batch size, pickup promises, and handling needs |
The most sensible first test is scheduling, not buying equipment. If the worker can prepare the next tray while a batch bakes and manage cooling without blocking the next task, the process may produce orders at a steadier pace. But the worker’s active workload remains 13 minutes per order in this model. Overlap improves the use of time; it does not erase labor.
Adding oven capacity is not justified by the 27-minute sum alone. Under the baseline calculation, the oven has more capacity than the worker. A larger or second oven could leave the main limit unchanged, while adding cost. It may become useful if measured demand exceeds current capacity or if oven availability proves more restrictive than assumed.
A step-by-step analysis for coursework
A strong operations analysis can follow this sequence:
- Map the flow. List each task, duration, resource, and required order. Confirm what must happen before the next step.
- State assumptions. Specify order size, trays per order, worker count, and which tasks can overlap.
- Separate measures. Report the 27-minute sequential lead-time baseline, 13 minutes of active worker labor, and 9 minutes of oven baking per order.
- Calculate capacity by resource. Divide available time by each resource’s workload; the lowest capacity is the modeled process limit.
- Test a schedule. Check whether preparation can happen during baking and whether cooling or customer service interrupts work.
- Recommend and validate. Compare likely service effects with labor and equipment costs, then collect actual operating data.
Profit also depends on more than capacity. A basic contribution calculation is selling price per order minus variable cost per order. To judge a proposed staffing or equipment change, the business would also need wages, ingredient and packaging costs, equipment cost, demand by time, and any added operating costs. The case does not provide those figures, so a precise profit estimate would be unsupported.
I teach this case as a reminder to make the model visible before recommending a fix. A student who shows the resource workloads can explain why buying another oven may not solve a worker bottleneck. The analysis is stronger when it also names what is unknown and proposes a way to measure it.
Key takeaway: Test task overlap and collect demand and cost data before recommending new staff or equipment.
Career Pathways: Operations, Supply Chain & Process Improvement
This case builds skills used in operations and supply chain work: mapping a process, measuring resource use, finding a bottleneck, and weighing service against cost. These skills apply beyond cookie production, but the conclusions here stay tied to the case’s stated tasks and assumptions.
An operations analyst might measure order arrivals and task times, then compare actual throughput with the model. A process-improvement role might test a new task sequence and check whether it reduces waiting without adding errors. A supply chain role might examine ingredient availability or packaging needs, but the case gives no supplier or inventory data to analyze.
For a class assignment, show the flow diagram, workload table, assumptions, and recommendation together. That makes it easier for a reader to see how the evidence supports the conclusion, and where further data is needed.
Key takeaway: The case is useful practice in explaining a process with evidence, not just suggesting a faster way to work.
Conclusion and FAQ
The cookie process has a 27-minute sequential baseline, but that figure combines active work, oven time, and cooling. Under the stated one-worker, one-tray assumptions, active worker work takes 13 minutes per order and baking takes 9 minutes. The worker is therefore the likely baseline bottleneck, while actual waits and profit depend on information the case does not provide.
Frequently asked questions
Does one order always take 27 minutes?
The listed tasks total 27 minutes when performed one after another. If work overlaps, the customer’s wait may differ.
Is 27 minutes the production capacity interval?
No. Capacity depends on workload at each resource and whether tasks can overlap. Dividing 60 by 27 would treat the entire sequence as one resource’s workload.
What is the worker’s workload per order?
Under the baseline assignment, the worker performs 13 minutes of active work per order. The 5-minute cooling period is waiting time, not active labor, unless it blocks a needed resource.
What is the oven’s capacity?
If baking alone occupies the oven for 9 minutes per tray, its theoretical capacity is about 6.67 trays per hour. If removal also blocks the oven for one minute, it is 6 trays per hour.
What is the likely bottleneck?
The worker is the likely bottleneck under the baseline assumptions: about 4.62 orders per hour compared with 6.67 oven trays per hour. This depends on one order requiring one tray and the stated task assignments.
Can the worker prepare another order while cookies bake?
The model allows that overlap because baking uses the oven while preparation uses the worker. Actual feasibility depends on task timing, safe handling, and whether other work interrupts production.
Would a second oven increase output?
Not necessarily. The baseline model points to worker capacity as the limit. More oven capacity helps only if oven availability is a real constraint or demand and other resource limits change.
What information is needed to estimate customer wait?
Record when orders arrive, how many trays they need, task overlap, cooling-space limits, and the time each order is completed. Demand patterns matter because several orders arriving together can form a queue.
What information is needed to estimate profit?
The business needs selling price, ingredient and packaging costs, wages, demand, and the cost of any proposed equipment or staffing change. The case’s task times alone cannot establish profit.
What is the strongest first recommendation?
Map and time the real process, then test whether the worker can prepare the next order during baking and cooling. Compare measured throughput and customer wait before investing in equipment or extra labor.
(This article was written by one of our staff writers, Alan Westbrook. Visit our Meet the Team page.)
