Should you Balance Capacity with Demand? | Rowtons Training by Laurence Gartside
Summary
TLDRLaurence Gartside explains why perfectly balancing capacity with demand in operations management is often a flawed strategy. Despite a cashier's capacity to serve 60 customers per hour matching the average demand, variations in both customer arrivals and service times lead to perpetual queues. Aiming for 100% utilization exacerbates the issue, causing waiting times to increase drastically. Instead, businesses should accept some idle time to maintain efficient service.
Takeaways
- 🧐 Balancing capacity with demand might seem efficient but often leads to long queues and customer dissatisfaction.
- 😤 Customers get frustrated when they encounter long waiting times, even if the business appears to have the right number of staff.
- 🛒 Supermarkets and other businesses face challenges in predicting customer arrival patterns and matching them with cashier availability.
- ⏰ Demand varies throughout the day, leading to periods of inactivity for cashiers and periods of queue growth.
- 📉 Lost capacity, such as when no customers arrive during a cashier's available minute, cannot be recouped.
- 📈 Queues can grow indefinitely if demand consistently outpaces capacity, especially in businesses operating 24/7.
- 💼 Operations managers must consider the impact of aiming for 100% utilization when there is variability in both demand and capacity.
- 🔍 Reducing variability in demand or capacity is challenging, especially in customer-facing businesses like supermarkets.
- 🏢 The decision on how much capacity to provide is crucial and involves balancing the cost of additional staff or equipment against customer wait times.
- 📊 Queue times increase significantly when utilization rates exceed 70-80%, depending on the level of variability.
- 🔗 It's important for businesses to plan capacity utilization carefully to avoid excessive waiting times and potential loss of customers.
Q & A
Why is balancing capacity with demand often a bad idea?
-Balancing capacity with demand can lead to long queues and customer dissatisfaction because of the inevitable variation in both demand and capacity. When demand and capacity rates match, the system can never catch up, leading to a perpetual queue that grows throughout the day.
What is the example given in the script to illustrate the problem with balancing capacity and demand?
-The script uses the example of a convenience store with one cashier who can serve 60 people per hour and historical demand data showing an average of 60 customers per hour. Despite this seeming balance, the reality is that the queue would continue to grow due to the variability in customer arrival times and service times.
How does the variation in customer arrival times affect the queue length?
-Variation in customer arrival times causes the queue to grow because when no customers arrive, the cashier's capacity is wasted, and when multiple customers arrive at once, the cashier can only serve one at a time, causing the queue to build up.
What is the role of capacity variation in the supermarket cashier scenario?
-Capacity variation, such as the cashier sometimes taking longer to serve a customer, contributes to the problem of queues. It adds to the unpredictability and can cause the queue to grow faster than if there was no variation.
Why can't the cashier catch up with the queue?
-The cashier can't catch up with the queue because the losses in capacity when no customers arrive cannot be recouped, and when two or more customers arrive at once, the cashier can only serve one, leaving the other to wait, thus the queue persists.
What is the impact of aiming for 100% utilization on queue times?
-Aiming for 100% utilization exacerbates the problem because any variation in demand leads to increased queue times. This is because there is no buffer to handle fluctuations in customer arrivals, leading to longer waiting times.
How does the concept of capacity utilization relate to different types of businesses?
-Capacity utilization is a critical concept across various businesses, including car factories, doctor's surgeries, call centers, and restaurant kitchens. It involves deciding how much capacity to have relative to the expected demand and understanding the trade-offs between underutilization and queue times.
What is the recommended level of utilization to avoid drastic increases in queue times?
-The script suggests that queue times start to increase drastically when utilization goes above 70 to 80 percent, depending on the level of variation. This implies that businesses should aim for less than 100% utilization to manage queue times effectively.
What are some strategies to reduce the variation of demand and capacity?
-Strategies to reduce variation include improving service time consistency, such as cashier training, and managing customer expectations, such as through预约系统 or peak-time pricing. However, these strategies may not always be feasible or desirable depending on the business model.
Why is it not practical to make customers book appointments with the cashier?
-Making customers book appointments with the cashier is not practical for supermarkets because it goes against the spontaneous nature of grocery shopping and would likely deter customers, leading to a loss of business.
What is the final advice given by Laurence Gartside regarding capacity management?
-Laurence Gartside advises that while it's tempting to aim for 100% capacity utilization to take on more work, businesses should be wary of the resulting increase in waiting times and queues. He suggests getting comfortable with some unused capacity to ensure better customer service.
Outlines
🛒 Balancing Capacity with Demand in Operations Management
The paragraph discusses the concept of balancing capacity with demand in operations management, using the example of a supermarket cashier. It explains that while it seems efficient to match capacity with demand, it often leads to long queues and customer dissatisfaction. The speaker, Laurence Gartside, points out that customers don't arrive at a steady rate, leading to periods of wasted capacity and growing queues. He illustrates this with a hypothetical convenience store that perfectly matches capacity with average demand but still experiences a perpetual queue due to the variability in customer arrival times. The paragraph emphasizes the challenges of managing capacity in the face of unpredictable demand and the importance of not aiming for 100% utilization to avoid infinite queues.
🔍 Managing Capacity to Reduce Queue Times
In this paragraph, Laurence Gartside continues the discussion on capacity management, focusing on the practical implications for operations. He suggests that reducing the variation in capacity, such as the cashier's service time, is not always feasible, especially in supermarkets where customer demand cannot be controlled. He notes that businesses often find that queue times increase significantly when utilization rates exceed 70-80%. The speaker advises that businesses should be comfortable with some level of unused capacity to prevent queues from growing excessively. He concludes by encouraging viewers to learn more about operations management and related topics through his courses and invites feedback on their experiences with queues.
Mindmap
Keywords
💡Capacity
💡Demand
💡Queue
💡Operations Management
💡Utilization
💡Variation
💡Efficiency
💡Supermarket Manager
💡Customer Satisfaction
💡Capacity Utilization
💡Process Improvement
Highlights
Balancing capacity with demand seems sensible but often leads to operational inefficiencies.
Aiming for 100% capacity utilization can lead to disastrous consequences in operations management.
Variation in demand makes it impossible to perfectly match capacity with demand, leading to inefficiencies.
When demand and capacity are perfectly balanced, queues will form and continue growing throughout the day.
Lost capacity during low-demand periods cannot be recovered, leading to longer queues during high-demand periods.
If the arrival rate of customers matches capacity, the queue will stabilize but won’t clear unless new customers stop arriving.
In a 24-hour operation, queues would grow infinitely if demand consistently matched capacity.
Customers may leave due to long wait times, leading to a loss of business, even if the capacity matches demand.
Excessive utilization leads to growing queues, while low utilization may seem inefficient but prevents delays.
Operational managers should aim for 70-80% utilization to maintain efficiency and avoid long queues.
Variation in capacity, such as customer service time, exacerbates the problem, making balancing even harder.
Reducing variation in capacity or demand is ideal but often not practical in environments like supermarkets.
Queuing theory shows that capacity utilization above 80% dramatically increases waiting times.
Operations managers must accept periods of idle capacity to maintain overall operational efficiency.
In many industries, like call centers or healthcare, managing capacity utilization is crucial to prevent service delays.
Transcripts
Should you ever balance capacity with demand? Sounds sensible doesn't it? Nice and efficient,
no wasted capacity, maximizing output. That's all true, so why is it often such
a terrible terrible idea and one of the most crucially misunderstood concepts in
Operations Management? Hi, I'm Laurence Gartside trainer and coach in Operations Management.
So I want you to think about this. Don't you hate it when you go into a supermarket to pick
up a few essentials and head to the checkout and oh no, there's a massive long queue to get served.
The one cashier is sat behind the till bleep, bleep with like five other people in front of
you with full trolleys and the other empty cashier counters with no one serving and you think
how hard can it be to hire the right amount of people? Does it make you angry and think
next time i'll just go somewhere else! Being a customer waiting in a long queue
is pretty annoying when the solution looks so obvious but imagine the decision of the
supermarket manager who has to decide how many cashiers to hire for the supermarket.
Actually, let's make our example super simple just one cashier in a convenience store corner shop.
The manager does some analysis and works out that one cashier is perfectly able to serve,
able to serve 60 people per hour one every minute and they are going to work full-time for 10 hours
a day. Well, keep it simple and ignore breaks et cetera. So that's the capacity of 600 per day,
the manager also looks at the historical demand data and sees that on average the shop gets
600 customers per day in the 10-hour day 60 people per hour. What good luck? That's perfect! But, do
customers turn up exactly every minute throughout the whole day? No, of course not. There's always
variation of demand sometimes no customers come to the checkout in a given minute and sometimes
two or more can arrive in a particular minute and the queue grows but these two things don't
cancel each other out. When there was no customer, that capacity is lost. You can't catch that up,
that's just lost time for the cashier and then if two customers arrive in the next minute,
well we serve one whilst the other waits in a queue. Then, if from the next minute new
customers do actually continue to arrive perfectly one customer exactly every minute then the queue
of one person waiting would remain for the rest of the day. The cashier always unable to catch up.
The losses accumulate but when the demand and capacity rates match
you can never catch up. In reality, in our example shop with one cashier who can serve 60 people per
hour, they really can and in a shop which does on average have 60 customers per hour, in reality we
would get a shop with a really long queue that continued to grow throughout the whole day. Only
with the backlog finally clearing at the end of the day when new customers could no longer arrive.
If it was a 24-hour shop, the queue would grow forever to infinity! Well,
okay it wouldn't because we customers would start to get so angry with the long wait they would just
leave and we lose the customers until we find a status quo of a moderate line of customers.
Enough to piss everyone off but not enough for many people to choose to go somewhere else.
This balanced capacity with demand though is definitely not good for the business. We mentioned
this is caused by aiming for a hundred percent utilization when we have variation of demand but
it's worse than that because inevitably we have variation of capacity too. Our cashier doesn't
always take one minute to process each customer, quite a few take only 30 seconds some take three
minutes which contributes to exactly the same problem. Remember, if customers always arrived
every minute exactly and our cashier could always serve a customer in exactly one minute then our
100 capacity utilization at full expected output would work perfectly! Now as operations managers,
we can work on reducing the variation of capacity, our cashier's serve time consistency but
in this case that's mostly based on the size of each customer's shopping trolley. So in this case
that's not really an option. Reducing variation of demand is a massively important topic of
all operations management but again in our supermarket making customers book appointments
with the cashier to turn up one every minute really isn't what supermarkets are about.
So that only leaves the management choice of how much capacity, how many cashiers to hire.
In business operations, what we find is that queue times start to drastically
increase when we go above a 70 to 80 percent utilization depending on the level of variation
that means getting comfortable with seeing the checkout cashier or your expensive machine doing
nothing for large portions of time not because of problems but just because it is waiting for work,
whether you are a build toward a car factory, a family doctor surgery, a telephone call center,
or a restaurant kitchen. Planning your capacity utilization is an essential choice with the
eternal temptation to just take on that bit more work or trim back on capacity or staffing because
you can see that excess 30 percent capacity. So can you match capacity with demand and have 100
capacity utilization? Yes, you can take on more work and get more done but beware because waiting
times and therefore queues will skyrocket to infinity. If you want to keep learning more about
Operations Management, Supply Chain, Inventory and Process Improvement. Check out my courses over on
my website rowtonstraining.com. Don't forget to like, subscribe, ring the bell and comment on your
queuing frustrations down below. Alright then, that's all from me until next time. Crack on!
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