When last I left you, I was off to enjoy my delicious hot pizza. Let me tell you, it was yummy! While eating it I was considering how we might help out this local business by offering to show them ways that they might increase efficiency by eliminating a bottleneck in their process flow. Just to remind you, we used a methodology called “capacity analysis” to identify the bottleneck in the pizza shop’s process. This bottleneck determined the pizza shop’s “theoretical capacity,” or the maximum number of pizzas they could produce and sell in a given hour. We looked at three “resource pools:” the oven could bake up to 20 pizzas per hour, the order taker/cashier could sell 18.75 pizzas per hour, and the pizza chef (AKA “Bottleneck Boy”) could assemble and load 15 pizzas per hour. (You can read the first part of this series here).
The Pizza shop could eliminate the bottleneck using two different strategies. One strategy would be to hire another pizza chef. Once this new worker is trained and fully up to speed, the output of this resource pool would be doubled, with a new maximum flow rate of 30 pizzas per hour! But would this really solve the problem? I think not. All this would do would be to add another salary, and only increase the maximum potential output by 3.75 pizzas per hour and make the cashier into the “new” bottleneck.
A different strategy might be more promising: increase the maximum potential output by reallocating the tasks performed by this resource pool and remove pressure from the pizza chef. Let’s look at the tasks performed by both workers:
Pizza chef (one batch of 5 pizzas):
- preparing the sauce – 4 minutes
- spinning the dough – 10 minutes
- assembling the pie – 5 minutes
- loading the oven – 1 minute per batch
- TOTAL: 20 minutes
Order taker/cashier (one batch of 5 pizzas):
- unloading/boxing – 1 minute per batch
- payment – 3 minutes per order
- TOTAL: 16 minutes
So, what if we also made the cashier responsible for the task of loading the pizzas into the oven? This would save the pizza chef 1 minute per batch for a new total of 19 minutes. Here is what the new formulas would look like:
Doesn’t seem like much, right? The pizza chef is still the bottleneck, but it does balance out the 3 resource pools a bit and if we consider the potential revenue it starts to add up, right? An increase of 0.8 pizzas per hour, over a 10 hour shift comes to 8 more pizzas to sell per day! If we assume that each pizza sells for an average of $10, then the total maximum revenue for the shop goes from $1,500 per day to $1,580 per day and increase of over 5.3%. Not bad considering that we didn’t spend a single penny in order to maximize revenue! Assuming the shop is open 7 days per week, 52 weeks per year the annual revenue could increase by as much as $29,120! All that extra cash generated just by having the cashier load the ovens. Sweet.
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