We are trying to figure out who runs the "fastest shifts" at our store. We have lots of different shift runners at our restaurant but not all of them run equal amounts of shifts. At first I figured I can just take the average Speed of Service (SOS) and that would be fair but it doesn't seem to give the repeat shift runners a fair shot at any of the awards. I feel like I'm missing a really simple formula or explanation in determining this "fairly". Do I need to weigh the averages differently or something? My last resort would be to award points for certain time frames: aka - 4:00-4:59 worth 3 points, 5:00-5:59 worth 1 point etc. But now that seems to favour only those who run large quantity of shifts. Any help would be appreciated! Thanks (I tried to attach a PDF of this or Excel sheet)
Trying to fairly use and rank averages for our restaurant
- Thread starter callmecap
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BigBeachBanana
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1) What does it mean to run the "fastest shift" in the store? Based on what criteria?
An example would be the number of customers the runners served during their shifts.
2) What are the times listed in your sheet?
As BBB said, we really need to know more about the business to give a remotely intelligent answer. The thing that immediately occurred to me is that you seem to be ignoring the ”load.” If you judge the productivity of a bank teller on Tuesday morning in the 9 to 10 slot versus the productivity of a bank teller at lunch hour on Friday, you are comparing apples to oranges. You do not have to be very swift in a restaurant at 3 in the afternoon.
I definitely can include some more info! Thanks for your insight. Currently we are just trying to use Speed of Service to determine the fastest shift. The document shows how fast, in minutes and seconds, a guest starts their placing their order to when they drive off. We have split the day into 4 parts, Breakfast, lunch, 2pm-5pm, and 5pm-close. I was hoping to just take the average speed of service of each leaders' shifts, but our shift runners who run the most shifts get beat out by someone who runs 1 or 2 shifts for that day part because their average is lower. There could be amny factors that contribute to this; nobody called out on that shift, the store was staffed with the most tenured team members, there were no big events happening those days or mornings, etc. So if I can avoid bringing in any external factors to keep it simple then great. Otherwise, my second idea was to essentially assign a 'point value' to certain time frames eg. 3:00-3:59 SOS would be worth 5 points, whereas 6:00-6:59 would be worth 0. But then you could easily win certain day parts if you just run the most shifts.
Could I do something with their average times (placed at the bottom of their column--and the current lowest avg for that day part is highlighted) or do I need to add in more information to the equation do y'all think?
I am not following something here. You say that they “get beat out (have a lower average?) by someone who runs fewer shifts because their average is lower.” This does not begin to make sense to me. If people who run more shifts have a slower speed of service, then they have a slower speed of service. So if that is what the data show, it is what it is.
There is something here that is obvious to you but not to me. You seem to be saying that someone who runs more shifts should have a slower speed of service so how should you adjust the averages to take that into account. But I am too ignorant to understand how more shifts intrinsically translates into slower time on average. Unless you are saying that the likelihood of some external bad event happening on someone’s shifts is higher the more shifts are worked. That should wash out if you average over a long enough period.That is, if I run three shifts in a day, it is far more likely that someone will call off in one of those three than if I ran just one shift that day. True. But if if we compare a month’s worth of days so we are comparing 90 shifts and 30 shifts the percentage of shifts affected by someone calling off should be close to the same on average.
There is something here that is obvious to you but not to me. You seem to be saying that someone who runs more shifts should have a slower speed of service so how should you adjust the averages to take that into account. But I am too ignorant to understand how more shifts intrinsically translates into slower time on average. Unless you are saying that the likelihood of some external bad event happening on someone’s shifts is higher the more shifts are worked. That should wash out if you average over a long enough period.That is, if I run three shifts in a day, it is far more likely that someone will call off in one of those three than if I ran just one shift that day. True. But if if we compare a month’s worth of days so we are comparing 90 shifts and 30 shifts the percentage of shifts affected by someone calling off should be close to the same on average.