Category Archives: 2.2.1-Time Dependant Workload

Time Dependant (Part 2 of 2)

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Time Dependant Workload (Part 2 of 2)

Back to our example, if we decide to round the number, the result of the above hour would be two. You do this math for every hour you are open and you end up with figure 1 below. If you lay out your workload through time, you’ll see the number of employees varying during the day. It directly reflects your customer’s flow.

 

Figure 1. Number of employees required per time of day

 

Some of you may say that since employees have a different productivity (some cashiers are faster than others for example), you could schedule according to the customer output directly. Why translate to number of employees, right? This would be the optimal way to schedule since you could have your fastest cashier on staff and therefore need one less cash register open, which would save you money. Then why isn’t it done this way? Simply to keep things manageable. Otherwise, a planner would need to measure against all sorts of different drivers to establish a schedule and it would become quite a challenge to manage. Imagine your fastest cashier calling in sick: does this mean you replace that person with two other cashiers? The daily management of the schedule would quickly become overwhelming. So be practical and express your workload in number of employees required.

 

The cashier workload is now ready. You’ll notice that in our example, there are some big peaks and valleys. The number of customers would require up to ten registers for one hour. In our store, not only we do not even have ten registers, but we can’t ask folks to come in for only one hour of work. There will be constraints (see chapter 4) that impose a minimum duration when someone is scheduled to work.

 

Again, to help yourself and for simplicity, you can smooth out the employee requirements by reducing the peaks that represent noise. The more your resolution gets to be precise, the more of these peaks you will see. The same goes for valleys where all of the sudden no cash register is required because you don’t expect customers between 9am and 10am let’s say. You’ll still need a minimum of one cashier open no matter what the customer count is. So in your translation exercise, put a minimum and a maximum. Also, look at differentials between the previous hour and the next hour. For example, if you need 2 cashier for one hour, then 10 cashiers for the next hour, then again 3 cashiers for the next two hours, you can see that this 10 should be 3 or 4 but will not be 10. Rule of thumb: when you have peaks like this, you may have the ability to schedule shifts that overlap (the end of the shift overlaps by one hour the beginning of the next one). Therefore, you can make this workload at the previous hour (2) added to the next hour (3) and make that number a 5 instead of a 10.

 

The same logic applies to valleys, but in this case, you may elect to keep the valleys intact and not readjust according to the previous and next hours. These valleys will allow you to schedule breaks later in the process or dispatch the time independent workload.

 

This daily workload not only will be different on each weekday, but will also change from week to week as seasonal patterns will influence customer behavior. Holiday season will have higher traffic than the beginning of the year when no special events are happening. Total volume will therefore change from week to week.

Time Dependant Workload (Part 1 of 2)

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Let’s take the Cashier workload and analyze how we will quantify that one. This workload has only time dependant tasks and therefore is directly related to the number of customers showing up at the cash register. These customers will have different number of items to buy and will pay through different methods (cash, credit, check, etc). As explained earlier, each customer will take some time to check out and each cashier will have a limited capacity in number of customers.

The first thing to do is to pick a resolution and a unit of measure. The unit of measure is the time it takes to serve a customer. The resolution is the period of time where you will measure the count of customers. You can count the number of customers per 15 minutes or per hour or anywhere below, above, or in between. Usually, you choose a resolution that is manageable depending on the tools you have. If you have a pen and paper, I would suggest never going lower than one hour. If you use Excel, you could manage all the way down to 30 minutes. High end software allow for as low as 5 minutes in some cases.

 

You may wonder why would anyone manage a schedule down to the 5-minute increment? In our simplified example of one store, the amount of time to service a customer will be counted in minutes. No point in counting seconds because I have four cash registers which of only two are open most of the time. So if I say it takes 55 seconds to serve a customer and I round it up to one minute to keep my math simple, the difference on the week is insignificant. Take 5 seconds times the number of customers visits, say two thousand, makes 10,000 seconds a week, which is roughly 3 hours over the whole schedule. Not much. By padding the time required to serve a customer, you are adding hours to your workload quantity that is not necessarily required but that saves you aggravation and funny math.

 

But if our grocery store is successful and if we buy more stores and now have a chain of hundreds of store, you can multiply that 3 hours by 200 stores which makes 600 hours of extra time scheduled. Use any hourly amount, it starts to become significant. And if you perform the same exercise for all tasks, your over-scheduled number becomes very significant. This is why large enterprises do buy software that measure to the second the tasks that are performed in order to reduce the waste that accumulates due to rounding. Your workload definitions will therefore get longer and more detailed and will be measured more precisely as you grow your business. It will be directly proportional. If you don’t, you are exposed to over scheduling once you get to the schedule.

 

So for the sake of simplicity in our example, we will pick a one minute per customer average serving time and a one-hour resolution. Therefore if it takes one minute to serve one customer, our cashier has a capacity of 60 customers per hour. We take the expected business of that hour (say we expect 100 customers), this would create 100 minutes of work to do in one hour. You divide the amount of work by the resolution (100/60) and you get 1.66 employees. Since you can’t schedule two thirds of a person, you have to decide what to do with the fraction (do you schedule someone or not). You may elect to cut the fraction all the time, make the fraction whole all the time (if the result is 1.1, make it 2) or simply round the result. This will have a direct impact on service and cost. If you decide to cut the fraction all the time, it’s good for cost, but bad for service. If you decide to make the fraction whole all the time, it’s good for service but bad for profit. You could also decide to have a different rule depending on the relative part of the fraction. In the math above 0.66 out of 1.66 is a big proportion. You could have a requirement for 10.66 employees. In this case, deciding between 10 or 11 employees will have a much reduced impact on customer service because the capacity is not greatly affected (versus choosing between 1 or 2 employees which represents 50% reduction in capacity). You can already feel that even though you haven’t even started talking about employees, a simple rule of thumb decided by a planner may have a huge impact on the business’s success.