CASHIER DOWNTIME IN RETAIL

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Mass merchandisers, discount retailers, grocery retailers and department stores have a unique challenge at the point of sale related to their cashier workforce.

While these varied retail formats sell many products, the value and volume per sale is lower and the typical customer return frequently to the store. To meet

the expected service level standards and reduce customer wait times, these environments have to keep multiple lanes open at all times. This leads to not only

higher cost for the front lanes but also increased downtime per lane. Without accurate measurements, the operational expenses related to the cashiers

cannot be reduced. This article gives an overview of cashier downtime and metrics to calculate and control it on a real time basis.

By Amit Dhall, Wipro Technologies

Background Cashier Downtime

Cashier Downtime Analysis

Queuing Theory

Queuing Scenarios

Solution to Reduce Cashier Downtime

Metrics to Capture Cashier Downtime & Productivity

Examples to Illustrate Cashier Downtime & Productivity Metrics

Conclusion

About the Author

CONTENTS

3

3

4

5

5

7

7

7

8

03

Due to intense competition and customer service becoming a very critical

parameter, store managers generally ignore the cost involved in keeping

excessive lanes open and hence the payroll cost gets skewed towards the

cashiers. This is further compounded by a tendency of the management to

ignore operational expenses of the front lanes in the name of

customer service.

This can lead to the neglect of other parts of the store particularly with a

limited store budget.

A scenario wherein the focus is to reduce checkout time by keeping the

cost skewed towards the front lanes can lead to the store managers

keeping the workforce on the front lanes and thus overlooking other

important areas in the store which though may not be critical but act as

hygiene factors and aid in store sales.

• An example could be the spillover of a liquid in an aisle making the

entire aisle dangerous for walking which could either lead to no sales

of products in that aisle or even injuries. It could also put off

customers from future visits to the store due to a feeling of untidiness.

• Another scenario could be a lack of focus on the backroom operations

which could lead to empty aisles, inadequate replenishment or wrong

inventory stocking; all three contributing to lost sales.

Background Cashier Downtime

In a retail environment, with the enormous push to improve customer shopping experience, there is a need to keep

as many checkout lanes open as can be and thus bring the customer wait time to the minimum or in other words

reach the idle state of one customer in a lane with no wait time. But to reach this stage, the store has to put an

enormous cost on the payroll.

Thus, even though providing excellent service through minimal wait time

is an important store performance criteria it should not lead to reduced

attention towards other parts of the store.

Cashier downtime is defined as the amount of time when a cashier is

logged-on to a register but is not ringing a transaction or in other words

the cashier is waiting for a guest to arrive in his lane.

Each minute of this time costs the payroll and leads to no productive

output as the cashier keeps manning the lane. If the cashier was not

manning the register waiting for customers he/she could be used to

perform other store activities. This would increase store productivity and

also would help in reducing store payroll costs as additional workforce

would not be required to perform those tasks.

But not all cashier downtime is useful time. An example to illustrate this is

as follows:

Consider a scenario wherein a cashier ends a transaction and there is no

new guest in his lane. The cashier waits for a minute before the new guest

arrives and the cashier starts ringing the transaction. This intervening time

period when the cashier was free is not useful downtime as the cashier

Cashier Downtime Analysis

04

couldn’t log off from the register and perform some other useful activity.

This downtime also depends on the number of cashiers manning the lanes

in a store at a time which in turn depends on the service level to be given

by the store to its guests. Some common service levels are a 1+ 0, 1+1 or

1+ 2. This means that at any given point of time their would be 0, 1 or 2

customers waiting in line while a transaction for a customer is being rung

on any lane of the store. If this threshold is exceeded the store needs to

open another lane.

When a queue in a retail store - be it a checkout queue or a returns queue

or even an inquiry queue - gets congested, there is a delay in service.

A good understanding of the cause of congestion and the resulting delay is

essential for optimizing the number of lanes which should be kept open at

a given point of time in a store to achieve the defined service levels.

The different components of delay in a lane can be classified into the

following categories:

Processing Delay: This is the delay between the guest arriving time at the

counter to the transaction completion time. This delay depends on the

cashier’s speed and on the speed of the application. Better the training

imparted to the cashier and more fine tuned the Point of Sale application,

lesser will be this delay.

Queuing Delay: This is the delay between a guest entering the queue to

the time his transaction is completed. This delay depends on the number

of guests in the queue which in turn depends on the number of lanes which

are open for guest service. More the lanes, lesser will be this delay.

Queuing Theory

Little's Theorem

Little's theorem states that:

The average number of customers (N) in a queue can be determined

from the following equation:

N = λ T

Where Lambda (λ) is the average customer arrival rate and T is the

average service time for a customer.

For a retail store, consider a scenario where the customer arrival rate

(Lambda) doubles but the customers still spend the same amount of time

in the store for shopping. This will effectively double the number of

customers in the store (N). By the same logic if the customer arrival rate

remains the same but the customer service time doubles, it will double the

total number of customers in the store.

The calculation can be illustrated by the following three examples which

represent three different scenarios:

A) In a checkout lane let's assume that the cashier always takes two

minutes to check out a customer. Let's also assume that there is

no line and that a new customer walks up to the cashier at the

exact moment that another customer was done checking out.

This will mean that their will be absolutely no delay between

customer checkouts.

B) If we assume that 10 people used the same checkout lane, but

each person arrived in line one minute after the last person was

done checking out. The cashier is just waiting for a customer for

one minute. The cashier is still capable of checking out a

customer in two minutes, so their will be absolutely no delay

between customer checkouts but for each new customer the

05

cashier will have a downtime of one minute which will be

useless downtime.

C) If we assume that 10 people used the checkout line at nearly the

same time; in other words, there was a line of nine people behind

a customer who is being checked out. For a customer the

checkout time is the amount of time from when they get in line

until they are done checking out. The first person to get to the

checkout lane wouldn't wait at all. The first person in line (not

the one being checked out currently) would wait two minutes to

start checking out, the second person would wait four minutes,

and so on until the last person who would wait 18 minutes to

start being checked out.

From a customer's perspective, the average customer checkout time is

greater, even though the cashier is still working at the same speed and is

able to push 10 people through the line in 20 minutes.

The checkout lane is saturated at the point when the rate at which new

customers getting into the lane exceeds the rate at which old customers

are being checked out.

In this last example, service levels start degrading when the customer

arrival rate to a lane becomes less than two minutes.

So the rate at which customers are getting in line and the number of lanes

which are open to counter the increase/decrease in rate makes all

the difference.

Queuing Scenarios

Solution to Reduce Cashier Downtime

Queuing requirements of a retail store will depend upon the

following factors:

• Customer arrival rate and the time of the day of arrival

(morning, afternoon, evening or weekends)

• Average shopping time per customer

• Variation in time duration for customer service time and

factors on which this variation occurs (type of goods bought

by the customer, type of transaction)

• Average number of lanes open in the store at any given time

and the rate change based on time of the day

In order to improve the performance of the store, queuing can be made

multi-threaded by adding more lanes based on the time of the day and the

day (weekend, holiday etc.) This concurrency will help in two ways:

Scenario A: Regular Flow of Customers Leading to Zero Cashier Downtimeand a Need to Open Register 6 to Meet Service Levels

The actors represent the customers. The color of the actors represents the queue they are in. Those customers who don’t have any color can move to any of the queues depending on the queue length.

POS Register 1(Closed)

POS Register 2(Open)

POS Register 3(Open)

POS Register 4(Open)

POS Register 5(Open)

POS Register 6(Closed)

Scenario B: Irregular flow of Customers Leading to Useless Cashier Downtime

The actors represent the customers. The color of the actors represents the queue they are in. Those customers who don’t have any color can move to any of the queues depending on the queue length.

POS Register 1(Closed)

POS Register 2(Open)

POS Register 3(Open)

POS Register 4(Open)

POS Register 5(Open)

POS Register 6(Closed)

Scenario C: Sparse Flow of Customers Leading to Useful Cashier Downtimeat Register 5

The actors represent the customers. The color of the actors represents the queue they are in. Those customers who don’t have any color can move to any of the queues depending on the queue length.

POS Register 1(Closed)

POS Register 2(Open)

POS Register 3(Open)

POS Register 4(Open)

POS Register 5(Open)

POS Register 6(Closed)

1. It will minimize the response time that each customer

experiences by reducing wait times in line

2. It will increase the number of transactions completed in a given

time period

Let's say there are 10 lanes and 10 customers that get to the checkout area

at the same time, each customer goes to a different lane, and each

checkout takes two minutes. Thus their will be absolutely no delay

between customer checkouts. But in this case, the number of cashiers has

increased to improve service level leading to higher payroll costs.

The solution to this issue is to analyze cashier downtime for a particular

duration of time for all times of the day with an assumption that any new

customer will try to get into a lane which will have the least waiting time i.e.

minimum length of the queue.

The next step would be to compare this downtime with the sales forecasts

for that particular store for the same time period. The breakup of the sales

forecast would have to be done for all hours of the day for all days of

the week.

The resulting comparison will illustrate that cashier downtime is inversely

proportional to the sales of the store and directly proportional to the

number of open lanes in the store.

Once we get the comparison we can deduce the number of cashiers

required in a store at a given point of time to provide a defined level of

service (1+0, 1+1, 1+2 etc.) and the acceptable level for

cashier downtime.

Once the retail chain sets a standard for acceptable cashier downtime it

can be monitored across all stores and brought to the defined standard.

For e.g.: If cashier downtime is more for a store from 12:00 PM to 3:00 PM

as compared to the sales; we need to reduce the number of cashiers in the

store at that time.

The table given below illustrates this concept:

Store X (A)

8:00 AM to 9:00 AM

9:00 AM to 10:00 AM

10:00 AM to 11:00 AM

11:00 AM to 12:00 PM

12:00 PM to 1:00 PM

1:00 PM to 2:00 PM

2:00 PM to 3:00 PM

3:00 PM to 4:00 PM

4:00 PM to 5:00 PM

5:00 PM to 6:00 PM

6:00 PM to 7:00 PM

7:00 PM to 8:00 PM

8:00 PM to 9:00 PM

9:00 PM to 10:00 PM

Sales

($) (B)

5000

7000

6000

10000

8000

2000

3000

3000

14000

9000

6000

4000

1000

1000

Average

Cashier Rate

($) / hour

(C)

8

8

8

8

8

8

8

8

8

8

8

8

8

8

No. of

Cashiers

(D)

8

8

16

20

20

16

16

16

20

12

12

12

8

8

Cashier

Cost ($) per

hour

(E) = (C)

* (D)

64

64

128

160

160

128

128

128

160

96

96

96

64

64

Cumulative

Cashier Downtime

per hour

(Hours) (F)

2

1

3

4

5

5

5

5

1

2

3

4

3

3

Cashier

Downtime

Cost ($) (G) =

(C) * (F)

16

8

24

32

40

40

40

40

8

16

24

32

24

24

Acceptable

Downtime

Cost ($) * (per

1000$ of

sales) (H)

1

Current Cost

($) per 1000$

of sales

(I) = (G) *

1000 / (B)

Cashier

Downtime

Cost reduction

opportunity ($)

(J)= (I) - (H)

3.20

1.14

4.00

3.20

5.00

20.00

13.33

13.33

0.57

1.78

4.00

8.00

24.00

24.00

2.20

0.14

3.00

2.20

4.00

19.00

12.33

12.3

-0.43

0.78

3.00

7.00

23.00

23.00

* At this cost the service level (1+0, 1+1, 1+2) as desired by the store is achieved.

Cashier Downtime Reduction

07

Metrics to Capture CashierDowntime & Productivity

Metrics Formula

∑ (Cashier Signoff - Cashier Login)

[Cashier Login

on a register, Cashier Sign off on that register] for all

intervals of a day for all registers logged in by the cashier

Cashier Productivity

percentage for a day

{

}

100 – [(Cashier Downtime for a day*) +

+

/

(Cashier

Login on a Register Time – Cashier Clock Punch-in

time) (Cashier Clock Punch-out Time – Cashier

Logoff on a Register Time) ∑ (Cashier Scheduled

End Time - Cashier Scheduled Start Time) -

[

]

(Cashier Scheduled Meal Time + Cashier

Scheduled Break Time) [Cashier Clock Punch In,

Cashier Clock Punch Out] *100]

Cashier Downtime

for a day*

∑

(Cashier Auto Logoff - Cashier Login)

for all intervals of a day for all registers logged in by the cashier

for all intervals of a

day for all registers logged in by the cashier

+ [Next Transaction Start Time – Previous

Transaction End Time]

∑ { if it is > X} [Cashier Login on a

register, Cashier Logoff on that register]

Where X is a threshold defined by the business

users

Examples to Illustrate Cashier Downtime & Productivity Metrics

The metrics can be illustrated by the following examples:

Total Hours worked by the Cashier for a day

= ∑ (10:30 AM – 8:30 AM) + (1:00 PM – 10:45 AM) +

(3:30 PM – 1:30 PM) + (4:30 PM – 3:45 PM)

= (120 + 135 + 120 + 45) / 60

= 7 hours

Cashier Downtime for a day

= (2:30 PM – 2:15 PM) + ∑ {[8:50 AM – 8:30 AM) + (9:20 AM – 9:00

AM) + (10:45 AM – 10:10 AM) + (12:27 PM – 11:51 AM) + (1:49 PM

– 1:21 PM) + (3:30 PM – 3:06 PM) + (3:59 PM – 3:33 PM)] if it is

> 20 minutes}

= {(15) + ∑ 20 + 20 + 25 + 36 + 28 + 24 + 26} / 60

= 3.23 hours

Cashier Productivity percentage for a day

= {100 – [(194) + (8:45 AM – 8:15 AM) + (4:45 PM – 4:30 PM) /

∑ [(4:45 PM – 8:15 AM) – (30 + 15 + 15)] *100]}

= {100 – [194 + 30 + 15 / ∑ [510 – (30 + 15 + 15)] *100]}

= {100 – [239 / 450] *100]}

= {100 – [239 / 450] *100]}

= 46.88 %

There are no definite studies which give the cost of cashier downtime as a

percentage of total store operational cost, however keeping the service

level high by loading the cost on to the cashiers is a common phenomenon

among discount, mass merchandizing, departmental and grocery retailers.

Defining metrics for computing cashier downtime will enable awareness of

productivity and guest wait opportunities i.e. service level of 1+0, 1+1,

1+2 etc.

This solution will enable immediate resolution to service level

performance and guest wait issues and the scores will motivate store team

members to improve their performance as well get training to enhance

their productivity.

Reduction of cashier downtime will also lead to improvement in cashier

productivity and could be used for generating progress reports,

recognition awards and mentoring store team members.

However zero cashier downtime is also not good as it implies that the

cashiers are busy all the time and there are guests waiting in line to be

serviced. So a balance has to be achieved to bring the downtime to a level

where it doesn’t affect the service levels.

Improving performance and guest shopping experience is a core function

of delivering exceptional guest service and reducing operational expenses

and cashier downtime reduction can lead to achievement of both.

Conclusion

Total Hours worked

by the Cashier for a

day

08

About the Author

About Wipro Technologies

Amit Dhall is a Consulting Manager in Retail Industry Advisory Group at Wipro Technologies. In this role, he is responsible for bringing thought leadership

and innovative solutions for Wipro's global retail clients. He has worked on various consulting assignments with US and European retailers in the areas of

Workforce Management, Store Solutions, Point of Sale, Supply Chain and Marketing Analytics. He can be reached at amit.dhall@wipro.com

Wipro Technologies, the global IT business of Wipro Limited (NYSE:WIT) is a leading Information Technology, Consulting and Outsourcing company, that

delivers solutions to enable its clients do business better. Wipro Technologies delivers winning business outcomes through its deep industry experience and a

360 degree view of “Business through Technology”– helping clients create successful and adaptive businesses. A company recognized globally for its

comprehensive portfolio of services, a practitioner’s approach to delivering innovation and an organization wide commitment to sustainability, Wipro

Technologies has 130,000 employees and clients across 54 countries. For more information, please visit www.wipro.com

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