1Ashish Khurana | Gunjan Solanki | Abhishek Singh | Akshay Sharma | Abhinav Pandey

Cash Counters Optimization

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Situation – Current State Desired Future State

Gap

Questions – which need answers

The Customer Service Manager of Big Bazaar wants to determine the optimal number of checkout counters in real time

Customer Service Manager of the Big Bazaar is responsible for planning the number of Frontline checkout counters to be opened in a real time scenario

He/She has observed that during peak time, less number of counters leads to customer dissatisfaction and during non-peak time, more number of counters leads to inefficient utilization of resource

He/She understands the factors that affect the traffic at the checkout counter

This has led him/her to successfully implement an automated system to identify the number of checkout counters

He/She has been able to achieve better customer satisfaction and efficient staff utilization

CSM needs to identify the parameters that determine the optimal number of checkout counters in real time

What are the factors that determine the arrival at checkout counters?

What are the factors that determine the exit from the checkout counters?

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Non Peak Time: Two counter are opened in spite of less crowd. Resource wastage

The Problem of Peak Time

Peak Time: Only one counter opened, too much rush

Customers: 3Counters: 2

Customers: 10Counter: 1

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The Science behind Waiting in Line

Customer Behaviour while waiting

Behaviour Synthesis Icon

Balking

Balking stands for abandoning planned purchases by customers before entering the check-out lines.

Reneging

Customers leave the queue if they have waited too long for service

Jockeying

Customers switch between queues if they think they will get served faster by so doing

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A Typical Queuing System Queue Length at cash

counter is dependent on :

Service time at counter Queue Arrival timeQueue Characteristics

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Survey 358 Customers

Types of sampling

Convenience Sampling

Systematic Sampling

1)Ambience Mall,Vasant Kunj,New Delhi-

110070

2) Community Centre,

Gafar Khan Marg,

New Delhi- 110070

3) Plot C-1,

Karol Baug,

New Delhi- 110005

4) Lake Market,Kalighar,Kolkata-700029

Findings of the Survey

70% customers done shopping in less than 1.5 hour

24% customers done shopping in less than 0.5 hours

45% customers buy less than 10 items

55% customers buy more than 10 items

Cost of Balking: After queue length has reached 4 ,1 person increase in the queue will make 18% of the consumer balk

Strong correlation (r=0.91) was observed between the number of items bought and checkout time

MaleFemale

18-3030-5050+

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Mathematical Modelling

Solutions for Current Queuing Problem

Short Term (Economical) Solution Long Term(Capital Intensive) Solutions

Self-Scanning “Tab Trolley”

Self Check-Out Counter

Mobile Check-Out

RFID Go-Through Scanning

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Mathematical Solution(Model-1)Data Driven Mathematical Modelling

Using analytics and taking data driven decisions

Model1:Lag-Excess Model

Key Highlights

Algorithm

Conclusion

1.Arrival Rate and service rate are determined for every 3 hour slot i.e. Total slots = 4 slot/day * 7 day = 28 slots

2.Queue Length was found out using M/M/s Queuing System

3.Queue length should not exceed 5 at any given time at any given counter as this would result in balking (Critical Number of Queue Length was chosen as “5”after surveying various customers ,store manager and team Brain-storming)

4. Critical number was put in the algorithm

Determine Queue Length based on Arrival Rate and Service Rate

If Queue Length < 5 If Queue Length > 5

• If Queue Length exceeded beyond 5

• Then, we need to open cash counters

• Then,λ (Mean arrival rate per counter ) decreases

• Queue Length decreases

• Resources are getting wasted • So, we need to close frontline

counters• Then,λ (Mean arrival rate per

counter increases• Queue Length increases

• Calculate lag of queue length at every counter

• Total Lag(L) = l1 + l2 + l3 + ...+ ln • New counters to be closed=

[Total Lag(L)] / 5

• Calculate excess of queue length at every counter

• Total excess(E)= e1 + e2 +..+ en

• New counters to open= [Total Excess(E)] / 5

Pros:1) Dynamic real time system2) This algorithm does not allow the queue length to go beyond the 5

customers

Cons:1)This model does not consider economic perspective. It is only

customer centric .So model-2 has to be developed which is both customer centric and organization centric

2) Critical number of 5 not valid for all big bazaar store

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Mathematical Solution(Model-2)Data Driven Mathematical Modelling

Using analytics and taking data driven decisions

Model 2:Economic Model

Introduction

Graph

1.2 factors play major role in determination of queue length:

(i)Arrival Rate (ii)Service Rate2.Total cost has 2 components (i)Operating Cost (ii)Waiting Cost

Total Cost=Operating Cost + Waiting Line Cost3. So at any point of time, Total cost should be minimum

More Counters: Less Waiting cost and high Operating costLess Counters: High Waiting cost and Low Operating cost

Objective

Determine optimum number of cash counters to maintain1. Reduced wait time.2. Optimal resource utilization

Terminology

Operating Cost:It include cost of operating the cash counter, labour involved and

labour to fix mechanical faults(if any)Waiting Line Cost:This cost has 2 components: Balking Cost and Reneging cost. It

refers to the cost of losing customers when customer decides not to join the queue or leaves the queue after joining it because of large waiting time

Waiting Line Cost=Balking Cost + Reneging Cost

 

Mathematical Model

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Mathematical Solution(Model-2)Data Driven Mathematical Modelling

Using analytics and taking data driven decisions

Model 2:Economic Model

Balking cost:It is the cost incurred to the organization when the customer don’t join the queue and leave the queue before joining it.

2 3 4 5 6 7 8 9 10 11 12 13 140%

20%

40%

60%

80%

100%f(x) = 0.147248598371433 exp( 0.169911248834359 x )

% of Balkers vs Queue Length

Queue Length

% of Balkers

Reneging cost:It is the cost incurred to the organization when the customer already in the queue leaves the queue before making the purchase.

Reneging Cost= (%of renegers )* (Queue Length)* 500 Rs

Operating cost:It include cost of operating the cash counter, labour

involved and labour to fix mechanical faults(if any)Operating Cost= 812n

Where n = numbers of counters 2 3 4 5 6 7 8 9 10 11 12 13 14 15 160%

25%50%75%

100%f(x) = 0.0457942155244307 exp( 0.233152186337464 x )

% of Renegers Vs. Waiting Time

Waiting Time

% of Renege Customers

3 4 5 6 7 8 9 100

5000

10000

15000

20000

25000Cost Model Analysis of Cash counter

Total Cost Operating Cost Waiting CostNumber of Counters

Cost (in Rs)

Total Cost

Waiting Cost

Operating Cost

For the given λ = 0.53 and mu=0.2,Total cost is minimum when 4 counters are opened

-Model consider both customer dissatisfaction as well as optimal resource utilization

-Real time and dynamic model

Multiple servers, Infini te population, Poisson arrival, FCFS, Exponential service time, Unlim ited waiting room

InputsUnit of tim e minArrival rate (l) 0.53 custom ers per minService rate (m) 0.2 custom ers per minNumber of identical servers (s) 8 servers

OutputsMean ti me betw een arrivals 1.887Mean ti me per service 5 minTraffic intensity 0.33125 min

Summary measuresAverage util ization rate of server 33.1%Average num ber of customer s waiting in l ine (nl ) #NAME? custom ersAverage num ber of customer s in system (ns) #NAME? custom ersAverage ti me waiting in line (tl ) #NAME? minAverage ti me in system (ts) #NAME? minProbabi lity of no custom ers in system (P0) #NAME? (this is the probabi lity of empty system)Probabi lity that a ll servers are busy #NAME? (this is also the "percentage w ho wait in queue")Probabi lity that at least one server is idle #NAME? (this is also the "percentage w ho don't w ait in queue")

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Futuristic Model-1Self-Scanning Trolley System

Customer scans the product through installed barcode scanner on the trolley

How it works

• Customer picks up items and adds them to the cart after scanning them on installed Bar-code scanner

• The updated items are displayed on the ‘Electronic Display’ on the trolley

• On the checkout counter, the unique trolley id is entered to fetch the details of the items added to the trolley

• The details of the trolley are synced with the computer at counter

• Payment can be done with cash, card or mobile wallets

• Installation of weight sensor will reduce eliminate of chance of theft or scanning mistake

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Futuristic Model-1 “Tab-Trolley”Cost benefit Analysis

Cost Benefits

Conclusion

• Cost of a 10” tablet/screen mounted on the trolley

• Barcode scanner to be used for scanning goods

• Mounting and installation of hardware on trolley

• Labour cost • Developing the application for the

screen/Tablet “Tab Trolley”• Back-end server required for supporting the

application• Maintenance of hardware and software

update• Aggregate cost of 550 million

• Scan items on the go. So no more waiting in long queues

• Better understanding of customers buying patterns and behaviour

• Product location map: Customer can search for an item on the Tab and find path to reach them

• Location triggered ads: Store can provide discounts and promotions as they trolley moves near the products

• Related products or suggested products

The cost of implementing the “Tab-trolley” across all 220 big bazaar stores is around Rs. 550 mn. The possible revenue increase will be around Rs. 8230 mn, with estimated break-even of around 1.5 years of the implementation

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Futuristic Model-2 Self-Checkout kioskSelf Checkout

Customer checkout himself using self-checkout kiosk

How it works

Benefit:1)Reduced Labour : 1 attendant for 4-5 kiosk 2)Takes less space3)High Speed and efficiency4)Form of Privacy

Conclusion

Limitations1.Cost of the self checkout kiosk is $250002. Potential for Theft3. Lack of Personal Interaction Lack of Personal Interaction

Scan the product at self checkout kiosk

Keep your products into balance

Invoice is issued and customer can remove the bag

Make payment using Card/Cash at self

checkout kiosk

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As per research conducted by IDC, an American market research, analysis and advisory firm,

Cost: 15,00,000 per self checkout counter

• Takes less space

• 1 attendant for 4-5 kiosks

• High speed and efficiency

• Form of privacy

• Fewer employees to pay

1. Lane light/ Store attendant call 2. Touch Screen Monitor3. Basket Stand 4. Barcode Scanner cum weighing

scale5. Payment module 6. ATM PIN pad

1. Cost of the self checkout kiosk is $25000

2. Potential for Theft3. Lack of Personal Interaction

Limitations

Cost Benefits

0

20

40

60% of Respondents

% of Respondents

Futuristic Model-2 Self-Checkout kiosk

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Futuristic Model-3 Mobile Checkout

Using Smartphone to checkout smoothly

How it works

1. Use Mobile App to scan your credit/debit card

2. Use Mobile App to scan and add items to cart, and then visit the checkout counter

3. Enter a previously stored passcode and scan a QR code at checkout kiosk

4. Pay at the counter to complete the payment process

5. Counter maps an attendant to that order who receives a list of items to check for in the shopper’s cart

Benefits:1)Fast and easy Checkout2)Reduced Queuing Problem3)Reduced Costs4)More Retail Space

Conclusion

Limitations:1)Apprehensions among ‘not so tech savvy customers2)Increased chances of shoplifting3)Difficult process for items that need to be weighed

Scan Credit Card Scan Product

Scan QR Code at checkout and pay

Attendant checks and gives approval

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Futuristic Model-3 “Smartphone Checkout”Cost benefit Analysis

Cost Benefits

Conclusion

• Cost of developing the app capable of scanning barcodes

• Cost of installing smartphone checkout kiosks in the store

• Back-end server required for supporting the application

• Maintenance of hardware and software update

• Aggregate cost of 184 million

• Reduced queuing problem at the checkout counter

• Easier and faster checkout• More power to consumers• Lowe operational costs as the traditional

counters will be lesser in number decreasing the number of staff required to man them

• More front-of-the-store real estate can be used for product display

The cost of implementing the “Tab-trolley” across all 220 big bazaar stores is around Rs. 184 mn. The possible revenue increase will be around Rs. 8230 mn, with estimated break-even of around 0.9 years of the implementation

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Futuristic Model-4RFID “Go Thru” Scanning Checkout

Using RFID(Radio Frequency Identification Techology) to completely eliminate scanning

How it works

1. A person adds the items to the trolley

2. The trolley is then passed through RFID scanners at the checkout counter

3. The scanner reads the code on the tags present at every item in the trolley

4. The total items are billed at the counter from the information received from the scanned codes

5. The user checks out by paying the billed amount at the counter

Benefits:1)Super Fast as it completely eliminates scanning process by

customer as well as operator 2)No Self-kiosk is involved. So less space consumption3)Man power reduced to greatest extent

Conclusion

Limitations:1)RFID system is very costly2)Increased chances of shoplifting

RFID Scanners

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Futuristic Model-4 “RFID Go-Thru”Cost benefit Analysis

Cost Benefits

Conclusion

• Cost of replacing barcode with RFID tags• RFID Reader/Scanner for scanning the

items in the trolley• Mounting and installation of hardware• Labour cost • Developing the software and programming

the controller• Back-end server required for supporting the

application• Maintenance of hardware and software

update• Aggregate cost of 300 million

• Scan all the items at one go, eliminating the possibility of long queues

• No more waiting in long queues or wasting time in scanning the items one by one

• Easy to operate even for people with minimal exposure to technology

• Manpower reduction• Longer durability of the hardware in

comparison to the barcode scanning checkout counters

The cost of implementing the “RFID Go-Thru Scanning Checkout Counter” across all 220 big bazaar stores is around Rs. 300 mn. The possible revenue increase will be around Rs. 8230 mn, with estimated break-even of around 1.45 years

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