Team 2:

Swati AdhauStephanie ChaissonMaura RizzutoEmily RoseEric SherBen Solomon

OM726 – Fall 2013

Optimizing Food Ordering/Serving Process at Viga

Agenda

Overview & Context Process Analysis Findings & Recommendations Predicting Impact after

Recommendations are Implemented Questions

OverviewAbout Viga: Family-run take-out &

catering business started in 1999, with 3 locations in Boston (our focus was on Stuart St. location in Back Bay)

Who are Viga’s Customers? Business professionals

stopping in on their lunch break who do not have a lot of time to wait in line (busy schedules)

304 Stuart Street, Boston

Goal & Competitive Advantage

Goal: “Provide a quality product

at a reasonable price with superior customer service…”

Competitive Advantage: Very fast service High-quality, fresh food Proximity to nearby

businesses

Layout of Viga (Stuart St. Location) Kitchen

Entrance/Exit

Sm

all

Counte

rCooler

for Cold

Salads and

Drinks

Large

Glass

Window

Large

Glass

Window

Cashier 1

Cashier 3

Silverware/

Napkins

Pizza/Calzones Pasta Hot

Sandwiches

Cold Sandwiches

Cashier 2

Existing Process Flow Diagram

Place and receive order

at Pasta station

Pay at Cash

Register

Place and receive order

at Hot Sandwich

station

Place and receive order

at Cold Sandwich

station

Place and receive order

at Pizza/ Calzone station

Exit

Pick up napkins/ silverwar

e

Queue

QueueDecision PointChoose Station

QueueGrab Chips, Drinks and Desserts

Queue

Queue

Queue

Queue

Queue

Queue

Queue

Observation

Our Goal: Find out ways in which Viga can improve its front-of-house

operations.

Our Questions: Are people abandoning the line, or avoiding Viga altogether due to

perceived wait time? Is Viga’s management utilizing its limited physical space in a way

that would allow for maximum capacity utilization? What type of technology might allow Viga to utilize its small space in

a more revenue-maximizing way?

Our Method: Explore Viga’s front-of-house process by observing/collecting data on

their daily operations at times of peak demand (12 – 1PM) throughout the week.

Observe volume of customers coming in and out (in 5 minute intervals) and customers’ throughput time during the hour.

Data collection• Date• Time of day• Throughput time• # customers in• # customers out• # customers abandoned

Date:• Sampled over six random

weekdays• Treated days equally

Throughput time:• Picked random customer• Tracked time from entry to exit

# customers:• The #in gave us the capacity• The #out gave us the cycle

time (#out/5min)• The #abandoned gave us

clues when there might be a problem

Time of day:• Took several observations around

lunchtime (12 – 1 PM)• Recorded data every five minutes

Station Task Times We attempted to measure individual task times for each station

Found it nearly impossible without interfering with their business (limited physical space)

We could easily conclude based on # of steps per station and station popularity, that the hot sandwich and pasta lines take the longest and cause the bottleneck.

1. Scoop 2. Add meat 3. Sprinkle cheese 4. Cover

5. Add sticker

1. Choose bread

2. Choose meat/fill

ing

3. Scoop sauce

4. Add cheese

5. Wrap/cl

ose sandwic

h

6. Package

7. Add sticker

1. Choose bread

2. Choose condiments

3. Choose meat/filling

4. Choose toppings

5. Wrap/close sandwich

6. Package 7. Add sticker

1. Put on plate

2. Put in bag

Hot Sandwich Station Tasks

Pasta Station Tasks

Cold Sandwich Station Tasks (often open and had two workers)…7 steps/2 workers = 3.5 steps per worker

Pizza Station Tasks

Discovering the problem

Hypothesis: high throughput times = long lines and abandonment1

1:4

5 A

M

12

:00

PM

12

:15

PM

12

:30

PM

12

:45

PM

1:0

0 P

M

1:1

5 P

M

00:0001:0002:0003:0004:0005:0006:0007:00

Time of entryThro

uhghput

dura

tion

(min

)

11

:45

AM

12

:00

PM

12

:15

PM

12

:30

PM

12

:45

PM

1:0

0 P

M

1:1

5 P

M

0

5

10

15

20

25

30

5-minute time periods

cycl

e t

ime

(seco

nds/

cust

om

er)

Higher throughput time from 12:30 to 12:45Abandonment can occur when > 5 minLines are likely out the door

Lower cycle time from 12:15 to 12:45Does not become less than 8 secAbandonment occurs when people are moving

What does this tell us?

Measuring success At cycle time = 8 seconds, capacity in five minutes = 37.5 customers CU = (60sec * 5min)/8sec CU = 300sec/8sec = 37.5

0%

20%

40%

60%

80%

100%

120%

140%

0% 5% 10%15% 20% 25%

Reduction in customers

Capaci

ty u

tiliza

tion

0

50

100

150

200

250

300

350

400

450

0% 5% 10%15% 20% 25%

Reduction in customersThro

ughput

tim

e (

sec)

Max CU at peak time = 123%Max CU < 100% if cust.reduction > %20Max CU goes from 123% to 98%Average CU becomes 60% from 76%

Max throughput at peak time = 6:22 (min:sec)Max throughput < 5 min if cust.reduction > 25%Max throughput goes from 6:22 to 4:51Average throughput becomes 2:42 from 3:38

This is our goal, but how do we get there?

Recommendations

Exit

Goal 1: To achieve shorter avg. throughput time, increased capacity and increased revenue

To Achieve Shorter Avg. Throughput

time, Increased

Revenue and Capacity

Build an online ordering platform to shift 25% of the

current in-store sales online

Utilize the large glass windows

behind the cash registers as literal takeout window.

Online orders can be prepared during the small periods of downtime they have throughout the peak lunch

time period.

Avg. throughput time can be reduced by

designating an employee to hand out paper menus, to help

customers decide their orders while in line.

Exit

Goal 2: To improve customer service

Improved Customer Service

Add a prepackaged

utensil set (fork, knife, spoon and

napkin) while bagging

customer’s order.

Install large signs above each food station to reduce

the confusion.

Light System for cashiers to

indicate their availability.

Designate an employee at the

door who can pass out paper menus to people in line.

Viga could re-order stations so that

items that customers are

likely to pair, are next to each other.

Recommendations

New Process Flow Diagram

Place and receive order

at Pasta station

Pay at Cash

Register

Place and receive order

at Hot Sandwich

station

Place and receive order

at Cold Sandwich

station

Place and receive order

at Pizza/ Calzone station

ExitQueue

Queue

Decision PointChoose Station

QueueGrab Chips, Drinks and Desserts

Queue

Queue

Queue

Queue

Queue

Queue

Queue

Start

In-Store or Online order?

Place Order Online

Show receipt and collect order from takeout window

Queue

Impact on the bottom-line• Online prepaid orders would

reduce the customers in store line by 25%

• Shorter in-store lines would decrease the rate of abandonment and attract new customers looking for faster service

• Increase in the number of customers served between the peak period of 12 – 1pm = 25%

• Current customers = 450 25% increase = 112.5 customers Avg order/customer = $7

• 25% Revenue increase/day = $787.5• 25% Revenue increase/month =

$15,750

Questions