PRESENTATION

TITLE

© 2017 MHI® Copyright claimed for audiovisual works and sound recordings of seminar sessions. All rights reserved.

Presented by:

Blair Labatt III, R&D Director

Alfonso Acosta, System Architect

Achieving

Maximum Levels

of Safety &

Productivity

Agenda

• Company and Project Overview

• Operations Strategy

• Opportunity

• Enter the Interns

• Conclusion

Labatt Overview

Company History

1910 1940

2010

2014

1980

T.W. Labatt opened the Collins Company.

T.W. Labatt opened Labatt Wholesale Grocery Company with sons Weir & Blair Sr. Company named the

authorized distributor for the HemisFair. Event prompted the formation of Labatt Institutional Supply Company, known today as Labatt Food Service. Blair Labatt Jr.

asked to lead the company. $8 million in annual sales.

Distribution changed to focus exclusively on food-away-from-home operators.

1989 The company opened a second warehouse in Dallas.

Introduced the use of Voice Technology to increase operational efficiencies.

2005 Labatt opened its third warehouse in Lubbock.

2007 Labatt opened its fourth distribution center in Houston.

2009 Labatt acquired Zanios Foods in Albuquerque, NM.

Labatt celebrated 100 years in the food industry.

2013 Labatt developed Native American Beef.

1968

2002

1984

2013 Over $1 Billion in annual sales.

1940 - 1984 Labatt Wholesale Grocery Co.

1910 Collins Co.

Innovation Timeline

IT Timeline

2008 2012 2004 2014

Helpdesk

Analyst Department

Agile Project Management

Business Leads

Fire Team

Topgrading

Governance & Policies

2006

Unplanned Work

2016 2010 2018

Continuous Deployment

On- Strategy

Continuous Integration

Automated Deploy

Peer Code Review

Micro- services

Legacy Team

Version Control

Bug Tracking

Internal Cloud / PaaS

IT Timeline

Check Digit Batch Number

Strategy

Voice Technology

200 Voice Technology

99.99%

First in the Industry

Pre Radio

Frequency

1996 %

With Radio

Frequency

FY 2002 %

With Voice

Technology

May 2003-Apr.

2004 % Oct-13 %

Shorts 76,564 0.82% 22,073 0.14% 6,016 0.03% 5,123 0.02%

Mispulls 63,608 0.68% 22,592 0.14% 4,248 0.02% 4,725 0.02%

Damages 30,788 0.33% 5,881 0.04% 4,407 0.02% 3,265 0.01%

Total Credits 170,960 1.84% 50,546 0.31% 14,671 0.07% 13,113 0.05%

Total Cases Shipped 9,297,955 16,228,685 20,038,844 26,468,317

Errors/10,000 Cases 184 31.1 7.3 5.0

99.95%October OPSL:

5 Errors per 10,000 Cases

Jan-15

January

KPI: Error Rate

KPI: Selector Throughput

Opportunity

Old System

Qualitative Assessment

Misvoices

Last Name First Name Position Total Picks Invalid Check Digits Invalid Check Percentage

MARTINEZ JORDAN C NIGHT FRZ SELECTOR 12904 4897 37.95%

GARCIA JR JESUS NIGHT DRY SELECTOR 6739 2525 37.47%

LONGORIA III MANUEL Y NIGHT FRZ SELECTOR 70022 24901 35.56%

ESPINOZA BENJAMIN E NIGHT DRY SELECTOR 9217 3211 34.84%

RODRIGUEZ ANDREW NIGHT FRZ SELECTOR 8620 2950 34.22%

SAENZ JR ANTONIO NIGHT FRZ PALLETIZER 51292 17315 33.76%

GAMBOA-MOJARRO DIEGO NIGHT DRY SELECTOR 12896 4087 31.69%

PRECIADO DANIEL NIGHT FRZ SELECTOR 78056 24460 31.34%

MURRAY COREY T NIGHT DRY SELECTOR 63286 19717 31.16%

LUNA ARTURO NIGHT DRY SELECTOR 5020 1390 27.69%

ANDRADE MONTOYA CESAR A NIGHT DRY SELECTOR 82759 22348 27.00%

MEDINA MARK ANTHONY NIGHT FRZ SELECTOR 12999 3433 26.41%

PEREZ FABIAN NIGHT DRY SELECTOR 6291 1627 25.86%

MALDONADODELEON ARCADIO NIGHT FRZ SELECTOR 48417 12455 25.72%

PEREZ CARLOS INES NIGHT DRY SELECTOR 37250 9296 24.96%

Re-trainings

Enter the Interns

System Architecture

AS 400Batch

Employee InfoInventory Info

Voxware ServerUser Profiles

Voice UnitChallenger

Unit

Challenger ServerUser Profiles

Vo

ice

Sig

n o

n

Use

r L

og

in fo

r P

ick

ing

Use

r Vo

ice

File

Do

wn

loa

de

d fo

r Pic

kin

g

Request Batch

Receive Batch

Batch ResultsBatch Results

Receive Batch

Request Batch

Unknown

Communication

Feasibility Study (St. Mary’s)

Implementation (Rice)

Conclusion

Product Comparison Voxware Vocollect

Unit ● Bulky

● Worn around the waist

● Lightweight

● Wireless

● Could be placed on the

tugger

● Model A730 had a built in

scanner

Headset ● Wired

● Sponge caused problems in

freezer

● Wireless – Bluetooth

● Microphone piece was

interchangeable with multiple

headsets

● Two additional microphones

cancel background noise

Battery ● Old and deteriorating ● Could last a whole shift

Voice Training

● Took 45-60 minutes to train

● Selector must also train logon

phrase

● Advanced training for specific

digits

● Took 30-40 minutes to train

● Continuously improved voice

recognition

User Login

● Selector repeated logon phrase

twice

● Could take several minutes if

unit does not understand

selector

● Selector used buttons on unit

to choose their name

Takeaways

• Don’t be “penny-wise pound foolish” … if you can’t make the

numbers what you want, consider the subjective factors too.

• Don’t expect “set it and forget it” even if you favor “buy vs

build” … Labatt operates with a continuous improvement

mentality, which is why we did this project in the first place.

• Have good industrial engineers on staff … for your own sanity,

they’re an extension of the executive him/herself, Drucker’s

“knowledge worker”

For More Information:

blabattiii@labattfood.com

aacosta@labattfood.com

www.vocollectvoice.com

www.labattfood.com

Or visit ProMat Booth S3974