10A WEGLEITNER RICKETTS Driving Supply Chain Performance

LOGISTICS 2009•February 8-11, 2009 ∙ Gaylord Texan ∙ Dallas, Texas

Steve WegleitnerDirector, Vendor Operations – Target Corporation

Ian RickettsDirector, Operational Excellence – Unilever US

Leveraging Fact-Based Decision Making for Continuous Improvement

Driving Supply Chain Performance

“Let’s work the problem people.Let’s not make things worse by guessing.”

Gene Kranz Apollo 13 Flight Director

• DMAI2C Approach• CAPDo Approach• Key Phases

— Objectives

— Methodology/Tools/Concepts

• ASN Match Improvement Project• Results• Key Messages

Agenda

DMAI2C is all about measurement , facts, and improv ements

DEFINE

¤ What is the scope of the problem?

MEASURE

¤ How big is the opportunity?

ANALYZE

¤What are the root causes of the problem?

¤What changes will eliminate the sources of the problem?

CONTROL

¤What is the plan to ensure the problem does not return?

IMPROVE / INNOVATE

Target – 6SIGMA Approach

4. Grasp the actual situation(Phenomenon)

3. Understand the Process &

Equipment

CCHECK2. Select and

Justify the Subject

1. Identify the Losses

12 Step Kaizen Method

8. Propose Counter

Measures7. Perform Root Cause Analysis

PPLAN

10. Verify the Results

9. Carry OutCounter-measures

DoIMPLEMENT

6. Make a Work Plan

5. Establish the objectives

ANALYZE

A

Were Objectives Obtained?

11. Standardize the Improvement

Begin aNew Cycle

Yes

12. Define Future Plans

Kaizen Charter

No

Unilever – CAPDo ApproachDocument Benefits

Key Phases

Define Scope

Data Collection

Determine Root Cause

Innovate Alternative Solutions

Drive Sustainability

Charter

A

P

Do

D

M

A

I2

C

C

ASN Match Improvement Project

Phenomenon: Unilever is not consistently compliant with Target 95% ASN match requirement

Key Phases

Data Collection




Objectives of this phase:

1. Identify specific problem / opportunity and cost

2. Identify current process

3. Identify customer requirements

4. Identify deliverables

Define Scope

Goal Statement

Problem Statement

Scope

Problem / Opportunity and Cost

S M A R TSpecific Measurable Attainable Relevant Time Bound

What WhoWhenWhere Which How

5 W 1 H

Product or Service Impacted: Target ASN Match Rate EDI 856

Business Unit: Customer Supply Chain

Project Manager: Merle Oelke Phone Number Project Champion:

Ian Ricketts Expected Project Savings $

Start Date: 04-16-2008 Target Completion Date

Element Description Team Charter

1. Process in which opportunity exists.

Target’s Unique Shipment Receipt Scheduling Processes

Unilever and its 3rd Parties are not consistently meeting Target’s Vendor Requirements for advance shipping notices to accommodate Target shipment receiving processes.

2. Project Description Eliminate defects in processes contributing to the Target defined and measured “ASN Match Rate”

Improve process reliability to achieve an adjusted match rate that qualifies Unilever for Vendor Certification (currently 95%, 3 mo. Ave.)

3. Objective:

Achieve Vendor Certification at Target by exceeding requirements (currently a 3 month 95% match rate)

Project Y’s

Baseline GOAL Entitlement units

4. Measurable variable(s) The “Statistical Problem”

Target-measured ASN Match Rate Metric 1 %

5. COPQ Cost of Poor Quality

$0.50 per case on non-compliant PO’s. Annualized non-compliance penalties (based on last quarter of 2007) of $537,000 deducted from Trade Funds

Metric 2 $/A

$.04 per case for Target if they fail to qualify for LEAP savings

Metric 3 units/A

6. Business Cases: Expected financial improvement

or other justification.

Unrealized LEAP supply chain efficiencies & Reduced Trade Funds stunt growth opportunities and impair competitiveness Qualifies more Unilever shipments for ART unloading.

Primary Metrics: ASN Match Rates for HPC, Slim Fast, and Foods Secondary Metrics: Not increasing work-around, manual processes in lieu of automated processes.

7. Team members & Roles:

Merle Oelke, Mark Matthews, David Piehl, John Sandusky, Shruti Sinha, Suzanne Pascarelli, Hillary Schiff, Julie Pierce, Jessica Grippo

Customer Supply Chain Customer Support & Data Mining Transportation & Distribution e Business, Supply Chain IT

6. Project Scope: In scope & out of scope

Out of Scope Non-Target ASN’s; Analysis of Unilever EDI/ASN HPC model Target Processes, ART barcode

In Scope: 3PL delivery of 856, Analysis of carrier processes, inconsistencies in the processes, scorecard failure reasons for all Unilever businesses, 3rd party processes, proximity timing

7. Benefit to External Customers:

(Who are the final customers, what are their key measures, and what benefits will they see?

1. Sub-optimal POS due to supply chain inefficiencies created at Target DC’s 2. Improved Cost of Goods Sold by qualifying for LEAP 3. Increased availability of trade funds that would otherwise be used to pay ASN fines

8. Schedule: Give the key milestones/dates.

Project Start April 21, 2008

9. Support Required: Will any special capabilities, hardware, trials, etc be needed?

Charter

Scope

Current ProcessBOSCARD

D

Deliverables

R

Risks

A

Assumptions

C

Constraints

S

Scope

O

Objective

B

Background

BOSCARD

Charter

ASN

Vendor

HeadquartersDC

Carrier

Logistics Inbound

Vendor

Transportation

OperationsDistributionOperations

Scope

Customer RequirementsRelationship Map

Scope

DeliverablesVoice Of Customer

• Potential for sub-optimal POS due to supply chain inefficiencies created at Target DC’s when ASN’s fail.

• Improved Cost of Goods Sold by qualifying for Unilever efficiency incentives.

• Gain visibility / understanding of currentASN match

• Identify potential avenues to increase ASN match score

External

Internal

Key Phases

Define Scope

Data Collection





1. Identify what to measureand why

2. Determine data plan

3. Gather baseline data

Data Collection

What to Measure and WhyCause & Effect

ASN MatchFailure

Process

Process

Product

Place

Product

Process

People

MC&BA's

Picking/LoadingErrors

Whs Overages

CPU

Dr ivers

IT

Dispatchers

Carr iers

Manual overr ide

Whs Overages

Target Pre-sched

carr ie rs/scheduling

Tra ining

RTS"BOL #

856 setubp by3PL"item setup

Multiple POTrucks"BOLFormat

LTL Timing

Proximity DC's

Tgt DC's

Reg DC's

3PL DC's

Par tial PO ListProv

Unscannable DC

BOLby DC

Fedex

masterbil ling

CPU

856 Timing"PGITiming"3pl set-up of 856

latePOchg

860Process

POL I temSetup"receiptagnst bad PO

MDG Item Setup

Cause-and-Effect / Fishbone Diagram

Partners on line (POL) Target

SAPUnilever

Excel data files

Validate (Target)

Validate (Unilever DC)

Validate(Carriers)

Data Collection

Data PlanCollaborate and collate

Collaborat ionDrill down into Target

systems

Data Collection

Baseline DataProcess Map

Key Phases

Define Scope

Data Collection


Innovate alternative solutions

Drive sustainability


1. Identify causal relationships

2. Determine primary drivers

ASN Match rate is not high enough

Failure at 3rd party DC

ASN Never Arrived

Creation time of appointment

Other than midnight or 17:00

#4 Why?

Failure / error at Target DC Bill Of Lading Error

Late ASN

System downtime

Midnight or 17:00, PRD

Some DCs are pre-scheduling loads

Some DCs require training

Root Cause

Causal Relationships5 Why

#3 Why?

#2 Why?

#5 Why?

#1 Why?

Root Cause

Causal RelationshipsCause / Effect

ASN MatchFailure

Process

Process

Product

Place

Product

Process

People

MC&BA's

Picking/LoadingErrors

Whs Overages

CPU

Drivers

IT

Dispatchers

Carriers

Manual override

Whs Overages

Target Pre-sched

carriers/scheduling

Training

RTS"BOL #

856 setubp by3PL"item setup

Multiple POTrucks"BOLFormat

LTL Timing

Proximity DC's

Tgt DC's

Reg DC's

3PL DC's

Partial PO ListProv

Unscannable DC

BOLby DC

Fedex

masterbi ll ing

CPU

856 Timing"PGITiming"3pl set-up of 856

latePOchg

860Process

POL ItemSetup"receiptagnst bad PO

MDG Item Setup

Cause-and-Effect / Fishbone Diagram

Loss Tree

ASN Match failure

Invalid BOL30%

Carrier sending Invalid BOL

51%

Warehouse sending Incorrect BOL

35%

Multiple ShipmentsFor 1 PO

3%

Backhaul Carrier Sending Incorrect

BOL6%

Late37%

Target DC “Pre-scheduling”

Appointments91%

EDI 856 Sent Late9%

Unscheduled17%

Never arrived16%

Root Cause

Causal Relationships

# of POs 239 198 178 130 2162063 941 545 498 466 454 297 295Percent 4 3 3 2 332 14 8 8 7 7 5 5Cum % 89 92 95 97 10032 46 54 62 69 76 81 85

SCACOthe

rCar

MCa

r KCa

r LCa

r JCar

FCa

r E

Cons

BCa

r DCa

r CCa

r BCar

A

Cons A

7000

6000

5000

4000

3000

2000

1000

0

100

80

60

40

20

0

# o

f PO

s

Perc

ent

Unscheduled SCAC Breakdown

Root Cause

Primary DriversData Display

Vendor A

0

50

100

150

200

250

0 - 50 50 - 100 100 -150

150 -200

200 -300

300 -400

400 -500

500 -600

600 -700

700 -800

800 -900

900 -1000

1000 +

Distance Range

# of

PO

s Auto MatchedLateTotal

Root Cause


Target

0

10

20

30

40

50

60

70

80

551

552

553

554

555

556

557

558

559

560

578

579

580

587

588

589

590

593

594

3801

3802

3803

3804

3806

3808

3809

DC

Auto MatchLateTotal

Root Cause


Root Cause

Primary DriversBox Plot

10

100

80

60

40

20

0

VICS

EDI

856

Mat

ch

Boxplot of EDI 856 Match

Key Phases

Define scope, problem, and goal

Data Collection




1. Evaluate possible solutions

2. Select best solution


Invalid Errors - Unilever Carriers

• Specific carriers andUnilever DCs impacting invalidBOL identified

• Counter-measures plan developed

Late Errors - Target

• Specific Target DCs identified

• Action plan developed collaboratively

Invalid BOL30% of total

Late37% of total

Carrier BOL51%

Warehouse BOL35%

Target DC Pre-Schedul ing

91%Prioritize

Loss Tree Analysis results

Alternative Solutions

Possible SolutionsLoss Tree

Prioritize

Alternative Solutions

Best SolutionFiltering Matrix

IMPACT/BENEFIT

EFF

OR

TH

igh

High

Low

Low10 2 43 5 6

1

2

3

4

7

SOLUTION FILTERING MATRIX

Key Phases

Define scope, problem, and goal

Data Collection


Innovate Alternative SolutionsObjectives of this phase:

1. Institutionalize improvement

2. Implement ongoing monitoring


Sustainability

Institutionalize ImprovementImplementation

Executed controllable actions

Invalid Errors –Unilever DCs & Carri ers

• Training packets for Carriers and DCs

• Plan to address labor churn

• Progress tracked weekly. Repeated errors were quickly identified and addressed

Late Errors - Target• Training delivered for DC employees

• Pre-scheduling was eliminated

• Plan to address labor churn

• Progress tracked. Issues addressed

Monitor, replicate, celebrate, continue to improve

Prioritize, Plan…TAKE ACTION (Do)

Sustainability

Ongoing MonitoringVisual Controls

Start of joint collaboration

Unilever Revised Scores 2008-07 2008-08 2008-09 2008-10 2008-11 2008-12

Revised PO Appointments 1,950 1,768 2,281 2,006 1,574 2,238ASN Matched POs 1,845 1,662 2,090 1,944 1,540 2,126ASN Match % 94.6% 94.0% 91.6% 96.9% 97.8% 95.0%

30405060708090

100110

AS

N M

atch

Rat

e %

2007 - 2008

Unilever ASN Match Rate at Target 2007 - 2008

Goal

HPC

Foods

The Value of Collaboration – Tangible results

• FI team kick off

Results

Define Scope

Data Collection




Voice of Customer

Pareto Chart

Process Map

6 Hats

Solution Selection

Filtering MatrixData Collection Plan

Potential Root Cause DiagramControl Plan

Fishbone

PilotRelationship Map

Data DisplayVisual Controls

Box Plots

5 Why

Loss TreeRun / Trend Chart

BOSCARD

Goal Statement

Problem Statement

S.M.A.R.T.

Key Messages

Toolkit

• Apply Resources where Needed

• Listen to Stakeholder(s)

• Laser Focus

• Open Minded / Curiosity

• Ownership / Alignment of Multiple PlayersAcross Supply Chain

Key Messages

Enablers of Success

Partnership

Common Objectives

Trust and transparency

TrueInnovation

1 + 1 = 3Synergy1 + 1 = 3Synergy

Key Messages

Value of Collaboration

Questions

10A WEGLEITNER RICKETTS Driving Supply Chain Performance

Documents

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