measure data quality

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Case Study: Utilize Quantitative Standards and Metrics to Measure Data Quality Initiatives: A Real-World Case Study from Delphi

Jose ZavalaDelphi

22

In This Session ...

• Reveal the magnitude and complexity of data required to satisfy Generation C (consumers) demand

Build a map with these interacting business elementsQuantify effects of these elements to the auto industry

• Find the value in creating a strong, yet simple data strategy (simplify)

• Review a model of a dynamic query creator (rule of thumb) to easily create/expand logical tests applied to your static dataset (Material Master Records)

Build from this model into other dynamic data elements (effectiveness metrics)

• Extend this approach with closed-loop cycles monitoring the bottom line (cash flow/inventories)

33

What We’ll Cover …

• Establishing and tracking metrics for data quality initiatives• Understanding how to build your own Information Quality Index• Browsing the Sigma levels of information quality• Monitoring and enhancing the business processes• Wrap-up

4

Generation C (Consumers): Aggressive Demand

Connected

ControlCash

Community

Creative

e-CommerceCustomized

Content

Consumer 2.0 Channel

Communicated

Conversation

Challenged

Charming

5

Order-To-Cash

SpeedQuality

Price?

Consumer Touch Points and the Information Flows

Blogs

Movies

Gaming

Research

Social

Music

Shopping

Peoples’ needs and desires are easily captured with current technology

Products are engineered, manufactured, and delivered fast!

Mass-Customization

FACT:

6

Example: Buying a New Car

DATABUSINESSELEMENTS

SizeColorSpeed

Technology

BrandPriceSound

SeatsTransmission

Engine

Headlights

Safe

Doors

SunroofEconomy

Reliable

Multiple CDDVDClass

Class

ServiceFinance

Value

Sharp

ResistantPower

Shape

That generates

But OEMs offer all these choices

Products are engineered, manufactured, and delivered faster!

… When supported with good data

We want this ...

7

Magnitude and Complexity of Data Required

Lead FreeUS SEC EU Canada

Electronics & Safety

Packard Electrical/Electronic Architecture

Powertrain Systems

Steering

Thermal Systems

Product & Service Solutions

Delphi Divisions

Laws and Regulations

Currencies and Markets Modular Products

8

Magnitude and Complexity of Data Required: Material Masters

NA MaterialMaster Recs:

165,000+116 fields

EU MaterialMaster Recs:

237,000+84 fields

AP MaterialMaster Recs:

237,000+87 fields

1.99 M

1.91 M 2.06 M

Combined Material Masters/Fields = 5.96 million

Delphi Packard

9

The Power to Simplify: Material Masters Quality Aspect

• Each intersection (data element) could be:Missing or lateInaccurate

SalesEngineeringPurchasingFinanceProd ControlLogistics

MATERIALS

ATTRIBUTES (fields)

5.96 Million Material Masters/Fields = Error Opportunities

Delphi Packard

1010



11

SAP Data Architecture

• So, how do you check for a data element that is:Missing or late?Inaccurate?

• If data is created/maintained by Sales, Engineering, Purchasing,Finance, Product Control, or Logistics …

… Then how do you measure its quality?

12

SAP Data Architecture (cont.)

• SAP has a well structured set of inter-related tables to minimize size of storage as well as to improve response time

• Realizing that we are building a data quality index and because size of data files are not a restriction, we can proceed to “fill in the blanks” and create a data matrix with key data elements

Unfold!

MARA MARC

VBKE

SalesVBEP VBKD

VBPA VBAP

VBSS

VBRK

VBRP

VBEH

VBFA

VBUK

VBLB

VBBE

EKPO

PurchEKET EORD

EKNN MKPF

MSEG

MVER

SO31

SO11

SO12

EINE

T161T

EKKO

MLAN

FICOPAYR BSAK

BKPF BSIS

BSAS

KNC1

LFC1

BVOR

BSAD

BSID

BSIP

BSIK

CRCA

PlanCRHS KAKT

CRID KAPA

KAPE

KAZY

T024C

CRCO

CRHD

CRHH

CRTX

KAKO

MAST

EngPLPO AFPO

AFKO MARM

MAKT

MVER

T001W

STKO

STPO

MAPL

PLKO

PLSO

MARA

SystemT100 T024

TAPLT AOQD

ADRP

ADR2

ADCP

T006

T247

T777A

T005

T023

MARA

SystemT069 T437L

T161F T134T

T001L

T024D

T157H

T16OQ

T160R

T160W

TLGR

T604

13

SAP Data Architecture and the QuickViewer SQVI Tool

• Off-the-shelf SAP contains over 100 data fields as part of master data records in multiple views

• First, identify data fields as part of the master data record of interest• Then, define ownership for data creation and maintenance

14

Four Steps to Extract Data for the Information Quality Index

1: Join Definition 2: Field Selection

4: Validate Results 3: Save/Test

1

2

3

4

15

Step 1: Join Definition

• Using QuickViewer — SQVIKeep table joins simple, as this will drive your processing timeField selection should consider current and future functionality

16

Step 2: Field Selection

• Select data fields of interest — SQVI• Data will be generated in the same order• Selection fields are part of interface screen created, if

run with transaction START_REPORT

17

Step 2: Field Selection (cont.)

• Create All Queries According to Areas of Interest — SQVIUse consistent query names according to the nature of the projectDo not bring unnecessary data fields to the model

18

Step 3: Save/Test

• Generate programs and get report names — SQVITest queries using transaction START_REPORTThese queries can also be used to validate data

19

Step 4: Validate Results

• Schedule a download job (t-code SM37)Add all queries to the download job as stepsConsider execution times to avoid system overloads

20

Step 4: Validate Results (cont.)

• Schedule a download job (t-code SM37)Daily analysis seems to be a good choiceData needs to be fixed, but most important is to enhancethe business processes as well

21


• Get to your spool list and export items as text (t-code SP02)Queries over empty data tables result in no spool outputDownload to user SAPGUI folder for conversion and upload to SQL

Once files are downloaded to your local drive, user should get an SAP notification

22


• Find your items in the SAPWorkDir folder using Windows Explorer

Make sure the file size is manageableDownloaded jobs can be directed to other users when scheduled

23


• Complete the validation process (text editor)This is a standard output when the spool item is “Export as Text”Use the tool of your choice to upload to SQL

24


• Upload the files to the SQL Server (MS-SQL)Data fields should be uploaded in the same sequenceThere should be one table for each query created

25

A Self-Sufficient Data Analysis System Algorithm

Truncate existing data MM tables + Results

Reload MM tables from SAPGUI

Open Audit Rules Table

Initiate variablesRow = 0

Row = Row + 1Read AuditRule Row #

End of fileAudit Rules?

Build New SQLStatement/Query

Select Table calledin Audit Rules

Apply Audit RulesScope (filter records)

Apply SQL Commandunder Rule to Field

End of TargetTable found?

Segregate non-complaintdata to AuditResults

NoYes

END

No

START

Yes

SP02SM37SM36SQVI

BrowsingExceptionsReport(AuditResults)

Tag each record with Client, RegionBusiness Unit & Plant

SAP

Microsoft Internet Explorer

26

Daily Refresh of Data Loaded to SQL Engine

• Preparing SAP download jobsOnce target tables and data fieldsare identified, jobs are scheduled to run at 1:00 AM EST Monday through FridayA Master Data Engineer (MDE) gets them into their SAP account

• Retrieving data from SAP to bring to a local system

Files are then downloaded as text to a local PCInformation is not structured at this time

• Uploading data to the SQL Server from a local system

Files are uploaded directly to the SQL Server from the production environment

27

Rules of Thumb (ROT) Examples

28

Additional ROT System Tables (Part of the SQL Model)

• MMPlantPBU tableHelps classify each record by Plant and Business UnitPlant (key), Business Unit, Plant Description, Master Data Manager (coordinator)

• MMAuditSummaryHeaderKeeps daily audit resultsClient, Region, Business Unit, Audit Fields, Total Records, RunDate & Plant

• MMAuditSummaryItemProvides count and links for non-conforming records by ruleRuleNumber, ErrorMessageExplanation, ErrorLevel, Owner, Client, Region, Business Unit, Errors, RunDate, Plant

2929



3030

Rules of Thumb: Browsing the AuditResults Records

Selectinga Target Dataset

Date/time stamp

Name of Business Process Owners (BPOs) and Total Rules created by them

MMs records audited

Total fields audited

MM Recs X Fields

Total exceptions found

PPM calculation

% deviations

% compliance to ROT

Info Quality Sigma Level

Errors per BPO area

Exporting Formats Continuous Improvement Model

Navigation

Zoom

Search

Report Name

31

Rules of Thumb: Browsing the AuditResults Records (cont.)

• Non-conforming data to ROT are presented by business unit (PBU) or plant level, following a standard set of information

32

Data Views Available — Following the Rules of Thumb

• When users are browsing non-conforming records, they can target a given client, region, and business unit data set

• Specific Rules of Thumb (logical conditions) are established or approved by the business process owners part of a business unit

Then they are put together in SQL Server language syntax by Master Data Engineers

• The list of non-conforming records looks like this:

33

Multiple Formats Available When Exporting Records

• The SQL Server Reporting Service contains a set of standard formats

End users can manipulate data after non-conforming records are identified

34

Benefits of the Reporting Services

• Quick access to informationFind any existing value

By ruleBy plantEtc.

• Exporting formats availableMost common formats are availableHelps processing errorsFacilitate Error Analysis such as:

Counts, average, etc.

35

Benefits of the Reporting Services (cont.)• Data is available for massive updates (t-code MM17)

Target Material Masters are copied tothe clipboard and provided to MM17MM17 can change up to 800+ recordsat one timeTables and fields are identifiedUpdate is done in just a few stepsProcessing time is minimized

36

Describing the Global ROT System

• Benchmarking is made possible by networking among Master Data managersWithin each regionWithin each business unitAt different levels of deployment phase(QN4 environment)Comparing:

Error LevelLogical statementScopeApplicabilityCustomized values

PN1 AP DCS 005-00 E [RefPackingMaterial] != 'REFPACK' [MaterialType] = 'HALB' AND [ProcType] ='E' AND [BUOM]='PC' ActivePN1 AP DEEDS 005-00 E [RefPackingMaterial] != 'REFPACK' [MaterialType] = 'HALB' AND [ProcType] ='E' AND [BUOM]='PC' ActivePN1 NA DCS 005-00 E [RefPackingMaterial] != 'REFPACK' [MaterialType] = 'HALB' AND [ProcType] ='E' AND [BUOM]='PC' ActiveQN4 NA DCS 005-00 E [RefPackingMaterial] != 'REFPACK' [MaterialType] = 'HALB' AND [ProcType] ='E' AND [BUOM]='PC' ActiveQN4 NA DEEDS 005-00 E [RefPackingMaterial] != 'REFPACK' [MaterialType] = 'HALB' AND [ProcType] ='E' AND [BUOM]='PC' Active

RefPackingMaterial <> “REFPACK”

37

Elements of the Global ROT

• 5-digit rule number3-digit data field number

A sequential, numerical ID that goes along with a given SAP data fieldIt’s standard for all PBUs in every regionCurrently have 148 fields available for creation of rules, and only 103 are partially coveredCan grow as data becomes available within SAP, in a solid table structure

38

Elements of the Global ROT (cont.)

• 5-digit rule number (cont.)2-digit sequential rule number

It’s also a global standardThis means we can create up to 100+ rules for every data field (by using alphabet)

The creation of a rule will help other regions to evaluate the applicability of the rule

39


Error is a condition that will not have an immediate impact, butwill create data accuracy deteriorated in the mid term

E

Warning is a condition that could be improved, but is completelyfunctional

W

Info OnlyI

Potential impact to cash flow$

Critical indicates this condition has the ability to stop a shipmentC

DescriptionError Level

• Error message explanationA short text message that describes the condition being tested in the database (human version of the rule)Will be used in reports to drive action on data maintenance

40


• OwnerSpecify the corresponding Business Process Owner of the data

These are the only groups with authority to create or approve a given rule

System architecture allows the creationof additional groups

• TableIt’s a technical element passed to the query generator during runtimeNarrow the focus of ROT applied to the specifiedcontent of that SQL table This is only used by the MDG Engineers. examples of those SQL tables are:

41


• FieldsSame as the table element, indicating to the engine which data field the query will be applied toThis is only for Master Data Managers

• RulesCorrespond to the technical SQL Server restricted language statement that will be applied by the engine to the data setRequire technical knowledge of the expected syntax needed by the engine

42


• ScopeThe technical statement that isolates the records to which the rule will be applied It’s also used strictly by the MDG

• StatusThis is a flag that shows if a rule has been deactivated for anyreason, avoiding the need for the deletion of rules

43

Elements of the Global ROT (cont.)• Client

Identifies the specific SAP environment from which data was obtained (examples: QN4-040, QN4-050, PN1-025)SQVI queries are recreated on those SAP environments used for data cleansing and conversion activities, and can be uploaded to the ROT engine

• RegionRegions might have slightly different needs for a given topic or variable within SAPThis field allows the engine to keep separate rules for every region/client

• PBUThis pull-down menu allows the user to display non-conforming records for a given business unit

4444



4545

Enhancing the Business Processes

46

Enhancing the Business Processes (cont.)

ROIROI$$$$$$$$$$

SAPSAPEffectiveness Effectiveness

MetricsMetrics

ROTROT(Rule of Thumb)(Rule of Thumb)

3

2

1

47

ROLE: SHIPPING MASTER

REPORT NAME:Outbound

Shipments not completed

Unexecuted Build Plans

Error in Backflush (caused by

missing Material Master data)

Error in Backflush (caused by missing Purchasing Master

data)

Inventory with negative quantity

Inventory with negative dollars

External Supplier Past Dues

Interplant Supplier Past

Dues

IMPACT:

Inventory is overstated, Missing Customer ASN, and Missing Customer

Invoices OR Customer

Requirements are understated and

Potential for Outbound Premium

Shipments

Increased Raw Material Inventory,

Potential for Overtime and

Outbound Premium Freight

Inventory is overstated on Raw

Material and understated on

Finished Goods/Higher

Assemblies, Labor is understated, Production Downtime

Inventory is overstated on Raw

Material and understated on

Finished Goods/Higher

Assemblies, Labor is understated,

Production Downtime

Understating inventory, increased

raw material inventory, Potential for Financial

Cash Flow Issue

Understating inventory, increased

raw material inventory, Potential for Financial Cash

Flow Issue

Cannot execute Build Plan, Potential

Inbound and Outbound Premium Freight, Potential

Overtime

Cannot execute Build Plan, Potential

Inbound and Outbound Premium Freight, Potential

Overtime

OWNER: Shipping Role Scheduling Role Inv Analyst / PC&L Team

Inv Analyst / PC&L Team



Supplier Order Management


GOAL:No open deliveries over 1 week old

No orders over 2 weeks old

No errors over 1 week old

Number of component part numbers per assembly

Number of parts - No parts with negative inventory

Dollar value of negative inventory

No orders older than 2 weeks

No orders older than 2 weeks

SAP T-CODE: VL06O Y_DN3_47000172 E-Parts ZCOGIA MF47 MB52 MB52 Y_DN3_4700037

8Y_DN3_4700037

8Target: 0 0 0 0 0 0 0 0

Plant Plant Plant Manager > 1 WEEK > 2 WEEKS > 1 WEEK > 1 WEEK REAL-TIME REAL-TIME > 2 WEEKS > 2 WEEKSFW61 Zacatecas R. Nunez 0 2 0 358 48 ($646) 24 10FW62 Fresnillo 1 A. Lozano 5 33 0 1432 176 ($835,130) 44 37FW63 Fresnillo 2 J. Moreno 1 4 0 820 80 ($42,603) 63 83FW80 Laredo Carlos Leyva / Gene Lindgren 13 0 0 0 6 ($663,931) 726 11FW81 Neuvo Laerdo R. Vega 0 0 0 515 423 ($454,177) 41 41FW84 Guadalupe 2 F. Olivas 0 17 0 152 25 ($7,774) 20 7FW86 Linares R. Mendoza 0 0 0 124 13 ($1,046) 23 2FW91 Victoria 1 R. Gutierrez 0 0 0 1121 82 ($49,836) 7 0FW92 Victoria 2 R. Gutierrez 0 0 0 3344 112 ($115,766) 91 5FW96 Guadalupe 3 J. Navarro 0 8 0 347 186 ($117,771) 0 0

INVENTORY SUPPLIER ORDER MANAGEMENT

1

2 3

Inventory Optimization$ XXX.5 MBy Dec 08

Enhancing the Business Processes with a Purpose

• Sigma level as a measure of speed and accuracy

• Supporting optimal business performance

48

• Sigma level as a measure of speedand accuracy


Monitoring Business Performance• Access the tool

• Use the specific intranet site where the reporting service is located

• Select the dataset of interest

• Check for the information quality level

49

Monitoring Business Performance (cont.)

• Browse the detailed results• Act on the exceptions

5a. Clean the data5b. Enhance/fix the

business process(see next slide)



50

Monitoring Business Performance (cont.)

5a. Clean the data5b. Enhance/fix the business process



51

Enhancing the Business Processes with a Purpose

Customer Order Management


Master Planning and Scheduling

Delphi Communications with SupplierDelphi Communications with Supplier

Supplier Communication with DelphiSupplier Communication with Delphi

Customer Communications with DelphiCustomer Communications with Delphi

Delphi Communication with SupplierDelphi Communication with Supplier

Shipping Receiving

Expertise RolesExpertise Roles

DATADATA

DATA DATA

DATADATA

52

Enhancing the Business Processes with a Purpose (cont.)

Transformationto Be Customer-Centric

P4P4

PDPD

RepetitivePulls

ERP DrivenPulls

53

Enhancing the Business Processes with a Purpose (cont.)DOH Index for FW62

Party Numbers with Excessive DOH INV: 72.0% 5/28/2008Part numbers with potential Premium 10.7%

INVENTORY (by SLOC) Pieces DollarsBlanks: In Transit 3,749,388 324,3730001: Receiving 80,334,594 3,813,0690002: WIP 57,566,936 2,158,1530003: to LADC 20,134 298,5970004: at LADC 65,797 1,700,4150007: Others 2,014,332 88,6640009: Finished 24,528 185,885Total 140,026,321 $8,244,783

16.8% 17.7% 19.6%INVENTORY ANALYSIS by Status Flag COMPONENTS CABL HARN TOTAL % LwrLimit UpperLim1 Red 198 66 23 287 10.70% -999 02 Yellow 224 105 31 360 13.42% 0.1 53 Green 59 30 15 104 3.88% 5.1 74 EXCESS INV ($$$) 1,206 560 166 1,932 72.01% 7.1 999

Total Part numbers 1,687 761 235 2,6835 PNs with -999 DOH 8 1 2 11 0.41%6 PNs with over 100 neg(DOH) 0 0 0 0 0.00%7 PNs with over 30 neg(DOH) 3 0 3 6 0.22%8 PNs with less than 0 DOH 180 59 16 255 9.50%9 PNs with 0 DOH 7 6 2 15 0.56%10 PNs with DOH less than 5 222 104 30 356 13.27%11 PNs with DOH less than 10 114 63 22 199 7.42%12 PNs with DOH less than 30 190 118 21 329 12.26%13 PNs with DOH less than 999 101 43 13 157 5.85%14 PNs with 999 DOH 862 367 126 1,355 50.50%15 Avg neg(INV_DOH) excl -999 DOH -4.0 -2.8 -12.816 Avg INV_DOH excluding 999 DOH 15.8 15.1 15.817 Generic MRP Controllers (no owner) 101 20 206 327 12.19%18 MRP Type = PD 1,686 761 1 2,448 91.24%19 MRP Type = P4 1 0 234 235 8.76%20 MRP Type = ND 0 0 0 0 0.00%

Exceptions Groups COMPONENTS CABL HARN TOTAL %1 Late in moving to a proposal 0 0 0 0 0.00%2 Late in moving to a commitment 0 0 0 0 0.00%3 Stock should have been there 252 119 1 372 13.87%4 A new requirement 0 0 0 0 0.00%5 BOM related issues 0 0 0 0 0.00%6 Too much or too little stock 8 1 2 11 0.41%7 Dates when needed/available differs 437 89 120 646 24.08%8 Marked for Deletion? 0 0 0 0 0.00%

Total Part numbers 697 209 123 1,029 38.35%

17.3%

PNs w/DaysOnHand

287 360104

1,932

0

500

1,000

1,500

2,000

2,500

Red Yellow Green EXCESS INV($$$)

11 0 6

255

15

356

199

329

157

1,355

-200

0

200

400

600

800

1,000

1,200

1,400

1,600

PN

s w

ith -9

99 D

OH

PN

s w

ith o

ver 1

00 n

eg(D

OH

)

PN

s w

ith o

ver 3

0 ne

g(D

OH

)

PN

s w

ith le

ss th

an 0

DO

H

PN

s w

ith 0

DO

H

PN

s w

ith D

OH

less

than

5

PN

s w

ith D

OH

less

than

10

PN

s w

ith D

OH

less

than

30

PN

s w

ith D

OH

less

than

999

PN

s w

ith 9

99 D

OH

DOH Index for FW62Party Numbers with Excessive DOH INV: 72.0% 5/28/2008

Part numbers with potential Premium 10.7%

INVENTORY (by SLOC) Pieces DollarsBlanks: In Transit 3,749,388 324,3730001: Receiving 80,334,594 3,813,0690002: WIP 57,566,936 2,158,1530003: to LADC 20,134 298,5970004: at LADC 65,797 1,700,4150007: Others 2,014,332 88,6640009: Finished 24,528 185,885Total 140,026,321 $8,244,783

16.8% 17.7% 19.6%INVENTORY ANALYSIS by Status Flag COMPONENTS CABL HARN TOTAL % LwrLimit UpperLim1 Red 198 66 23 287 10.70% -999 02 Yellow 224 105 31 360 13.42% 0.1 53 Green 59 30 15 104 3.88% 5.1 74 EXCESS INV ($$$) 1,206 560 166 1,932 72.01% 7.1 999

Total Part numbers 1,687 761 235 2,6835 PNs with -999 DOH 8 1 2 11 0.41%6 PNs with over 100 neg(DOH) 0 0 0 0 0.00%7 PNs with over 30 neg(DOH) 3 0 3 6 0.22%8 PNs with less than 0 DOH 180 59 16 255 9.50%9 PNs with 0 DOH 7 6 2 15 0.56%10 PNs with DOH less than 5 222 104 30 356 13.27%11 PNs with DOH less than 10 114 63 22 199 7.42%12 PNs with DOH less than 30 190 118 21 329 12.26%13 PNs with DOH less than 999 101 43 13 157 5.85%14 PNs with 999 DOH 862 367 126 1,355 50.50%15 Avg neg(INV_DOH) excl -999 DOH -4.0 -2.8 -12.816 Avg INV_DOH excluding 999 DOH 15.8 15.1 15.817 Generic MRP Controllers (no owner) 101 20 206 327 12.19%18 MRP Type = PD 1,686 761 1 2,448 91.24%19 MRP Type = P4 1 0 234 235 8.76%20 MRP Type = ND 0 0 0 0 0.00%


Total Part numbers 697 209 123 1,029 38.35%

17.3%

PNs w/DaysOnHand

287 360104

1,932

0

500

1,000

1,500

2,000

2,500

Red Yellow Green EXCESS INV($$$)

11 0 6

255

15

356

199

329

157

1,355

-200

0

200

400

600

800

1,000

1,200

1,400

1,600

PN

s w

ith -9

99 D

OH

PN

s w

ith o

ver 1

00 n

eg(D

OH

)

PN

s w

ith o

ver 3

0 ne

g(D

OH

)

PN

s w

ith le

ss th

an 0

DO

H

PN

s w

ith 0

DO

H

PN

s w

ith D

OH

less

than

5

PN

s w

ith D

OH

less

than

10

PN

s w

ith D

OH

less

than

30

PN

s w

ith D

OH

less

than

999

PN

s w

ith 9

99 D

OH

54

Enhancing the Business Processes with a Purpose (cont.)DOH Index for FW62

Party Numbers with Excessive DOH INV: 18.6% Date: 09/23/2008Part numbers with potential Premium 3.2%

INVENTORY for ACTIVE PARTS Pieces Dollars

COMPONENTS 46,759,315 3,857,620CABLE 11,334,460 703,710

HARNESS 51,951 1,277,758

Total 58,145,726 $5,839,088TOTAL INV IN EXCESS VALUE 3,925,414

INVENTORY IN EXCESS VALUE 3,012,811 404,025 508,579% Optimal PN by groups -> 81.8% 52.6% 83.8%

DaysSupply Analisys by Commodity) COMPONENTS CABL HARN TOTAL % LwrLimit UpperLim1 Red (pot shortage) 129 71 36 236 3.19% -999 02 Yellow (risk for shortage) 229 93 83 405 5.48% 0.1 53 Green (Opt Days Supply) 3,560 441 1,380 5,381 72.78% 5.1 74 EXCESS INV ($$$) 716 410 246 1,372 18.56% 7.1 999

Total Part numbers 4,634 1,015 1,745 7,3945 PNs with -999 DOH 0 0 0 0 0.00%6 PNs with over 100 neg(DOH) 1 0 1 2 0.03%7 PNs with over 30 neg(DOH) 12 9 3 24 0.32%8 PNs with less than 0 DOH 92 58 25 175 2.37%9 PNs with 0 DOH 229 93 83 405 5.48%

10 PNs with DOH less than 5 3,560 441 1,380 5,381 72.78%11 PNs with DOH less than 10 171 75 40 286 3.87%12 PNs with DOH less than 30 144 65 14 223 3.02%13 PNs with DOH less than 999 94 66 20 180 2.43%14 PNs with 999 DOH 292 200 159 651 8.80%15 Avg neg(INV_DOH) excl -999 DOH -27.9 -12.7 -157.416 Avg INV_DOH excluding 999 DOH 865.5 575.3 936.917 Generic MRP Controllers (no owner) 2,919 253 812 3,984 53.88%18 MRP Type = PD (SAP generated) 4,457 1,015 1,744 7,216 97.59%19 MRP Type = P4 (user sched some) 115 0 1 116 1.57%20 MRP Type = ND (NO SAP MRP) 25 0 0 25 0.34%21 Rounding Values undefined 2,686 137 1,584 4,407 59.60%


Total Part numbers with Exceptions 855 237 100 1,192 16.12%

78.3%

PNs w/DaysOnHand

ACTIVE PARTS ONLY

236 405

5,381

1,372

0

1,000

2,000

3,000

4,000

5,000

6,000

Red (potshortage)

Yellow (risk forshortage)

Green (OptDays Supply)

EXCESS INV($$$)

0 2 24175

405

5,381

286 223 180

651

-1,000

0

1,000

2,000

3,000

4,000

5,000

6,000

PN

s w

ith -9

99 D

OH

PN

s w

ith o

ver 1

00 n

eg(D

OH

)

PN

s w

ith o

ver 3

0 ne

g(D

OH

)

PN

s w

ith le

ss th

an 0

DO

H

PN

s w

ith 0

DO

H

PN

s w

ith D

OH

less

than

5

PN

s w

ith D

OH

less

than

10

PN

s w

ith D

OH

less

than

30

PN

s w

ith D

OH

less

than

999

PN

s w

ith 9

99 D

OH

DOH Index for FW62Party Numbers with Excessive DOH INV: 18.6% Date: 09/23/2008

Part numbers with potential Premium 3.2%

INVENTORY for ACTIVE PARTS Pieces Dollars

COMPONENTS 46,759,315 3,857,620CABLE 11,334,460 703,710

HARNESS 51,951 1,277,758

Total 58,145,726 $5,839,088TOTAL INV IN EXCESS VALUE 3,925,414

INVENTORY IN EXCESS VALUE 3,012,811 404,025 508,579% Optimal PN by groups -> 81.8% 52.6% 83.8%

DaysSupply Analisys by Commodity) COMPONENTS CABL HARN TOTAL % LwrLimit UpperLim1 Red (pot shortage) 129 71 36 236 3.19% -999 02 Yellow (risk for shortage) 229 93 83 405 5.48% 0.1 53 Green (Opt Days Supply) 3,560 441 1,380 5,381 72.78% 5.1 74 EXCESS INV ($$$) 716 410 246 1,372 18.56% 7.1 999

Total Part numbers 4,634 1,015 1,745 7,3945 PNs with -999 DOH 0 0 0 0 0.00%6 PNs with over 100 neg(DOH) 1 0 1 2 0.03%7 PNs with over 30 neg(DOH) 12 9 3 24 0.32%8 PNs with less than 0 DOH 92 58 25 175 2.37%9 PNs with 0 DOH 229 93 83 405 5.48%

10 PNs with DOH less than 5 3,560 441 1,380 5,381 72.78%11 PNs with DOH less than 10 171 75 40 286 3.87%12 PNs with DOH less than 30 144 65 14 223 3.02%13 PNs with DOH less than 999 94 66 20 180 2.43%14 PNs with 999 DOH 292 200 159 651 8.80%15 Avg neg(INV_DOH) excl -999 DOH -27.9 -12.7 -157.416 Avg INV_DOH excluding 999 DOH 865.5 575.3 936.917 Generic MRP Controllers (no owner) 2,919 253 812 3,984 53.88%18 MRP Type = PD (SAP generated) 4,457 1,015 1,744 7,216 97.59%19 MRP Type = P4 (user sched some) 115 0 1 116 1.57%20 MRP Type = ND (NO SAP MRP) 25 0 0 25 0.34%21 Rounding Values undefined 2,686 137 1,584 4,407 59.60%


Total Part numbers with Exceptions 855 237 100 1,192 16.12%

78.3%

PNs w/DaysOnHand

ACTIVE PARTS ONLY

236 405

5,381

1,372

0

1,000

2,000

3,000

4,000

5,000

6,000

Red (potshortage)

Yellow (risk forshortage)

Green (OptDays Supply)

EXCESS INV($$$)

0 2 24175

405

5,381

286 223 180

651

-1,000

0

1,000

2,000

3,000

4,000

5,000

6,000

PN

s w

ith -9

99 D

OH

PN

s w

ith o

ver 1

00 n

eg(D

OH

)

PN

s w

ith o

ver 3

0 ne

g(D

OH

)

PN

s w

ith le

ss th

an 0

DO

H

PN

s w

ith 0

DO

H

PN

s w

ith D

OH

less

than

5

PN

s w

ith D

OH

less

than

10

PN

s w

ith D

OH

less

than

30

PN

s w

ith D

OH

less

than

999

PN

s w

ith 9

99 D

OH

55



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Resources

• www.sap-img.comSAP Tables Help File and ABAP Programming

• www.dmreview.com/channels/data_quality.htmlWhite paper library

• www.findwhitepapers.com/index.phpTechnology Research For Business Professionals

• www.ittoolbox.com/Professional IT Community

5757

7 Key Points to Take Home

• Focus on data fields of interest (remember the SAP built-in validation for data during the creation process)

• Keep current and future SAP functionality in mind during development

• Identify proper SAP tables required for the Information Quality Model

• Create simple queries (minimize more than two joins per query)• Use structured names for SQL tables and programs• Share system ownership with functional areas by co-authoring

rules and resolving their issues• Maintain high coloring standards for Information Quality and

Business Performance Assessment (Red/Yellow/Green)

5858

Your Turn!

How to contact me:Jose V Zavala

[email protected]

59

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