Building the Business Case for Data

A Case Study in Action

Jody L. Dyerfox – Client Partner Sushil Tiwari – Delivery Director Information and Data Quality Conference (IDQ) November 4-7, 2013 Little Rock, Arkansas

Agenda

The Business Case: Understanding the Risks and Opportunities The Economic Impact of Data Use Cases – CSL Behring, RasGas, Kimberly Clark (and Others!) The Essentials: People, Process and Technology

Why Are We Here? Master Data Challenges Materialize Across the Organization

Gaining Supply Chain Efficiencies Reduce procurement spend Optimize inventory levels Drive down warehouse management costs Improve lead-time accuracy Increase production efficiency Align your materials and production teams to improve customer service Enhance the accuracy of your forecasting and planning activities

Ineffective Business Decisions Lack of consistent information needed to make critical decisions supporting innovation and growth Business decisions are corrupted by data integrity challenges

Reduced Sales Effectiveness Lack of consolidated view of customer data across all channels Territory alignment and analytics Customer hierarchy and grouping visibility/profitability analysis

Operational Efficiencies Reusable frameworks to leverage best practices across all data domains

Data Integrity and the Impact on Business Outcomes

§Inventory Optimization / reduction in carrying cost §Spend Analysis savings §Strategic Sourcing § Procuring the same functional material for different prices §Plant Maintenance efficiencies §Optimizing ERP Processes

Business Initiatives Affected Data Issues

§Eight Functional Equivalent Duplicate Material Masters § Only Six Vendors captured, Client is buying the same MM for two different prices from the same Vendor § Procuring the same functional material for Eight different prices - 700% Premium §Incomplete Attribute Fill Rate

Achieving Benefits in Multiple Master Data Categories

Business Benefit Areas

Information Technology

Reduced data cleansing cost

Sales & Marketing Supplier Relationship

Business Intelligence

Better decision making through data integrity

Improved M&A integration efficiency

Customer Relationship

Supply Chain

Significant benefits are realized through consistent,

accurate, available data.

Reduced cost of fixing data issues

Reduced support for systems maintaining multi-source data

Consolidation of R/3 instances

Enabling global best price – vendor and parts consolidation

Improved procurement efficiency

Reduced out-of-stock parts

Increased customer support and service efficiency

Reduced customer complaints

Improved speed to market for new products

Reduced invoice write-offs

Improved sales and marketing effectiveness

Improved sales and marketing efficiency

Reduced shipment returns

Reduced expediting cost

Reduced logistics cost

Reduced warehouse receiving and handling cost

Inventory Optimization

Risk & Compliance

Reduced cost of compliance – management and penalties

Improved store operations

Reduced DSO

Reduced Risk; Increased Security

Business Value Quantified

Potential One time Benefit Conservative Estimate

Likely Scenario

One-time benefit

Potential Annual Benefits

$14.3M

Procurement $4.2 - $6.2

Reduced maverick spend and consolidation of

vendors

$23.5M

Finance $0.6 - $1.0

Sales $1.3 - $1.9

Increased revenue due to improved delivery

Improved efficiency due to reduction in system

breakdown

Information Technology $1.9 - $4.3

Improved efficiency by streamlining close process

Improved DPO by better management of payment terms attributes

$9.1 $12.7

$0.5 $0.3

$0.5 $0.3

Strategic $1.0- $1.8M

Reduced in capital expenditure by improved

decision making $1.8 $1.0

$3.2 $2.8

$2.8 $0.7

$2.6 $3.7

$1.9 $1.3

Improved reporting capability by streamlined master data

relationships Reduced spend by vendor consolidation across

Company XYZ

$1.4 $3.0

Improved revenue by reducing time to market

NPI $1.1 - $1.9

Ongoing revenue uplift by reducing time to market

$1.1 $1.9

$4.3 $6.4

Reduced master data project spend

$1.2 $1.4

Human Resource $0.2 - $0.2 Reduced costs for ad-hoc

needs, like a phone book $0.2 $0.2

Operations $4.0- $6.2M

Reduced inventory due to single view of the product

Reduced inventory carrying cost $0.3 $0.3

$2.2 $2.6

Reduced damage and obsolete cost

$0.4 $0.6

Improved efficiency driven by better master data across the

organization

$1.0 $1.8

Reduced cost in asset management

$0.5 $0.5

Transportation cost reduction due to better segmentation

$2.0 $3.0

Efficiency

Cost Reduction

Revenue

Gartner, Master Data Management Excellence

Ø RELEASED MID-MARCH 2012 Ø Description: Utopia, http://www.utopiainc.com/, headquartered in

Mundelein, IL, USA, sells services to help organizations manage their information lifecycle, especially within and across complex ERP landscapes most common in SAP ERP and Oracle ERP environments.

Ø Utopia particularly focuses on the data model design, entity relationships and how the data will behave and be consumed from the MDM repository. Guidance is directed to the governance processes and organizational structure to support and sustain product data stewardship.

Ø Andrew White, VP Research, Master Data Management, Gartner

EDLM Phase 1: Assessment

Business Requirements: – Achieve a 360¡

View of the Customer

• Customer Profitability • Cross Selling • Up Selling • Sunshine Act Compliance

– Enable Global Spend – Optimize Supply Chain

Deliverables: EDM Job Descriptions - Roles and Responsibilities Organizational Risk and Readiness Assessment (ORRA) Organizational Risk Mitigation Plan Stakeholder Analysis EDM Infrastructure Assessment

• EDM Best Practices • EDM Reference Architecture

MDM Project Plan Review

Purpose: To establish a strategic Enterprise Data Management initiative that provides the foundation and infrastructure for EDM across people, process and technology; to assess the organizational commitment and readiness for strategic EDM; and to identify organizational resources who will own EDM for their areas.

EDLM Phase 1, 2 and 3: Strategy and Roadmap Enabling Global Visibility

Business Requirement: • Single Version of the Truth • Global Reporting and Leverage • Customer and Financial Visibility • Enabling Spend Analytics

Developed a strategic Enterprise Data Lifecycle Management (EDLM) roadmap to establish global Master Data Management (MDM) with the appropriate enterprise data governance framework, to support their cross-boundary (cross-functional, cross-geography) business processes and enable enterprise-wide reporting.

• Global business ownership and data governance were not effectively established or maintained.

• Multiple data quality issues existed and were impacting the client’s ability to establish cross-boundary business processes.

Enterprise Data Lifecycle Management Framework

LIPSTICK ON A PIG

PUTTING A PRETTY REPORTING DASH BOARD ON BAD DATA DOESN’T FIX THE ISSUE

Incremental Program Approach to Enable Information Governance

Data Health Assessment

One Size Does Not Fit All

1 2 3 4 5 0

1 2 3 4 5 0

1 2 3 4 5 0

1 2 3 4 5 0

Data Integration

Maintenance

Stewardship

Governance

Decentralized Centralized

Siloed Enterprise Wide

None Real-time

Operational App Application Agnostic

Organizational Structure – The People

Governance Options: Which is Best for You?

“Federated” “Totally Centralized”

Architecture

Organization

Processes

Maintenance & Quality

Characteristics

n Deep skills for advanced needs n Rapid problem resolution n Larger prioritization queue n Local dependencies on central group

(timezones, legal) n High resource efficiency n “Guarantees” global visibility

n Accommodates local needs in timely response

n Tighter alignment with business governance

n Weakens standards enforcement n Slower to respond to enterprise needs n Risk of creating duplicate data n Risk of losing global visibility

n Rapid response to local needs n Ownership aligned with individual

business organizations n Starting point for newly acquired

companies n Reporting and terminology in

specific business vernacular

Standards

“Totally Decentralized”

EDLM Maturity Model

Utopia’s EDLM Maturity Model is used to establish benchmarks, set future goals, and measure progress towards targets.

EDLM Maturity Assessment Sample Output

-

1.00

2.00

3.00

4.00

5.00Governance

Data Stewardship

Business Controls

Technical DataManagement

Data Standards

Data Integration

IT Governance

Analytics, Reporting

Data Quality

Data MgmtProcesses

Enterprise Data Lifecycle Management Maturity Evaluation

People

Technology

Process

Current Assessment

Desired Target

How to Get to the Next Level

Industry Standards & Best Practices

Ente

rpris

e O

bjec

tives

Indu

stry

Driv

ers

Prog

ram

Pla

nnin

g

Reference Architecture The Four Squares

CHANGE MGMT / ENABLEMENT

n Deployment n Data embedded in IT methodology n Data process improvement n Enabling the Organizaiton

QUALITY

n Data metrics based on standards n 6 Sigma methodologies for data

process design n Metric alignment with data Roles &

Responsibilities

THD Standard Data Deletion Process

Subj

ect M

atte

r Ex

pert

Busi

ness

Dat

a O

wne

rBu

sine

ss D

ata

Cha

mpi

onO

ther

Hom

e D

epot

Dat

a C

ham

pion

Yes

No

Start

Initiate SES for data deletion

Delete data & notify company data steward

Verify correct data deleted

Deletion request

approved?

Consult with business data owners and requestor to

determine “special” requirements

Last Revised:

Author: Lyndsi Caracciolo Date Created: 11/9/2005

Filename: THD Standard Data Deletion Process v2.vsd

11/11/2005 4:25:23 PM

Project: Enterprise Data Management Strategy

Metrics indicate need to delete

data

Determine exact data to be deleted

A

Create and verify recovery media

copies

Create Special Processing Instructions

Request data to be deleted

Notify Requestor End A

End GOVERNANCE

n Strategic Data Policy n Data Ownership n Roles & Responsibilities Consensus Stds

Metrics

Data Trustee

Material –Customer –

Vendor –

Data Stewards• Material -• Customer –• Vendor –

BU 1Data Owner

BU 1Data Custodians

BU 2Data Owner

BU 2Data Custodians

BU 3Data Owner

BU 3Data Custodians

AuthorityBusiness Goals

Business Unit 1Leadership

Business Unit 2Leadership

Business Unit 3Leadership

Support ServicesLeadership

Major IssuesSummary Metrics

AuthorityBusiness Goals

Staffing notes:1. Redeployment of existing resources2. Official recognition of existing “de facto” assignments3. Business determines number of Owners and Custodians based on Data volume and value

STANDARDS

n Common data definitions n Data Model - Schemas

(hierarchies and groupings) to support business functional needs

Data Standards• SAP• Legacy• eCommerce

Core Business Processes• Procure to pay• Plan to fulfill• Order to cash

Core Business Processes• Procure to pay• Plan to fulfill• Order to cash

ManagementReporting

ManagementReporting

Operations

ARCHITECTURE

n Where, When & How the data is n Entered n Stored n Transmitted n Reported

MDMMDM

SAP UIOPTIONS

SAP UIOPTIONS

SAP IndustrySolution

SAP IndustrySolution

Web Site

Specialty

Distribution

Services

Partners

Regulatory

Legacy 1

Legacy 2

Legacy 3

SAP B/WSAP B/W

ExternalSourcesExternalSources

SelfService

SelfService

© SAP and ASUG DG SIG

Enterprise Data Management Framework Orchestration of Processes

EDLM and EDM Inter-connected Frameworks

Industry Standards & Best Practices

Ente

rpris

e O

bjec

tives

Indu

stry

Driv

ers

Prog

ram

Pla

nnin

g

Customer Vendor Material Other…

• Vision, Goals, Objectives • Direction • Strategy • Principles, Models • Frameworks • Multi-Generation Plan

• Business Alignment • Standards • Data Governance • Organization Model • Management of Change

Level 1: Enterprise Architecture Level 2:

Data Object Architecture

Data Standards – Enforcing your Policy

POP vs SODA vs COKE

There is no Business Intelligence without Data Integrity

?

Jody L. Dyerfox Client Partner Utopia Global, Inc. +1 214-448-9484 jdyerfox@utopiainc.com

YOUR BUSINESS IS READY FOR SUCCESS BUT IS YOUR DATA?