Sap increase your return on information by focusing on data governance - managing data quality - by scott barrett

© 2011 SAP AG. All rights reserved. 1

Scott Barrett

Senior Director │ Information Management │ SAP EMEA

Return on Information: Managing Data Quality

25th September 2013

Welcome to the ‘Return on Information’ webinar series dedicated to Information Management

Solutions by SAP. This is the first of four webinars, the following webinars will be on:

9th Oct:

Return on Information:

Managing Master Data

23rd Oct:


Managing Content

6th Nov:


Managing Information Lifecycles

Register now › bit.ly/1b26WRY


What is Information Governance?

Information Governance

A discipline that includes people, processes, policies, and metrics for the

oversight of enterprise information to improve the business value

High Value Information:

Optimized Business Processes

Smarter Business Analytics

Timely Mergers and Acquisitions

Compliance with Laws and Regulations

Process People

Policies &

Standards

Metrics


Why Should You Care About Information Governance?

SAP Solutions are uniquely integrated with SAP Business Suite

and SAP BusinessObjects BI solutions

Utilize entire EIM stack by providing a complete solution

that can address needs at any stage of their information governance program

Talk to the business by discussing business priorities

and how high-quality information can help them

Elevate conversation above technology discussion by

showing how SAP can support information governance

1

2

3

4


What Aspects of Information Can Be Governed?

People

Information ownership and accountability

Information access (who, when, where, what)

Process

Data handling (creation, updating, deleting)

Information storing (archiving, security)

Metrics

Data quality levels

Reporting (who, when, what)

Policies and Standards

Data definitions

Allowable values

Information architecture

Begin with the business priority that is enabled most by quality information.


Information Governance is a Key Pillar of the Global

Transformation Program Business Model For Vodafone


Information Governance and MDM Transforming the Data Organization at Vodafone

Single governance process for

management of SCM, Finance

and HR master data

Creation of a data definition for each

master data object

Enforcement of data policies and

standards

Centralization of data management to

Global Shared Services Organization

Establishment of Data Review Board

Transformation from free text

purchasing to catalogues


Information Governance is a Best Practice Discipline

Required for Enterprise Information Management

Data Migration

Data Integration for

Data Warehousing

Master Data Management

Data Quality Management

A B

Before After

A

B

C

D

Mergers & Acquisitions

Business Analytics

Business Process Efficiency

Compliance

EIM Initiatives (Examples) Business Goals

Info

rmati

on

Go

vern

an

ce


SAP Information Governance Solutions Maximize the value of your enterprise information

Easier information

stewardship

Governance

analytics

Business and

IT collaboration

Embedded in the

business process

Governance

workflow

Enrich business process with

enterprise content

Optimized

data quality

Continuous

monitoring

Unlock insights from

unstructured data

Empower the Business Govern In Process Trust Your Information


Govern Information in Process from the Point of

Information Creation to Consumption

information

information

Systems of Record

3rd Party

Systems

SAP

Business

Suite

information

information

Data

Warehouse

Systems of

Analysis

Employees

Other

Systems

Customers

Other

Systems

Is it correct

and valid?

Does it meet

standards?

Is it a new

record?

Active Information

Governance

Is it correct

and valid?

Does it meet

standards?

Is it a new

record?

Passive Information Governance

information

information

Information Creation Information Consumption


information

information

Govern Information in Process with SAP Solutions for

Enterprise Information Management

Systems of Record

Non SAP

Systems

SAP

Business

Suite

information

informationx

information

information

Data

Warehouse

Systems of

Analysis

Employees

Clean data at point

of user entry with

SBOP DQM for

SAP ERP/CRM

Other

Systems

Clean and check

for duplicates with

SBOP DS

Create global

master data with

SAP MDG

Customers

Other

Systems

SBOP DQM for

Oracle or

Informatica

SAP NW MDM

SBOP DS

Measure and

monitor data

quality with

SBOP

Information

Steward

Clean, match, and

integrate data with

SBOP DS

Create global

master data with

SAP NW MDM

Legend:

SBOP = SAP BusinessObjects

DS = Data Services

DQM = Data Quality

Management

NW = NetWeaver

MDG = Master Data Governance

SAP Solutions

Information Creation Information Consumption


Manage

Cleanse

Create

Monitor Integrate

Optimize Quality and Consistency of Information with

Marketing Leading Solutions for Data Quality and MDM

Information

Governance

Rated as a MARKET

LEADER IN DATA

QUALITY AND DATA

INTEGRATION by Gartner,

Forrester, and TDWI

SAP customers KRAFT FOODS

INC., Gartner MDM

Excellence Award

2009, Lexmark

International 2011


Suppliers End Consumer

Retailer Distributor Warehouse Plant

Social media data for

segmentation,

sentiment, behavior information

Geo spatial data identifies best

routes/ number of trucks/timing

Warehouses use bar code data

to speed shipping

Plant operators use carbon

input data to identify

compliance

Manage suppliers relationships to

optimize purchasing

Decrease

COGS

Decrease days

sales outstanding

Increase promotion

effectiveness

Decrease compliance issues Decrease time to delivery

Benefits of End-to-End Information Governance

throughout the Business Process


Considering what the Experts Say

Lower Profits

Poor Customer

Relations

Low Productivity

Average organization loses $8.2 million annually through poor data quality. Gartner “

“ 55% of all CRM projects failed to meet software customers' expectations. Poor customer data is one of the biggest factors. Gartner “

“ 50% to 70% of ERP implementations are reported as “challenged” in part due to data integrity and/or data accuracy problems. =Adaptive Growth, Inc. “

“


How does Poor Data Quality Impact Business Process?

Problems experienced when data quality

practices are not followed

Difficult to determine the right recipients for

marketing campaigns

Inaccurate order information causes delayed or lost

shipments and lower customer satisfaction

Sales representatives are not able to identify relevant

accounts

Costs are high due to account duplications, while

response rates are low

Potential customers are annoyed by redundant mails,

e-mails and phone calls

Reporting uses wrong data and this leads to wrong

conclusions/decisions


What Kind of Data Are We Dealing with?

Materials/ Products

Customers

Financial

Business Partners Suppliers

Distributors Retailers

“What kind of data is most susceptible to data quality problems?”

Enterprise

Information


What Are the Sources of Bad Data Problems?

Enterprise Information

Employee Data Entry

Customer Self-

Service

Data Migration Projects

IT Application

Updates

Purchased or Rented External

Data


People & Process Maturity

Valu

e

Building a Roadmap for Data Quality is Key for Success

1. Data

READINESS

4. Data

GOVERNANCE

Understand what data

assets you have and how

they are being used

Deliver trusted information

repeatable and reliably at

the right form, to the right

place at the right time

2. Data

INTEGRATION &

CLEANSING

3. Data

CONSOLIDATION

Understand

Govern

Consolidate

Understand

Consolidate

Understand Understand

Consolidate diverse

master data landscapes

and increase trust and

reliability in information

Technology enabling

people to implement a

repeatable process to

manage the use, quality

and lifecycle of

information

Cleanse Cleanse Cleanse


Data Quality Provides Value Throughout Portfolio maps to the People and Process Maturity

END-TO-END Data

Management

Full Enterprise COVERAGE

1. Data

READINESS

4. Data

GOVERNANCE

2. Data

INTEGRATION &

CLEANSING

3. Data

CONSOLIDATION

Information

Steward

Enterprise MDM

MDM

Information

Steward

MDM

Information

Steward

Information

Steward

Data Quality Data Quality Data Quality

People & Process Maturity

Valu

e


The Data Quality Framework

Continuous

Monitoring CONTINUOUS MONITORING

MEASURE

ANALYZE

PARSE

STANDARDIZE

CORRECT

ENHANCE

MATCH

CONSOLIDATE

Data

Assessment

Enhance Data

Cleansing

Match & Consolidate

YOUR DATA


Gartner Magic Quadrant for Data Quality Tools www.sap.com/campaign/na/usa/Gartner_Data_Quality/index.html

SAP ranked as a LEADER

in the

“Gartner Magic Quadrant

for Data Quality Tools”

for the 7th consecutive year.

http://www.sap.com/campaign/na/usa/Gartner_Data_Quality/index.html


Goal: Achieving Pristine Data Quality with SAP

Bob oldstead 175 Riviington Ave suite 2 Manhatten, new yourk 10002

INPUT

PARSE 1

First Name: Bob Last Name: Oldstead AddressL1: 175 Rivington Ave AddressL2: Suite 2 City: Manhattan State: New York Zip Code: 10002

CORRECT 3

First Name: Robert MiddleName: E Last Name: Oldstead AddressL1: 175 Rivington Ave AddressL2: Suite 2 City: Manhattan State: New York Zip Code: 10002 Phone: (847) 442-5555 Email: [email protected]

ENHANCE

First Name: Robert MiddleName: E Last Name: Oldstead AddressL1: 175 Rivington Ave AddressL2: Suite 2 City: Manhattan State: New York Zip Code: 10002-2517 Longitude: 40.7325525 Latitude: -74.004970 Phone: (847) 442-5555 Email: [email protected]

6

MATCH

Robert E. Oldstead Manhatten, NY 10002 [email protected]

847 442-5555

4

CONSOLIDATE

STANDARSIZE 2

5

mailto:[email protected]





Technologies Required for Effective Information

Governance

Technologies EIM Solutions

Extract transform load (ETL) SAP BusinessObjects Data Services

Data quality SAP BusinessObjects Data Services

Data profiling SAP BusinessObjects Information

Steward

Metadata Management SAP BusinessObjects Information

Steward

Workflow management SAP MDG

Business rules engine SAP MDG

Master data management SAP MDG

BI dashboards and scorecards SAP BusinessObjects Information

Steward or SAP BusinessObjects

Dashboards


SAP Business Objects Data Services Data integration, data quality, stewardship, and text analytics

Move

Improve

Govern

Unlock

One Runtime Architecture

& Services

Business UI (Information Steward)

Unified Metadata

Technical UI (Data Services)

SAP BusinessObjects Data Services

4.0

ETL

Data Quality

Profiling

Text Analytics

One Administration Environment

(Scheduling, Security, User Management)

One Set of Source/Target Connectors


Monitor

Quality

continuously

Improve

Data quality

and

governance

SAP BusinessObjects Information Steward Collaborative environment for your IT and business users

Empower business and IT users with a single environment

to manage the quality of their enterprise data assets

Discover

Understand and catalog enterprise

data

Assess

Overall data quality

Define

Rules and ownership


Validation Rule for

Business Process

Centric Data

Profiling, Advanced

Data Profiling

System landscape

and architecture

metadata

cataloging

(Dependency

analysis, lineage

etc.)

DQM Functionality

for party and

non-party data

(Create/MaintainCle

ansing Packages)

Comprehensive

Business Taxonomy

(Search, tagging,

Ownership etc.)

Data Profiling

DQ Monitoring

Metadata

Analysis

Cleansing

Rules

Business

Term

Taxonomy

Single Solution with Integrated Data Stewardship

Capabilities


Master Data is the “DNA” of the Enterprise

Enterprise MDM

Master data domains

across Business

Applications and

Business Analytics

Line of Business

specific and cross

Line of Business

processes

Cross Value Chain in

Business Network

Enterprise

Master Data

Procurement Supply Chain

CRM PLM

Finance Manufacturing


Lack of Single View Hinders Business Decisions,

Business Processes, and Business Transformation

Lack of single view and data

quality

New systems Complexity to consolidate

existing and new systems

Reporting/analytics Lack of trusted decisions

Business partners Lack of business insight

and collaboration

Lines of business Inefficient business processes

Cloud Complexity to bridge cloud

and corporate master data

Business Impact Diminished revenue and service

Uncontrolled costs

Lack of compliance


Enterprise MDM Capabilities

Centralized ownership

LoB Customer LoB Procurement other LoB

Decentralized ownership

New systems Reporting/analytics Business partners Cloud

LoB Finance LoB Manufacturing

Enterprise Master Data

Consolidation and high

velocity integration

Central creation

Data quality

stewardship

Data quality

continuous

monitoring


Seamlessly Support Key Data Quality Best Practices

Data Quality Management, version for SAP Solutions (DQM for SAP) Improve the quality of customer, partner, and supplier data from within SAP ERP, SAP CRM, and SAP MDG

applications by utilizing SAP DQM’s address cleansing, matching and de-duplication capabilities

Enforce Verify

Real-time data validation

(address reference data

available for 230+ countries)

Batch data cleansing

(ensure ongoing data

accuracy and completeness)

Pre-built best practice data

quality templates

(tuned specifically for SAP

ERP, SAP CRM, and SAP

MDG apps)

Detect pre-existing records

during data loads

(Prospect lists, trade show

leads, webinars, etc.)

Improve

Duplicate record detection

(Potential duplicates are

identified and tracked for best

record resolution)

Clearer, more efficient

customer segmentation

(with the ability to match

on marketing attributes

for SAP CRM)


Automatically Completes and Corrects Entries,

then Presents to User for Approval

In-complete

Address entered.

Automatic

Accurate address

returned in each

address

component


Previously Unknown Entries are Identified,

Before Another Duplicate can be Created

List of pre-existing

entries are presented


9th Oct:


Managing Master Data

A single version of the truth is critical

when governing the data in your

operational systems – whether ERP,

CRM or HCM. Learn how to improve

efficiency and reduce costs across six key

data domains: Customer, Supplier,

Finance, Material, Vendor, and Employee.

Register now ›

bit.ly/1b26WRY

23rd Oct:


Managing Content

Seventy per cent of all data in your

organization resides outside of databases.

By governing unstructured content such as

documents, invoices, notes and images

from directly within your Operational

System, you can reduce costs while

boosting productivity and user adoption.

Register now ›

bit.ly/18nbeRF

6th Nov:


Managing Information Lifecycles

Information Governance is a cradle-to-the-grave exercise. Learn how to understand the data

in legacy systems, migrate it into your Operational System, and decommission legacy

systems. Also discover how to effectively meet regulatory and statutory requirements around

data retention and removal, by managing the entire information lifecycle.

Register now › bit.ly/1dGeXgw

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