Master Data Management Webinar

H O W T O G E T Y O U R M D M P R O G R A M U P & R U N N I N G

Introduction:

My blog: Information Management, Life & Petrolhttp://infomanagementlifeandpetrol.blogspot.com

@InfoRacer

uk.linkedin.com/in/christophermichaelbradley/

Christopher Bradley

Chief Data Officer

FROMHEREON

Introduction To Chris Bradley

Chris is the Global Chief Data Officer of FromHereOn (FHO).

FromHereOn is an Enterprise Design consultancy. We help leaders

of global organisations discover and develop a vision for

meaningful change. Then we partner on the journey to make it

real.

With 34 years experience in the Information Management field,

Chris works with leading organisations including Total, Barclays,

ANZ, GSK, Shell, BP, Statoil, Riyad Bank & Aramco in Data

Governance, Information Management Strategy, Data Quality &

Master Data Management, Metadata Management and Business

Intelligence.

He is a Director of DAMA- I, holds the CDMP Master certification,

examiner for CDMP, a Fellow of the Chartered Institute of

Management Consulting (now IC) member of the MPO, and SME

Director of the DM Board.

A recognised thought-leader in Information Management Chris is

creator of sections of DMBoK 2.0, a columnist, a frequent

contributor to industry publications and member of standards

authorities.

He leads an experts channel on the influential BeyeNETWORK, is a

regular speaker at major international conferences, and is the co-

author of “Data Modelling For The Business – A Handbook for

aligning the business with IT using high-level data models”. He also

blogs frequently on Information Management (and motorsport).

Recent PresentationsEnterprise Data & Business Intelligence 2014: (IRM), November 2014, London, UK

“Data Modelling 101 Workshop”

Enterprise Data World: (DataVersity), May 2014, Austin, Texas, “MDM Architectures &

How to identify the right Subject Area & tooling for your MDM strategy”

E&P Information Management Dubai: (DMBoard),17-19 March 2014, Dubai, UAE

“Master Data Management Fundamentals, Architectures & Identify the starting Data

Subject Areas”

DAMA Australia: (DAMA-A),18-21 November 2013, Melbourne, Australia “DAMA

DMBoK 2.0”, “Information Management Fundamentals” 1 day workshop”

Data Management & Information Quality Europe:

(IRM Conferences), 4-6 November 2013, London, UK

“Data Modelling Fundamentals” ½ day workshop:

“Myths, Fairy Tales & The Single View” Seminar

“Imaginative Innovation - A Look to the Future” DAMA Panel Discussion

IPL / Embarcadero series: June 2013, London, UK, “Implementing Effective Data

Governance”

Riyadh Information Exchange: May 2013, Riyadh, Saudi Arabia,

“Big Data – What’s the big fuss?”

Enterprise Data World: (Wilshire Conferences), May 2013, San Diego, USA, “Data and

Process Blueprinting – A practical approach for rapidly optimising Information Assets”

Data Governance & MDM Europe: (IRM Conferences), April 2013, London, “Selecting

the Optimum Business approach for MDM success…. Case study with Statoil”

E&P Information Management: (SMI Conference), February 2013, London,

“Case Study, Using Data Virtualisation for Real Time BI & Analytics”

E&P Data Governance: (DMBoard / DG Events), January 2013, Marrakech, Morocco,

“Establishing a successful Data Governance program”

Big Data 2: (Whitehall), December 2012, London, “The Pillars of successful knowledge

management”

Financial Information Management Association (FIMA): (WBR), November 2012,

London; “Data Strategy as a Business Enabler”

Data Modeling Zone: (Technics), November 2012, Baltimore USA

“Data Modelling for the business”

Data Management & Information Quality Europe: (IRM), November 2012, London;

“All you need to know to prepare for DAMA CDMP professional certification”

ECIM Exploration & Production: September 2012, Haugesund, Norway:

“Enhancing communication through the use of industry standard models; case study

in E&P using WITSML”

Preparing the Business for MDM success: Threadneedles Executive breakfast briefing

series, July 2012, London

Big Data – What’s the big fuss?: (Whitehall), Big Data & Analytics, June 2012, London,

Enterprise Data World International: (DAMA / Wilshire), May 2012, Atlanta GA, “A Model Driven Data Governance Framework For MDM - Statoil Case Study”“When Two Worlds Collide – Data and Process Architecture Synergies” (rated best workshop in conference); “Petrochemical Information Management utilising PPDM in an Enterprise Information Architecture”

Data Governance & MDM Europe: (DAMA / IRM), April 2012, London, “A Model Driven Data Governance Framework For MDM - Statoil Case Study”

AAPG Exploration & Production Data Management: April 2012, Dead Sea Jordan; “A Process For Introducing Data Governance into Large Enterprises”

PWC & Iron Mountain Corporate Information Management: March 2012, Madrid; “Information

Management & Regulatory Compliance”

DAMA Scandinavia: March 2012, Stockholm, “Reducing Complexity in Information Management” (rated best presentation in conference)

Ovum IT Governance & Planning: March 2012, London; “Data Governance – An Essential Part of IT Governance”

American Express Global Technology Conference: November 2011, UK, “All An Enterprise Architect Needs To Know About Information Management”

FIMA Europe (Financial Information Management):, November 2011, London; “Confronting The Complexities Of Financial Regulation With A Customer Centric Approach; Applying IPL’s Master Data Management And Data Governance Process In Clydesdale Bank “

Data Management & Information Quality Europe: (DAMA / IRM), November 2011, London, “Assessing & Improving Information Management Effectiveness – Cambridge University Press Case Study”; “Too Good To Be True? – The Truth About Open Source BI”

ECIM Exploration & Production: September 12th 14th 2011, Haugesund, Norway: “The Role Of Data Virtualisation In Your EIM Strategy”

Enterprise Data World International: (DAMA / Wilshire), April 2011, Chicago IL; “How Do You Want Yours Served? – The Role Of Data Virtualisation And Open Source BI”

Data Governance & MDM Europe: (DAMA / IRM), March 2011, London, “Clinical Information Data Governance”

Data Management & Information Management Europe: (DAMA / IRM), November 2010, London, “How Do You Get A Business Person To Read A Data Model?

DAMA Scandinavia: October 26th-27th 2010, Stockholm, “Incorporating ERP Systems Into Your Overall Models & Information Architecture” (rated best presentation in conference)

BPM Europe: (IRM), September 27th – 29th 2010, London, “Learning to Love BPMN 2.0”

IPL / Composite Information Management in Pharmaceuticals: September 15th 2010, London,“Clinical Information Management – Are We The Cobblers Children?”

ECIM Exploration & Production: September 13th 15th 2010, Haugesund, Norway: “Information Challenges and Solutions” (rated best presentation in conference)

Enterprise Architecture Europe: (IRM), June 16th – 18th 2010, London: ½ day workshop; “The Evolution of Enterprise Data Modelling”

Recent Publications

Book: “Data Modelling For The Business – A Handbook for aligning the business with IT using high-level data models”; Technics Publishing;

ISBN 978-0-9771400-7-7; http://www.amazon.com/Data-Modeling-Business-Handbook-High-Level

White Paper: “Information is at the heart of ALL Architecture disciplines”,; March 2014

Article: The Bookbinder, the Librarian & a Data Governance story ; July 2013

Article: Data Governance is about Hearts and Minds, not Technology January 2013

White Paper: “The fundamentals of Information Management”, January 2013

White Paper: “Knowledge Management – From justification to delivery”, December 2012

Article: “Chief INFORMATION Officer? Not really” Article, November 2012

White Paper: “Running a successful Knowledge Management Practice” November 2012

White Paper: “Big Data Projects are not one man shows” June 2012

Article: “IPL & Statoil’s innovative approach to Master Data Management in Statoil”, Oil IT Journal, May 2012

White Paper: “Data Modelling is NOT just for DBMS’s” April 2012

Article: “Data Governance in the Financial Services Sector” FSTech Magazine, April 2012

Article: “Data Governance, an essential component of IT Governance" March 2012

Article: “Leveraging a Model Driven approach to Master Data Management in Statoil”, Oil IT Journal, February 2012

Article: “How Data Virtualization Helps Data Integration Strategies” BeyeNETWORK (December 2011)

Article: “Approaches & Selection Criteria For organizations approaching data integration programmes” TechTarget (November 2011)

Article: Big Data – Same Problems? BeyeNETWORK and TechTarget. (July 2011)

Article “10 easy steps to evaluate Data Modelling tools” Information Management, (March 2010)

Article “How Do You Want Your Data Served?” Conspectus Magazine (February 2010)

Article “How do you want yours served (data that is)” (BeyeNETWORK January 2010)

Article “Seven deadly sins of data modelling” (BeyeNETWORK October 2009)

Article “Data Modelling is NOT just for DBMS’s” Part 1 BeyeNETWORK July 2009 and Part 2 BeyeNETWORK August 2009

Web Channel: BeyeNETWORK “Chris Bradley Expert Channel” Information Asset Management

http://www.b-eye-network.co.uk/channels/1554/

Article: “Preventing a Data Disaster” February 2009, Database Marketing Magazine

chris.bradley@fromhereon.com

@inforacer

uk.linkedin.com/in/christophermichaelbradley/

+44 7808 038 173

infomanagementlifeandpetrol.blogspot.com

Chris BradleyChief Information Architect

E N T E R P R I S E D E S I G NWe call this new capability Enterprise Design, by combining design

thinking with the human value of information and the scale of

enterprise architecture, we take a people centered approach to

transform large organizations and build better consistency,

efficiency, simplicity and experiences.

This approach ensures people and their motivation to realize a vision

worthy of their passion remain at the heart of major change

initiatives, from concept right through to delivery.

Uniquely FHO combines Service Design, Information Management

and Enterprise Architecture capabilities to enable transformation

end-to-end, from strategy development, roadmap design, costing

& estimation, business case development, through to program

management and project level architecture and design services.

Enterprise DesignB U S I N E S S T R A N S F O R M A T I O N

Service DesignHUMAN-CENTERED

With a people-oriented design approach we are able to better

connect individuals with what needs to be achieved for customers

and how their role contributes to make it happen.

Enterprise ArchitectureENTERPRISE-SCALE

By taking a whole-of-enterprise view we are able to overcome issues

of complexity and bridge the implementation gap between

strategic planning and what really happens on the ground.

Information ManagementINFORMATION-ENABLED

Simplify the language of the business, collaborate more seamlessly

at an enterprise-scale, invest in data as an asset and enable more

personalized customer experiences.

BUSINESS-LED

HUMAN-CENTERED

ENTERPRISE-SCALE

INFORMATION-ENABLED

Reference & Master Data Management

DATAARCHITECTUREMANAGEMENT

DATADEVELOPMENT

DATABASEOPERATIONS

MANAGEMENT

DATA SECURITYMANAGEMENT

REFERENCE & MASTER DATAMANAGEMENT

DATA QUALITYMANAGEMENT

META DATAMANAGEMENT

DOCUMENT & CONTENTMANAGEMENT

DATA

WAREHOUSE & BUSINESS

INTELLIGENCE MANAGEMENT

DATA

GOVERNANCE

› Enterprise Data Modelling› Value Chain Analysis› Related Data Architecture

› External Codes› Internal Codes› Customer Data› Product Data› Dimension Management

› Acquisition› Recovery

› Tuning› Retention› Purging

› Standards› Classifications› Administration› Authentication› Auditing

› Analysis› Data modelling› Database Design› Implementation

› Strategy› Organisation & Roles› Policies & Standards› Issues› Valuation

› Architecture› Implementation› Training & Support› Monitoring & Tuning

› Acquisition & Storage› Backup & Recovery› Content Management› Retrieval› Retention

› Architecture› Integration› Control› Delivery

› Specification› Analysis› Measurement› ImprovementReference &

Master Data Management

C O N T E X T ( D M B O K )

What is Event / Transaction Data?

“Bob bought a Mars bar from Morrison's on Monday 3rd Jan at 4pm and paid using cash.”

E V E N T D A T A E X A M P L E :

WHO WHAT WHERE WHEN HOW QUANTITY AMOUNT

Bob Bobson Mars bar Morrison's, Bath 16:00 Monday

3rd January 2011

Cash 1 £0.60

CUSTOMER

CODE

PRODUCT

CODE

VENDOR

CODE

DATE PAYMENT

METHOD

QUANTITY AMOUNT

BB005 CONF101 WMBATH 2011-01-03 16:00 CASH 1 £0.60

Terminology

FIELD (or attribute): column in a database table

RECORD: row in a database table

About Event Data

AKA Transaction data

Describes an action (a verb)E.g. “buy”

May include measurements about

the action:

› Quantity bought

› Amount paid

Does not include information:

describing the nouns:

› Bob Bobson is male, aged 25

and works for British Airways

› Monday 3rd Jan 2011 is a bank

holiday

› The address of Morrisons Bath

is: York Place, London Road,

Bath, BA1 6AE.

Includes information:

identifying the nouns that were

involved in the event

(the Who / What / Where / When

/ How and maybe even the Why):

› Bob Bobson

› Mars bar

› Morrisons, Bath

› 16:00 Monday 3rd Jan 2011

› Cash

What is…

MASTER DATA?

› Defines and describes the nouns

(things) of the business.e.g. Field, Well, Rig, Product, Store,

Theraputic Area, Adverse Event, etc.

› Data about the “things” that will

participate in events.

› Provides contextual information about

events / transactions.

› Stored in many systems

› Packaged Systems

› Line of Business Systems

› Spreadsheets

› SharePoint Lists

MASTER DATA MANAGEMENT

(MDM)?

› The ongoing reconciliation and

maintenance of master data.

› Control over master data values to

enable consistent, shared, contextual

use across systems, of the most

accurate, timely, and relevant version

of truth about essential business

entities.

[DAMA, the Data Management

Association]

MASTER DATA MANAGEMENT

(MDM)?

› Comprises a set of processes and

tools that consistently defines and

manages the non-transactional data

entities of an organisation.

[Wikipedia]

Master Data – What’s the problem?

No organisation has just one system

(unless the are tiny)

Details about the same noun are found in

multiple systems, e.g. Customer

Problems

Data may need to be rekeyed in each system

Systems may not be in synch (new records, updated

records)

Duplicate data: are “ABC Ltd” and “ABC Limited” the

same thing?

No single version of the truth

Reporting / Analysis: difficult to combine data from

multiple systemsThe same customers may be defined in:

• Finance systems

• Marketing systems

• Line of business systemsS O L U T I O N :

Master Data Management!

MDM Architectures

Standard “Hub” architectures

1. REPOSITORY

2. REGISTRY

3. HYBRID

4. VIRTUALISED

*A key difference is the

number of fields that are

stored centrally

Example: Customer

Customer

code

First

name

Last

name

Date of birth Preferred delivery

address line 1

Preferred

delivery address

post code

Credit

rating

Occupation Car

BB005 Bob Bobson 1985-12-25 Royal Crescent BA1 7LA A Information

Architect

Audi R8

I D E N T I F I E R S

C O R E F I E L D S

A L L F I E L D S

ALL FIELDS Repository

CORE FIELDS Hybrid

IDENTIFIERS Registry

NONE Virtualised

Select your MDM Architecture

and Toolset carefully

A physical hub is not the

“only” way...

Select your MDM Architecture and Toolset carefully

A HUB IS NOT THE ONLY WAY.. .

Typical MDM Capabilities

DATA INTEGRATION

& ACQUISITIOND

ata

D

iscovery

& In

take

Con

solid

ati

on

Da

ta

Qu

ality

MA

STE

R D

ATA

SER

VIC

ES

AC

CESS C

ON

TRO

L

DATA DELIVERY

User

In

terf

ace A

pplica

tion

Inte

gra

tion

Bu

sin

ess

Serv

ices

MASTER DATA “HUB”

MDM Architecture

Master Data Models

Reference Data

Metadata Management

Business Rules

Hierarchy Management

Master Data “Repository”

D A T A S Y N C H R O N I S A T I O N

O P E R A T I O N A L M A N A G E M E N T / D A T A G O V E R N A N C E & S T E W A R D S H I P

MDM… A Hub is not the only way

MASTER DATA CONTRIBUTORS

ERP CRM LEGACY

MIDDLEWARE SYNCHRONISATION LAYER

Synchronized Master

ERP CRM LEGACY

EXTRACT-TRANSFORM-LOAD

SYNCHRONISATION LAYER

Hub Based Master

OPERATIONALDATA-STORE

E.G. CUSTOMERMASTER

Operational Hub structure that overlaps operational and

analytical environments

Supports concept of an Enterprise Data Warehouse

Multiple systems acting as data providers

Appropriate for low data latency and velocity operations

Requires careful data quality management

Multiple operational systems acting as master data

contributors

Real-time information availability

Well suited to enterprises where data is stored across

multiple source systems

Well suited to low data velocity operations

MDM…A Hub is not the only way

SINGLE DATA

SOURCE

ERP CRM LEGACY

SYNCHRONISATION LAYER

Application Specific Master

ERP CRM LEGACY

SYNCHRONISATION LAYER

Master Overlay

INDUSTRY SPECIFICMASTER

Stand-alone, application-neutral master data

Industry-specific data model

Well suited to vertical industries in aligning front-office &

back-office systems in real time

One operational system as master data provider

Well suited to enterprises where data is primarily stored

in a single source system

Support from many enterprise vendors

MDM…A Hub is not the only way

Non

SAP

CRM

LEGACY

Real Time Data Movement

SAP 2

SAP 3

SAP 1

DW

DSL

REPORTS

MESSAGING

Data Virtualization (Federated) Master Data

DV (FEDERATED) MASTER DATA

MASTER

DATA

DATABASES

ORACLE

SAP

SIEBEL

PACKAGES

…..

…..

…..

…..

…..

…..

FILES XML

Virtual MDM hub created via DV layer

DV layer informed from Logical Data Model

Powerful data integration to access multiple disparate systems

Rapid time to solution

Outstanding prototyping, proof of value approach

Compliments other Data Integration approaches

Data is moved between the various systems using a

messaging integration hub or ESB

Data movement is done in real time

Movement of data can be one or two way as required

Complete DV Master Data View

MDM applications alone frequently

cannot fully support all requirements as

data frequently exists outside of MDM hub

Complementary data integration solutions

are needed to deal with data maintained

outside of MDM hubs often in complex,

disparate data silos

DV can extend the Master Data and

provide a complete 360o view by using

master data from the hub as the foreign

key to quickly and easily federate master

data with additional transactional and

historical data to get a complete single

view of master data

Complete DV Master Data View

ORACLE

SAP

SIEBEL

…..…..…..

…..…..…..

ETL SERVER

MASTER DATAMASTER

DATAMASTER DATA

Existing Master Data Hub

COMPLETE 360° VIEW OF MASTER DATA

Single Domain & Multi Domain MDM

Eg Product (PIM), Customer (UCM), Vendor,

Laboratory (LIM)

Incorporate specific “domain” features …

› House holding

› Address chaining

› Company Hierarchies

› Tailored data matching (deterministic or

probabilistic)

Engineered to exploit 3rd party data sources

› GB PAF, USPS Zip+4, Electoral Roll, CCJ …

› D&B, Liquidations, Companies House, …

› CAS, COSHH, …

Interfaces to domain LoB apps

S I N G L E D O M A I N

Highly configurable MDM solutions

Informed by Data Model

Fewer specific data domain features

Interfaces to mainstream apps

Results in fewer MDM solutions throughout

the Enterprise

M U L T I D O M A I N

Reference vs Master Data

Reference Master

Number of Values Low, Fixed/Known Medium-High,

Variable/unknown

Volatility Stable, Low rate of change Medium-Frequent rate of

change

Source External (mostly); Standards

bodies

Internal (mostly)

Ease of Governance Easy Harder, Higher number of

stakeholders

Number of Attributes per data

area

Very low; typically code

type/value/description

High

Federation/ownership of

attributes per business area

None (all attributes) Much federation: e.g..

Business Area A masters

Attribute 1/Attribute 2,

Business Area B masters

Attributes 3/4/5

Tool Cost Low (ref data only) High (MDM tools often have

ref-data management also)

Aligning MDM with Business Program

A L I G N M D M I N I T I A T I V E S , P R O C E S S E S A N D R E C O M M E N D A T I O N S F O R

T E C H N O L O G Y W I T H C O R P O R A T E A N D B U S I N E S S U N I T S T R A T E G Y

Be

nef

its$

# projects / reused objects

Portfolio planning / design for reuse

Project by project / without reuse

Design for reuse: First projects hit a “cost” as there is nothing in place

that can be re-used / leveraged for

benefit.

Project based accounting

discourages infrastructure

investment.

Seed Money: To not penalise initial projects, but rather encourage them to do the “right

thing” for the corporation, seed money helps

with provision of resources, budget offset etc

Design for reuse: Once a few reusable artefacts, models, Master Data

objects, reusable methods, skills etc

are established, projects start to reap

big benefits

Design in isolation: Initially no interaction outside the confines of “the

project” and just a few interfaces will

appear attractive as no wider

considerations need to be made

Design in isolation: Costs increase dramatically with Increasing number

of point to point interfaces, undo-

redo work as clashes about data

concepts explode.

Portfolio vs Per Project

MDM Approach: Align With a "Lead" Business ProjectThink Big & Execute Small

P H A S E S

E X P L O R E E X E C U T E M A N A G E

E N T E R P R I S E I N F O R M A T I O N M A N A G E M E N T P L A N

M D M & D A T A A S S E T P L A N

P R I N C I P L E S M A S T E R D A T A I M P L E M E N T A T I O N

Master &

Reference

Data

Management

Data

Warehousing

Business

Intelligence

Transaction

Data

Management

Semi-

Structured

Data

Management

Content &

Document

Management

Data

Integration &

Interoperability

Data

Quality

Management

Information

Lifecycle

Management

Data

Governance

Data

Asset

Planning

EIM

Goals &

Principles

Big

Data

Analytics

Data Models

& Taxonomy's

Metadata

Management

Geospatial

Data

Management

Consider MDM within the context of ALL Information Dimensions (our EIM Framework)

Business-Driven Goals

Drive a Robust

Enterprise

Information

Management Practice

EIM goals and strategies are business-driven for the

entire enterprise, underpinned by guiding

principles supported by senior managementProactive planning for the information lifecycle

including the acquisition, manipulation, access,

use, archiving & disposal of information

The identification of appropriate data

integration approach for business challenges

e.g. ETL, P2P, EII, Data Virtualisation or EAI.

The full lifecycle control and

management of information from

acquisition to retention & destruction

Organise information to align

with business & technical goals

using Enterprise, Conceptual,

Logical & Physical models

Roles, responsibilities, structures and

procedures to ensure that data

assets are under active stewardship

Processes, procedures and

policies to ensure data is fit

for purpose and monitored

Metadata capture,

management, & manipulation

to place data in business &

technical context

Manage diverse data sources across the

organisation from transaction data

management, to data warehousing and

business intelligence, to Big Data analytics

Statoil MDM challenges

Lack of Meta and Master data within and across

environments

Silo oriented/stand alone applications

Master Data Management established in different

processes e.g.:

› Exploration

› Marketing and Supply

› Supply Chain Management

› Finance and Control

› Human Resources

› Service Management

W H A T I S T H E “ M A S T E R D A T A ”

T O B E M A N A G E D ?

85% of SCM Service incidents

due to “master data” errors

FINANCE

Cost Centre

Account

Profit Centre

Wbs

Etc.

HUMAN RESOURCE

Employee

Organisation

Position

SERVICE

MANAGEMENT

Assignment Groups

Services

Etc.

SUPPLY CHAIN

MANAGEMENT

Material

Service

Vendor

MARKETING &

SUPPLY

Customer

Vendor

Product

SUBSURFACE

Licence

Well, field

Reservoir

Country

Etc.

Statoil MDM challenges

W H A T I S T H E “ M A S T E R D A T A ”

T O B E M A N A G E D ?

Location

Wells

Field

License

Location

Tag

VendorPipeline

Projects

Processes

Applications

Roles, position

Org. unit

Employee

Service

G E O G R A P H I C A L I N F O R M A T I O N ( G I S )

M E T A & M A S T E R D A T A

Subsurface

InformationBI / DW Data

Admin.

Information

Marketing &

Supply

Information

Operation &

Maintenance

Information

Project

Development

Information

C O L L A B O R A T I O N I N F O R M A T I O N

Structured

Unstructured

Statoil MDM challenges

Drilling and Wells (Well Master)

Global licence/lease information project

Supply chain management

Marketing, processing and renewable energy

MapIT project (LCI information)

Management system project

Environmental reporting project

Collaboration project

Enterprise content management project

W H A T B U S I N E S S P R O J E C T S A R E D R I V I N G

T H E N E E D F O R A C O R P O R A T E A P P R O A C H

T O M D M ?

How can we build a

business case for

Master Data Management?

Master Data Management Maturity

LEVEL 1 - INITIAL LEVEL 2 - REPEATABLE LEVEL 3 - DEFINED LEVEL 4 - MANAGED LEVEL 5 - OPTIMISED

Limited awareness of

MDM.

Master Data domains

have not been defined

across the enterprise.

Silo based approach to

data models (where

models exist) results in

multiple definitions of

potential master data

entities, such as

customer or product.

The impact of master

data issues gain

recognition within the

enterprise.

Limited scope for

effective management

of master data due to

lack of Data

Governance &

Ownership Model.

Project or department

based initiatives

attempt to understand

the enterprise's master

data.

No MDM strategy

defined.

Definition of MDM

strategy in progress.

Master data domains

identified.

Several domains are

targeted for delivering

master data to specific

applications or projects.

Differing software

products may be

adopted in these silos

for MDM.

Senior management

support for MDM grows.

Recognition of need to

develop or align with

Data Governance

model.

A complete MDM

strategy has been

defined and adopted.

MDM joined up with

data governance and

data quality initiatives.

Robust business rules

defined for master data

domains.

Data cleansing and

standardisation

performed in the MDM

environment.

Specific products

adopted for MDM.

Master data models

defined.

A full integrated MDM

environment exists and

has been adopted

across the enterprise for

all key master data

domains.

The MDM environment

controls access to

master data entities.

Many applications

access the MDM

environment through a

service layer.

Business users are fully

responsible for master

data.

AS-IS TO-BETRANSITION PLAN

INTERIM

Statoil Enterprise Models

Business partner

Statoil Enterprise Data Model

Exploration ( DG1) & Petroleum technology (DG1-DG4)

Seismic Wellbore data

Geological & reservoir models

Production

volumes

ReservesTechnical info (G&G reports)

License

Contractors

Supply chain

Inventory

Requisitions

Agreements

IT

Administrative info

Operation and Maintenance

Petroleum

technical data

Corporate Executive Committee

Operations

Government

Marketing & Supply

Contract

Price

Email

Operation

assurance

Delivery

Finance & Control

Perform reporting

Production, License split (SDFI), Invoice

Management

system

Governing doc.

SDFI

Customer

Drilling & well technology ( DG4)

Drilling data

Monitoring data

IT inventory

Geography

IT project portfolio

LogisticsProject portfolio

(Business case)

Global ranking Redeterminations

Reservoir mgmt plans

Maintenance program

Material master

Technical information (LCI)

Risk information

Archived info

Mgmt info (MI)

Vendor Vendor

Authorities

Partners

Directional data

Process area

Equipment monitoring

Contract

Deal

Market info

Profit structure

Invoice

Volume

Commodity

Invoice

Position and risk result

Delivery

Monitoring plan

Operating model

Human

Resources

Health, Safety &

EnvironmentHealth info Safety info

HSE Risk Incidents

Attraction information Security info Env. info

Emergency info

Plant

Project portfolio

Drilling candidates Master drilling plan

Drilling

plans Well construction

Project development Technical concepts Facility def. package Technology qualifications

Quality planProject framing Project work planWBS Manpower projection planProject portfolio

CD&E:

Management system Values

Variation orders

Project documentation

GSS O&P

Financial transactions

Financial reports Fin planning

Calendar

Investment analysis

Fin authorities

Operation profit

IM/IT strategies

Estimates Risk register Document plan

Credit info

Supply plan

Refining plan

Lab analysis

Contact portfolio

Financial results

Legal

Company register

Service Management

Service catalogue

Ethics &

anti-corruption

Corp. social resp.

Social risks and impacts

Governing body doc

Integrity Due

Diligence reportsSustain. rep CSR plans Enquiries Agreements

Technology

dev.R&D portfolio

IPR register

Communication

Brand

Authority information

Facilities

Real Estate

Access info

Country analysis

Risk

Corp risk

Business continuity plans

Insurance

Organisational info

Capital Value Process

Business planning DG0 Feasibility DG1 Concept DG2 Definition DG3 Execution DG4 Operation

Post Investment ReviewBenchmarkingDecision Gate Support Package Decision memo Project infoBusiness Case Leadership Team infoBusiness case

Functional location (tag) Volume monitoring

Version 21-Jan-2011

Investment project structure: PETEC, D&W, FM, OM

Perf. and reward info

A yellow background indicates that the information subject area contains Enterprise Master Data

Maintenance projects

Statoil Enterprise Master Data Model

Why Producea Model?

_ The Business NEEDS a common

vocabulary for communication

_ Clarify terms, collect synonyms

(& homonyms)

_ Understand current situation WRT owners,

stewards (prepare to be horrified!)

_ XREF data concepts to current systems

_ It works best if you don’t talk about

“data modelling”

It’s NOT “The Field of Dreams”

_ Statoil projects cannot afford to wait for

Master Data to be delivered

_ Subsets of the Master Data must be delivered “just in

time” as the Business projects need to use them

_ This is NOT “The Field Of Dreams”

_ This means aligning the MDM initiatives with the Business

Projects

In E&P in general, managing voluminous

complex data types involves compromise

and ‘creaming off.’

E&P data management is about

compromise and the art of the possible.

Understand Corporate Plan

Y E A R 3 Y E A R 4 Y E A R 5Y E A R 2Y E A R 1

SUBSEA HARMONISATION

PLANT INTEGRITY

SEISMIC INTERPRETATION

ADVANCED FIELD MANAGEMENT

PROGRAMME X

PROGRAMME Y

Catalog Current Initiatives

U S I N G T H E P R O J E C T P O R T F O L I O

Decision gate: Where is the initiative in the life project process right now?

Owner: Which Business area owns this initiative?

Item Name: What’s the internal name of the project / program / initiative?

Business Data Objects: What (in their own terms) are the Business Data “things” affected by this program?

Interest: How willing to engage with MDM initiative is this project?

Importance: How important to the MDM initiative is this Data area?

Forget: Timescales, level of engagement, strategic importance wrong. “Train has left the station”

Improbable: Timescales for Business initiative too tight to successfully introduce MDM without

adversely affecting Business programme.

Stretch: Good engagement, good strategic fit, tight timescales. Spiking in resources immediately can

make these data areas fly.

Prime Candidates: Great engagement, good strategic fit, ok timescales & widely usable Data

subject areas.

Prioritise by multiple criteria( W I L L I N G N E S S T O E N G A G E , F E A S I B I L I T Y ,

T I M E S C A L E S , I M P O R T A N C E )

Harmonise & Xref with Data Model

Prioritise by interest

Plan Big – implement small

Business Initiative / Project 1

Some of MD area A

needed here

Some of MD area B needed here

Business Initiative / Project 2

More of MD area A

needed here

Some of MD area C needed here

More of MD area B needed here

Business Initiative / Project 3

More of MD area C

needed here

More of MD area B needed here

More of MD area A needed here

Business Initiative / Project 4

Lots of MD area D

needed here

More of MD area B needed here

More of MD area A needed here

Project4 later includes MD for

area D

MDM program cannot deliver Data Subject Area D at this time

for Project 4.Project 4 gains exemption to add

this MD later

IN THE CONTEXT OF THE BIG PICTUREIMPLEMENT MDM IN ALIGNMENT WITH BUSINESS INTITIATIVES

MDM Dashboards›BATCH

ROR PENETRATION

ACTIVE BATCHES:

GLOBAL TARGET:

55,000

508,000

NEXT STEPS Poland manufacturing facility

2Q 2013 penetration 20%

XYZ Commercial go-live

3Q 2014 100% Complete

DEFINITION:

CompleteSubject to cross segment

review

ROR PROFILE

MDM Process

Data ModellingData

GovernanceData Quality

ManagementMDM Service

Initial Conceptual Data Model in place

Some Data Stewardship in place (tbc)

Profiling performedon XYZ data and

ABC

Batch ID Service in POC

Data Quality Criteria

Accuracy Coverage Currency

Data OwnerData

Steward(s)DG Process

MDM Platform

Go Live Date

Mary Berry (R&D) John Smith & ANO (R&D)

TBD Manufacturing

Defined, still subject to

agreement in Manufacturing

SAP MDM April 2013 subject to

successful POC in XYZ

SCOPE: Tracking of batch identifiers and genealogies for any type

of XYZ development and/or manufacturing batch of

interest to the R&D and Manufacturing organisations.

BUSINESS DRIVER: Projects need to confront the challenge of synching up

R&D and Manufacturing process and analytical

measurement data as movement of materials within the

company often results in batches being registered and

assigned a new Batch ID in multiple IT systems. To resolve

this involves many hours extracting data from R&D and

Manufacturing lab systems, linking common fields across

spreadsheets, and connecting multiple, duplicate Batch

ID#s.

Currently there is no central batch identification for

Biological substance batches, this primarily being recorded

in lab notebooks. This prevents easy traceability of

biological substances through a substance id back to their

original batch.

MDM PROJECT PROCESS

Conclusion

MATURITY OF MDM ESTABLISHED IN DIFFERENT PROCESSES

DATA GOVERNANCE MATURITY

INFORMATION SYSTEMS

MDM Challenges & Considerations

DETERMINING THE “MASTER DATA” TO BE MANAGED

› Not simply the “usual” suspects: Customer, Product, Location, etc.

› MD frequently also covers Agreements, Patents, Trade Marks, Licenses …

› How do you make the case for MDM?

LACK OF CONSISTENCY

› Definition & meaning (can a Supplier also be a Customer?)

› Presence & level of metadata

› Silo oriented/stand alone applications

› Data Quality

› “The key to successful master data management is management support for relinquishing local control of shared data.” [DAMA]

› Service Management

› HR, Finance, etc…

› Master Data for most domains span the business

› Data Ownership & Stewardship

› Who has the wisdom of Solomon?

› Do multiple business systems require update to the master data?

› What are the conflict resolution rules? (Did I mention Data Governance)

› Is a decoupled Master Data Hub sufficient?

› Which MDM pattern is appropriate?

Conclusions

Don’t believe you can

“build it and they will come”An MDM initiative needs to be just

ahead of the business projects &

deliver just in time aligned to the

business initiatives.

Data models for MDM

programs are essentialExtended with rich metadata

including Ownership, Source

systems, Transformations etc.

Beware the hype on MDM

technologiesA hub is NOT the only way.

Rarely will one MDM technology

be appropriate for ALL Data

Subject Areas.

Governance is vitalMDM initiatives cannot be successful

without addressing Data Governance

for that data subject area.

chris.bradley@fromhereon.com

@inforacer

uk.linkedin.com/in/christophermichaelbradley/

+44 7808 038 173

infomanagementlifeandpetrol.blogspot.com

Chris BradleyChief Data Officer

N E W Y O R KThe Seagram Building375 Park Avenue, Suite 2607,New York City, NY 10152, U.S.A

+1 212 634 4834

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