keys to master data management

Keys to Master Data Management (MDM)

Effectiveness in the Federal Government Sector

April 23, 2015


Building a path to business value

¡Focus on solving the business problem not the data problem

¡A top down approach to sustain change and measure benefits

¡Establish dependency of specific business processes on high quality data

¡Business functions own data quality to drive business transformation

¡Business assumes ownership over the data ‘Business Case’

¡ IT’s role is one of an enabler of capabilities - not an owner of data

¡A large majority of the root cause of data issues are NOT related to technology

¡Data processes should be standardized to sustain data quality

¡Data standards and definitions are jointly established by functional and technical teams

¡All-encompassing enterprise data projects are difficult to sustain

¡Many effective dataprojects are embedded in largerbusiness transformation efforts

¡Establish a foundation of data capabilities and efficiently apply to multiple domains

1. Solve business problems

2. Establish business ownership

3. Technology is not the cure 4. Deploy in phases


Information and Data Management

Business drivers for MDM in Federal Government sector

Provide official, timely and accurate information about defense operations

Provide the American public with trusted,affordable, universal serviceImprove access to healthcare and provide exceptional patient experience

Maintain stability and public confidence in the nation's financial system

Protect the public health by assuring the safety of food and drugs


Employee• Workforce distribution,

planning, and retention• Benefits administration• Learning, training, and

development

Examples

• Employee ID• Employee names• Addresses• Skills and Experiences

Master data domains critical to mission effectiveness

Product/Service• Supply Chain• Product Spend• Go-to-Market Strategy• Inventory Management• Product Life Cycle

Customer Supplier• Customer 360• Customer Retention• Upsell/Cross-sell• Customer Behavioral

Patterns

• Global Supplier Base• Contracts and Policies• Master Service

Agreements• Managing Supplier

Spend

Example Example Example

• Product/Service ID• Description• Physical Attributes• Suppliers

• Customer Names• Addresses• Contact Information

• Supplier Names• Addresses• Global Identifiers• Tax ID

Location• Retail/Wholesale

Locations• Manufacturing Sites• Distribution Network• Merchandising Traits

Example

• Addresses• Square Footage• Geographical Hierarchies


Master Data Management (MDM) is a discipline focused on effective management of the fundamental data building blocks, shared across multiple business units.

Master Data Management

Data Quality Management

Deloitte’s business driven approach to MDM

View Information as a Strategic Asset

Driven by

Business Value

Linked toStrategic

Objectives

Enabled with Change Leadership


How to get started on the MDM effectiveness?

Measure Business Impact

MDM Model Envisioning

Confirm Enterprise Priorities

Confirm Current Capabilities

Gaps Issue ID

Quick Win Hit ListM

DM

Val

ue A

ppro

ach

Define Strategic Priorities

Rationalize Against

Enterprise Plans

MDM Priority and Roadmap

Align on MDM Capabilities Prioritize MDM Roadmap

Engage Business Stakeholders Map to Data Gaps

RoadmapStrategy

Quick wins

Document Business Impact

Pursue the Low Hanging Opportunities

Identify Key Stakeholders

Where should the focus be for the data

strategy?

What are the measures of maturity for each capability?

What business processes are being

impacted?

What business pain points are critical to

solve?

What is the sequencing of MDM

projects?

What business stakeholders should

have a voice in setting priorities?

What data capability gaps are the root cause of business impacts?

What improvements can be made to the data

management processes, standards?


• Realistic scope and timeline

• Measurable goals

• Consistent use of methodology and approach

• Documented lessons learned

• Relevant data management tools and accelerators

• Relentless focus on value

• Alignment with strategic priorities of the business

• Business ownership and executive sponsorship

• Appropriate training, communication and stakeholder engagement

Competencies for Effectiveness

1. What should be done first?

2. How to balance foundational activities vs. critical business requirements?

3. Where will business engagement and participation come from?

4. What hurdles could impact effectiveness?

Action Plan Items

Day 1 planning for implementation

This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication."

As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.

Copyright © 2015 Deloitte Development LLC. All rights reserved.36 USC 220506Member of Deloitte Touche Tohmatsu Limited

Greg Jones, Director Deloitte Consulting LLPBusiness Intelligence and Data Warehouse Capability Lead

[email protected] | +1 571 882 7625

Rahul Chande, Specialist Leader Deloitte Consulting LLPEnterprise Data Management

[email protected] | +1 703 251 4182

www.deloitte.com/us/about

mailto:[email protected]

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keys to master data management

Technology

data business case

data quality data standards

data problem

owner of data

business ownership

effective data projects

technology data processes

business problems