Jaime Fitzgerald: A Master Data Management Road-Trip - Presented Enterprise Data World 2010

Tales from a Master Data Management Road Trip

March 17, 2010

1:30 – 2:30 pm

Architects of Fact-Based Decisions™

Jaime FitzgeraldArt Garanich

22010-3-17 Enterprise Data World Presentation

Table of Contents

Overview: Why Did We Embark on This Journey?2

Key Landmarks on the Journey3

A Crucial Turning Point: Moving to Execution4

Results: What Makes it All Worthwhile6

Journey of MDM

Transformation

Lessons Learned5

Introduction1


Table of Contents





Journey of MDM

Transformation

Lessons Learned5

Introduction1


Introduction:What Are We Going to Cover Today?

Today, we would like to:

Introduce ourselves

Share our experiences on the “Journey of MDM Transformation”

Share the lessons we’ve learned – what worked well, what didn’t

Answer questions you may have

Encourage others to start their own transformation!


Art Garanich

Who Are We?


25 Years in Technology Focus on legacy modernization Enjoys metaphors and parenting

13 years in Management Consulting Focus on the strategic value of data, and

helping companies profit from it Enjoys cycling and parenting

Private label credit card issuer Subsidiary of Bridgestone Firestone

Boutique strategy consulting firm focused on fact-based decisions

Takes a holistic approach to turning “data into dollars”

About My Company

About Me

Jaime Fitzgerald


Table of Contents

Introduction1





Journey of MDM

Transformation

Lessons Learned5


Before our Journey, the Data Environment at CFNA was “Messy”

CFNA’s data environment was not actively managed…causing pain and tension in many places

Prior to our MDM Transformation, we faced: Multiple platforms Numerous locations of data Limited documentation of:

– Data locations– Data elements– Relationships between elements– Business rules– Business purposes & users of data– Data flow– Existing documentation not always utilized

No holistic view of our customers Extremely time-consuming to pull new information Significant tension between business users, analysts,

and IT staff

Our Legacy Data Environment

This presentation is about our journey to “a better place”


Examples of the Tension “Back Then”

“Our analysis generated millions of dollars in new

value… but it took forever to obtain and clean the data!”

“When I talk to customers I scroll through 12 screens to find the info I

need…then I don’t know where to put the info I capture!”

“Poor data, systems, and product features are holding us back!”

Analytics Team

Sales and Marketing

Operations Functions


Executivesde-prioritized

fact-based decisions

Users didn’t trustexisting reports . . .

Examples of the Tension “Back Then”

So they kept demanding more new reports

They created “homegrown” reports with “surprising results”

“We don’t have data to measure customer value.”

“Why bother asking for

something they can’t do?”

“Before I can tell you what I want from it, I need to know what it

can do!”

“I THINK we should try new

pricing….”

An unhealthy relationship developed between users

and IT…


An Ongoing Journey Towards Improvement

Suffering Ledto Interest

“What is MDM?”“Should I care?”

…Which Led to Desire for A Cure…

“How do we get there?”

…and to a Never-Ending Journey

Towards Better MDM…“Feeling better every day”

1 2 3Phase of Journey

State of Information Landscape:

Results ofCurrent

State:

MDM Knowledge: Low

Data Situation: Messy

Brittle Systems“We can’t change that!”

Complexity Increasing“Here’s a workaround.”

Data Quality: Low

There Is a Cure!

Get Me to It!

Where To?

Let’s Stop the Bleeding …

…And Start with the Basics

MDM Function Setup

MDM Governance in Place

“Show me the Results!”

More confident decisions

More effective system modernization

Reduced operational risk

More transparency

List of Pain Points Growing

Many Pain Points…

Our adventure got underway via three main phases…

“Targeted” Application to Gain:


Table of Contents





Journey of MDM

Transformation

Lessons Learned5

Introduction1


Key Landmarks

Stopping the Bleeding

Getting Buy-in & Alignment

Building the MDM Function

1

2

3

Key Landmark:

Since beginning this journey, we passed four key landmarks…

Turning the Corner to “Targeted Application”

4

Some problems were SO painful and SO immediate, we needed to apply MDM principles “surgically” even before we had a fully fledged MDM function.

For example: building our customer profitability database, we encountered and solved data quality issues and created a “safe route” for data to enable this analysis…

A few early wins on analysis increased the appetite for even better information

The organization recognized the role of MDM in improving information AND agility

The IT department shifted towards more strategic imperatives

We built a new MDM function to define and institutionalize key best practices

Established our policies, standards, governance, and stewardship roles We reached a fork in the road: lots of new knowledge built, where

should we begin applying them?

The list of pain points is long: we realized that we can’t “boil the ocean” We developed a “targeted approach” to applying MDM capabilities Our first successful case: a new Data Warehouse for the growing

analytics team

What it was like:


About “Stopping the Bleeding”

If the skills, experience, andbest practices are missing . . .

You can TRY and FAIL tostop the bleeding . . .

This preserved existing problems with data and created new ones!

New SQL instance withconsolidated data

Led to more misuse of data(right data, wrong use)

Created self-serve data access via Intranet

Data security issues arose“Home-grown data stores”

We had tried many times to fix data-related problems, without addressing the root issues well…


Our First Landmark: “MDM Critical Care” to “Stop the Bleeding”

Diagnosis

1. Request for Change to Systems / Data

2. Workaround Solution

3. Increased Complexity

Systemic Issue:“The Downward Spiral” 1. A Systemic Problem w/ Data Systems.

Frequent symptoms point to a larger problem…with broader root causes.

Change the Way you Manage Data. Manage data as distinct from systems or processes, but keeping in mind the inter-relationships

1. Short-term: stop the bleeding

Symptoms (Systemic)

Immediate Issue:“Toxic Data”

Symptoms (Immediate)

High Stakes Analysis Underway . . .

Data Quality Low

Strategic Growth At Risk

Prescriptions

2. Once bleeding stops: deal with the more fundamental issues

We needed to stop the bleeding before we could resolve the systemic patterns causing them…


Value of Analytics Increases

Our Second Landmark: Gaining Buy-In

Drivers of Buy-In How Buy-In Was “Formalized”

Strategy for Growth

Required more analytics

Required better systems, new products, etc.

High profile “wins”

Desire for more

Creation of MDM function

Establishment of governance

Skills and knowledge built and acquired

Dissatisfaction with Status Quo

We took the time to “connect the dots” in ways that built buy-in for an MDM function…


Our Third Landmark: Building the MDM Function

Establishing the function included creation of 1) the MDM Team itself and 2) the data stewards…

1. Sales & Marketing 2. Operations

Responsible for optimizing the benefits of data at the enterprise level

Reviews and advises on MDM consequences of IT/Business changes

Builds & Maintains MDM function, including:

1) Guiding principles

2) Essential capabilities

3) Documentation

3. Finance 4. Analytics 5. Information Technology

Responsible for optimizing the benefits of data at the departmental level

Responsible for ensuring standard use of data according to MDM principles and standards

Ensures clear business requirements with regard to data elements, usage, business rules, and communication with IT

Data Stewards (Department Level)

MDM Team(Enterprise Level)


Our Fourth Landmark: Turning the Corner to “Targeted Application”

Application of MDM Principles

Pain-Point Identification

Prioritization of Pain Points

Initiative-Level Prioritization

Resource Allocation

Selection of Opportunities

Implementation standards and frameworks

Tools

Integration with SDLC (System Development Lifecycle) and Project Management Standards

To get value from our investment, it was essential to move from theory to execution…


Table of Contents




Lessons Learned5


Journey of MDM

Transformation

Introduction1


Execution

At first, we were overwhelmed with choices . . .

Where to start? What destination first?

Prior to our MDM Transformation, we faced: Multiple platforms Numerous locations of data Limited documentation of:

– Data locations– Data elements– Relationships between elements– Business rules– Business purposes & users– Data flow– Existing documentation not always utilized

No holistic view of our customers Extremely time-consuming to pull new information Significant tension between business users,

analysts, and IT staff

Our Legacy Data Environment


Our Solution: “Work Backwards from the Goal” of ROI on MDM Programs

Applied Case 1

Precondition: Application of MDM Principles in High ROI Ways . . .

Ultimate Goal = Return on Investments in MDM Programs

Case 2 Case 3 Case 4

How Do We “Bridge this Gap”?


“Unpacking the Steps” on the Pathway to ROI . . .

Ultimate Goal = Return on Investment

Apply MDM Principles & Best Practices to High-Impact Use-Cases

Understand Problems it Solves, and Therefore the Value Proposition Understand Concepts, Principles, Application, and High-Level Techniques to Measure Value

Organizational Commitment

Preconditions:

Principles Best Practices

Governance Framework Data Stewardship Roles and Processes

Develop Governance Capability: “How do we manage this?”

Pain-Point Identification Prioritization of Pain Points

Initiative-Level Prioritization Resource Allocation

Capability to Select & Execute on the Best Opportunities

1. Commitment

4. Execution

Implementation Standards and Frameworks Tools

Integration with SDLC (Solution Development Lifecycle) and Project Management Standards

2. Governance

3. Selection


Challenges at Each Stage

Stage (Precondition) Challenges Solutions and Learnings

1. Organizational Commitment

Without broad buy-in, implementation will be “messy”

The link between MDM and business results is not obvious to everyone. Some people NEED specifics to believe in it…

Use specific examples to help people understand the problems MDM solves

Solve a problem right away, even if this happens before a full-fledged program exists

2. Develop Governance Capability: “How do We Manage This?”

There is a lot to learn Governance requires ongoing

commitment Governance alone doesn’t unlock

results

Align governance with OTHER key areas where standards already exist

Link with Knowledge Management

Maximize cross-functional breadth

3. Capability to Select & Execute on the Best Opportunity

Users often report pain points without broader context

The business case for solving individual pain points can be ambiguous

Look for projects with the biggest business benefit AND most likely to benefit from MDM

“Bundle” pain points into the projects that would solve them

4. Apply MDM Principles & Best Practices to High-Impact Use-Cases

Some organizations try to jump right to this point! (the myth of turnkey application)

Even WITH preparation, this is a tough transition to make

A good “toolkit” is essential Facing specifics improves the

frameworks and standards also Getting results maintains

momentum


Our Decision:To Focus our Limited MDM Resources on Building a Better Data Warehouse…

The Data Warehouse will provide consolidated data which enables better strategic decisions

Category Current State Future-State Benefits with Data Warehouse

High Stakes Decisions

Decisions often made with imperfect data

Better data (more accurate, relevant and holistic) will enable better decisions

Efficiency of Analysis

Analysis is time consuming Involvement from IT necessary to

source data

Increased speed of analysis More frequent updates available Fewer resources needed per analysis Analysts will not be accessing operational data,

reducing operational burden

Integration of Sources

Inconsistent data limits ability to use multiple data sources

Combined data will provide holistic view of customer and business

Security Ad-hoc use of data exports is not optimal

Analysts access operational data, causing some risk to systems

Data Warehouse data will mask sensitive customer data

Standard source will limit ad-hoc usage Analysts will not be accessing operational data

Data Clarity Data sources are not documented Inconsistent fields across data

sources

Greater clarity about data thanks to: – Well documented sources– Data management standards– Data dictionaries

Benefits of the Data Warehouse


Table of Contents




Lessons Learned5


Journey of MDM

Transformation

Introduction1


Lesson Learned: Value of Buy-in

Buy-in from the Executive team was essential to moving forward


Lesson Learned: An Iterative Approach Maintains Momentum

Time and Money Invested

Capabilities

↑$

More Capabilities

↑$

Building Capabilities

Applying Capabilities

Target high ROI application Get value Measure value Communicate and promote

Target next opportunity

Get value Measure value

By taking an iterative approach that mixes building and applying capabilities, we’ve found it easier to maintain momentum and buy-in…

Mea

sure

able

Ben

efits

Unl

ocke

d


Lesson Learned: Importance of Capability Building

We had to put in place the basic infrastructure and skills before we could move forward

Develop Basic Knowledge

Data Stewards

Governance Policy, Standards, and Procedures

Develop Basic Skills

MDM Team


Table of Contents




Lessons Learned5


Journey of MDM

Transformation

Introduction1


A Better Pattern: Then vs. Now

Old Pattern

Via a Long

Journey

New Pattern

MDM Function ROI

Pain Points

Business Goals

Business Results

Learnings

1. Request for Change to Systems / Data

2. Workaround Solution

3. Increased Complexity

“The Downward Spiral”


Results: Enterprise-Level Progress!

Our strategy is working, analytics has become a strength, IT is more nimble, and profits are up!

Strategy

Area of Progress:

Analytics

Legacy Modernization

Profit Growth

Growth strategy has gained traction, with new capabilities driving growth in card sales volume, fee revenue, and profits

Confidence in organizational capacity for continued growth is up

Starting with construction of customer profitability analytics, the team has unlocked tens of millions of dollars in new profit growth

Analytics team has grown from one person to six (and from a team to an official function!)

We have begun phased legacy modernization that will enable more strategic growth

Our MDM capabilities will be essential to this modernization initiative

Despite the economic crisis, we achieved record sales and profits this year While regulatory uncertainty has increased this year, our analytic

capabilities are helping us to rapidly adapt…


Continue the Journey with Us!


Art Garanich Jaime Fitzgerald

[email protected]

917-846-3759

[email protected]

216-362-3418

Our journey continues…we hope to stay in touch with you, our “fellow travelers,” to learn from each other and improve results!