Unlocking Master Data Management (MDM) Success: Real-World Insights and Strategies

| @ema_research
Dan Twing
President and COO
Enterprise Management Associates (EMA)
Steven Lin
Product Marketing Manager
Semarchy
Unlocking Master Data
Management (MDM)
Success: Real-World Insights
and Strategies

| @ema_research 2
Watch the On-Demand Webinar
• Unlocking Master Data Management (MDM) Success: Real-World
Insights and Strategies On-Demand Webinar:
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© 2023 Enterprise Management Associates, Inc.

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Featured Speakers
Dan is responsible for developing and executing
strategic market research, delivering value to IT
organizations through consulting engagements, and
directing product developments and marketing efforts.
Dan joined EMA in 2005 and has over 25 years of
experience in information systems, software
development, and technology outsourcing. Dan
focuses on all aspects of intelligent and automated
management of IT.
© 2023 Enterprise Management Associates, Inc. 3
Dan Twing
President and COO
EMA
Steven Lin
Product Marketing Manager
Semarchy
Steven is responsible for executing the go-to-market
strategy for the award-winning data company
Semarchy. Prior to joining Semarchy, Steven was a
Technology Strategy Consultant at Ernst & Young,
advising large-scale data initiatives for global & Fortune
500 companies.

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| @ema_research
State of MDM
Survey Participants
MDM Goal
MDM Challenges
MDM Benefits
Lessons Learned
Q&A
Agenda
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| @ema_research
Most Organizations Find Value in an MDM
Sample Size = 102
Agree
33%
Strongly agree
65%
The effort invested in implementing and operating an MDM has
been worthwhile.
98%
Agree or Strongly agree
MDM is worthwhile

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| @ema_research
4 years is the average time an MDM has been in production use
Sample Size = 102
2%
32%
50%
12%
4%
0%
10%
20%
30%
40%
50%
60%
Less than 1 year 1 to 2 years 3 to 5 years 6 to 10 years More than 10 years
How long has your MDM been in production use?

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| @ema_research
More than half of organizations are running multiple MDMs
Average: 2.24 MDM products per organization
Sample Size = 102
1%
3%
3%
3%
4%
4%
5%
7%
11%
11%
17%
17%
31%
54%
54%
0% 10% 20% 30% 40% 50% 60%
Other (Please specify)
Tibco EBX
Stibo Systems MDM
Reltio MDM
Semarchyx DM
Profisee MDM
Talend MDM
EnterWorks Enable
Magnitude MDM (formerly Kalido)
SyncForce MDM
Informatica MDM
Informatica MDM Cloud (formerly Siperian MDM)
SAS Master Data Governance
IBM InfoSphere MDM
SAP Master Data Governance (MDG)
Which MDM solution(s) are used?
Note: this chart does not reflect market share.
41%
27%
12% 12%
8%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 2 3 4 5+
MDMs In Use

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| @ema_research
State of MDM Use
Sample Size = 133
4%
1%
3%
16%
2%
25%
38%
9%
3%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
No Plans Failed Planning 12-
24 months
Planning 6-
11 months
Less than 1
year
1 to 2 years 3 to 5 years 6 to 10 years More than
10 years
No Plans Failed Planning Implemented

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Survey Participants

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| @ema_research
Respondents are 82% middle and executive IT management in NA
Sample Size = 102
2%
3%
5%
7%
25%
26%
31%
0% 5% 10% 15% 20% 25% 30% 35%
Application Owner (e.g., ERP)
Business Executive
Integration/Data Manager, Architect
Chief Data Officer
IT Manager
IT Executive
IT Director
Role in Organization
22%
32%
17%
11%
6%
13%
0% 5% 10% 15% 20% 25% 30% 35%
500-999
1,000-2,499
2,500-4,999
5,000-9,999
10,000-19,999
20,000 or more
Number of Employees
1%
15%
20%
39%
25%
0% 10% 20% 30% 40% 50%
Less than $5 Million
$5 Million to under $20 Million
$20 Million to under $100 Million
$100 Million to under $1 Billion
$1 Billion or more
Annual Sales Revenue
3%
3%
4%
4%
4%
5%
9%
14%
23%
27%
0% 5% 10% 15% 20% 25% 30%
Government, Eductaion, Nonprofit
Hospitality/Entertainment/Travel
Consulting and Professional Services
Telecommunications
Transportation/Airlines/Trucking/Rail
Utilities/Energy
Other (Please specify)
Healthcare/Medical/Pharmaceutical
Retail/Wholesale/Distribution
Finance/Banking/Insurance
Industry

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| @ema_research
Improved data quality, Data integration, and Data-driven innovation are
the top three goals
Sample Size = 102 Select 3
7%
13%
15%
16%
17%
17%
20%
22%
23%
30%
32%
39%
51%
0% 10% 20% 30% 40% 50% 60%
Single source of truth
Better customer experiences
Data consolidation
Competitive advantage
Enhanced data governance
ROI and cost reduction
Faster decision-making
Scalability
Support digital transformation
Operational efficiency
Data-driven innovation
Data integration
Improved data quality
What are the primary goals and objectives your organization
hoped to achieve from an MDM?
Select Top 3

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MDM Challenges

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| @ema_research
Data quality issues, Data migration, and Performance optimization are the
three biggest challenges during implementation
Sample Size = 102
2%
5%
10%
11%
12%
14%
15%
16%
17%
17%
19%
19%
21%
21%
23%
25%
28%
29%
0% 5% 10% 15% 20% 25% 30% 35%
No budget/insufficient budget
Resource constraints
Executive buy-in
Vendor selection
Establishing data governance
Data ownership and accountability
Change management
Complexity of vendor solution
Testing and validation
Data culture readiness
Data source complexity
Integration complexity
Customization and configuration
Data security and compliance
Data mapping and transformation
Performance optimization
Data migration
Data quality issues
What were the most significant challenges your organization encountered
during the MDM implementation process?
Select Top 3

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| @ema_research
Comparing those who implemented successfully with those who required multiple attempts
1%
15%
15%
1%
18%
10%
20%
23%
23%
7%
17%
34%
7%
27%
17%
31%
13%
21%
3%
10%
13%
13%
13%
16%
16%
16%
16%
16%
16%
19%
19%
19%
23%
23%
23%
26%
0% 5% 10% 15% 20% 25% 30% 35% 40%
No budget/insufficient budget
Change management
Resource constraints
Testing and validation
Establishing data governance
Integration complexity
Customization and configuration
Data security and compliance
Executive buy-in
Data culture readiness
Data quality issues
Vendor selection
Performance optimization
Data source complexity
Data migration
Complexity of vendor solution
Data mapping and transformation
What were the most significant challenges your organization encountered during
the MDM implementation process?
Multiple Attempts Implemented
Sample Size = 102
Key challenges for those who
fail at MDM implementation:
• Struggles with data
mapping and
transformation
• Complexity of vendor
solution
• Data source complexity
• Vendor selection

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| @ema_research
Data security, Data quality assurance, and Data volume and scalability are
the three biggest challenges after implementation
Sample Size = 102
6%
7%
9%
11%
12%
12%
12%
14%
14%
22%
22%
22%
25%
25%
28%
31%
31%
0% 5% 10% 15% 20% 25% 30% 35%
Data governance maintenance
Data governance culture
Measuring ROI/KPIs
Vendor support
Frequency of MDM software updates
Change management
Scalability costs
Complexity of operating and maintaining
Data integration complexity
Legacy systems integration
Data privacy and compliance
User adoption
Data migration
Data volume and scalability
Data quality assurance
Data security
Which challenges has your organization experienced using your MDM after
implementation?
Select Top 3

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| @ema_research
Those taking multiple attempts to implement an MDM struggle more with
User adoption, Legacy systems integration, and data integration complexity
Sample Size = 102
8%
10%
11%
11%
11%
14%
11%
34%
10%
23%
27%
11%
34%
18%
17%
20%
30%
0%
0%
3%
10%
13%
13%
13%
16%
16%
19%
19%
19%
26%
29%
32%
35%
35%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Data governance maintenance
Data governance culture
Measuring ROI/KPIs
Vendor support
Frequency of MDM software updates
Scalability costs
Change management
Data volume and scalability
Data privacy and compliance
Data migration
Complexity of operating and maintaining
Data quality assurance
Data integration complexity
Legacy systems integration
User adoption
Data security
Which challenges has your organization experienced using your MDM after
implementation?
Multiple attempts Implemented MDM

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| @ema_research
Improved data quality, Improved reporting and analytics, and Faster
decision-making are the top three benefits
Sample Size = 102
15%
16%
16%
17%
19%
22%
27%
29%
32%
32%
33%
33%
35%
38%
44%
54%
0% 10% 20% 30% 40% 50% 60%
Consolidation of data silos
360-degree view of customers
Encourages data-driven culture
Compliance risk mitigation
Improved strategic planning
Scalability
Data-driven innovations
Data integration
Cost reduction
Improved reporting and analytics
Which benefits have you observed as a result of implementing MDM?

| @ema_research
| @ema_research
Improved data quality, Improved reporting and analytics, and Faster
decision-making are the top three benefits
Sample Size = 102
21%
14%
15%
15%
21%
14%
28%
35%
31%
31%
27%
34%
30%
45%
32%
51%
13%
16%
16%
16%
23%
23%
26%
29%
35%
35%
35%
39%
42%
42%
52%
61%
0% 10% 20% 30% 40% 50% 60% 70%
Compliance risk mitigation
Consolidation of data silos
360-degree view of customers
Encourages data-driven culture
Improved strategic planning
Data integration
Data-driven innovations
Scalability
Cost reduction
Improved reporting and analytics
Which benefits have you observed as a result of implementing MDM?

| @ema_research
| @ema_research
Data quality, Data accuracy, and Data security are the top 3 metrics used
to measure MDM impact
Sample Size = 102
8%
9%
10%
12%
13%
13%
15%
18%
18%
23%
24%
28%
30%
33%
48%
0% 10% 20% 30% 40% 50% 60%
Data duplication
Data lifecycle management
Data governance
Business process efficiency
Data mastering
Data scalability
Cost of data management
Data consistency
Data usage
Data integration
ROI
Revenue growth
Data security
Data accuracy
Data quality
Which metrics do you use/track to measure the impact of MDM?
Select Top 3

| @ema_research
| @ema_research
Those taking multiple attempts to implement are far more focused on ROI
Sample Size = 102
17%
10%
11%
18%
14%
21%
6%
17%
10%
32%
23%
30%
30%
14%
48%
3%
3%
6%
6%
6%
10%
16%
19%
19%
19%
23%
32%
42%
45%
48%
0% 10% 20% 30% 40% 50% 60%
Data mastering
Data duplication
Data governance
Cost of data management
Business process efficiency
Data consistency
Data lifecycle management
Data usage
Data scalability
Revenue growth
Data integration
Data security
Data accuracy
ROI
Data quality
Which metrics do you use/track to measure the impact of MDM?

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| @ema_research
Overall, 94% report Some or Significant improvement for most metrics
Sample Size = 102
59%
35%
4% 2% 0%
0%
10%
20%
30%
40%
50%
60%
70%
Significant
improvement for
most metrics
Some
improvement for
most metrics
Mixed results
across metrics
Most metrics did
not improve
No metrics
improved
What have been the results for your key MDM metrics?
68%
24%
6%
3%
0%
39%
61%
0% 0% 0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Significant
improvement for
most metrics
Some
improvement for
most metrics
Mixed results
across metrics
Most metrics did
not improve
No metrics
improved
What have been the results for your key MDM metrics?
Implemented MDM Multiple attempts

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Lessons Learned

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| @ema_research
How did your organization address or overcome these [MDM
implementation] challenges?
Testing on a pilot project has been our
solution to see what might cause problems.
Contracted specialist
group and flash-trained
or employees.
We had to work hand in hand with customer
support to ensure we were implementing and using
as efficiently as possible. Training and team
meetings were the norm for 1 to 2 months and that
training is ongoing for new and existing employees.
Held ALOT of meetings to get stakeholder
input and provided updates to senior
leadership and to others in the org. Defined
clear RACIs.
We used SAP consultation services
after our MDM proved challenging.
We implemented strict data ownership
policies, established clear accountability
roles, invested in robust data security
measures, ensured compliance with
relevant regulations, and implemented
data quality control processes.
By being data quality
conscious and making every
effort to improve data quality
Testing on a pilot project has been our
solution to see what might cause problems.
Form task forces.

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| @ema_research
Vendor support, Give it time, and Outside Help are the
top three means to overcome challenges
4
1
1
1
1
1
1
1
1
1
2
2
2
5
5
5
6
7
8
14
16
17
0 2 4 6 8 10 12 14 16 18
I don't know
No issues
Central Team
Domain Selection
Executive Support
Peer Insight
Phased approach
Pray
Testing
Use AI
Automation
Hire the right skills
Pilot/Testing
Data Collection Techniques
Focus on Data Security
Training
Planning
Task Forces
Communication
Outside help
Give it time
Vendor Support
How did your organization address or overcome these challenges?

| @ema_research
| @ema_research
Defining KPIs is by far the top strategy for promoting MDM adoption
Sample Size = 102
9%
12%
12%
14%
15%
18%
18%
18%
19%
19%
20%
22%
23%
24%
25%
37%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Celebrate milestones
Involve users early
Establish a network of champions
Begin with pilot programs
Tailor training to different user roles
Identify and involve key stakeholders
Share use cases and success stories
Create training and certification programs
Encourage culture of continuous improvement
Establish feedback mechanisms
Communicate to all stakeholders
Comprehensive support
Keep users informed with regular updates
Secure executive support
Select an MDM with a user-friendly interface
Define key performance indicators (KPIs)
Which strategies were most effective in promoting MDM adoption?
Select Top 3

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| @ema_research
The importance of data quality metrics is the top lesson learned
Ongoing data quality concerns rank second, followed by vendor selection
Sample Size = 102
6%
11%
13%
14%
15%
19%
20%
20%
21%
24%
25%
27%
37%
50%
0% 10% 20% 30% 40% 50% 60%
Start small with pilots
Change management is crucial
Cross-functional collaboration is required
Focus on specific data domains
Clearly define data ownership
Executive support is vital
Data standardization matters
Data integration is complex
Data governance is paramount
User training is crucial
Data security is non-negotiable
Selecting the right MDM vendor is critical
Data quality is ongoing
Data quality metrics are key
Which key lessons or best practices has your organization learned from its
MDM journey?
Select Top 3

| @ema_research
| @ema_research
Those taking multiple attempts to implement are far more sensitive to
selecting the right vendor
Sample Size = 102
7%
20%
10%
21%
11%
20%
25%
11%
28%
20%
17%
41%
23%
46%
3%
3%
13%
16%
16%
19%
19%
19%
19%
23%
23%
29%
39%
58%
0% 10% 20% 30% 40% 50% 60% 70%
Start small with pilots
Clearly define data ownership and stewardship roles
Change management is crucial
Data standardization matters
Cross-functional collaboration is required
Data integration is complex
User training is crucial
Focus on specific data domains rather than all data…
Data security is non-negotiable
Data governance is paramount
Executive support is vital
Data quality is ongoing
Selecting the right MDM vendor and solution is critical
Data quality metrics are key
Which key lessons or best practices has your organization learned
from its MDM journey?

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| @ema_research
If you were to start the MDM implementation process again, what would
you do differently?
Start with one data domain at a
time and focus on data quality.
I might start off with a small
group before implementing to
everyone and scaling.
Training is where we failed the first
time and not involving our
stakeholders more. Everyone had
to be on the same page and know
how to use these new programs.
I would equip myself with more firsthand knowledge.
Definitely collaborate more with my team in the early
stages to ensure we are all on the sane page and
understanding what the main end goal is.
Not rush it and ensure that we properly
selected the right KPIs. Also we needed
to do a better job of cost estimation.
Assemble the right MDM team from across
the organization and make sure we define
business value with clearly established,
justified, and prioritized goals.
More frequent
feedback and more
end user involvement.
I would invest more time upfront in data
profiling and cleansing to ensure better data
quality from the beginning. Additionally, I
would involve end-users more actively in the
data governance process to gather their
insights and requirements.
We would make sure that we have certain metrics in
place that need to be met in order to take it from testing
and put it into production. We would then also
continuously monitor and evaluate on a daily basis until
we are certain that it is performing at peak.
We would do more research on
what was needed from the outset so
we could better prepare our
leadership team for the upcoming
changes. We were not able to
communicate effectively until the
ROI started to show through.

| @ema_research
| @ema_research
Vendor Selection, Better/More Training and Better Communication/Planning are
the top three things organizations would do differently
3
1
1
1
1
2
2
2
2
2
2
3
3
5
5
5
6
8
8
14
26
0 5 10 15 20 25 30
I don't know
Do it sooner
Focus on Data Security
Involve end users earlier
Use AI earlier in the project
Better KPIs
Front load resources
Hire Experienced Resources
Improved Testing
Secure Executive Support
Stepwise Domains/Data Quality
Normalize Data
Pilot projects
Better Planning
Data Domain Selection
Reatin Outside Help
Focus on Data Quality
Better Communication/Planning
Better/More Training
Vendor Selection
Nothing
If you were to start the MDM implementation process again,
what would you do differently?
Summary of Open-End Responses
25% would do nothing
different.

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| @ema_research
Looking Forward to MDM Success
• 98% find value in their MDM
• Biggest challenges during implementation:
• Data quality issues
• Data migration
• Performance optimization
• Biggest challenges after implementation:
• Data security
• Data quality assurance
• Data volume and scalability
• Top 3 means to overcome challenges:
• Vendor support
• Give it time
• Outside help
• Defining KPIs is the top strategy for promoting MDM adoption
• Top 3 things those with an MDM would do differently:
• Vendor selection
• Better/more training
• Better communication/planning

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| @ema_research
Most Organizations Realized Benefits from an MDM Beyond Expectations
Sample Size = 102
0%
10%
20%
30%
40%
50%
60%
Improved data
quality
Faster decision-
making
ROI and cost
reduction
Competitive
advantage
Data integration Operational
efficiency
Data-driven
innovation
Scalability Enhanced data
governance
Data
consolidation
Single source of
truth
51%
20%
17% 16%
39%
30%
32%
22%
17%
15%
7%
54%
38%
35% 33% 33%
32% 32%
29%
22%
16% 15%
Desired Benefits Achieved Benefits

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36
36
36
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