The document discusses the Data Management Maturity Assessment (DMMA) and its importance in helping organizations become data-driven by evaluating and improving their data management practices. It outlines various maturity levels, the goals of the assessment, and the need for organizational alignment with business strategy. The framework also highlights the business drivers for conducting maturity assessments and the steps involved in implementing the evaluation process.

1. Topic: Data Management Maturity Assessment (DMMA)
Making data based decisions makes instinctive sense, and evidence is mounting that it makes
strong commercial sense too. Whilst being aware of this kind of potential is undoubtedly
valuable, knowing it and doing something about it are two very different things.
So how do you go about becoming a data driven organization?
And how does the Data Management Maturity Assessment help in achieving your data
strategy goals?
Speaker: Firas Hamdan
Data Management and Analytics Professional with more than 15 years experience working in
the Technology and Information industry, providing technical, management and consulting
services, and building and leading innovative teams in challenging complex projects.
In Australia he has been working on big data projects with major organisations such as
Deloitte, Cloudera, Caltex, Channel 7, Optus, CBA, AusNet and NBN, where he has
demonstrated success at all functions as well as every aspect of data analytics and data
management.

2. Data Management Maturity
Assessment
DAMA Sydney - September 2019
Firas Hamdan

3. DAMA Sydney Firas Hamdan
A data strategy defines how an organization achieves specific business goals through the strategic use of
its data assets.

4. DAMA Sydney Firas Hamdan
DMMA
● Maturity models are defined in terms of a progression through
levels that describe process characteristics.
● When an organization gains an understanding of process
characteristics, it can:
○ evaluate its level of maturity and put in place a plan to
improve its capabilities.
○ measure improvement and compare itself to competitors or
partners, guided by the levels of the model.

5. DAMA Sydney Firas Hamdan
DMMA Levels
With each new level, process execution becomes more consistent, predictable, and
reliable. Processes improve as they take on characteristics of the levels. Progression
happens in a set order. No level can be skipped. Levels commonly include:
● Level 0: Absence of capability
● Level 1: Initial or Ad Hoc: Success depends on the competence of individuals
● Level 2: Repeatable: Minimum process discipline is in place
● Level 3: Defined: Standards are set and used
● Level 4: Managed: Processes are quantified and controlled
● Level 5: Optimized: Process improvement goals are quantified

6. DAMA Sydney Firas Hamdan
DMMA Goals
● The primary goal of a data management capability assessment is to evaluate
the current state of critical data management activities in order to plan for
improvement.
● Typically, Data Management programs develop in organizational silos. They
rarely begin with an enterprise view of the data. A DMMA can equip the
organization to develop a cohesive vision that supports overall organizational
strategy.

7. DAMA Sydney Firas Hamdan
DMMA Goals
Such an assessment helps identify what is working well, what is not working well,
and where an organization has gaps. Based on the findings, the organization can
develop a roadmap to target:
● High-value improvement opportunities related to processes, methods,
resources, and automation
● Capabilities that align with business strategy
● Governance processes for periodic evaluation of organizational progress
based on characteristics in the model

8. DAMA Sydney Firas Hamdan
Business Drivers
Organizations conduct capability maturity assessments for a number of reasons:
● Regulation
● Data Governance
● Organizational readiness for process improvement
● Organizational change
● New technology
● Data management issues

9. DAMA Sydney Firas Hamdan
Assessment Levels

10. DAMA Sydney Firas Hamdan
Assessment Criteria
● Each capability level will have specific assessment criteria related to the processes being
evaluated.
● At any level, assessment criteria will be evaluated along a scale.

11. DAMA Sydney Firas Hamdan
Assessment Criteria
When assessing using a model that can be mapped to a
DAMA-DMBOK Data Management Knowledge Area, criteria
could be formulated based on the categories in the Context
Diagram:
● Activity
● Tools
● Standards
● People and resources

12. DAMA Sydney Firas Hamdan
DMMA Assessment Chart

13. DAMA Sydney Firas Hamdan
DMMA Frameworks
A data management maturity assessment framework is segmented into discrete data management
topics. Framework focus and content vary depending on whether they have a general or
industry-specific focus.
● CMMI Data Management Maturity Model (DMM)
● EDM Council DCAM
● IBM Data Governance Council Maturity Model
● Stanford Data Governance Maturity Model
● Gartner’s Enterprise Information Management Maturity Model

14. DAMA Sydney Firas Hamdan
DMMA Frameworks

15. DAMA Sydney Firas Hamdan
DMMA Implementation
● The purpose of the evaluation is expose current strengths and opportunities for
improvement – not to solve problems.
● Evaluations are conducted by soliciting knowledge from business, data
management, and information technology participants.
DAMA Activities:
1. Plan Assessment Activities
2. Perform Maturity Assessment
3. Interpret Results
4. Create a Targeted Program for Improvements
5. Re-assess Maturity

16. DAMA Sydney Firas Hamdan
DAMA Sydney
https://www.dama.org.au/about/sydney/
Firas Hamdan
https://www.linkedin.com/in/fhamdan/
Thank You