Building the Business Case for Metadata in the
Enterprise: Looking At Models, Architectures, and
Business Processes As Building Blocks for
Cost Benefit Analysis and ROI
G. Philip Rogers, PMP
Senior Business Analyst, School of Public Health,
Instructional and Information Systems, UNC Chapel Hill
Doctoral Student, Information Science, UNC
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About Me
• Professional experience. Over the past 20
years, worked in Business Analyst,
Project/Program Management, Technical
Communications, and Management roles
(before joining UNC, worked for Cisco Systems,
Web startup, Intel Corporation, USAF).
• Academic interests. Doctoral student in UNC’s
School of Information and Library Science –
academic interests include metadata
interoperability, Semantic Web, Business
Intelligence, and the role of IT as an enabler for
addressing research challenges.
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Corporate Circle Goals
• The goals of the Global Corporate Circle are to:
• Promote the use of the Dublin Core standard by
enterprise organizations/corporations for both internal
and external information.
• Coordinate with developers and information providers to
ensure interoperability with enterprise-wide applications.
• Develop a body of work which provides best practices,
case studies and examples of how Dublin Core is
implemented and its' value to the organization.
Examples can include what elements are used, how they
are interpreted for the organization, values/controlled
vocabularies developed and the return on investment
(ROI) of metadata, specifically Dublin Core, for a
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DCAM and Its Applicability to Business
Process and EA Modeling
• Pulis & Neville propose a UML-compliant model
of the DCAM as a means of moving toward the
development of a UML meta-model so that UML
can be used to develop DC-conformant
Application Profiles.
• Perhaps additional modeling languages could be
considered as a basis for additional DCconformant Application Profiles, as a means of
enhancing interoperability.
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Do You Know Where Your Data Is?
… And what would you do with it if and
when you find it?
If someone were to ask you, in a work context,
“How’s it going?” – what would your answer be?
– The key to answering this question is of course defining
• Financial results (profitability, market share)
• Customer-related metrics (satisfaction, loyalty)
• Quality measures (defects, discrepancies)
• Performance measures (employee productivity)
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Working Definitions of Metadata
• Semantic layer between IT systems and
business users (McComb)
• “Structured information that describes, explains,
locates, or otherwise makes it easier to retrieve,
use, or manage an information resource” (NISO)
• “Metadata is the information and documentation
which makes data understandable and
shareable for users over time. Data remain
useable, shareable, and understandable as long
as the metadata remain accessible.”
(ISO/IEC 11179-1)
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Enterprise Metadata Management
• Enterprise metadata management should
provide insight into:
– What data exists
– Where data is being used
– How data is labeled and referenced
– How data is related to other information
– Who uses the data
– Why the data is needed
– When the data was last accessed or updated
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The Changing Role of Metadata
• The role of metadata has been transformed – it
has gone from being an afterthought to being an
architectural principle (McComb)
• Metadata plays a critical role in investments in
data warehousing, data mining, business
intelligence, customer relationship management,
enterprise application integration, and
knowledge management (to name some of the
big-ticket items in which enterprises have
invested over the past 5 to 10 years).
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Framing the Question
• Because the term metadata is abstract and not
widely understood in a corporate environment,
asking someone “how they use metadata” in
their job is a question many people will struggle
to answer.
• Asking someone to describe their job, such as
the systems and tools that they use, and to what
extent and how they might use the data entered
in those systems and tools, should make it
possible to make deductions about the role
metadata plays in their job and in their
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Solutions Intended to Address Gaps In
Systems and Processes
• ETL. Extract, Transform, Load (reading data
from one database, performing transformations
on the data so that that it can be read in a
different database, and writing the transformed
data to the target database)
• Data warehouses, data marts. Provide a central
repository and enable data mining.
• Middleware. Hides inconsistencies in underlying
architectures (recent examples include web
services integration, enterprise service buses) .
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Problems with Scoping and
Justifying Metadata Projects
• Projects where metadata is the central component often
are not successful, because they are not:
1. Driven by a distinct and evident business need
2. Clearly defined
3. Based on achievable or measurable goals
4. Properly resourced, both during and after the project
is complete
Metadata repository projects are prone to failure
because their contents are not sufficiently integrated
across the enterprise – for example, they are not fully
compatible with ETL or data integration applications.
Focusing too much attention on the metadata itself,
as opposed to accomplishing clear goals with
metadata, can be a costly mistake.
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Challenges Associated with Metadata
“The vast majority of metadata repositories are
unidirectional. Modeling tools that extract, transform, and
load information into the repositories are responsible for
capturing both business (business metadata) and IT
(technical metadata) meta information flow in only a
single direction… Many enterprise tool vendors are
trying to solve this particular problem, but …an
organization would need to fully embrace the metadata
repository approach for it to work and could not adopt it
in bits and pieces. The repository will be required to
store the latest version of the metadata source in which it
will propagate changes. Concurrency issues will arise in
this situation… [and] integration interfaces will have to be
constructed to map and move metadata repository
information back and forth to the metadata source.”
- McGovern
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Has Something Like This Ever Happened
Where You Work?
• A large amount of money is allocated to
building a data warehouse. Despite
management support and ample funding,
the initiative fails mainly due to inflexible
business processes and lack of access to
or understanding of critical business data.
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The Need For Metadata Management
Tools AND Frameworks
“ A metadata-driven framework is MANDATORY to enable
companies to understand the different forms, types, and
definitions that common data elements share with each
other. It is important to maintain the distinction between
managing metadata through a generalized metadata tool
versus having a metadata-driven framework designed for
a specific purpose, such as supporting customer data
integration and master/reference data management. In
my experience, the most successful companies combine
'best practices' from both approaches.”
- Anurag Wadehra, VP of Marketing, Siperian
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Metadata Management Maturity Curve
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Observations About Enterprise Behavior
• Profit-driven enterprises are often heavily
influenced by short-term, one-quarter-at-atime, “tactical” thinking.
• Business justification for individual projects
tends to be driven by short-term needs.
• Developing business cases and
calculating ROI for long-term investments
is very difficult in such an environment.
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The Executive Sponsor’s Dilemma
• A certain project is expected to produce
benefits, but will require a capital
• That same capital could be invested
elsewhere, potentially producing a
different set of benefits
• How does the sponsor decide which
project or projects to invest in?
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Building the Business Case
• Building a business case typically includes
steps such as the following:
– Estimate future expected costs
– Estimate future expected benefits
– Determine implied return
– Compare implied return to alternatives
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The Cruel World of Estimation
• Projections of expected costs and benefits are
often educated guesses, at best, particularly for
software projects.
• The greater the degree of uncertainty (risk)
about a potential project, the higher the
expected rate of return to justify the project.
• A preliminary business case may be only a first
step preceding additional analysis,
understanding of requirements, and preparation
of a more formal business case. The assumption
is that investing additional time should reduce
uncertainty (risk).
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Estimating Costs and Benefits
• When estimating costs:
– Level of cost is directly proportional to
complexity of requirements
– Uncertainty about costs reduces as
requirements are refined
• When estimating benefits:
– An existing problem is solved or at least
mitigated in order for the expected benefit to
– The problem and the cost of living with the
problem are well understood
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Standard ROI Calculation
ROI is often calculated as the average benefit over a
specified time period divided by the cost.
That is,
 Given the sum of the costs
 Given the sum of the benefits
 Given other parameters
Then the ROI can be computed in a number of ways.
However, the calculation of costs and benefits is not
always based on realistic data, and under what is often
tight schedule pressure, insufficient time is typically
allocated for the preparation of business cases and
similar deliverables.
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Strategic Perspectives on Enterprise
Data Management
• Understanding enterprise business
processes is an essential part of strategic
• In order to help the enterprise attain its
goals, enterprise architecture must be
aligned with enterprise business
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Business Process Definition
• Set of business events that enable the delivery
of an organization’s products or services to its
customers. Categories for business processes:
– Information – processing of data within and
movement of data among systems
– Operations – individual contributors, equipment,
operational policies and procedures
– Management – managers, authority, organizational
dynamics, management policies and procedures
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Business Process Modeling
A business process:
1. Has a Goal
2. Has specific inputs
3. Has specific outputs
4. Uses resources
5. Has a number of activities that are performed in
some order
6. May affect more than one organizational unit.
7. Creates value of some kind for the customer (internal
or external).
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Potential Business Process Focus Areas
• Generalized (broadly applicable)
– Business Intelligence/Knowledge Management
– Content Management
– Enterprise Resource Planning
– Portfolio Management
– Customer Relationship Management
• Specialized (industry-specific)
– Academia/government (grant-funded research)
– Financial services (investment banking)
– Health care (patient health records)
– Libraries/archives (digitization)
– Pharmaceuticals (clinical drug trials)
– Semiconductors (microprocessor design)
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Enterprise Architecture (EA) Definition
• Principles, methods, and models that shape the
organizational structure, business processes,
information systems, and infrastructure of an
“Enterprise architecture captures the essentials of the
business, IT and its evolution. The idea is that the
essentials are much more stable than the specific
solutions that are found for the problems currently at
hand. Architecture is therefore helpful in guarding the
essentials of the business, while still allowing for
maximal flexibility and adaptability. Without good
architecture, it is difficult to achieve business success.”
- Lankhorst
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EA Views
• Business architecture. Shows how business is done -models the enterprise using business processes and the
events that trigger them.
• Information (data) architecture. Enables the enterprise to
develop a shared, distributed, consistent data resource -consists of data models and databases that serve all
participants in the enterprise business environment and
the strategies, standards, policies required to develop
and implement them.
• Application architecture. Supports business processes,
provides automated solutions, manages information
storage and retrieval, links the Data and Business
• Technology (infrastructure) architecture. Meets the
infrastructure needs of business clients -- interoperates
with and supports the Application, Business, and Data
Architectures to provide interoperable technology
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EA View Components
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Architecture Stack
Business Processes
Service Framework
Access Mechanisms
Operating Software
Physical Infrastructure
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Sample Business Architecture
Process integration
Business policies/
Data management
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Business Intelligence
User interaction
Metadata Requirements Stack
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EA Governance Categories and
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EA Governance Instruments
• Strategic Management (BSC). Emphasizes a balanced
approach (traditional management focus is on finances)
based on customer, financial, business process, and
learning/growth perspectives.
• Strategy Execution (EFQM). Inspired by Malcolm
Baldridge (USA) and Deming (Japan), provides
management framework for performance excellence.
• Quality Management (ISO 9001). Focuses on integrated
design, management, and documentation of business
processes and supporting IT systems.
• IT Governance (COBIT). Provides control objectives and
management guidelines for 34 IT processes. Also provides
IT governance maturity model.
• IT Service Delivery and Support (ITIL). Provides set of
best practices and training materials for IT service delivery.
• IT Implementation (CMM/CMMI). Model for evaluating
maturity of software development processes.
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Finding Data Where It Lives:
Semantic Elicitation from Processes
• Long duration business transactions (LDBTs)
are a valuable source for uncovering semantics
in business processes (workflows).
• A good place to start for any enterprise is the
“predominant flow” – typically a flow that occurs
frequently, has significant cost implications, and
is central to the core mission of the enterprise.
• Looking at variations in the primary flow,
whether the variations make business sense,
and whether they merit a time investment can
yield valuable information about how to manage
critical business data (McComb).
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On Data Governance
• Due in part to relatively recent business drivers
related to compliance such as Basel II and
Sarbanes-Oxley, data governance is an area
that is seeing substantial enterprise investment.
• Data governance seeks to ensure that there is a
management framework that can deliver
availability, usability, integrity, and security of
enterprise data. Such a framework should
include a governing body, a defined set of
procedures, and a plan to execute those
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Why Metadata for Governance?
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Business Imperatives Driving Data
• Agility (ability to respond more quickly)
• Simplification (reduce unnecessary
complexity, and ideally, costs)
• Rapid increase in the volume of
• Rapid business growth
• Geographic dispersion (due to outsourcing
and other factors)
• Compliance
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Metadata Uses in Data Governance
• Strategic (data stewardship; information
reuse; information management; data
integration strategy)
• Tactical (project flexibility and adaptability;
portfolio management)
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Architecture (BPM, Metadata Repository,
and EA) Tools
Tools that at least partially address the central EA
challenge of representing enterprise information and
technology portfolios:
• BPM (top down) tools:
– ARIS (IDS Scheer); Corporate Modeler (Casewise); MEGA
International Software Suite; ProVision (Proforma).
• Metadata repository tools:
– Architecture Manager (Adaptive Enterprise). MOF-compliant
repository that integrates with many modeling tools.
– Rochade (Allen Systems Group). Provides publication,
visualization of models; CWM support.
• EA Tools:
– Architect (BiZZdesign); Enterprise Framework (Ptech); Metis
(Computatis); System Architect (Popkin); Troux 4 (Troux
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Metadata Extraction Tool Example:
• Saphir (Silwood Technology) is a tool that reads the data
structures of Peoplesoft,, SAP (BW & mySAP ), Siebel,
and JD Edwards databases and extracts the definitions
and relationships of the tables and columns, which can
then be exported into tools such as ERwin,
PowerDesigner, Popkin System Architect, or Visio.
• “Data warehouse designers, reporting teams and data
architects use this powerful application to analyse their
data requirements from the key enterprise applications.
Saphir helps you take control of your data management
projects as you strive to understand exactly where vital
business information is stored.”
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Saphir (continued)
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Facilitating Interoperability: An EA/BPM
• Metadata interoperability projects have generally been based
on one of the following approaches:
Application profiling/schema customization
Derivation (e.g., MODS and MARC Lite are derived from MARC21)
Switching schema (e.g., OAI)
Lingua franca (set of core attributes derived from multiple schemas)
Metadata framework/container (e.g., RDF, METS)
• For EA/BPM, possible areas for further research:
– Survey individuals working in areas such as EA, business process
modeling (Architects, Business Analysts)
– “Crosswalk of frameworks/models,” leveraging GRAAL framework for
conceptualizing and comparing IT architectures and Value-Based IT
Alignment (VITAL) approaches
– Business process model (flow) registry
– Further application profiling (e.g, BPML-compliant model of DCAM)
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Formulating a Business Case for Enterprise
Metadata Management
• What is driving investment in projects and
initiatives -- Organizational needs?
Business requirements? Technology
• What are the main limitations in the use of
information? Inappropriate organizational
structures? Cumbersome business
processes? Outdated technologies?
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Simple Information Assessment
Evernden & Evernden information diagnostic:
There is a clear and distinct vision of information as a corporate resource
There is an organization unit responsible for information and knowledge that is
distinct from the information technology function
3. There is a well-defined strategy and action plan for improving the effectiveness
of information use across the organization
4. Information that is vital and necessary to make key decisions is always readily
and easily available
5. All information is available in a consistent and integrated format
6. Management believes that there is considerable value to be gained from the
organization’s use of information
7. Information management is seen as the responsibility of business people as
well as the information technology functions
8. Information has a key role in all business processes
9. Financial approval is readily available for investment in the information
infrastructure of the organization (as opposed to technology investments)
10. Information is used to support innovation and creativity in product and service
development, business processes, and customer support
Total Score:
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Surveying EA/BPM Practitioners
• Questions that might yield insight via a survey
(or similar instrument), possibly using an
approach such as the COBIT IT Maturity Model,
could focus on areas such as:
– Enterprise data warehouse or metadata repository
initiatives attempted or planned
– Modeling frameworks or tools being used
– Extent to which business processes are understood
and documented
– Extent to which EA aligns with business processes
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EA Frameworks and Business Process Models:
Is There a Role for Dublin Core?
• Pulis & Neville have already proposed a UMLcompliant model of the DCAM – how might this
model be leveraged as part of the larger OMG
Model-Driven Architecture (MDA), which
includes the Meta Object Facility (MOF) and the
Common Warehouse Meta-model (CWM)?
• Other frameworks and models that appear to
have traction in the U.S. are The Open Group
Architecture Framework (TOGAF), the Business
Process Modeling Initiative (BPMI), and the
Federal Enterprise Architecture Data Reference
Model (FEA DRM).
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Selected References
ANSI X3.285, Metamodel for Management of Shareable Data
Cook, M. (1996). Building Enterprise Information Architectures: Reengineering
Information Systems. Prentice Hall.
Evernden & Evernden (2003). Information First: Integrating Knowledge and
Information Architecture for Business Advantage. Elsevier.
Finneran, T. (2003). Enterprise Architecture: What and Why.
ISO/IEC 11179-1. Specification and standardization of data elements - Part 1:
IT Governance Institute (2006). COBIT 4.0.
Lankhorst, M., et al. (2006). Enterprise Architecture at Work: Modelling,
Communication, and Analysis. Springer.
McComb, D. (2004). Semantics in Business Systems: The Savvy Manager’s Guide.
Morgan Kaufmann.
McGovern, J., et al. (2004). A Practical Guide to Enterprise Architecture. Prentice
NISO. Understanding Metadata.
Silverston, L. (2001). The Data Model Resource Book, Revised Edition, Volume 2: A
Library of Universal Data Models by Industry Types. Wiley.
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Backup Slides
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COBIT Maturity Model for IT Governance
• The Control Objectives for Information and
related Technology (COBIT) for IT governance,
first published in 1996 by ISACA, along with
control objectives and management guidelines
for 34 IT processes, also includes an IT
governance maturity model.
• The maturity model has five levels, from the
lowest (“Ad Hoc”) level where there are no
standardized processes, to the highest
(“Optimized”) level, where processes have been
refined to the level of external best practices.
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COBIT Maturity Model for Internal
Maturity Level
0 (non-existent)
Complete lack of recognizable processes; organization does not acknowledge
that there are issues to be addressed.
1 (Initial/ad hoc)
Organization recognizes that issues exist; no standardized processes - ad hoc
approaches applied on a case by case basis; overall management approach is
2 (Repeatable but
Similar procedures are followed by different people undertaking same task; no
formal training or communication on standard procedures; responsibility is left to
individual; high degree of reliance on the knowledge of individuals.
3 (Defined process)
Standardized and documented procedures, communicated through training; still
left to individual to follow processes; procedures are non-sophisticated based on
formalization of existing practices.
4 (managed and
Compliance with procedures can be measured/monitored and action taken
where processes are not working effectively; processes are under constant
improvement; automation and tools are used to a limited extent.
5 (Optimised)
Processes refined to level of best practice, based on the results of continuous
improvement and maturity modelling with other organisations; IT employed in
integrated way to automate workflow and provides tools to improve quality and
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Business Process Analysis: A Key To Gaining
Insight Into Organizational Data
An operation is composed of processes designed to add value by transforming inputs
into useful outputs. Inputs may be materials, labor, energy, and capital equipment.
Outputs may be a physical product (possibly used as an input to another process) or
a service. Processes can have a significant impact on the performance of a business,
and process improvement can improve a firm's competitiveness.
The first step to improving a process is to analyze it in order to understand the
activities, their relationships, and the values of relevant metrics. Process analysis
generally involves the following tasks:
Define the process boundaries that mark the entry points of the process inputs and
the exit points of the process outputs.
Construct a process flow diagram that illustrates the various process activities and
their interrelationships.
Determine the capacity of each step in the process. Calculate other measures of
Identify the bottleneck, that is, the step having the lowest capacity.
Evaluate further limitations in order to quantify the impact of the bottleneck.
Use the analysis to make operating decisions and to improve the process.
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Framework for Comparative Analysis
• Based on an analysis of frameworks for
systems engineering, industrial product
engineering, and software engineering,
Wierenga et al. developed the GRAAL
conceptual framework for describing and
comparing IT architectures.
• The four dimensions of the framework are
system aspects, system aggregation,
systems processes, and description levels.
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GRAAL Conceptual Framework
• GRAAL program,
• A Conceptual Framework for Architecture
Alignment Guidelines. Project GRAAL WP1
Whitepaper P. A. T. van Eck (editor), H. Blanken,
M. Fokkinga, P. W. G. Grefen, R. J. Wieringa,
October 17, 2002
• Project GRAAL: Towards Operational
Architecture Alignment. Pascal van Eck, Henk
Blanken, Roel Wieringa
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Value-Based IT Alignment (VITAL)
• Value-based IT ALignment (VITAL),
• Daneva, M., Wieringa, R. (2005). Requirements Engineering for
Cross-Organizational ERP Implementation: Undocumented
Assumptions and Potential Mismatches. In: Proc. Int. Conference on
Requirements Engineering (RE'05), Paris, Aug/Sept 2005, IEEE
Computer Society Press, Los Alamitos, CA.
• Daneva, M., Eck, P. van (2006). What Enterprise Architecture and
Enterprise Systems Usage Can and Cannot Tell About Each Other.
CTIT Technical Report TR-CTIT-06-02, Centre for Telematics and
Information Technology. University of Twente, Enschede, The
• Santana Tapia, R. (2006). IT Process Architectjures for Enterprise
Development: A Survey from a Maturity Model Perspective.
CTIT Technical Report TR-CTIT-06-04, Centre for Telematics and
Information Technology. University of Twente, Enschede, The
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Traditional Industry Categories for
Which Data Models Exist
• Silverston provides an extensive library of
universal data models for the following industry
Health Care
Financial Services
Professional Services
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Traditional Data Modeling: Entities and
• An entity represents a category of information
that must be managed by the business.
– Entities are data that are captured, used in
calculations, reported, and so on.
– Entities come in groups. For example, an entity called
“supplier” implies that multiple suppliers exist.
• An attribute is a characteristic of an entity that
reveals information about the entity that needs to
be managed.
– For example, a “supplier” entity might have attributes
such as “supplier ID,” “supplier name,” etc.
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Data Structure Example: Health Care
• For any given HEALTH CARE EPISODE,
there can be:
associated with a HEALTH CARE OFFERING
(that identifies possible HEALTH CARE
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Data Model Example: Health Care
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DC Element Set
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Zachman Framework
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Activities That Use Information
• Organizational use of information:
– Analyze org structure, strategy & skills
– Define goals and objectives, critical success factors and
– Identify org structure and strategy changes
– Identify org impact of biz or technical requirements
• Business use of information:
Identify required functions
Identify required data
Identify business activities and critical business processes
Identify required activities
Map functions to data
Map functions to activities
Map activities to data
Review biz impact of org or technical requirements
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Activities That Use Information
Plan or design how information will be used in a particular context:
Design workflows
Design information structures
Specify data storage and data access
Specify application functionality
Specify technical support
Design organizational structures
Review business requirements and designs
Examine org, biz, and technical benefits and costs
Prioritize solutions
Plan implementations
Use information effectively:
– Analyze strategies, competitive environment, skills, and competencies, org
design, management structures
– Analyze processes and workflows, functions, data and information use
– Analyze existing application, network, and system architecture
– Analyze existing databases, applications, and systems
– Review org impact, biz requirements, and technical architectures
– Prioritize redevelopment needs
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On Metrics
Keys to Measurement:
– Measure the right things.
– Metrics must be specific, measurable,
actionable, relevant, and timely (SMART)
– Understand who the “customers” (internal or
external are)
– Understand process inputs and outputs
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Building the Business Case for Metadata in the Enterprise