• Data management professionals looking to improve the organization’s ability to leverage data in value-added ways
• Data governance managers and data analysts looking to improve the effectiveness and value of their organization’s data management practice

• Align data management plans with business requirements and strategic plans.
• Create a collaborative plan that unites IT and the business in managing the organization’s data assets.
• Design a data management program that can scale and evolve over time.

• Business leaders creating plans to leverage data in their strategic planning and business processes
• IT professionals looking to improve the environment that manages and delivers data

• Perform data strategy planning and incorporate data capabilities and plans into your broader plans.
• Identify gaps in current data services and the supporting environment and determine effective corrective actions.

• The organizational appetite for data is increasing, with growing demands for data to better support business processes and inform decision making.
• For data to be accessible and trustworthy for the business it must be effectively managed throughout its lifecycle.
• With so much data circulating throughout our systems and a steady flow via user activity and business activities, it is imperative that we understand our data environment, focus our data services and oversight on what really matters, and work closely with business leads to ensure data is an integral part of the digital solution.

• Despite the growing focus on data, many organizations struggle to develop an effective strategy for managing their data assets.
• Successful management and consistent delivery of data assets throughout their lifecycle requires the collaboration of the business and IT and the balance of technology, process, and resourcing solutions.
• Employees are doing their best to just get things done with their own spreadsheets and familiar patterns of behavior. It takes leadership to pause those patterns and take a thoughtful enterprise and strategic approach to a more streamlined – and transformed – business data service.

• Incremental approach: Building a mature and optimized practice doesn’t occur overnight – it takes time and effort. Use this blueprint’s approach and roadmap results to support your organization in building a practice that prioritizes scope, increases the effectiveness of your data management practice, and improves your alignment with business data needs.
• Build smart: Don’t do data management for data management’s sake; instead, align it to business requirements and the business’ vision for the organization’s data. Ensure initiatives and program investments best align to business priorities and support the organization in becoming more data driven and data centric.

1. Client Intimacy/Service Excellence
2. Product and Service Innovations
3. Operational Excellence
4. Risk and Compliance Management

• Data Governance
• Data Strategy Planning
• Data Architecture
• Data Operations Management
• Data Risk Management
• Data Quality Management

US$11M:

With frequent government scandals and corruption dominating the news, transparency to the public is quickly becoming a widely adopted practice at every level of government. Open government is the guiding principle that the public has access to the documents and proceedings of government to allow for effective public oversight. With growing regulations and pressure from the public, governments must adopt a comprehensive data management strategy to ensure they remain accountable to their rate payers, residents, businesses, and other constituents.

1. Transparency Transparency is not just about access; it’s about sharing and reuse.
2. Social and commercial value Everything from finding your local post office to building a search engine requires access to data.
3. Participatory government Open data enables citizens to be more directly informed and involved in decision making.

A professional sports team is essentially a business that is looking for wins to maximize revenue. While they hope for a successful post-season, they also need strong quarterly results, just like you. Sports teams are renowned for adopting data-driven decision making across their organizations to do everything from improving player performance to optimizing tickets sales. At the end of the day, to enable analytics you must have top-notch information management.

1. Talent identification
2. In-game decision making
3. Injury reduction
4. Athlete performance
5. Bargaining agreement

6. Fan engagement
7. Licensing
8. Sports gambling

Data offers key insights and opportunities when it comes to supply chain management. The supply chain is where the business strategy gets converted to operational service delivery of the business. Proper data management enables business processes to become more efficient, productive, and profitable through the greater availability of quality data and analysis.

Fifty-seven percent of companies believe that supply chain management gives them a competitive advantage that enables them to further develop their business (FinancesOnline, 2021).

Involving Data in Your Supply Chain

Maintaining a Product Portfolio
What is selling? What is not selling?

• Based on current consumer buying patterns, what will they buy next?
• How will this product be received by consumers?
• What characteristics do consumers find important?

• Organizational sales performance

• Competitor performance
• Market analysis
• Consumer trends and preferences

Businesses of today operate in real time. To maintain a competitive edge, businesses must identify and respond quickly to opportunities and events.

To effectively do this businesses must have accurate and up-to-date data at their fingertips.

To support the new demands around data consumption, data velocity (pace in which data is captured, organized, and analyzed) must also accelerate.

• Strong integration capabilities
• Intelligent and efficient systems
• Embedded data quality management
• Strong transparency into the history of data and its transformation

Studies and projections show a clear case of how data and its usage will grow and evolve.

Analytic Competitor

Respond to industry disruptors

Optimize the way you serve your stakeholders and customers

Develop products and services to meet ever-evolving needs

Manage operations and mitigate risk

40%

66%

33%

30%

The journey to being data-driven

The journey to becoming a data-driven organization requires a pit stop at data enablement.

The Data Economy

Measure success to demonstrate tangible business value

• Tie the value of data management and its initiatives back to the business capabilities that are enabled.
• Leverage the KPIs of those business capabilities to demonstrate tangible and measurable value. Use terms and language that will resonate with senior leadership.

Don’t let measurement be an afterthought:

Start substantiating early on how you are going to measure success as your data management program evolves.

• Data Management Leadership & Org Structure Definition
  Define the home for data management, as approved by senior leadership.
• Data Management Charter and Policies
  Create a charter for your program and build/refresh associated policies.
• Data Culture Diagnostic
  Understand the organization’s current data culture, perception of data, value of data, and knowledge gaps.

• Use Case Build and Prioritization
  Build a use case that is tied to business capabilities. Prioritize accordingly.
• Business Data Glossary/Catalog
  Build and/or refresh the business’ glossary for addressing data definitions and standardization issues.
• Tools & Technology
  Explore the tools and technology offering in the data management space that would serve as an enabler to the program (e.g. RFI, RFP).

Insight 1

Insight 2

Insight 3

Key deliverable:

Use this template to guide you in translating your project's findings and outcomes into a presentation that can be shared with your executive team and project sponsors.

Blueprint deliverables

Data Management Assessment and Planning Tool Use this tool to support your team in assessing and designing the capabilities and components of your organization's data management practice.	Data Culture Diagnostic and Scorecard Leverage Info-Tech’s Data Culture Diagnostic to understand how your organization scores across 10 areas relating to data culture.
Business Capability Map This template takes you through a business capability and value stream mapping to identify the data capabilities required to enable them.

• Aligning your data management program and its initiatives to your organization’s business capabilities is vital for tracing and demonstrating measurable business value for the program.
• This alignment of data management with value streams and business capabilities enables you to use business-defined KPIs and demonstrate tangible value.

In Phase 2, we will help you develop a plan and a roadmap for addressing any gaps and improving the relevant data management capabilities so that data is well positioned to deliver on those defined business metrics.

DIY Toolkit

Guided Implementation

Workshop

Consulting

Diagnostics and consistent frameworks used throughout all four options

1.1 Review the Data Management Framework

1.2 Understand and Align to Business Drivers

1.3 Build High-Value Use Cases

1.4 Create a Vision

2.1 Assess Data Management

2.2 Build Your Data Management Roadmap

2.3 Organize Business Data Domains

• Call 1
• Call 2
• Call 3
• Call 4

• Call 5
• Call 6
• Call 7
• Call 8
• Call 9

• An understanding of the core components of an effective data management program
• Your organization’s business capabilities and value streams
• A business capability map for your organization
• High-value use cases for data management
• Vision and guiding principles for data management

• An understanding of your organization’s current data management capabilities
• Definition of target-state capabilities and gaps
• Roadmap of priority data management initiatives
• Business data domains and ownership

Phase 1

Phase 2

Call #2: Get a detailed overview of Info-Tech’s approach, framework, Data Culture Diagnostic, and blueprint.

Call #4:Further discuss alignment of business capabilities to data management capabilities and use case framework.

Call #6: Plan target state and corresponding initiatives.

Call #8: Identify and prioritize improvements. Define a RACI chart.

Workshop Overview

Understand and contextualize

1.1 Review your data strategy.

1.2 Learn data management capabilities.

1.3 Discuss DM capabilities cross-dependencies and interactions.

1.4 Develop high-value use cases.

Assess current DM capabilities and set improvement targets

2.1 Assess you current DM capabilities.

2.2 Set targets for DM capabilities.

Formulate and prioritize improvement initiatives

3.1 Formulate core initiatives for DM capabilities improvement.

3.2 Discuss dependencies across the initiatives and prioritize them.

Plan for delivery dates and assign RACI

4.1 Plan dates and assign RACI for the initiatives.

4.2 Brainstorm initiatives to address gaps and enable business goals.

Next steps and wrap-up (offsite)

5.1 Complete in-progress deliverables from previous four days.

5.2 Set up review time for workshop deliverables and to discuss next steps.

1. Understanding of the data management capabilities and their interactions and logical dependencies
2. Use cases

1. DM capability assessment results
2. DM vision and guiding principles

1. Prioritized DM capabilities improvement initiatives

1. DM capabilities improvement roadmap
2. Business data domains and ownership

1. Workshop final report with key findings and recommendations

What is data management and why is it needed?

Achieving successful management and consistent delivery of data assets throughout their lifecycle requires the collaboration of the business and IT and the balance of technology, process, and resourcing solutions.

Who:

• Data management heads and professionals looking to improve their organization’s ability to leverage data in value-added ways.
• Data management and IT professionals looking to optimize the data environment, from creation and ingestion right through to consumption.

Are your data management capabilities optimized to support your organization’s data use and demand?

• The volume and variety of data are growing exponentially and show no sign of slowing down.
• Business landscapes and models are evolving.
• Users and stakeholders are becoming more and more data-centric, with maturing and demanding expectations.

• Organizations struggle to develop a comprehensive approach to optimizing data management.
• In their efforts to keep pace with the demands for data, data management groups often adopt a piecemeal approach that includes turning to tools as a means to address the needs.
• Data architecture, models, and designs fail to deliver real and measurable business impact and value. Technology ROI is not realized.

A data strategy should never be formulated disjointed from the business. Ensure the data strategy aligns with the business strategy and supports the business architecture.

Adapted from DAMA-DMBOK and Advanced Knowledge Innovations Global Solutions

Data subject areas provide high-level views of the data assets that are used in business processes and enable an organization to perform its business functions.

Classified by specific subjects, these groups reflect data elements that, when used effectively, are able to support analytical and operational use cases of data.

This layer is representative of the delivery of the data assets and the business’ consumption of the data.

Data is an integral business asset that exists across all areas of an organization

For a data management practice to be effective it ultimately must show how its capabilities and operations better support the business in accessing and leveraging its key data assets.*

*This project focuses on building capabilities for data management. Leverage our data quality management research to support you in assessing the performance of this model.

Components at the Information Dimensions layer manage the different types of data and information present with an environment.

At this layer, data is managed based on its type and how the business is looking to use and access the data.

• Structured data
• Semi-structured data
• Unstructured data

Info-Tech categorizes data management enablers as the processes that guide the management of the organization’s data assets and support the delivery.

Data Strategy Planning

To support the project in building an accurate understanding of the organization’s data requirements and the role of data in its operations (current and future), the framework first guides organizations on a business and subject area assessment.

By focusing on data usage and strategies for unique data subject areas, the project team will be better able to craft a data management practice with capabilities that will generate the greatest value and proactively handle evolving data requirements.

Data Management Assessment

To support the design of a fit-for-purpose data management practice that aligns with the business’ data requirements this assessment will guide you in:

• Determining the target capabilities for the different dimensions of data management.
• Identifying the interaction dependencies and coordination efforts required to build a successful data management practice.

Phase 1

1.1 Review the Data Management Framework

1.2 Understand and Align to Business Drivers

1.3 Build High-Value Use Cases

1.4 Create a Vision

Phase 2

2.1 Assess Data Management

2.2 Build Your Data Management Roadmap

2.3 Organize Business Data Domains

This phase will walk you through the following activities:

• Identify your business drivers and business capabilities.
• Align data management capabilities with business goals.
• Define scope and vision of the data management plan.
• This phase involves the follow

This phase involves the following participants:

• Data Management Lead/Information Management Lead, CDO, Data Lead
• Senior Business Leaders
• Business SMEs
• Data Owners, Records Managers, Regulatory Subject Matter Experts (e.g. Legal Counsel, Security)

This step will guide you through the following activities:

• Understand the main disciplines and makeup of a best-practice data management program.
• Determine which data management capabilities are considered high priority by your organization.

Outcomes of this step

• A foundation for data management initiative planning that’s aligned with the organization’s business architecture: value streams, business capability map, and strategy map

Organizational Goals & Objectives

Business Drivers

Industry Drivers

Data Management Capability Maturity Assessment

Data Culture Diagnostic

Regulatory and Compliance Requirements

Generate Game-Changing Insights

Fuel Data-Driven Decision Making

Innovate and Transform With Data

Thrive and Differentiate With a Data-Driven Culture

Elevate Organizational Data IQ

Build a Foundation for Data Valuation

What is a data strategy and why is it needed?

• Your data strategy is the vehicle for ensuring data is poised to support your organization’s strategic objectives.
• For any CDO or equivalent data leader, a robust and comprehensive data strategy is the number one tool in your toolkit for generating measurable business value from data.
• The data strategy will serve as the mechanism for making high-quality, trusted, and well-governed data readily available and accessible to deliver on your organizational mandate.

What is driving the need to formulate or refresh your organization’s data strategy?

Who:

This research is designed for:

• Chief Data Officer (CDO) or equivalent
• Head of Data
• Chief Analytics Officer (CAO)
• Head of Digital Transformation
• CIO

Info-Tech Insight

A data strategy should never be formulated disjointed from the business. Ensure the data strategy aligns with the business strategy and supports the business architecture.

What is data governance and why is it needed?

• Data governance is an enabling framework of decision rights, responsibilities, and accountabilities for data assets across the enterprise.
• It should deliver agreed-upon models that are conducive to your organization’s operating culture, where there is clarity on who can do what with which data and via what means.
• It is the key enabler for bringing high-quality, trusted, secure, and discoverable data to the right users across your organization.
• It promotes and drives responsible and ethical use and handling of data while helping to build and foster an organizational culture of data excellence.

Do you feel there is a clear definition of data accountability and responsibility in your organization?

Who:

This research is designed for:

• Chief Data Officer (CDO) or equivalent
• Head of Data Governance, Lead Data Governance Officer
• Head of Data
• Head of Digital Transformation
• CIO

Info-Tech Insight

Data governance should not sit as an island in your organization. It must continuously align with the organization’s enterprise governance function.

Info-Tech’s Data Platform Framework

Data pipeline for versatile and scalable data delivery

What are the data platform and practice and why are they needed?

• The data platform and practice are two parts of the data and analytics equation:
  • The practice is about the operating model for data; that is, how stakeholders work together to deliver business value on your data platform. These stakeholders are a combination of business and IT from across the organization.
  • The platform is a combination of the architectural components of the data and analytics landscape that come together to support the role the business plays day to day with respect to data.
• Don’t jump directly into technology: use Info-Tech tools to solve and plan first.
• Create a continuous roadmap to implement and evolve your data practice and platform.
• Promote collaboration between the business and IT by clearly defining responsibilities.

Does your data platform effectively serve your reporting and analytics capabilities?

Who:

This research is designed for:

• Data and Information Leadership
• Enterprise Information Architect
• Data Architect
• Data Engineer/Modeler

Info-Tech Insight

Info-Tech’s approach is driven by business goals and leverages standard data practice and platform patterns. This enables the implementation of critical and foundational data and analytics components first and subsequently facilitates the evolution and development of the practice and platform over time.

What is reporting and analytics and why is it needed?

• Reporting and analytics bridges the gap between an organization’s data assets and consumable information that facilitates insight generation and informed or evidence-based decision making.
• The reporting and analytics strategy drives data warehouse and integration strategies and the data needs to support business decisions.
• The reporting and analytics strategy ensures that the investment made in optimizing the data environment to support reporting and analytics is directly aligned with the organization’s needs and priorities and hence will deliver measurable business value.

Do you have a strategy to enable self-serve analytics? What does your operating model look like? Have you an analytics CoE?

Who:

This research is designed for:

• Head of BI and Analytics
• CIO or Business Unit (BU) Leader looking to improve reporting and analytics
• Applications Lead

Info-Tech Insight

Formulating an enterprise reporting and analytics strategy requires the business vision and strategies to first be substantiated. Any optimization to the data warehouse, integration, and source layer is in turn driven by the enterprise reporting and analytics strategy.

1. 1. Prioritize your core business objectives and identify your business driver.
   2. Learn how business drivers apply to specific tiers of Info-Tech’s five-tier data architecture model.
   3. Determine the appropriate tactical pattern that addresses your most important requirements.

2. 4. Select the areas of the five-tier architecture to focus on.
   5. Measure your current state.
   6. Set the targets of your desired optimized state.

3. 7. Roadmap your tactics.
   8. Manage and communicate change.

What is data architecture and why is it needed?

• Data architecture is the set of rules, policies, standards, and models that govern and define the type of data collected and how it is used, stored, managed, and integrated within the organization and its database systems.
• In general, the primary objective of data architecture is the standardization of data for the benefit of the organization.

Is your architecture optimized to sustainably deliver readily available and accessible data to users?

Who:

This research is designed for:

• Data Architects or their equivalent
• Enterprise Architects
• Head of Data
• CIO
• Database Administrators

Info-Tech Insight

Data architecture is not just about models. Viewing data architecture as just technical data modeling can lead to a data environment that does not aptly serve or support the business. Identify your business’ priorities and adapt your data architecture to those needs.

What is data quality management and why is it needed?

• Data is the foundation of decisions made at data-driven organizations.
• Data quality management ensures that foundation is sustainably solid.
• If there are problems with the organization’s underlying data, it can have a domino effect on many downstream business functions.
• The transformational insights that executives are constantly seeking can be uncovered by a data quality practice that makes high-quality, trustworthy information readily available to the business users who need it.

Do your users have an optimal level of trust and confidence in the quality of the organization’s data?

Who:

This research is designed for:

• Chief Data Officer (CDO) or equivalent Head of Data
• Chief Analytics Officer (CAO)
• Head of Digital Transformation
• CIO

Info-Tech Insight

Data quality suffers most at the point of entry. The resulting domino effect of error propagation makes these errors among the most costly forms of data quality errors. Fix data ingestion, whether through improving your application and database design or improving your data ingestion policy, and you will fix a majority of data quality issues.

Regulatory, Legal –›

Efficiency, Cost-Effectiveness –›

Customer Service –›

User Experience –›

• Establish decision-making committee
• Define and formalize roles (RACI, charter)
• Develop policies
• Create business data glossary
• Decide who approves documents in workflow
• Operating models

• Information categories (taxonomy)
• Classifications, retention periods
• Metadata (for findability and as tags in automated workflows)

• Review and approval process, e.g. who approves
• Process for admins to oversee performance of IM service
• Process for capturing and classifying incoming documents
• Audit trails and reporting process

• Centralized index of data and records to be tracked and managed throughout their lifecycle
• Data retention policy
• E-signature policy
• Email policy
• Information management policies
• Access/privacy rules

• Understand the flow of content through multiple systems (e.g. email, repositories)
• Define business and technical requirements to select a new content management platform/service
• Improve integrations
• Right-size solutions for use case (e.g. DAM)

• Communication/Change Management
• Data Literacy

What is enterprise content management and why is it needed?

“Enterprise Content Management is the systematic collection and organization of information that is to be used by a designated audience – business executives, customers, etc. Neither a single technology nor a methodology nor a process, it is a dynamic combination of strategies, methods and tools used to capture, manage, store, preserve and deliver information supporting key organizational processes through its entire lifecycle.” (AIIM, 2021)

• Changing your ECM capabilities is about changing organizational behavior; take an all-hands-on-deck approach to make the most of information gathering, create a vested interest, and secure buy-in.
• It promotes and drives responsible and ethical use and handling of content while helping to build and foster an organizational culture of information excellence.

Who:

This research is designed for:

• Information Architect
• Chief Data Officer (CDO)
• Head of Data, Information Management
• Records Management
• CIO

Info-Tech Insight

ECM is critical to becoming a digital and modernized operation, where both structured data (such as sales reports) and unstructured content (such as customer sentiment in social media) are brought together for a 360-degree view of the customer or for a comprehensive legal discovery.

Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource. Metadata is often called data about data or information about information (NISO).

Metadata management is the function that manages and maintains the technology and processes that creates, processes, and stores metadata created by business processes and data.

• Data consumption
• Quality management
• Risk management

Value of Effective Metadata Management

• Supports the traceability of data through an environment.
• Creates standards and logging that enable information and data to be searchable and cataloged.
• Metadata schemas enable easier transferring and distribution of data across different environments.

Critical Success Factors of Metadata Management

• Consistent and documented data standards and definitions
• Architectural planning for metadata
• Incorporation of metadata into system design and the processing of data
• Technology to support metadata creation, collection, storage, and reviews (metadata repository, meta marts, etc.)

Data has massive potential to bring insight to an organization when combined and analyzed in creative ways.

It is difficult to bring data together from different sources to generate insights and prevent stale data.

Answer: Info-Tech’s Data Integration Onion Framework summarizes an organization’s data environment at a conceptual level and is used to design a common data-centric integration environment.

What is data integration and why is it needed?

• To get more value from their information, organizations are relying on increasingly more complex data sources. These diverse data sources have to be properly integrated to unlock the full potential of that data.
• Integrating large volumes of data from the many varied sources in an organization has incredible potential to yield insights, but many organizations struggle with creating the right structure for that blending to take place, and that leads to the formation of data silos.
• Data-centric integration capabilities can break down organizational silos. Once data silos are removed and all the information that is relevant to a given problem is available, problems with operational and transactional efficiencies can be solved, and value from business intelligence (BI) and analytics can be fully realized.

Is your integration near real time and scalable?

Who:

This research is designed for:

• Data Engineers
• Business Analysts
• Data Architects
• Head of Data Management
• Enterprise Architects

Info-Tech Insight

Every IT project requires data integration. Any change in the application and database ecosystem requires you to solve a data integration problem.

Master data management (MDM) “entails control over Master Data values and identifiers that enable consistent use, across systems, of the most accurate and timely data about essential business entities” (DAMA, 2017).

Fundamental objective of MDM: Enable the business to see one view of critical data elements across the organization.

What is MDM and why is it needed?

• Master data management (MDM) “entails control over Master Data values and identifiers that enable consistent use, across systems, of the most accurate and timely data about essential business entities” (DAMA, 2017).
• The fundamental objective of MDM is to enable the business to see one view of critical data elements across the organization.
• What is included in the scope of MDM?
  • Party data (employees, customers, etc.)
  • Product/service data
  • Financial data
  • Location data

Is there traceability and visibility into your data’s lineage? Does your data pipeline facilitate that single view across the organization?

Who:

This research is designed for:

• Chief Data Officer (CDO)
• Head of Data Management, CIO
• Data Architect
• Head of Data Governance, Data Officer

Info-Tech Insight

Successful MDM requires a comprehensive approach. To be successfully planned, implemented, and maintained it must include effective capabilities in the critical processes and subpractices of data management.

Data Modeling Framework

• The framework consists of the business, enterprise, application, and implementation layers.
• The Business Layer encodes real-world business concepts via the conceptual model.
• The Enterprise Layer defines all enterprise data asset details and their relationships.
• The Application Layer defines the data structures as used by a specific application.
• The Implementation Layer defines the data models and artifacts for use by software tools.

Model hierarchy

• The Conceptual data model describes the organization from a business perspective.
• The Message model is used to describe internal- and external-facing messages and is equivalent to the canonical model.
• The Enterprise model depicts the whole organization and is divided into domains.
• The Analytical model is built for specific business use cases.
• Application models are application-specific operational models.

Info-Tech Insight

The Conceptual model acts as the root of all the models required and used by an organization.

Objectives of Data Operations Management

• Implement and follow policies and procedures to manage data at each stage of its lifecycle.
• Maintain the technology supporting the flow and delivery of data (applications, databases, systems, etc.).
• Control the delivery of data within the system environment.

Indicators of Successful Data Operations Management

• Effective delivery of data assets to end users.
• Successful maintenance and performance of the technical environment that collects, stores, delivers, and purges organizational data.

This step will guide you through the following activities:

• Leverage your organization’s existing business capability map or initiate the formulation of a business capability map.
• Determine which business capabilities are considered high priority by your organization.
• Map your organization’s strategic objectives to value streams and capabilities to communicate how objectives are realized with the support of data.

Outcomes of this step

• A foundation for data management initiative planning that’s aligned with the organization’s business architecture: value streams, business capability map, and strategy map

Key Questions

• Who are your customers?
• What are the benefits we deliver to them?
• How do we deliver those benefits?
• How does the customer receive the benefits?

If the organization does not have a business architecture function to conduct and guide Activity 1.2.1, you can leverage the following approach:

• Meet with key stakeholders regarding this topic, then discuss and document your findings.
• When trying to identify the right stakeholders, consider: Who are the decision makers and key influencers? Who will impact this piece of business architecture–related work? Who has the relevant skills, competencies, experience, and knowledge about the organization?
• Engage with these stakeholders to define and validate how the organization creates value. Consider:
  • Who are your main stakeholders? This will depend on the industry in which you operate. For example, they could be customers, residents, citizens, constituents, students, patients.
  • What are your stakeholders looking to accomplish?
  • How does your organization’s products and/or services help them accomplish that?
  • What are the benefits your organization delivers to them and how does your organization deliver those benefits?
  • How do your stakeholders receive those benefits?

Align data management to the organization’s value realization activities.

Value streams enable the organization to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

Info-Tech Insight

Your organization’s value streams and the associated business capabilities require effectively managed and governed data. Without this, you could face elevated operational costs, missed opportunities, eroded stakeholder satisfaction, negative impact to reputation and brand, and/or increased exposure to business risk.

Business capabilities can be thought of as business terms defined using descriptive nouns such as “Marketing” or “Research and Development.”

If your organization doesn’t already have a business capability map, you can leverage the following approach to build one. This initiative requires a good understanding of the business. By working with the right stakeholders, you can develop a business capability map that speaks a common language and accurately depicts your business.

Working with the stakeholders as described in the slide entitled “Define or validate the organization’s value streams”:

• Analyze the value streams to identify and describe the organization’s capabilities that support them.
• Consider the objective of your value stream. (This can highlight which capabilities support which value stream.)
• As you initiate your engagement with your stakeholders, don’t start a blank page. Leverage the examples on the next slides as a starting point for your business capability map.
• When using these examples, consider: What are the activities that make up your particular business? Keep the ones that apply to your organization, remove the ones that don’t, and add any needed.

Align data management to the organization’s value realization activities.

Info-Tech Insight

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data management program must support.

For more information, refer to Info-Tech’s Document Your Business Architecture.

Example business capability map – Retail Banking

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip: Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realization capabilities under discussion. This will help to build awareness and visibility of the data management program.

Example business capability map for: Retail Banking

For this business capability map, download Info-Tech’s Industry Reference Architecture for Retail Banking.

Example business capability map – Higher Education

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip: Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realization capabilities under discussion. This will help to build awareness and visibility of the data management program.

Example business capability map for: Higher Education

For this business capability map, download Info-Tech’s Industry Reference Architecture for Higher Education.

Example business capability map – Local Government

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip: Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realization capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Local Government

For this business capability map, download Info-Tech’s Industry Reference Architecture for Local Government.

Example business capability map – Manufacturing

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip: Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realization capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Manufacturing

For this business capability map, download Info-Tech’s Industry Reference Architecture for Manufacturing.

Example business capability map – Retail

A business capability map can be thought of as a visual representation of your organization’s business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip: Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realization capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Retail

For this business capability map, download Info-Tech’s Industry Reference Architecture for Retail.

Example of business capabilities categorization or heatmapping – Retail

This exercise is useful in ensuring the data governance program is focused and aligned to support the priorities and direction of the business.

• Depending on the mandate from the business, priority may be on developing cost advantage. Hence the capabilities that deliver efficiency gains are the ones considered to be cost advantage creators.
• The business’ priority may be on maintaining or gaining a competitive advantage over its industry counterparts. Differentiation might be achieved in delivering unique or enhanced products, services, and/or experiences, and the focus will tend to be on the capabilities that are more end-stakeholder-facing (e.g. customer-, student-, patient,- and/or constituent-facing). These are the organization’s competitive advantage creators.

Example: Retail

For this business capability map, download Info-Tech’s Industry Reference Architecture for Retail.

Example of a strategy map tied to data management

• Strategic objectives are the outcomes the organization is looking to achieve.
• Value streams enable an organization to create and capture value in the market through interconnected activities that support strategic objectives.
• Business capabilities define what a business does to enable value creation in value streams.
• Data capabilities and initiatives are descriptions of action items on the data and data governance roadmap that will enable one or multiple business capabilities in its desired target state.

Info-Tech Tip: Start with the strategic objectives, then map the value streams that will ultimately drive them. Next, link the key capabilities that enable each value stream. Then map the data and data governance initiatives that support those capabilities. This process will help you prioritize the data initiatives that deliver the most value to the organization.

Example: Retail

For this strategy map, download Info-Tech’s Industry Reference Architecture for Retail.

This step will guide you through the following activities:

• Understand the main disciplines and makeup of a best-practice data management program.
• Determine which data management capabilities are considered high priority by your organization.

Outcomes of this step

• A foundation for data management initiative planning that’s aligned with the organization’s business architecture: value streams, business capability map, and strategy map

Data use cases

Sample Data

Use case 1

Sample Data

Use case 1: challenges, risks, and opportunities

Sample Data

Use case 1 (cont'd)

Sample Data

Use case 1 (cont'd)

Sample Data

What business capability (or capabilities) in your business area is this use case tied to?

What are your data-related challenges in performing this today?

What are the steps in the process/activity today?

What are the applications/systems used at each step today?

What data domains are involved, created, used, or transformed at each step today?

What does an ideal or improved state look like?

What other business units, business capabilities, activities, or processes will be impacted and/or improved if this were to be solved?

Who are the stakeholders impacted by these changes? Who needs to be consulted?

What are the risks to the organization (business capability, revenue, reputation, customer loyalty, etc.) if this is not addressed?

What compliance, regulatory, or policy concerns do we need to consider in any solution?

What measures of success or change should we use to prove the value of the effort (KPIs/ROI)? What is the measurable business value of doing this?

Conclusion: What are the data capabilities that need to be optimized, addressed, or improved to support or help realize the business capability (or capabilities) highlighted in this use case?

(Tip: This will inform your future-state data capabilities optimization planning and roadmapping activities.)

Data Management Workshop
Use Case 1: Covid-19 Emergency Management

[SAMPLE]

Inability to provide insights to DPH due to inconsistent data, inaccurate reporting, missing governance, and unknown data sources resulting in decisions that impact citizens being made without accurate information.

• Data is not suitable for analytics. It takes lot of effort to clean data.
• Data intervals are not correct and other data quality issues.
• The roles are not clearly defined.
• Lack of communication between key stakeholders.
• Inconsistent data/reporting/governance in the agencies. This has resulted in number of issues for Covid-19 emergency management. Not able to report accurately on number of cases, deaths, etc.
• Data collection systems changed overtime (forms, etc.).
• GIS has done all the reporting. However, why GIS is doing all the reporting is not clear. GIS provides critical information for location. Reason: GIS was ready with reporting solution ArcGIS.
• Problem with data collection, consolidation, and providing hierarchical view.
• Change in requirements, metrics – managing crisis by email and resulting in creating one dashboard after another. Not sure whether these dashboards being used.
• There is a lot of manual intervention and repeated work.

• One set of dashboards (or single dashboard) – too much time spend on measure development
• Accurate and timely data
• Automated data
• Access to granular data (for researchers and other stakeholders)
• Clear ownership of data and analytics
• It would have been nice to have governance already prior to this crisis
• Proper metrics to measure usage and value
• Give more capabilities such as predictive analytics, etc.

• DPH
• Schools
• Business
• Citizens
• Resources & Funding
• Data Integration & GIS
• Data Management
• Automated Data Quality

• HIPAA, FERPA, CJIS, IRS
• FEMA
• State compliance requirement – data classification
• CDC
• Federal data-sharing agreements/restrictions

• Reduction in cases
• Timely response to outbreak
• Better use of resources
• Economic impact
• Educational benefits
• Trust and satisfaction

Data Management Workshop
Use Case 1: Covid-19 Emergency Management

[SAMPLE]

Inability to provide insights to DPH due to inconsistent data, inaccurate reporting, missing governance, and unknown data sources resulting in decisions that impact citizens being made without accurate information.

1. Collect data through Survey123 using ArcGIS (hospitals are managed to report by 11 am) – owned KYEM
2. KYEM stores this information/data
3. Deduplicate data (emergency preparedness group)
4. Generate dashboard using ArcGIS
5. Map to monitor status of the update
6. Error correction using web portal (QAQC)
7. Download Excel/CVS after all 97 hospital reports
8. Sent to federal platform (White House, etc.)
9. Generate reports for epidemiologist (done manually for public reporting)

Data Management Workshop
Use Case 1: Covid-19 Emergency Management

[SAMPLE]

Inability to provide insights to DPH due to inconsistent data, inaccurate reporting, missing governance, and unknown data sources resulting in decisions that impact citizens being made without accurate information.

Prior to COVID-19 Emergency Response:

• ArcGIS data integrated available in data warehouse/data lake.
• KYEM data integrated and available in data warehouse/data lake.
• CHFS data integrated and available in data warehouse/data lake.
• Reporting standards and tools framework established.

After COVID-19 Emergency Response:

• Collect data through Survey123 using ArcGIS (hospitals are managed to report by 11 am) – owned KYEM.
• Error correction using web portal (QAQC).
• Generate reports/dashboard/files as per reporting/analytical requirements:
  • Federal reporting
  • COVID dashboards
  • Epidemiologist reports
  • Lab reporting

This step will guide you through the following activities:

• Leverage your organization’s existing business capability map or initiate the formulation of a business capability map, guided by info-Tech’s approach.
• Determine which business capabilities are considered high priority by your organization.
• Map your organization’s strategic objectives to value streams and capabilities to communicate how objectives are realized with the support of data.

Outcomes of this step

• A foundation for data management initiative planning that’s aligned with the organization’s business architecture: value streams, business capability map, and strategy map

Create a common data management vision that is consistently communicated to the organization

A data management program should be an enterprise-wide initiative.

• To create a strong vision for data management, there must be participation from the business and IT. A common vision will articulate the state the organization wishes to achieve and how it will reach that state. Visioning helps to develop long-term goals and direction.
• Once the vision is established, it must be effectively communicated to everyone, especially those who are involved in creating, managing, disposing, or archiving data.
• The data management program should be periodically refined. This will ensure the organization continues to incorporate best methods and practices as the organization grows and data needs evolve.

Info-Tech Tips

• Use information from the stakeholder interviews to derive business goals and objectives.
• Work to integrate different opinions and perspectives into the overall vision for data management.
• Brainstorm guiding principles for content and understand the overall value to the organization.

A clear vision statement helps align the entire organization to the same end goal.

Your vision should be brief, concise, and inspirational; it is attempting to say a lot in a few words, so be very thoughtful and careful with the words you choose. Consider your strengths across departments – business and IT, the consumers of your services, and your current/future commitments to service quality.

Remember that a vision statement is internally facing for other members of your company throughout the process.

While your vision is a declaration of where your organization aspires to be in the future, your mission statement should communicate the fundamental purpose of the data management practice.

It identifies the function of the practice, what it produces, and its high-level goals that are linked to delivering timely, high-quality, relevant, and valuable data to business processes and end users. Consider if the practice is responsible for providing data for analytical and/or operational use cases.

A mission statement should be a concise and clear statement of purpose for both internal and external stakeholders.

Corporate

Group 1

Group 2

The vision is a statement about the organization’s goals and provides a basis to guide decisions and rally employees toward a shared goal.

The principles or themes communicate the organization’s priorities for its information management program.

Policies are a set of official guidelines that determine a course of action. For example: Company is committed to safety for its employees.

Procedures are a set of actions for doing something. For example: Company employees will wear protective gear while on the production floor.

• The beginning of a data management practice is a clear set of goals and key performance indicators (KPIs).
  A good set of goals takes time and input from senior leadership and stakeholders.
• The data management program lead is selling a compelling vision of what is possible.
• The vision also helps set the scope and expectations about what the data management program lead is and is not doing.
• Be realistic about what you can do and how long it will take to see a difference.

Example vision statements: The organization is dedicated to creating an enabling structure that helps the organization get the right information to the right people at the right time. The organization is dedicated to creating a program that recognizes data as an asset, establishing a data-centric culture, and ensuring data quality and accessibility to achieve service excellence.

Is it modern and high end, with digital self-service?

Twelve data management universal principles

Phase 1

1.1 Review the Data Management Framework

1.2 Understand and Align to Business Drivers

1.3 Build High-Value Use Cases

1.4 Create a Vision

Phase 2

2.1 Assess Data Management

2.2 Build Your Data Management Roadmap

2.3 Organize Business Data Domains

This phase will walk you through the following activities:

• Understand your current data management capabilities.
• Define target-state capabilities required to achieve business goals and enable the data strategy.
• Identify priority initiatives and planning timelines for data management improvements.

This phase involves the following participants:

• Data Management Lead/Information Management Lead, CDO, Data Lead
• Senior Business Leaders
• Business SMEs
• Data owners, records managers, regulatory subject matter experts (e.g. legal counsel, security)

This step will guide you through the following activities:

• Assess the current state of your data management capabilities.
• Define target-state capabilities required to achieve business goals and enable the data strategy.
• Identify gaps and prioritize focus areas for improvement.

Outcomes of this step

• A prioritized set of improvement areas aligned with business value stream and drivers

Define current state

• Based on Info-Tech’s Data Management Framework, evaluate the current-state performance levels for your organization’s data management practice.
• Use the CMMI maturity index to assign values 1 to 5 for each capability and enabler.

This step will guide you through the following activities:

• Identify and understand data management gaps.
• Develop data management improvement initiatives.
• Build a data management–prioritized roadmap.

Outcomes of this step

• A foundation for data management initiative planning that’s aligned with the organization’s business architecture: value streams, business capability map, and strategy map

This step will guide you through the following activities:

• Identify business data domains that flow through and support the systems environment and business processes.
• Define and organize business data domains with assigned owners, artifacts, and profiles.
• Apply the domain map to building governance program.

Outcomes of this step

• Business data domain map with assigned owners and artifacts

Business and data domains

[SAMPLE]

Embrace the technology

• Data catalog
• Business data glossary
• Data lineage
• Metadata management

Additional Support

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889

To accelerate this project, engage your IT team in an Info-Tech workshop with an Info-Tech analyst team.

Info-Tech analysts will join you and your team at your location or welcome you to Info-Tech’s historic Toronto office to participate in an innovative onsite workshop.

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