Introduction

The Data Management Strategy & Business Case determines how data management is defined, organized, funded, governed and embedded into the operations of the organization. It defines the long-term vision including a description of stakeholders or stakeholder functions that must be aligned. Data Management Strategy demonstrates the business value that the program will seek to achieve. It becomes the blueprint for the organization to evaluate, define, plan, measure and execute a successful and mature Data Management (DM) initiative.

The purpose of developing a DM strategy and business case is to articulate the rationale for the DM initiative. The strategy defines why the initiative is needed, as well as the goals, and expected benefits. The strategy also describes how to mobilize the organization in order to implement a successful DM initiative. The DM business case provides the rationale for the investment in the Data Management initiative. Data Management is no different than any other established business process. It needs to be justified, funded, measured and evaluated. It provides clarity of purpose, enabling agreement and support of initiative objectives from senior executives as well as program stakeholders.

Definition

The Data Management Strategy (DMS) & Business Case component is a set of capabilities to define, prioritize, organize, fund and govern data management and how it is embedded into the operations of the organization in alignment with the objectives and priorities of both the Enterprise and Operating Units. The DM business case is the justification for creating and funding a DM initiative. The business case articulates the major data and data related issues facing an organization or operating unit and describes the expected outcomes and benefits that can be achieved through the implementation of a successful DM initiative.

Scope

• Establish a DMS function within the Office of Data Management (ODM).
• Work with Data Management Program Management Office (PMO) to design and implement sustainable BAU processes and tools for the DMS function.
• Align the DMS with the business strategy, objectives, and priorities, including prioritization of data based on its criticality to the business.
• Define the rationale and business case for management of data as an asset through the organization-wide DM initiative.
• Ensure the DMS is aligned with the organization-wide Enterprise Data Management Principles.
• Articulate the DM target and current-state. Then, using DCAM as an assessment tool for gap analysis and prioritized gap closure, create a cohesive execution plan.
• Define the high-level execution roadmap.
• Define strategy execution risks and mitigations.
• Define Data Management performance metrics.
• Document the DMS with a compelling presentation of the value of an organization-wide DM initiative.
• Ensure that the DMS governance is integrated into Data Governance.

Value Proposition

Organizations that have Enterprise and Operating Unit executives who understand, support, and offer direction for the organization-wide DM initiative lower organizational risk and get better acceptance of the DM Initiative at all levels of staff. Staff engagement in the sustainable management of data for the short and long-term success of the organization is essential. Organizations that implement effective data management get a return on investment from several areas:

• Efficiency and effectiveness of data issue resolution, compliance, and auditable demonstration
• Improved enterprise risk management
• Efficiency in business process optimization
• Innovation and differentiation for customers

Overview

The DMS component is one of the three foundational components of the DCAM Framework. The DMS is what integrates the strategies of each of the other components of the Framework into an overall strategy for the execution of the DM initiative. It is important to note that the DMS is a function, within the Office of Data Management in which strategic planning capabilities and skills reside. (You may refer to “Overview” in the “Data Management Program” section of this guide for detail on the structure of the Office of Data Management).

Using the DCAM Framework provides a structure for the DM initiative that includes the core principles of data management. It also helps stakeholders understand the value of data management as it relates to their Operating Units and strategic initiatives.

The strategy should align with the organization’s articulated Target Operating Model for executing data management with a roadmap and timeline to achieve the target. It is important for a strategy to compare the target-state to the current-state in order to show the organizational, functional, operational, and technological gaps and inefficiencies. The Strategy can then define, prioritize, and schedule gap closure. DCAM used as a capability assessment tool is fundamental to the analysis of gaps in each operating level and organizational unit.

The DMS integrates the Framework components at each operating level throughout the organization. For detail on the levels and context at which data management operates, refer to “Data Management Operating Levels” in the introductory section of this guide.

A strategy must be documented for each organizational unit at the various operating levels of the organization and work in concert with the other organizational units across the organization. Within a single organizational unit, each DCAM component has unique input to the strategy that are then integrated with the other component input and prioritized in the final strategy for that organizational unit. These inputs must align with the Data Management Target Operating Model for the organization. The Target Operating Model defines the expected component and capability requirements for the operating level of the organizational unit.

Because not all organizational units will be at the same maturity in the design and execution of their DM initiative these strategies are specific to their business objectives, priorities, and identified data management inefficiencies and gaps.

The importance of the physical documentation should not be underestimated because the document is the primary internal marketing tool to drive understanding and support from all stakeholders at all levels of the organization.

The DMS includes the business case that describes how value will be realized from the data assets of an organization, through the collaboration of business, data, and technology.

Diagram 1.1: Data Asset Value Model

The DM business case is the cost-benefit realization of the set of activities and deliverables expected from the DM initiative. The DM business case answers the question: Why the firm is focusing on data management? This helps achieve alignment across the stakeholders. The business case helps management understand the costs, benefits, and risks associated with the evolution of the DM initiative. It is essential to link the business case with realistic strategic and tactical measurement criteria and align them with the long-term sequence plan for the DM initiative. This enables the organization to understand the total costs associated with implementation as well as maintenance of the DM initiative and helps ensure that it is sufficiently funded to meet both near and long-term objectives.

The DM business case articulates the benefits of data management, in alignment with the objectives defined, communicated and agreed upon in the DMS. It discusses the defensive benefits of the initiative including operational cost reduction, improved regulatory reporting, streamlined risk management, controlled data governance, improved data quality. It also highlights the offensive benefits of the initiative which include advanced analytics, improved customer service, innovative product development, increased revenues, improved market penetration.

In some cases, the best way to build support for the business case is through a demonstrative proof of concept or pilot project. In these instances, a specific pain point or high-profile business objective would be selected and used to demonstrate the benefits of implementing effective data management. If this approach is used, it is important to select a project that is achievable and can provide quick wins. This approach builds confidence among stakeholders on the foundational benefits of data management to ensure sustainability. Regardless of whether you define the business case with or without a proof of concept, all activities must align to the strategic business objectives of the organization.

The DM strategy and the business case are not static and must be able to evolve as the priorities and needs of the organization change. The most effective and successful data management strategies are living artifacts that are visibly endorsed by executive management and are supported by mandatory organizational policy.

Processes, Tools, & Constructs

• Target Operating Model
• Strategic Plan Documentation
• Data Management Business Glossary
• Data Management Principles
• Data Management Accountability Matrix
• Stakeholder Analysis
• Business Strategy Integration Matrix
• Business Case Construct
• DM initiative Metrics
• DCAM Framework inclusive of capability assessment tool
• Capability Optimization Roadmap
• Capability Optimization
• RACI Matrix
• Process Designs and End-to-End Process Integration
• Procedures Guide
• Process Performance Measurement

Core Questions

• Does the DMS clearly articulate the reason and the importance of implementing the DM initiative at each level of the organization?
• Is there executive buy-in across business, operations and technology?
• Do stakeholders agree to support and sustain a DMS function?
• Has the DMS sufficiently defined the immediate, medium and long-term goals and objectives of the organization-wide DM initiative?
• Is the DMS in line with organizational priorities?
• Has the DMS effectively identified the critical areas of focus, including how priorities are established and verified?
• Has the DMS identified the operating model and required staffing resources needed to establish, lead and maintain the Data Management initiative?
• Is the Data Management Business Case aligned with the strategic goals of the organization?

First Capability

In most organizations ad-hoc data initiatives will not be enough to help the business achieve success. To create success the data management organization needs to understand the high-level business requirements and associated data requirements. These requirements are critical to establish and prioritize data management initiatives. The data management initiatives must be aligned to the needs, priorities, and desired outcomes of the business stakeholders.

First Sub-Capability

Description

High-level business requirements are those identified by the operating units, often reflecting the high-level enterprise requirements identified by executive management. It is important that the data strategy and data management strategy reflect both the organizational requirements as well as operating units’ requirements.

Next Sub-Capability

Description

The prioritized enterprise and operating units’ business and data requirements will inform the priorities of data initiatives.

Next Sub-Capability

Establishing the Data Strategy is a critical component of the Data Management Program. A robust Data Strategy encompasses the entire organization and outlines the necessary elements from the Data Management program, such as data requirements, functional capabilities, and resources, to achieve the organization's strategy and objectives. It incorporates feedback from all stakeholders, both business and functional, and prioritizes their needs to enhance the overall benefits to the organization.

First Sub-Capability

Description

Defining a data strategy is established and informed by business objectives and includes: a data content strategy identifying what data is required; a data usage strategy for how the data will be used; and a data deployment strategy that aligns the business objectives to a prioritized execution roadmap.

Next Sub-Capability

Description

The data content strategy identifies the sources and types of data that are required to meet the prioritized objectives of the business. Sources include both internal and external data.

Next Sub-Capability

The Data Management Strategy is a collaborative result of business, data and technology stakeholders. The Data Management Strategy should be informed by elements identified and prioritized in the business requirements and the Data Strategy. The Data Management Strategy should include the objectives of each of the components in the DCAM Framework and the priorities from the Data Strategy that result in an integrated implementation roadmap. As business objectives evolve and require adjustment to the Data Strategy, the Data Management Strategy should also incorporate necessary updates.

First Sub-Capability

Description

The Data Management Strategy is a collaboration with the full spectrum of business, technology and operations management stakeholders. Together they document the Data Management Strategy. The Data Management Strategy focuses on how to best apply the data management functions to deliver data and information to the organization in support of the business objectives.