Robert Audet


We live in an ever-evolving global and inter- connected world, fueled by data to help organizations stay relevant, impactful and successful. Data is foundational for meeting the growing information needs to enable decision-making, regulatory reporting, and service delivery. Navigating this evolving landscape, a greater need for organizations is to become more data-informed and data-driven. Competing organizational priorities, limited skilled resources in data disciplines, complex governing structures and myriad other internal and external forces — at right — complicate the journey toward becoming a data-driven and resilient organization

Internal Forces

• Large Volumes and Variety of Data Types — Increasing volumes of data are created daily, necessitating more sophisticated data management platforms to ingest, process, analyze, and store data.

• Limited Skilled Resources — Organizations lag in building a data culture and having enough resources proficient in proactively managing and leveraging data as a strategic asset.

• Poor Data Quality — 84% of senior leadership is concerned about the quality of the data they are basing their decisions on, paralyzing their organization from moving forward.

• Constrained Budget — Budgetary pressures require organizations to do more with less and

collaborate with other enterprise leaders to align on priorities.

External Forces

• Demanding Data Consumers — Expectations for faster, more personalized, and more sophisticated decision-making, including the increased usage of third-party data to augment internal data sources.

• Rapid Technology Advancements — Digitization increases the complexity and diversity of data sets, and opportunities to use artificial intelligence or robotic process automation to apply rule and algorithm-based automation requires quality data.

• Expanded Laws/Regulatory Compliance (when applicable) — The Foundations for Evidence

based Policymaking Act (“Evidence Act”), the Federal Data Strategy, Financial Transparency Act, and the General Data Protection Regulation (GDPR) are placing greater focus on data management, data compliance, data governance, and the demand for increased public transparency.

Rather than see these forces as burdensome or as roadblocks, organization executives should look at them as opportunities to transform their data landscape in a strategic manner. To do so, they need to develop or refine their data strategy, then look at resetting their data operating model to bring that strategy to life (this topic will be covered in a future article).

Forbes press release, “Poor-Quality Data Imposes Costs and Risks on Businesses,” May 31, 2017,

The absence of a well-thought-out, business-driven data strategy can lead to an inability to execute the organization’s mission and meet strategic goals and objectives. Such an inability can, in turn, increase the likelihood of failure right out of the gate and could lead to an expensive redesign. A well-defined data strategy sets the stage to transform the operating model to better manage and leverage data by defining strategic goals, objectives, and desired capabilities with an executable path to delivery.

Organizations that can visualize the course, e.g., define goals and objectives focused on advancing the organization’s data capabilities and ensure alignment with the organization’s overall mission, and navigate the terrain, e.g., turn strategy into execution through a practical holistic approach, have the greatest chance of success. There are multiple success factors when defining and executing your organization’s data strategy.


Empowered leadership. We advocate a top-down approach that begins with identifying a key data leader who can champion the change effort. If your organization has not appointed a chief data officer, we recommend waiting to define the data strategy until the CDO is appointed; otherwise, a future CDO may be less invested in the strategy.

Leverage the right approach. Many organizations approach data strategies using a bottom-up approach to identify existing data assets and architecture and subsequently define a plan to implement technical solutions to address the gaps, which can lead to misalignment with business needs. We advise using a business-centric approach focused on identifying information-al needs and use cases based on how data consumers access and leverage data. When defining a data strategy, Michael Conlin, the United States Department of Defense chief data officer, says “CDOs should start with a mission-first approach by focusing on business data domains, collaborate with executive sponsors who represent each business data domain, understand their goals and objectives, and determine what improvements are needed to maximize the value of data to best enable these goals and objectives. Data strategies should never purpose data for its own sake, avoid the common anti-patterns such as surveying all the data assets and avoiding the use case by use case-based approach.” A well-defined data strategy should include:

1. Data vision, goals and objectives.

2. Information needs and use cases to improve the data life cycle, and data capabilities to develop, improve, and/or maintain.

3. Future-state conceptual architecture to visualize how the technology landscape will change.

4. Proposed projects — prioritized by leadership — with well-defined scope, articulation of qualitative and quantitative benefits, assumptions, dependencies, and resource estimates.

5. A time-phased road map to highlight projects to improve the maturity of data capabilities, key dependencies, and quick-hit projects to deliver rapid value.


When defining a data strategy, federal CDOs will need to account for recent federal data requirements. More specifically, the Open, Public, Electronic, and Necessary (OPEN) Government Data Act establishes CDO as a required role for federal agencies. In addition to general CDO requirements, federal CDOs need to account for the various requirements from the Evidence Act and the Federal Data Strategy (FDS).

For example, both the Evidence Act and FDS require agencies to inventory critical agency data assets and make data open with well-maintained and accessible metadata. This approach better identifies the desired data capabilities and gaps to inform proposed data initiatives and projects linked to anticipated benefits.

Non-federal organizations should account for compliance with GDPR, the California Consumer Privacy Act and other regulations to avoid negative privacy and brand impacts.


Establish a platform for ongoing collaboration. Since many data initiatives involve stakeholders from the business, IT and data organizations, success of these efforts requires continuous collaboration to foster teamwork around issues like priorities, funding, resources and execution. For example, CDOs will need to work closely with the chief information officer (CIO) to integrate the prioritization of data initiatives and projects with the IT project portfolio.

Mobilize for success. Many organizations struggle with pivoting from defining their strategy and road map to execution and delivery. Successful mobilization requires a clear articulation of resource needs and how the enterprise will provide these resource needs and programmatic capabilities to effectively govern decisions, manage issues and risks, provide transparency on road map execution, and manage dependencies. Furthermore, the CDO needs to continually champion the execution of the strategic road map and take the lead on driving accountability at all levels of the program.

Manage the change. A data strategy will introduce change, which will need to be effectively managed from the outset. CDOs and those involved in drafting and driving a data strategy need to understand the current state, including contextual factors, key drivers for change, and organization and personnel readiness for change and transformation. This information will better inform the change vision and strategy for executing a successful transformation. For example, if the strategy will introduce a new data cataloging capability for data stewards to better manage metadata for an organization’s data assets, this capability will require change management to create awareness, enable data stewards to use the new capability, and reinforce the desired behaviors.


1. Hire or appoint a CDO to lead the organization’s data efforts.

2. Assemble a cross-functional team from business divisions and IT that can support defining the data strategy.

3. Perform a data maturity assessment to evaluate the current state of all data-related activities and capabilities.

4. Identify and understand the external forces placing more demands on how your organization manages and leverages data.

5. Draft a data strategy document that aligns to your organization’s overall vision, goals, and objectives.

Defining your data strategy is a key first step toward maximizing the value of your organization’s data assets and preparing your organization to successfully navigate the storms ahead. Look for our follow-up article focused on how organizations can transform their operating models to enable their business-driven data strategy.

Robert Audet leads Guidehouse’s Data Management Team and advises federal and commercial CDOs on better managing and leveraging data as an asset. He has 20+ years of experience, primarily advising chief data officers (CDOs), chief information officers, and data/IT leadership across different industries. He specializes in information strategy, data strategy, Office of the chief data officer Operating Model Design, Data Management Maturity Assessments, Business Intelligence and Data Warehousing, Data Governance, and Data Quality Programs.

Carly Mitchell is a director in Guidehouse’s Financial Services practice, focusing on delivering high-impact business transformation and operational strategies for commercial and public sector clients. Carly is a certified facilitator who brings a unique combination of strategy techniques, industry insights, and project management discipline to help agency leaders and C-suite executives develop successful strategies to transform and innovate their operations. Carly is also the 2019-2020 president of the Junior League of Washington, and a graduate of Leadership Greater Washington’s Signature Program.