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Build a Robust and Comprehensive Data Strategy

Build a data strategy that’s organization first, not technology first.

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Data finds its greatest value when it can help with critical decisions and lead to outcomes. For data to achieve those goals, it’s essential that data leaders are the ultimate translators between organizational requirements and technical data capabilities. Use this blueprint to decode your stakeholders’ key concerns and organizational goals and objectives, so you can build a data strategy that powers the enterprise and makes you a trusted and valued partner to the organization.

Data isn’t a backroom concern; it’s a strategic resource that’s becoming even more critical as organizations seek to make the most of digital transformations and AI and get more out of their investments. Data teams already add value to their organization – the key to success for data strategy is in aligning with the organization and communicating the value to your stakeholders.

1. Data has no inherent value without an organization-aligned strategy

You can collect and store endless amounts of data, which alone will have no value. The power of data is in the way your organization uses it. Data leadership is often siloed from the wider decision-making capabilities of the organization. A robust and comprehensive data strategy is the first essential step in making data leaders valuable partners.

2. Don’t forget the people in "people, process, and technology"

Engage with leaders and stakeholders in various functions within the organization to understand what data would be valuable to them. It’s critical to align your data strategy with organizational and department outcomes and communicate the data strategy effectively to become an invaluable partner.

3. Take an organization-first approach, not a technology-first approach

Many data strategies place focus on the tools and technical capabilities being employed, rather than the benefits they provide to the organization. Focus on your organization’s strategic vision and key initiatives first, and the technical capabilities of your data team next. A data leader must be both an organizational strategist and a technical savant.

Use this step-by-step blueprint to create your organization-aligned data strategy

By empowering your organization to shape its data journey and create strategies that are driven by organizational needs, you can ensure that their data initiatives yield meaningful, long-term value. This comprehensive research includes actionable templates as tools to help you:

  • Establish the scope of your data strategy and the key stakeholders required to identify supporting strategies, pain points, and needs from across your organization.
  • Develop a vision and guiding principles for your data strategy that prioritize value-driven initiatives.
  • Communicate your data strategy to key stakeholders in commercial terms rather than technical terms to earn support for ongoing data-led initiatives.

Build a Robust and Comprehensive Data Strategy Research & Tools

1. Build a Robust and Comprehensive Data Strategy Storyboard

Maximize the value of your data with an organization-first, technology-second strategy. This storyboard delineates a five-phase process to defining and developing a modern data strategy.

Build a Robust and Comprehensive Data Strategy – Phases 1-5

2. Data Strategy C-Suite Presentation Template

This in-depth presentation template provides an example of a complete data strategy, ready to be tailored to your organization and presented to your executive leadership to gain support for your strategy.

Data Strategy C-Suite Presentation Template

3. Business Context Interview Guide

This template identifies key organization leaders and questions needed to understand top priorities.

Use this template as a starting point to interview your organization leaders to elicit the right context, extracting business goals, organizational priorities, and key initiatives that will play a critical role in building your data strategy.

Business Context Interview Guide

4. Data Strategy Stakeholder Interview Guide and Findings

This template guides you through a robust interview process to determine your organization’s current data and analytics utilization.

Use the structure and questions within this template to help you frame your discussion with stakeholders and support your team in defining the data and analytics needs related to your line of business objectives.

Data Strategy Stakeholder Interview Guide and Findings

5. Data Initiatives & Strategy Ideation Primer

Use this primer to help connect the dots between what the organization needs and what is technically possible for your data team.

Data Initiatives & Strategy Ideation Primer

6. Data Value Mapping Tool

This holistic value mapping tool guides you through a step-by-step process to understand how to realistically deliver tangible value from data that your executives will understand, care about, and are willing to support.

Use this tool to document and assess potential data initiatives, prioritize them against organization needs, assess key risks, and develop an indicative timeline for your key initiatives.

Data Value Mapping Tool
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Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.

9.4/10

Overall Impact

$44,826

Average $ Saved

30

Average Days Saved

Client

Experience

Impact

$ Saved

Days Saved

State of South Dakota Bureau of Information and Telecommunications

Workshop

9/10

$34,250

20

Best was the collaboration among the Agency representatives that resulted by bringing them together. For the amount of material that there is on... Read More

Starkey Hearing Technologies

Workshop

8/10

$34,250

10

We went into the workshop knowing that we had to reduce scope. We did an tactical internal assessment of sorts, without business stakeholder partic... Read More

Education Service Center Region 20

Guided Implementation

10/10

$34,250

20

Great stating point. I don't know the full extent of the impact on our overall goals, but I answered conservatively as of right now.

CELL THERAPY CATAPULT LIMITED

Guided Implementation

10/10

$3,420

20

Practical advise and good infographics to use

Red de Carreteras de Occidente, S.A.B. de C.V.

Guided Implementation

10/10

$34,250

50

This project will have a good impact in our orgenization.

Heritage Petroleum Co Ltd

Guided Implementation

9/10

$6,850

2

City of Peoria, AZ

Workshop

10/10

N/A

110

Best part - we have a clear path forward and it includes some key stakeholders. We were able to prioritize what was important to them, help them s... Read More

Heritage Petroleum Co Ltd

Guided Implementation

9/10

$4,110

5

Wolf & Company, P.C.

Guided Implementation

9/10

$44,525

9

Hydro Tasmania

Guided Implementation

10/10

$1,820

20

Best parts was having access to the Infotech team and their expertise. Great templates for getting started and guiding the way.

Oregon Public Defense Services Commission

Guided Implementation

10/10

$6,850

32

The pre-built documentation (templates, slideshows), the maturity assessment, and the knowledgeable assistance and guidance through the process of ... Read More

City of Tucson Information Technology Department Office of the Deputy Director

Guided Implementation

10/10

$13,700

10

Suncoast Credit Union

Workshop

10/10

$68,500

20

The best part is getting all the deparments together and discussing the challenges they have and building a roadmap out of those discussions. Howa... Read More

Heritage Petroleum Co Ltd

Guided Implementation

8/10

$4,110

2

Southwest Gas Corporation

Workshop

10/10

$75,350

80

Claudia did a great job facilitating and keeping the group engaged. The content was very informative and sets us up for success as we establish a f... Read More

Heritage Petroleum Co Ltd

Guided Implementation

9/10

$2,329

5

PG Group

Guided Implementation

10/10

N/A

110

The best was having a sounding board in Crystal and the invaluable advice and experience she shared with me. The tools she was able to share with m... Read More

Kindercare Education LLC

Guided Implementation

8/10

$75,350

20

Best: Excellent discussions to zero-in and prioritize which components of the Data Strategy are the most important for Kindercare. Worst: Ther... Read More

Norfolk State University

Guided Implementation

10/10

$13,700

20

The data strategy resources shared were most helpful.

Rosemont Pharmaceuticals Ltd

Guided Implementation

9/10

N/A

N/A

Lilima said "I would give 9 to Igor, he is really helpful". Obviously this is an ongoing engagement so will consider any time impact at the end.

Lindt & Sprungli (north America) Inc.

Guided Implementation

10/10

$1,370

1

Tessy Plastics Corporation

Guided Implementation

10/10

$41,100

10

Best - Working with Igor Worst- (Not really a worst) - Being unable to utilize all the great information and be able to impact change immediately.

Angola LNG Limited - Sucursal de Angola

Guided Implementation

10/10

N/A

10

Best part 1 - Time saving by using Infotech tools and advice 2 - Prompt support from Crystal 3 - Tools and documentation Worst part N/A

Rollins

Guided Implementation

10/10

$13,700

10

The best part has been that Crystal Singh is exceptionally informative and deeply knowledgeable about data strategy and related subject matter. She... Read More

Oregon Department of Education

Guided Implementation

10/10

$12,330

55

Lindt & Sprungli (north America) Inc.

Guided Implementation

7/10

N/A

2

I'm not sure I had a good idea of what I wanted to get from the call, so in the end the outcome was limited. However, I got a few good nuggets and ... Read More

City Of Avondale

Workshop

10/10

$65,075

26

Howard was an excellent facilitator and very knowledgeable on the topic of data.

ENERGYUNITED ELECTRIC MEMBERSHIP CORPORATION

Guided Implementation

9/10

$6,850

2

Modesto Irrigation District

Workshop

10/10

$137K

110

The workshop was a big success for us. The deliverables are immediately useful and have jumpstarted our data journey. Gordon McMaster did a fanta... Read More

Dead River Company, LLC

Guided Implementation

10/10

$137K

N/A

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Data Strategy

All of our Info-Tech Academy courses have closed captioning available. To turn this function on, click on the C.C. in the bottom right corner of the video screen and click "English" on the options that pop-up.

  • Course Modules: 7
  • Estimated Completion Time: 1.5 hours

Now Playing:
Academy: Data Strategy | Introduction

An active membership is required to access Info-Tech Academy

Workshop: Build a Robust and Comprehensive Data Strategy

Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.

Module 1: Establish scope of your data strategy

The Purpose

Define the full scope of your data strategy.

Key Benefits Achieved

Alignment with the group on how far your data strategy will (and won’t) go.

Activities

Outputs

1.1

Identify your organization’s strategic vision and goals.

  • Business context; strategic drivers.
  • Sample vision and mission statements.
1.2

Identify the business initiatives that support the organizational strategy.

1.3

Discuss the importance of vision, mission, and guiding principles of the organization’s data strategy.

  • Data strategy guiding principles.

Module 2: Gather the key inputs for your strategy

The Purpose

Align and bring together what will inform your data strategy.

Key Benefits Achieved

  • A clearer view of the organization’s needs and pains outside of your data team.
  • A view of your overall data maturity and culture.

Activities

Outputs

2.1

Conduct line-of-business deep dives to understand supporting strategies and tactics, pain points, and current and desired uses and applications of data.

  • Line-of-business inputs and considerations for data initiatives and strategies.
2.2

Identify critical risks to your data strategy.

  • Data strategy risks and inhibitors.
2.3

Assess your current data culture.

  • Data culture diagnostics results.

Module 3: Align on how to increase business value from data

The Purpose

Focus on a business-first approach to your data strategy by thinking about how you can leverage data to achieve key business outcomes.

Key Benefits Achieved

Take the first step in changing the culture of both your data teams and users to focus on business outcomes.

Activities

Outputs

3.1

Establish line-of-business data gain and pain-relieving initiatives.

3.2

Establish data team(s) gain and pain-relieving initiatives.

  • Data initiatives definition.
3.3

Consolidate your data initiatives and establish your top data strategies.

  • Data strategies definition.

Module 4: Develop your data strategy and value delivery horizons

The Purpose

Formalize elements of your data strategy and provide an initial view of future delivery based on the strategy.

Key Benefits Achieved

Be in a position to ask for executive alignment along with a clear view of next steps.

Activities

Outputs

4.1

Assess data initiative feasibility.

  • List of prioritized data strategies and initiatives.
4.2

Map value to corporate and functional strategic goals (and timing).

  • Data value maps.
4.3

Rationalize your initiative list based on strategic value alignment.

4.4

Establish your “big bet.”

  • Your data strategy “big bet.”
4.5

Complete your data strategy tactic cards.

  • Data strategy tactic cards.
4.6

Outline your key CXO asks and next steps.

  • Outline key CxO asks.

Build a Robust and Comprehensive Data Strategy

Build a business-first, not technology-first, data strategy.

Analyst perspective

Build a business-first, technology-second strategy to maximize the value of your data.

Ryan Brunet

Ryan Brunet

Principal Research Director
Info-Tech Research Group

Steve Willis

Steve Willis

Principal Research Director
Info-Tech Research Group

Data strategies too often get mired in technical details or remain overly simplistic, failing to connect with the real goals of the organization. A successful strategy should resonate with executive leadership, emphasizing how data initiatives directly support the organization’s mission and critical goals. By clearly articulating the value of data in business terms, data leaders can secure executive sponsorship, ensuring alignment and resources for impactful initiatives.

The data leader must function as the ultimate translator, playing a critical role in aligning data initiatives with the strategic priorities of the organization. This is not just about applying data to meet current needs but about envisioning how data can fuel future growth and innovation through its vast array of applications. By empowering the organization to shape the data journey and creating strategies that are driven by business needs, organizations can ensure that their data initiatives yield meaningful, long-term value.

The future is bright for data leaders who embrace this transformative journey. With the right alignment, data becomes more than a byproduct — it becomes a renewable resource fueling sustainable growth and strategic advantage. Embrace the change and lead with confidence, because the impact of a well-executed data strategy can elevate the entire organization.

Executive summary

Your Challenge

  • Data & Analytics Are Not Well Understood: The CDO role and the full potential of data and analytics are often misunderstood, seen merely as reporting functions rather than transformative levers to drive value through data.
  • Lack of Focus on Outcomes: Data leaders often struggle to define success in terms of business outcomes, making it difficult to meet executive expectations and build trust in the data program.
  • Difficulty Gaining Executive Sponsorship: Misalignment between data strategies and corporate goals results in challenges securing sponsorship and funding from the C-suite, creating a significant opportunity cost.

Common Obstacles

  • Existing Data Strategies Are Poorly Formed: Many data strategies are either too detailed or too shallow, resulting in a failure to gain the necessary buy-in and support to execute.
  • Organizations Focus on Technical Capabilities Over Business Value: Strategies often emphasize data tools and technical capabilities, losing stakeholders in technical jargon and concepts along the way, distracting from a value-first approach for strategy development.
  • Conventional Wisdom Misguides Data Leaders: Data experts are not always strategy experts, and standard frameworks often guide them to focus on what they are doing instead of how they are driving organizational success.

Info-Tech’s Approach

  • Focus on Business Outcomes: Shift the emphasis from technical data capabilities to how data initiatives can directly support and enable the achievement of critical business goals.
  • Simplify Communication for Executive Buy-In: Develop a clear, high-level strategy that resonates with the C-suite by aligning data initiatives with corporate objectives, making it easier to gain executive sponsorship and funding.
  • Separate Strategy From Execution: Avoid conflating strategy with detailed operational plans; instead, focus on defining a clear direction and priorities first, allowing time for thorough assessments and implementation roadmaps to follow later.

Info-Tech Insight: Data strategies often focus on aggregating use cases, but this rarely drives progress toward corporate goals. A strategy should be focused on how data will be used to achieve the corporate mission, not just loosely linked to it. In the rush to prove value, we must ensure that the value aligns with and supports the organization's objectives. A use-case-driven strategy is reactive; a business-focused strategy shapes use cases to fulfill broader business goals.

Your challenge

Data leaders will be required to develop new strategies to meet exponentially growing demand for data and analytical capabilities or risk being left behind.

  • The demand for data, and the increasing speed at which it can be processed and made available, will continue to grow exponentially.
  • With the advancement of AI technologies, organizations can now tackle more complex problems and build systems that will take advantage of real-time data from multiple sources. Organizations will start collecting new types of data (e.g. data from IoT devices, data generated by physical processes, synthetic data generated to support development of new products and services). These data sources will allow organizations to innovate and solve new, complex problems.
  • This exponentially growing demand for data increases the pressure on technology and data leaders to deliver the processes, capabilities, and technologies to service that demand; however, with only a few data leaders considered genuine business value generators by business executives, most of these leaders will be required to develop new tactics to meet these expectations or risk being left behind.

“It is predicted that by the end 2025 around 463 exabytes of data will be generated daily worldwide.”

Source: Edge Delta, 2024

“72% of leading organizations note that managing data is already one of the top challenges preventing them from scaling AI use cases.”

Source: “The Data Dividend," McKinsey, 2023

“OpenAI’s ChatGPT-3 was trained on around 570GB of data sets. Your AI use cases will demand significant quantities of quality data.”

Source: BBC Science Focus, 2023

Common obstacles

These barriers make this challenge difficult to address for many organizations:

  • Wasting time and resources on managing all data assets equally and missing business opportunities due to a lack of understanding of the most valuable data assets as the actual differentiator in value generation.
  • Inability of data and analytics team to meet business needs to innovate, grow, create differentiators, and stay ahead of the competition. The business views data, analytics, and AI only as a business enabler rather than as a product and driver in achieving the greater outcomes, for example, shaping products and services and driving new business value. IT needs to work with the business to understand how data needs to be managed to meet the business’ need to innovate and grow.
  • Organizations are struggling to understand the impact that new AI technologies have across the organization, including the impact on business strategy, data, IT, and AI strategy. Organizations are wasting time and missing opportunities due to the lack of a clear framework that should be used to assess how new technologies should shape the business model.

49.1%

Less than half of organizations report that they are currently managing data as a business asset.

Source: Wavestone, 2024

89%

While 99% of respondents recognize the positive impacts generative AI can have on their organization, 89% of respondents report that their use of generative AI is being slowed.

Source: Elastic, “Global Generative AI Adoption Study,” 2024

The pains are felt across the entire organization

Organizations are not prepared for the exponential speed and scale of AI innovation and the increasing amount of real-time data driven by AI growth, which makes data management and pipeline provisioning more complex and difficult to execute.

Business and IT transformations fail due to a lack of business leadership. Organizations need to build an urgency and trust with business leaders. In most organizations, business stakeholders do not lead data and AI innovation and transformation, which results in the failure of digital transformation efforts. This leads to wasted money, time, and effort.

  • The greatest challenges to becoming data-driven are the function of culture, people, process change, and organizational alignment (77.6%) rather than technology limitations (23.4%) (Wavestone, 2024).

69%

69% of respondents stated that employees in their organization struggle to access the data they need when they need it.

Source: Elastic, 2024

Nine Steps to Understanding the Data and Analytics Landscape. The key to landscaping your data environment lies in ensuring foundational disciplines are optimized in a way that recognizes the interdependency among the various disciplines.

Info-Tech’s methodology to Build a Robust and Comprehensive Data Strategy

1. Understand your corporate objectives & initiatives

2. Gather the key inputs for your strategy

3. Ideate on how to increase business value from data

4. Rationalize priorities that enable business goals

5. Finalize your business data strategy

Phase Steps

  1. Identify your organization’s strategic vision and goals.
  2. Discuss the importance of vision, mission, and guiding principles for the organization’s data strategy.
  1. Conduct line-of-business deep dives to understand supporting strategies and tactics, pain points, and current and desired uses and applications of data.
  2. Identify critical risks to your data strategy.
  3. Assess your current data culture.
  1. Establish line-of-business data gain and pain-relieving initiatives.
  2. Establish data team’s gain and pain-relieving initiatives.
  3. Consolidate your data initiatives and establish your top data strategies.
  1. Assess data initiative feasibility.
  2. Map value to corporate and functional strategic goals (and timing).
  3. Rationalize your initiative list based on strategic value alignment.
  4. Establish your “big bet.”
  5. Complete your data strategy tactic cards.
  1. Create your executive summary.
  2. Create your strategy on a page.
  3. Consolidate your final strategy.
  4. Outline your key CxO asks and next steps.

Phase Outcomes

  1. Business context; strategic drivers
  2. Sample vision and mission statements
  3. Data strategy guiding principles
  1. Line-of-business inputs and considerations for data initiatives and strategies
  2. Data strategy risks and inhibiters
  3. Data culture diagnostics results
  1. Data initiatives definition
  2. Data strategies definition
  1. List of prioritized data strategies and initiatives
  2. Data value maps
  3. Data strategy tactic cards
  4. Your data strategy “big bet”
  1. Final data strategy
  2. C-suite data strategy presentation deck
  3. Key asks and next steps

Insight summary

Overarching insight

Data strategies often focus on aggregating use cases, but this rarely drives progress toward corporate goals. A strategy should be focused on how data will be used to achieve the corporate mission, not just loosely linked to it. In the rush to prove value, we must ensure that the value aligns with and supports the organization's objectives. A use case-driven strategy is reactive; a business-focused strategy shapes use cases to fulfill broader business goals.

Data Isn’t Special

Data, in isolation, is simply raw information with no inherent value. It only becomes meaningful when it is aligned with and actively drives the organization’s strategic goals. By embedding data into decision-making processes, organizations can turn it into actionable insights that lead to measurable outcomes and accelerate your corporate strategic objectives. It is only a strategic asset if you know how to apply the right way.

Do Your Homework

Failing to engage and gather input from key line-of-business stakeholders when developing a data strategy leads to misalignment with business needs and objectives, resulting in a strategy that does not address the actual pain points or priorities of different teams. A lack of stakeholder input often results in low adoption rates, as the tools and strategies developed do not align with the day-to-day realities of the business. Not getting the right people in the room creates an unnecessary and avoidable opportunity cost.

Earn Your Right

Your data strategy is only the starting point of your data and analytics transformation journey. You earn the right to execute and secure funding by clearly articulating the value that your data initiatives will drive. You accomplish this by being the ultimate translator, balancing between commercial guru and technical savant. Marrying the most pressing opportunities with the art of the possible and clearly articulating the value proposition in business language will earn you your right to bring to your strategy to life.

Tactical insight

Be thorough and thoughtful in finding the right cross section of stakeholders to provide input into your strategy development. Missing key stakeholders can derail your effort.

Tactical insight

Don’t overpromise when defining the value horizons for your initiatives; they only need to be directionally correct. You need to provide a rough guideline to secure your funding and support.

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

Business Context Interview Guide

Understand the strategic objectives of your organization so that you can align the right data initiatives.

Data Initiatives & Strategy Ideation Primer

Understand the art of the possible as you ideate through your data initiatives.

Data Strategy Stakeholder Interview Guide and Findings

Understand the line-of-business imperatives for data and analytics applications in your organization.

Data Value Mapping Tool

Establish and rationalize your data initiatives and tactics to support your organizational goals.

Key deliverable

Data Strategy C-Suite Presentation Template

A highly visual and compelling presentation template that enables easy customization and executive-facing content.

Measure the value of this blueprint

Leverage this blueprint’s approach to ensure your data strategy and initiatives align and support your organization’s strategic direction.

Project outcome

Metric

Strategy funding secured Approved budget allocation
Approval to move to execution plan and scoping Strategy sign-off
Executive partnership and resourcing established CxO sign-off
Improved stakeholder sentiment toward your data program Improved data culture diagnostic results

Case study

Inside IKEA’s data-led digital transformation strategy

IKEA

INDUSTRY

Retail

SOURCE

Harvard Business Review

Challenge

IKEA, a leading global home furnishings retailer, faced the challenge of adapting its traditional, store-centric business model to meet the demands of a digital world. With shifting customer preferences and the rapid rise of ecommerce, IKEA needed to integrate digital capabilities across its operations while preserving its brand identity and values. The company grappled with managing unprecedented ecommerce growth, aligning its physical stores with digital operations, and creating a seamless omnichannel experience for customers. Additionally, ensuring robust data governance and integration across supply chain, inventory, and customer service functions was crucial to support this transformation.

Solution

To address these challenges, IKEA implemented a comprehensive data-driven transformation that integrated AI and advanced analytics. The company developed a unified data ecosystem across various functions to ensure data accuracy and accessibility, laying a foundation for effective data governance. By embedding AI-driven insights into decision-making, IKEA improved forecasting, inventory management, and personalized engagement, supporting its digital and operational goals. To enhance customer experience, IKEA introduced tools like the “Shop & Go” app, allowing customers to scan and purchase items in-store, and virtual room visualization, enabling customers to view products in their spaces. This transformation aligned with IKEA’s values, fostering cross-team collaboration and developing new digital skills essential for the future.

Results

IKEA’s data strategy and digital transformation led to measurable improvements across various business metrics. Ecommerce sales tripled within three years, with online revenue growing from 7% to 31% of total sales. Operational efficiency increased significantly, as stores were transformed into fulfillment centers, which reduced time-to-insight by 30% and optimized supply chain processes. Through its Customer Data Promise, IKEA also improved data transparency, leading to increased trust and engagement among customers. By aligning its data strategy with its corporate goals and leveraging advanced analytics, IKEA successfully transformed into a data-driven retailer, ready to meet the evolving needs of customers in a digital-first world.

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

"Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful."

Guided Implementation

"Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track."

Workshop

"We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place."

Executive & Technical Counseling

"Our team and processes are maturing; however, to expedite the journey we'll need a seasoned practitioner to coach and validate approaches, deliverables, and opportunities."

Consulting

"Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project."

Diagnostics and consistent frameworks are used throughout all five options.

Guided Implementation

What does a typical GI on this topic look like?

Phase 1

Phase 2

Phase 3

Phase 4

Phase 5

  • Call #1: Scope requirements, objectives, and your specific challenges.
  • Call #2: Establish business context for your strategy.
  • Call #3: Establish vision, mission, and guiding principles.
  • Call #4: Debrief line of business deep dive.
  • Call #5: Identify risks and inhibitors to your data strategy.
  • Call #6: Define your data initiatives portfolio.
  • Call #7: Define your data strategies and key tactics.
  • Call #8: Assess data initiative feasibility and prioritization.
  • Call #9: Rationalize your initiatives portfolio and align strategic value.
  • Call #10: Define your “big bet” and complete your strategy cards.
  • Call #11: Summarize results and plan next steps.

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is 8 to 12 calls over the course of 2 to 3 months.

Data Strategy – Workshop Overview

Contact your account representative for more information.

workshops@infotech.com
1-888-670-8889

Pre-Workshop

Understand data & analytics concepts and data culture

Session 1

Establish scope of your data strategy

Session 2

Gather the key inputs for your strategy

Session 3

Align on how to increase business value from data

Session 4

Develop your data strategy and value delivery horizons

Post-Workshop

Next steps and wrap-up (offsite)

Activities

CxO to:

  • Review Data Initiatives and Strategy Ideation Primer.
  • Complete Data Culture Diagnostic (Optional).
  • Schedule participants.
  • Complete prework.
  • Identify your organization’s strategic vision and goals.
  • Identify the business initiatives that support the organizational strategy.
  • Discuss the importance of vision, mission, and guiding principles of the organization’s data strategy.
  • Conduct line-of-business deep dives to understand supporting strategies and tactics, pain points, and current and desired uses and applications of data.
  • Identify critical risks to your data strategy.
  • Assess your current data culture.
  • Establish line-of-business data gain and pain-relieving initiatives.
  • Establish data team’s gain and pain-relieving initiatives.
  • Consolidate your data initiatives and establish your top data strategies.
  • Assess data initiative feasibility.
  • Map value to corporate and functional strategic goals (and timing).
  • Rationalize your initiative list based on strategic value alignment.
  • Establish your “big bet.”
  • Complete your data strategy tactic cards.
  • Outline your key CxO asks and next steps.
  • Generate workshop deliverables.
  • Set up review time for workshop report and to discuss next steps.

Outcomes

  • Activity outputs to be shared with workshop facilitator at Info-Tech.
  • Business context; strategic drivers
  • Sample vision and mission statements
  • Data strategy guiding principles
  • Line-of-business inputs and considerations for data initiatives and strategies
  • Data strategy risks and Inhibiters
  • Data culture diagnostics results
  • Data initiatives definition
  • Data strategies definition
  • List of prioritized data strategies and initiatives
  • Data value maps
  • Data strategy tactic cards
  • Your data strategy “big bet”
  • Outline key CxO asks
  • Completed workshop deliverables
  • Provide exercise tools leveraged in workshop with content entered in workshop (optional)

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 analytical solutions to your business in support of your highest value objectives.

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: Your data strategy is about determining how to drive value for your organization from your data. Your data strategy is not a data management plan. Data management is about how you execute against your strategy from an operational perspective. Your strategic plan is a prerequisite for your executional plan.

Your data isn’t special

Your data is only as good as your ability to derive value from it.

  1. Data is not the new oil

    While the phrase "data is the new oil" is often used to emphasize the value of data in the digital economy, it is a flawed analogy. Unlike oil, which is a finite resource and depleted when used, data is an infinite, renewable resource that can be replicated, reused, and continuously generated without depletion. Oil has intrinsic value once extracted and refined, while data’s value is only realized when it is properly analyzed, contextualized, and leveraged for insights.

  2. Data & analytics is a journey, not a destination

    Building a data strategy is a journey, not a destination. It requires organizations to continually evolve and adapt their data practices to ensure they are extracting maximum value from their data. Organizations must focus on building the capability to extract value from their data, whether through analytics, machine learning, or business intelligence tools. A successful data strategy is not just about technical capabilities; it’s about ensuring that data-driven insights are driving the business forward, supporting key goals, and enabling innovation.

  3. Misalignment to the business is an opportunity cost

    Without a clear connection to business goals, data initiatives often fail to address the most pressing needs, limiting the strategy’s impact and relevance, presenting a substantial opportunity cost. This misalignment can result in data projects that consume valuable resources but fall short of driving meaningful outcomes, such as improved decision-making, operational efficiency, or customer insights. By not anchoring data efforts to specific business priorities, organizations miss the opportunity to leverage data fully as a strategic asset. As McKinsey advises, “Think business backwards, not data forward.”

Changes in business and technology are altering how organizations use and manage data

The world moves a lot faster today

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 (the pace at which data is captured, organized, and analyzed) must also accelerate.

Data Management Implications

  • 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.

Zettabyte Era

181

More Data

The amount of data expected to be created, consumed, and stored globally is 181 zettabytes in 2025, up from 147 zettabytes in 2024 (DemandSage, 2024).

Evolving Technologies

$805B

Cloud Proliferation

Global end-user spending on public cloud services is forecast to reach $805 billion in 2024 and expected to double by 2028 (IDC, 2024).

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About Info-Tech

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We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

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What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

You get:

  • Data Strategy C-Suite Presentation Template
  • Business Context Interview Guide
  • Data Strategy Stakeholder Interview Guide and Findings
  • Data Initiatives & Strategy Ideation Primer
  • Data Value Mapping Tool

Need Extra Help?
Speak With An Analyst

Get the help you need in this 5-phase advisory process. You'll receive 11 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Understand Your Corporate Objectives & Initiatives
  • Call 1: Scope requirements, objectives, and your specific challenges.
  • Call 2: Establish business context for your strategy.
  • Call 3: Establish vision, mission, and guiding principles.

Guided Implementation 2: Gather Your Key Inputs for Your Strategy
  • Call 1: Debrief line of business deep dive.
  • Call 2: Identify risks and inhibitors to your data strategy.

Guided Implementation 3: Ideate on How to Increase Business Value From Data
  • Call 1: Define your data initiatives portfolio.
  • Call 2: Define your data strategies and key tactics.

Guided Implementation 4: Rationalize Priorities That Enable Business Goals
  • Call 1: Assess data initiative feasibility and prioritization.
  • Call 2: Rationalize your initiatives portfolio and align strategic value.
  • Call 3: Define your “big bet” and complete your strategy cards.

Guided Implementation 5: Finalize Your Business Data Strategy
  • Call 1: Summarize results and plan next steps.

Authors

Crystal Singh

Steve Willis

Ryan Brunet

Contributors

Three Anonymous External Contributors:

  • CDO (Government Entity)
  • Sr Director Data & Analytics (Investment Management)
  • Director of Business Intelligence (B2C SaaS Product)

Related Content: Data Management

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