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Create a Data Management Roadmap

Enhance your data management program with our simplified framework.

Data has quickly become one of the most valuable assets in any organization. But when it comes to strategically and effectively managing those data assets, many businesses find themselves playing catch-up. The stakes are high because ineffective data management practices can have serious consequences, from poor business decisions and missed revenue opportunities to critical cybersecurity risks.

Successful management and consistent delivery of data assets requires collaboration between the business and IT and the right balance of technology, process, and resourcing solutions.

Build an effective and collaborative data management practice

Data management is not one-size-fits-all. Cut through the noise around data management and create a roadmap that is right for your organization:

  • Align data management plans with business requirements and strategic plans.
  • Create a collaborative plan that unites IT and the business in managing data assets.
  • Design a program that can scale and evolve over time.
  • Perform data strategy planning and incorporate data capabilities into your broader plans.
  • Identify gaps in current data services and the supporting environment and determine effective corrective actions.

This blueprint will help you design a data management practice that builds capabilities to support your organization’s current use of data and its vision for the future.


Create a Data Management Roadmap Research & Tools

1. Create a Data Management Roadmap Storyboard – Use this deck to help you design a data management practice and turn data into a strategic enabler for the organization.

Effective data delivery and management provides the business with new and improved opportunities to leverage data for business operations and decision making. This blueprint will help you design a data management practice that will help your team build capabilities that align to the business' current usage of data and its vision for the future.

2. Data Management Strategy Planning Tools – Use these tools to align with the business and lay the foundations for the success of your data management practice.

Begin by using the interview guide to engage stakeholders to gain a thorough understanding of the business’ challenges with data, their strategic goals, and the opportunities for data to support their future plans. From there, these tools will help you identify the current and target capabilities for your data management practice, analyze gaps, and build your roadmap.

3. Stakeholder Communication and Assessment Tools – Use these templates to develop a communication strategy that will convey the value of the data management project to the organization and meet the needs of key stakeholders.

Strong messaging around the value and purpose of the data management practice is essential to ensure buy-in. Use these templates to build a business case for the project and socialize the idea of data management across the various levels of the organization while anticipating the impact on and reactions from key stakeholders.

4. Data Management Strategy Work Breakdown Structure Template – Use this template to maintain strong project management throughout your data management project.

This customizable template will support an organized approach to designing a program that addresses the business’ current and evolving data management needs. Use it to plan and track your deliverables and outcomes related to each stage of the project.

5. Data Management Roadmap Tools – Use these templates to plan initiatives and create a data management roadmap presentation.

Create a roadmap for your data management practice that aligns to your organization’s current needs for data and its vision for how it wants to use data over the next 3-5 years. The initiative tool guides you to identify and record all initiative components, from benefits to costs, while the roadmap template helps you create a presentation to share your project findings with your executive team and project sponsors.

6. Track and Measure Benefits Tool – Use this tool to monitor the project’s progress and impact.

Benefits tracking enables you to measure the effectiveness of your project and make adjustments where necessary to realize expected benefits. This tool will help you track benefit metrics at regular intervals to report progress on goals and identify benefits that are not being realized so that you can take remedial action.


Member Testimonials

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Having reference material to build from that has all the research and analysis pre-done and vetted

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Best part of the experience is being obtaining tangible steps, techniques and processes to work on in the next 2 years to mature our data managemen... Read More


Create a Data Management Roadmap

Ensure the right capabilities to support your data strategy.

Contents

Executive Brief
Analyst Perspective
Executive Summary
Phase 1: Build Business and User Context
Phase 2: Assess Data Management and Build Your Roadmap
Additional Support
Related Research
Bibliography

Create a Data Management Roadmap

Ensure the right capabilities to support your data strategy.

EXECUTIVE BRIEF

Analyst Perspective

Establish a data management program to realize the data strategy vision and data-driven organization.

Data is one of the most valuable organizational assets, and data management is the foundation – made up of plans, programs, and practices – that delivers, secures, and enhances the value of those assets.

Digital transformation in how we do business and innovations like artificial intelligence and automation that deliver exciting experiences for our customers are all powered by readily available, trusted data. And there’s so much more of it.

A data management roadmap designed for where you are in your business journey and what’s important to you provides tangible answers to “Where do we start?” and “What do we do?”

This blueprint helps you build and enhance data management capabilities as well as identify the next steps for evaluating, strengthening, harmonizing, and optimizing these capabilities, aligned precisely with business objectives and data strategy.

Andrea Malick
Director, Research & Advisory, Data & Analytics Practice
Info-Tech Research Group

Frame the problem

Who this research is for
  • 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
This research will help you
  • 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.
This research will also assist
  • 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
This research will also help you
  • 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.

Executive Summary

Your Challenge
  • 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.
Common Obstacles
  • 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.
Info-Tech’s Approach
  • 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.

Info-Tech Insight

Use value streams and business capabilities to develop a prioritized and practical data management plan that provides the highest business satisfaction in the shortest time.

Full page illustration of the 'Create a Data Management Roadmap' using the image of a cargo ship labelled 'Data Management' moving in the direction of 'Business Strategy'. The caption at the top reads 'Data Management capabilities create new business value by augmenting data & optimizing it for analytics. Data is a digital imprint of organizational activities.'

Data Management Capabilities

A similar concept to the last one, with a ship moving toward 'Business Strategy', except the ship is cross-sectioned with different capabilities filling the interior of the silhouette. Below are different steps in data management 'Data Creation', 'Data Ingestion', 'Data Accumulation, 'Data Augmentation', 'Data Delivery', and 'Data Consumption'.

Data is a business asset and needs to be treated like one

Data management is an enabler of the business and therefore needs to be driven by business goals and objectives. For data to be a strategic asset of the business, the business and IT processes that support its delivery and management must be mature and clearly executed.

Business Drivers
  1. Client Intimacy/Service Excellence
  2. Product and Service Innovations
  3. Operational Excellence
  4. Risk and Compliance Management
Data Management Enablers
  • Data Governance
  • Data Strategy Planning
  • Data Architecture
  • Data Operations Management
  • Data Risk Management
  • Data Quality Management

Industry spotlight: Risk management in the financial services sector

REGULATORY
COMPLIANCE

Regulations are the #1 driver for risk management.

US$11M:

Fine incurred by a well-known Wall Street firm after using inaccurate data to execute short sales orders.
“To successfully leverage customer data while maintaining compliance and transparency, the financial sector must adapt its current data management strategies to meet the needs of an ever-evolving digital landscape.” (Phoebe Fasulo, Security Scorecard, 2021)

Industry spotlight: Operational excellence in the public sector

GOVERNMENT
TRANSPARENCY

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.

Industry spotlight: Operational excellence and client intimacy in major league sports

SPORTS
ANALYTICS

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.

Team Performance Benefits
  1. Talent identification
  2. In-game decision making
  3. Injury reduction
  4. Athlete performance
  5. Bargaining agreement
Team Performance Benefits
  1. Fan engagement
  2. Licensing
  3. Sports gambling
(Deloitte Insights, 2020)
Industry leaders cite data, and the insights they glean from it, as their means of standing apart from their competitors.

Industry spotlight: Operational excellence and service delivery within manufacturing and supply chain services

SUPPLY CHAIN
EFFICIENCY

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

25%

Companies can reap a 25% increase in productivity, a 20% gain in space usage, and a 30% improvement in stock use efficiency if they use integrated order processing for their inventory system.

36%

Thirty-six percent of supply chain professionals say that one of the top drivers of their analytics initiatives is the optimization of inventory management to balance supply and demand.
(Source: FinancesOnline, 2021)

Industry spotlight: Intelligent product innovation and strong product portfolios differentiate consumer retailers and CPGs

INFORMED PRODUCT
DEVELOPMENT
Consumer shopping habits and preferences are notoriously variable, making it a challenge to develop a well-received product. Information and insights into consumer trends, shopping preferences, and market analysis support the probability of a successful outcome.

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

Product Development
  • 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?
A combination of operational data and analytics data is required to accurately answer these questions.
Internal Data
  • Organizational sales performance
External Data
  • Competitor performance
  • Market analysis
  • Consumer trends and preferences
Around 75% of ideas fail for organizational reasons – viability or feasibility or time to market issues. On the other hand, around 20% of product ideas fail due to user-related issues – not valuable or usable (Medium, 2020).

Changes in business and technology are changing 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 (pace in 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

64.2

More Data

The amount of data created, consumed, and stored globally is forecast to increase rapidly, reaching 64.2 zettabytes in 2020 and projected to grow to over 180 zettabyes in 2025 (Statista, 2021).

Evolving Technologies

$480B

Cloud Proliferation

Global end-user spending on public cloud services is expected to exceed $480 billion next year (Info-Tech, 2021).

To differentiate and remain competitive in today’s marketplace, organizations are becoming more data-driven

Pyramid with a blue tip. Sublevels from top down are labelled 'Analytical Companies', 'Analytical Aspirations', 'Localized Analytics', and 'Analytically Impaired'.

Analytic Competitor

“Given the unforgiving competitive landscape, organizations have to transform now, and correctly. Winning requires an outcome-focused analytics strategy.” (Ramya Srinivasan, Forbes, 2021)
Data and the use of data analytics has become a centerpiece to effective modern business. Top-performing organizations across a variety of industries have been cited as using analytics five times more than lower performers (MIT Sloan).

The strategic value of data

Power intelligent and transformative organizational performance through leveraging data.

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

Harness the value of your data

Despite investments in data initiatives, organizations are carrying high levels of data debt

Data debt is the accumulated cost that is associated with the suboptimal governance of data assets in an enterprise, like technical debt.

Data debt is a problem for 78% of organizations.

40%

of organizations say individuals within the business do not trust data insights.

66%

of organizations say a backlog of data debt is impacting new data management initiatives.

33%

of organizations are not able to get value from a new system or technology investment.

30%

of organizations are unable to become data-driven.

(Source: Experian, 2020)

The journey to being data-driven

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

The Data Economy

Diagram of 'The Data Economy' with three points on an arrow. 'Data Disengaged: You have a low appetite for data and rarely use data for decision making.' 'Data Enabled: Technology, data architecture, and people and processes are optimized and supported by data governance.' 'Data Driven: You are differentiating and competing on data and analytics, described as a “data first” organization. You’re collaborating through data. Data is an asset.'

Measure success to demonstrate tangible business value

Put data management into the context of the business:
  • 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.

Enhance your data management program with our simplified framework.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

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.

MEMBER RATING

10.0/10
Overall Impact

$34,000
Average $ Saved

16
Average Days Saved

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.

Read what our members are saying

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:

  • A data management framework built on deep insight and best practices.
  • Detailed step-by-step processes and tools to evaluate core disciplines such as governance and data architecture and build a roadmap that’s relevant to your organization.
  • Easy-to-customize templates to develop a right-sized, business-aligned data management practice.

Need Extra Help?
Speak With An Analyst

Get the help you need in this 2-phase advisory process. You'll receive 9 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Align with the business
  • Call 1: Understand drivers, business context, and scope of data management at your organization. Learn about Info-Tech’s approach and resources.
  • Call 2: Get a detailed overview of Info-Tech’s approach, framework, Data Culture Diagnostic, and blueprint.
  • Call 3: Align your business capabilities with your data management capabilities. Begin to develop a use case framework.
  • Call 4: Further discuss alignment of business capabilities to data management capabilities and use case framework.

Guided Implementation 2: Plan for the future
  • Call 1: Assess your current data management capabilities and data environment. Review your Data Culture Diagnostic Scorecard, if applicable.
  • Call 2: Plan target state and corresponding initiatives.
  • Call 3: Identify program risks and formulate a roadmap.
  • Call 4: Identify and prioritize improvements. Define a RACI chart.
  • Call 5: Summarize results and plan next steps.

Authors

Rachel D'Hollander

Andrea Malick

Contributors

  • Michael Blaha, Consultant and Author, Patterns of Data Modeling
  • David Birmingham, Senior Solutions Architect, BrightLight Consulting
  • Mario Cantin, Chief Data Strategist, Prodago
  • Nancy Couture, Delivery Enablement Lead, Datasource Consulting
  • Mehrdad Novin, Senior Data Architect/Modeler Consultant
  • Martin Sykora, Director, NexJ Analytics
  • Kirti Shetty, Data Quality Business Delivery Manager, TD Canada Trust
  • Anne Marie Smith, Ph.D, Board of Directors, DAMA International
  • John Talburt, Chief Data Scientist, BlackOak Analytics
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