1. Create a Plan for Establishing a Business-Aligned Data Management Practice
Make sure the right information gets to the right people, at the right time.
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2. ANALYST PERSPECTIVE
IT needs to spend more time on “I” and less on “T.” (Harvard Business Review )
Insightful data-focused strategies are driving today’s business agendas. There is a growing gap between the exceptional leaders in each market and their market followers. Data is used in ways never before imagined, calling to action the need for relevant, complete, consistent, transparent, precise, timely, and accurate data. 
This requires an enterprise-wide approach to data management founded in business strategy. Aligning your business’s data strategies with key data management enablers will ensure that your data management practice is fit-for-business purpose and is right-sized to meet your unique business data needs.
Steven J. Wilson,
Senior Director, Data Management, BI, EI Practice
Info-Tech Research Group

3. Confirm this data management blueprint aligns with your project’s mission and expected outcomes
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 its data assets
Design a data management program that can scale and evolve over time
Business leaders create plans for leveraging 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 their broader plans
Identify gaps in current data services and the supporting environment and determine effective corrective actions

4. Executive Summary
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.
Data management is not one size fits all Cut through the noise related to data management and create a strategy and process that is right for your organization.
Take a data-oriented approach People stop thinking about data and the “art of the possible” when you bring up business functions. Maintain a data focus during a project’s planning, delivery, and evaluation stages.
Quickly generate business returns
Take immediate action on quick resolution issues uncovered in business interviews to help overcome the common inhibitors to strategic planning projects.
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.
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, but instead align it to business requirements and the business’s 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.
Culture of Collaboration: For a data management practice to be successful and have longevity, it must actively engage the business during its planning and implementation. Through this cross-functional and collaborative approach, data assets can be best managed and leveraged by the business.

5. 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
Data Management Enablers
Data Governance
Data Strategy Planning
Data Architecture
Data Operations Management
Data Risk Management
Data Quality Management 1
Client Intimacy / Service Excellence 2
Product and Service Innovations 3
Operational Excellence 4
Risk and Compliance Management

6. Regulatory Compliance
Industry Spotlight: Risk Management in the Financial Services Sector
Regulatory
Compliance
$11M
USD Fine
Fine incurred by a well-known Wall Street firm after using inaccurate data to execute short sales orders.
Regulations are the #1 driver for risk management.
In 2008, the world experienced the worst financial crisis since the Great Depression. Major financial institutions were badly affected by risky assumptions and poorly informed decisions. One common cause among many of those worst affected was being unaware of the risk they were exposed to. Robust data management is imperative to accurately understanding your risk, as well as maintaining compliance with ever-expanding regulations.

7. GOVERNMENT TRANSPARENCY
Industry Spotlight: Operational Excellence in the Public Sector 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
By opening up data, citizens are enabled to be more directly informed and involved in decision making.
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.

8. Industry Spotlight: Operational Excellence and Client Intimacy in Major League Sports
Team Performance Benefits 1
Optimal line-ups
SPORTS
ANALYTICS 2
Player salary optimization 3
Real time play calling 4
Gathering proprietary data
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. 5
Draft analysis
Customer Intelligence and Revenue Benefits 6
Dynamic ticket pricing 7
Marketing optimization 8
Fan loyalty analytics
(Davenport, 2014)
Industry leaders cite data, and the insights they glean from it, as their means of standing apart from their competitors.

9. Supply Chain Efficiency
Industry Spotlight: Operational Excellence and Service Delivery within manufacturing and supply chain services
Supply Chain Efficiency
Involving Data in Your Supply Chain 6x
Leaders are 6 times more likely to report an increase in supply chain efficiency of 10% or greater.
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. 5x
Leaders are 5 times more likely to report shortened order-to-delivery cycle times.
97% of executives have an understanding of how data can improve their supply chain, but only 17% reported implementing any analytics in a supply chain function. 5x
Leaders are 5 times more likely to report an improvement in demand-driven opportunities.
(Accenture, 2015)
(Lewis, 2014)

10. Informed Product Development
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 the development of a well-received product a challenge. Supporting the probability of a successful outcome requires information and insights into consumer trends, shopping preferences, and market analysis.
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?
Internal Data
Organizational sales performance
External Data
Competitor performance
Market analysis
Consumer trends and preferences
The number of product launches deemed successful based on first year revenue performance.
(Schneider and Hall, 2011) 3%
The ability to accurately answer these questions requires a combination of operational and analytical data.

11. Changes in business and technology are changing how organizations use and manage data
The world moves a lot faster today.
Studies and projections show a clear case of how data and its usage will grow and evolve.
Zettabyte Era
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 the business must have accurate and up-to-date data at their fingertips.
To support the new demands around data consumption, improved Data Velocity (pace in which data is captured, organized, and analyzed) must also accelerate. ≠
44x
More Data
Annual Data Production in 2020 is expected to be 44 times greater than levels in (CSC, 2012)
Evolving Technologies
Cloud Proliferation ≠
1/3
Data Management Implications
Strong integration capabilities
Intelligent and efficient systems
Embedded data quality management
Strong transparency into the history of data and its transformation
Cloud is not a new technology, but its rise as a mainstay storage and application platform will have ripple effects in data management practices.
It is projected that, by 2020, one-third of data created will live in or pass through the Cloud. (CSC, 2012)

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