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Building Your Data Management Strategy

Posted On 10/27/2016

Copyright 2016 by TDWI, a division of 1105 Media, Inc. Reprinted by permission of TDWI. Visit TDWI.org for more information.

A data management strategy is the foundation of any data management program. The strategy provides both the framework and the architecture that will last throughout the life of your program. Ensuring your foundation is built on solid rock may be the most critical success factor of your program. This can ensure consistent project and integration approaches, best practices in design and implementation, modern technologies, and effective data policies. Let’s understand more about evaluating the current state of your data management program.

Today’s data management programs often evolve piecemeal over time as projects, teams, technologies, systems, and data assets are mingled together through business changes and company mergers, acquisitions, and reorganizations. In time, a lacking program strategy takes a toll on even the best-intentioned data management program. Then, as senior management places greater demands on the struggling program’s capabilities, teams grapple with making the disjointed pieces work together.

In some cases, a meaningful data management strategy was never developed to kick off the program effectively. Without strategic planning, a data management program can quickly veer off course or lose momentum in the corporate shuffle. First, let’s take a baseline of a healthy data management program framework, which has the following components:

  • Clearly-defined program vision
  • Current-state and future-state reference architectures
  • Integration strategies (for people, process, technology, and data!)
  • Delivery model
  • Adoption strategy
  • Communication plan
  • Strong, unified leadership team
  • Executive sponsorship
  • Data management maturity model and road map

If you are missing too many of these key components or they are out of date, then you are most likely seeing decreased momentum in your delivery and missing out on the potential business value of your program. Take the following steps to create a strategy that moves your data management program and teams in the right direction.

Building a Strategic Data Management Action Plan

  1. Seek external, third-party, vendor-neutral help for this. Professional resources can bring fresh perspective and expertise about the latest technology trends. An unbiased third party can help your program get needed acceptance from leadership and participants.
  2. Add a one-month phase zero to your program’s project plan to create a multiyear, data management maturity road map.
  3. Identify the successes and gaps in your current program. Design the new model to build on the current successes and bridge the gaps.
  4. Evaluate the latest trends in cloud, big data, data integration, analytics, and BI technologies. After considering their total cost of ownership, take a smarter look at those that add value to your program. Add technologies and methodologies that can complement your overall framework.
  5. Leverage agile project management concepts to align business and IT. Sprints can help produce tangible results at the speed required today.
  6. Design current-state and future-state architectures and clearly delineate gaps between the two.
  7. Clearly define teams, roles, and responsibilities in the program. Form a strong, unified leadership team united by enterprise-wide vision.
  8. Create a communication plan to routinely highlight the program’s business value and showcase the team’s value-added contributions. Design the plan to keep all participants and the business at large informed, engaged, and aligned with the program’s strategic global vision.
  9. Obtain solid executive sponsorship to keep the program in the forefront as a business priority despite future business changes, mergers, acquisitions, and reorganizations.

An out-of-date or piecemeal strategy is equal to a missing strategy. Take time now to revamp and strategically architect your data management program’s framework. This can significantly improve your data assets over time, decrease your delivery timelines, and improve insights into business opportunities, providing a substantial return on your investment.


About the Author

Wesley Flores

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