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Every complex program, portfolio, and initiative can benefit from the development of a program roadmap.  A roadmap shows the major events, their links, and the milestones graphically

Whether an organization is beginning to develop an analytics program, or re-architecting an existing one, long term success depends on having a right-sized, sound approach, and a realistic plan.

 A program roadmap is high-level representation of a program’s direction.  It is a communication tool created by a program manager and product team to outline and visualize the program lifecycle, including its various phases and objectives.

Roadmap Defined and Described

A roadmap is part of a strategic plan that defines a goal or desired outcome, and includes the major steps or milestones needed to reach it.  A roadmap also serves as a communication tool, a high-level document that helps articulate the strategic thinking — the why — behind both goal and the plan for getting there.

A roadmap shows the level of importance for the various pieces of the program and the expected results.  The project team should use throughout the course of the program’s journey.  Why?  There will be events or hurdles that will require some adaptation to plans, perhaps slightly, perhaps more significantly.  One of the most common mistakes used by organizations that create a roadmap is to file it away in a drawer and never look at it again. 

A well-constructed roadmap will:

  • Identify the current state of the organization from both business and technical perspectives.  It will address culture, organization, experience with analytics, level of BI maturity, and readiness.
  • Specify business goals and data / analytics strategy
  • Key business drivers.
  • Recommend areas of business focus.
  • Recommend connections between areas to leverage resources, artifacts, deliverables, etc.
  • Recommend a strategy for communication of the results.
  • Identify key areas required for success.

Roadmap Areas

  • Technology – Level of technical solutions and tools based on platforms.
  • Metadata – Many organizations struggle with identifying metadata solutions and integrating them.
  • Data governance – Foundational component for effective data management.
  • Data Integration – Every BI / analytics program is based on integrating data from multiple sources.  The roadmap must reflect activities, milestones, and leverage points from all the other areas
  • Data Quality – Every IT program has data quality challenges.  Displaying the high level activities and milestones for DQ on this roadmap will show stakeholders that the program is serious about delivering high-quality data for BI / analytics.
  • Organizational changes or enhancements – This is always a significant area for both the business and IT to address.
  • Define a high level plan for how to achieve the identified goals and objectives.  This is the visual roadmap, with a breakdown of project groupings that cover the technology identification, infrastructure, pilot or prototype efforts, business opportunities, supporting areas and tools (like data governance, metadata, data security, etc.).

Roadmap Purpose

Frequently, program managers are charged with executing projects that are high priority, very visible, but not planned for how they fit into a long-term vision.  Invariably, these efforts satisfy a need or two, but neglect to provide a solution that will bring value to the rest of the organization.  As system expansion is demanded and attempted, failures highlight the original flaws or lack of long-term design and planning.  Eventually, the original project gets negative publicity, even though it served the initial purpose.

So why would anyone not go through the effort to have a roadmap, based on strategic planning?  Perhaps the primary answer goes back to bad experiences of the past.  This type of planning does not take long or cost millions of dollars, but experiences with planning efforts gone awry often cause organizations to skip this phase.  Avoiding this planning is a critical mistake that will cause the organization to overspend and result in very little value in comparison to having a sound and feasible plan for a major endeavor.

When it comes to analytics, the value for a program roadmap is magnified.  Perhaps this is because success with BI/analytics is dependent on so many other areas of data management (data governance, metadata, data integration, master data, and data quality).  Ideally, the BI / analytics development team has accounted for these areas in their plan and can share the information about activities, artifacts, milestones, connections, etc., that are needed from each contributing discipline.  Having a program roadmap will allow all the participants from each area to visualize the full program.   

Keys to Building a Successful Roadmap

Taking the right amount of time to build an appropriate plan is the goal of a roadmap effort.  There are some key points to getting through this effort as quickly as possible, while realizing program and organizational value.

Skilled Resources – Creating an analytical roadmap requires significant experience in technical architecture, analytics tools, and business analysis techniques.  This unique combination of skills is found in data warehouse architects that have many years of designing solutions for many different types of users.  They have seen a wide array of possible options and understand when to apply or use an appropriate option.

Strong Sponsorship – For any proposed plan to be accepted in an organization, an internal leader must be convinced of the plan’s value.  If that level of leadership has been identified and is eager to participate, success often follows.  If not, be very cautious about proceeding with this type of effort until the program can acquire strong sponsorship.

Access to the Right Level of Leadership – To understand organizational needs and what to target, acquire access to the key business resources, at the right time.  A roadmap without executive interviews will rarely garner support, and will not survive to achieve the desired goals.

Taking the Time to Gather Information – One of the most common areas that will be shortened or eliminated is information gathering.  In many cases, someone already has a solution in mind and they only want a technical design and build.  However, skipping this step is not worth the short time it takes in comparison to the targeted planning that aligns with key business drivers.

Sharing Results and Gaining Support – The last piece of producing a roadmap is creating a presentation to be circulated around the organization.  This can be a great educational tool, and it gets the organization excited and encouraged for the program and its connections to business and IT areas.  The communication should continue with the roadmap serving as a living artifact to gather, maintain, and increase support and enthusiasm.  


To be financially responsible and ensure the business goals and drivers are reflected in the programs that are funded, an analytics roadmap is a necessity, one that shows all the connections to other areas of data management.  While creating a roadmap is critical, the primary value is found in the use of the roadmap throughout the BI / analytics program’s development and implementation. 


Bruce D. Johnson

Bruce D. Johnson is an experienced IT consultant focused on data / application architecture, and IT management, mostly relating to Data Warehousing. His work spans the industries of healthcare, finance, travel, transportation, and retailing. Bruce has successfully engaged business leadership in understanding the value of enterprise data management and establishing the backing and funding to build enterprise data architecture programs for large organizations. He has taught classes to business and IT resources and speaks at conferences on a variety of data management, data architecture, and data warehousing topics.

© Since 1997 to the present – Enterprise Warehousing Solutions, Inc. (EWSolutions). All Rights Reserved

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