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Developing Funding Approaches for Data Management and Analytics Programs

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Finding and securing sufficient and sustained funds for data management, data governance, data quality, business intelligence, and analytics programs can be challenging.  Follow these steps for success

Acquiring funding for data management and analytics efforts is a significant challenge that most organizations face at one time or another, often year after year.  Companies of all sizes must be able to be able to justify a reason for a program, and identify a reason for any funds required for the solution.

Many data management programs and their staff develop strong business needs, great plans and great strategies for a program, but they cannot secure the funding.  All data management / data governance / metadata management and analytics efforts have resource costs in time and money.  Many programs require supporting infrastructure such as hardware and software needed to implement the solution.  Examining foundational challenges for data management / data governance, and analytics program funding may help to discover some techniques that will improve data management / data governance / analytics leaders’ attempts to subsidize these essential programs.

Challenges to Securing Funding for Data Management or Analytics

Reputation: Executives frequently have the experience of watching a data management / data governance / analytics effort that was a source of great financial spending and little realization of value.  As is common, one bad experience or story can cause fear or hesitancy that will cause all subsequent efforts to be voted down (never started) or shut down before value can be demonstrated.  This common situation creates a potential roadblock that the proposing team must be prepared to address effectively enough that leadership will be convinced to start the new program.

Financial Priorities: Every organization has many different efforts that need funding.  Know the organization’s current and anticipated financial priorities and work with them to develop a case to include data management / data governance / metadata management / data quality / analytics into the highest-priority efforts as a starting point.

Leadership: Regardless of the power of the business case presented, funding comes from executive leadership.  The more visible and powerful the program’s champion, the more likely the story will be heard. Look for executives and other champions who have been data management practitioners, if possible to enlist their active support.

Proven Success: When certain areas or leaders have seen success consistently, from business areas, specific resources, or specific technologies, they are more likely to embrace and support new proposals coming from those areas.

Strong, Thorough Plan: Any proposal for funding must be accompanied by a plan that is well thought out, confidently communicated, and has frequent deliverables that show progress and value.  Develop a set of well-written proposals, with accurate and detailed cost-benefit analysis and a solid business case based on best practices and realities.  Include strategic and tactical plans for execution, and all the other hallmarks of effective financial and business planning to help secure funding.

Critical Success Factors for Securing Funding

How to take that business need and sound approach forward with the right materials that will garner the attention of leadership?  How to build a proposal that will sell itself?  Budgets are reviewed and re-prioritized constantly by senior leadership.  Here are a few critical success factors to understand and incorporate:

Executive Awareness and Support: Often, the greatest efforts were much easier due to superb executive support.  Find the leaders, to paint a picture that can be shared with them and other key executives who are known to have the business problems with data management / data governance / data quality / analytics.  Share with them reasons for their challenges and why they need to be the visible point that can provide a solution.  Most real leaders are waiting for great ideas and strong proposals that they can bring forward and support.

Benefit Driven Proposal: Too often programs do not address specific pain points that are felt across the business, by multiple groups.  If the solution solves one problem or answers one question, that is a good start, but when it comes to gaining funding, it is essential to share how that solution can have a positive impact across the various business areas.  Otherwise, the proposal will struggle to gain continued funding and become a victim to budget cutting.

Cost vs. Value: Connect the proposal to existing costs and show how this solution will improve the business, drive down costs, increase revenues, or increase the position of the organization’s crucial business drivers.  Leaders often focus on Return on Investment (ROI), but many technical resources do not realize that ROI is not just measured in dollars.  Significant movement for achieving business drivers and realizing organizational goals is hard to quantify monetarily, but easy to connect with what the organization wants to be.

What Happens If We Don’t Do This?  Often, this can be the key point in the proposal, since it shows that doing business as usual will result in increased cost, unrealized value, and prohibit the business from reaching its goals.  In many cases, this point can be connected to financials and benefits and business drivers so that funding the program becomes an easy decision.

An Incremental Approach: Realize value quickly and often.  Most businesses in every industry have had bad experiences with efforts that deliver little value.  Make sure to have a plan that delivers real value, frequently.  If the team does not know how to plan, approach, and deliver an enterprise solution in an incremental manner, the data management / data governance / analytics effort will fail.  However, there are many organizations whose data management / data governance / data quality / analytics efforts, started incrementally, have been tremendously successful and had dramatic impact on the success of a company.

Prototype/Pilot Project: After the development of the solid plan, proven incremental approach and approval from leadership to start a data management or analytics program, demonstrate value quickly.  This is not a “throw-away effort”; it is simply the first small project in the new program.  Most pilot projects should take less than 6 months and, ideally around 2 to 3 months.  All successful data management / data governance / data quality / analytics efforts have this pilot project in common.  A successful pilot develops trust and ensures continuing support from leadership, and it builds confidence in the team and resources that are responsible for developing the full program.


Funding a data management / data governance / data quality / analytics effort is rarely an easy proposition.  Designing a solid plan and approach, exhibiting confidence and demonstrating value will all go further to gaining funding than any strong technical acronyms or software.  Align with those internal and external resources that can help build the type of proposal to secure the proper funding level for sustaining data management / data governance / data quality / analytics.


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.

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