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When funding a project or system or system from multiple sources, often state, and local, tribal, and territorial governments will need to fill resource gaps. For example, they may need additional resources to make their system more comprehensive, or to add enhancements to align with their data or security architecture, or to manage project timing or cash flow. This can be true in a variety of circumstances, including:

• In the initial building stage for the system, when it is not yet operational.
• As the IDS matures and regularly provides analytics, insights, and data products to users as they demand these products.
• In a jurisdiction where a leader or legislature is committed to robust uses of data, to provide performance information to their residents or citizens.
• This section addresses five types of non-federal funds that can help to fill in different kinds of gaps.

Section 4.A. General Revenue Funds

Many integrated data systems have gotten their start from a legislature convinced of the importance of data to drive good decision-making. Using general revenue funds (GRF) as a sweetener or an incentive to help partner agencies put their own data (and money) in the system is a common practice across integrated data systems nationwide. GRF is most often used during the early phases of planning, design, and actual build of the integrated data system. It is usually the easiest and least complex way to get a project started.

Section 4.B. Capital Funds or Debt Financing

Capital funds are ideal to generate funding for the initial design and build of a system. Capital funds that flow from debt issues backed by revenue sources, such as fees or payments, are often a possibility. Capital funds that come from bond financing can be more complicated. This is because there are statutory or constitutional limits on how they can be used. Non-taxable municipal bonds – the most commonly utilized debt instruments for states, local governments, tribes, and territories – may not be used to fund intangible assets such as information technology, data, or cloud-based services.

However, there are debt instruments that can be used to finance the upfront costs of planning and design as well as initial build. Some states and municipalities have used Certificates of Participation (COP), a debt instrument that is also tax exempt but is secured with revenue from a lease on the assets. For a real-world example, see the field guide case study on how Ohio used COPs to finance shared services.

For a real-world example, see the field guide case study on how Ohio used COPs to finance shared services.

Section 4.C. Vendor-Financed Models

As more and more technology has moved to the cloud, vendor-financed models can offer creative ways to fund planning, design, operations and maintenance of integrated data systems. Sometimes, an IDS can lock into a technology or a capability that a vendor will finance over, say, a 10 year period, incurring significant upfront costs, but agreeing to a flat “lease” rate for each year of the contract.

Other vendors provide analytics, visualizations, or other data services on top of the facility, allowing the sponsoring agency to amortize the lease payments against a stream of chargebacks to users for these value-added services. The government rebids the contract for services and products through an open procurement process periodically.

What can this model look like in practice? See the field guide case study on North Carolina’s public-private partnership that developed enterprise data-sharing tools.

Section 4.D. Chargebacks or Fee-for-Service

Integrated data systems often build out extensive staff teams of business analysts, experts in evaluation, data scientists, and other highly skilled individuals that are difficult for an individual agency or program to acquire and support. Chargebacks or fee for service arrangements are a common way to recoup costs for this kind of centralized service unit in government. These fees may be charged internally within government, as well as to outside researchers and users from the academic or non-profit community.

Chargebacks or fee-for-service arrangements are best used when costs of providing services are variable and could be one-time charges or be based upon the demand or consumption of the services. Fees may be on an hourly, project, or other basis.

How can jurisdictions build this approach? See the field guide case study on Arkansas’ billing for value-added integrated data services.

Section 4.E. Philanthropic Sources

Hear Katy Collins, Chief Analytics Officer in the Allegheny County Department of Human Services, describe how local foundations helped the county start up their integrated technology infrastructure.

Philanthropies are increasingly focused on assisting public and non-profit social impact organizations to use information to improve the effectiveness of programs and policies. A number of national and regional philanthropies provide direct support to governments to strengthen their technical capacity to securely link and analyze individual-level data for projects that can have a measurable impact on vulnerable populations.

For example, philanthropic funders have supported data fellows embedded within government agencies, communities of practice, and intensive training workshops to build data and analytical skills of government professionals. They have also helped fund the development of third-party, cloud-based data platforms that governments use to securely and inexpensively link their data across programs and jurisdictions and with nonprofit service providers.

Some philanthropies provide direct financial support in the form of donations to support start-up of data-related initiatives that the government commits to sustain. Philanthropies provide indirect financial support when they fund academic researchers and non-profit organizations that pay service fees to state and local governments to get access to their integrated data and analytical services.

How can philanthropy help grow IDS and analytic capacity? See the field guide case study on how South Carolina leveraged philanthropic funds to demonstrate to state agencies, health care researchers, and policy makers the benefits and insights of using integrated data, while maintaining patient/client confidentiality.

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