Why Your Agency’s Data Analytics Initiatives Require a Data Sharing Agreement

 

Why Your Agency’s Data Analytics Initiatives Require a Data Sharing Agreement

If your government organization is like many, you’re investing in data analytics. Analytics give you new insights into areas that affect how you run your organization and how you serve your constituencies.

But meaningful analytics rely on the availability of data, and often that data is collected and owned by a variety of entities. As long as data exists in silos, you’ll never be able to realize its full value. You need a way to gain the participation of those organizations and gather their data in a timely and useful way.

To achieve those goals, you need a data sharing agreement. Based on Qlarion’s long experience helping organizations optimize their data governance, a data sharing agreement is the most efficient, reliable and effective way to get the data you need to power your analytics.

Creating a Data Trust – to Achieve Trusted Data

So how do you implement a data sharing agreement? The best approach is through a data trust, a legal framework for managing shared data. A data trust:

  • Formalizes the relationship among participating organizations
  • Sets rules for data security and privacy
  • Provides a mechanism for participants to connect their data sources and create a shared data repository

To reach success with a data trust, follow these steps:

Step 1: Understand why a data trust is necessary

Typical data agreements involve lengthy negotiations between each participant, resulting in confusion, cost and complexity. A data trust enables you to:

  • Simplify processes. You create a common legal and technical framework for sharing data that easily scales to new datasets and use cases.
  • Assure confidentiality and minimize risk. A chief data officer (CDO) implements a consistent standard for data custody, protection and distribution, at no cost to participants.Ensure access to resources. You provide a standard set of features, such as visualization tools, for all authorized users of the data.

Step 2: Build a business case

A business case delineates the strategy, investment and expected return on the initiative. This can help you gain support from an executive champion.

Your business case should highlight the most compelling justification for the project, which could include:

  • Solving a problem that can’t be solved without data sharing and analytics
  • Identifying a use case that has a high likelihood of achieving success and delivering measurable value
  • Focusing on an issue that’s likely to start addressing an issue or delivering returns quickly – ideally within 90 days

Learn more about how to build a business case for your analytics project.

Step 3: Identify and onboard participants

A data trust involves two primary stakeholders: the office of the CDO, which serves as the trustee, and the contributors of the data, who become the data trust members.

Depending on your use case, you’ll likely have an idea of the initial members you want to include. As the initiative expands, you can identify additional datasets and use cases – and, if necessary, additional participants.

Data trust members should follow a journey map of participation in which they:

  • Learn about the data trust.
  • Sign the data trust agreement.
  • Provide the relevant data to the technical team.
  • Validate the data.
  • Gain access to customized reports based on the data analysis.

Step 4: Define participant responsibilities

Both the trustee and the trust members should expect to be responsible to the trust. For instance, the trustee should:

  • Provide the technical and organizational infrastructure.
  • Maintain and update the terms of data usage.
  • Keep member-contributed data secure.

Trust members, for their part, should:

  • Review and approve use of shared data.
  • Share technical details such as data type, format and quantity.
  • Deliver the necessary data and metadata to help maintain the member-contributed data resources.

 

Moving forward with data sharing

Now is the time to begin powering your analytics with a data sharing agreement enabled by a data trust. Forward-looking organizations are already achieving tangible results.

For instance, Qlarion worked with the Commonwealth of Virginia to build the Framework for Addiction Analysis and Community Transformation (FAACT). The data sharing platform combines previously siloed information from agencies, secretariats, localities, social services, public safety, corrections, drug courts, community coalitions and private healthcare systems. FAACT has been crucial to Virginia’s response to the opioid epidemic, and at the start of COVID-19 it was expanded to inform the management of this new public health crisis. Not only did FAACT position the Commonwealth to take a data-driven response to the pandemic, it prepares them to respond to any and all future public health crises.

Analytics are increasingly central to how organizations carry out their missions. A data sharing agreement can help ensure your analytics initiatives result in unified data insights, data-based decisions and positive, data-driven outcomes.