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Modernizing government disclosures with structured data systems

Modernizing government disclosures with structured data systems
7 min read

Dean Ritz

Senior Advisor to the CEO, Open Data Policies and Practices
Published: June 27, 2017
Last Updated: November 4, 2022

This is the first in a series of two blogs discussing the case for adopting a consistent taxonomy for structured data across government disclosures.

The process of creating a financial disclosure document can feel like drudgery—not just because the work is tedious and highly detailed, but also because the beneficiaries may have difficulty identifying the benefits.

What if you could substantially simplify the method by which those numbers tell important stories about your institution? What if you could use them to think about who you are, as an organization, in relationship to your peer organizations?

Modernizing your disclosures entails reporting them in an interactive data format for both people and computers. The process is characterized most simply as data where each unique reported value or fact is encapsulated with information about what it means.

In financial reporting, a disclosed fact would bind together the following:

  • A value
  • A reference to reporting codifications or a tag identifying that value's specific meaning—e.g., "Claims Payable for Government Activities"
  • The type of unit so that every numeric value is unambiguously defined—e.g., dollars, megawatts
  • Numeric precision—e.g., rounded to the nearest thousand
  • A date for which the value is relevant, either over a period of time or as of a moment in time—e.g., January 1, 2017, through March 31, 2017

This capability enables organizations to own their financial stories because data has more meaning when tagged with context. Meaningful data helps communicate an organization's value and shows its commitment to transparency.

The technology necessary to modernize disclosures already exists—so, disclosure modernization really means adopting this technology and beneficially learning from organizations who have already modernized their disclosures with interactive data.

For nearly a decade, the U.S. Securities and Exchange Commission (SEC) has blazed a trail by requiring many actors in the financial sector to report their data in eXtensible Business Reporting Language (XBRL). XBRL is a royalty-free computer language standard used by governments and businesses worldwide to represent financial reporting information as interactive data. In doing so, the SEC created the market discipline necessary to develop the technology and experience needed to support those who will build on the foundation of XBRL. It could be you.

The problem with PDFs—dead documents, buried data

Most institutions have computers that serve as a burial ground for PDFs—dead data that represents millions of hours of work. As institutions lose personnel, they often lose track of where data is stored and what it represents. When people use PDFs or Excel® files to transport data, they must rely on an inefficient method of passing around documents, such as email attachments or uploading to a shared drive. These processes are manual and error-prone, especially as people copy and paste from one document to another or pass around different versions of the same documents.

Additionally, data is most meaningful within the context of that single document, and one should use caution when aggregating it with other data or analyzing outside of that context. If someone did want to analyze that data, that person would have to spend hours combing through documents to create a curated set—only if all of the most recent versions of each document could be found, and each document was sufficiently specific about the context for each data value.

These dead documents represent a waste of human capital. People submit forms to fulfill requirements, but the data doesn't do any work for their organizations. As a result, submitting these forms becomes a bureaucratic requirement rather than a useful way to build knowledge about the organization. Managing these forms purely for appearance rather than value introduces inefficiency and errors that cause institutions to lose money and time. The reports created should be of value to the provider as well as the recipient.

In the end, PDFs are useful if you want to control how a document is viewed on different devices. But if you want data to have genuine value to others, it should be used—not just seen.

Advantages of interactive data reporting

As noted above, structured data systems solve myriad problems by tagging individual data points with information such as the date, purpose, and type of data. As a result, data can retain its identity even when it is decoupled from its original document.

Interactive data represents knowledge—it is data that can now become a resource. We do not know what questions we will be asking two years from now, but machine-readable, tagged data prepares us for an uncertain future. Anyone with access to the information can search an interactive data database and organize that data into a curated set. Used in this way, data allows organizations to tell meaningful stories about significant accomplishments and make data-driven policy decisions.

Collaboration and control

Interactive data facilitates collaboration at every stage of the disclosure process. Internally, people can collaborate on financial documents without worrying that information will be misunderstood due to copying and pasting information into the wrong column or rekeying it incorrectly. When institutions collaborate with outside contractors, such as analysts and lawyers, they can send information in a secure form. Externally, regulators and investors can create datasets and analyze the information more quickly and accurately than they did in the past.

Interactive data allows information to be used as it was meant to be—to communicate meaningful information about an institution's financial status and goals.

Competing with the private sector

Disclosure modernization could allow governments to catch up and compete with the private sector. Interactive data formats allow investors greater access to higher quality information, giving them the chance to create more accurate data models and compare different investment opportunities. Investors are more likely to invest in vehicles where relevant, trustworthy financial information can be accessed easily and quickly.

For example, small and local governments rely on municipal bonds to fund important projects. However, as reporting in interactive data formats becomes the standard in the corporate bond market, small governments issuing municipal bonds face a series of disadvantages. Though government bonds are historically more reliable than bonds issued by private companies, investment in municipal bonds is hampered by the lack of publicly available information about these bonds and the absence of a centralized marketplace.

Other benefits arise with the ability to compare your institution with your peers. Municipalities can better compare bond issuance proposals they receive with the costs incurred by other comparable issuers. Performance standards can be set with a more context as to what happens elsewhere, i.e., what performance is realistic to expect. Interactive data is what makes this possible.

The Municipal Securities Rulemaking Board (MSRB) developed the Electronic Municipal Market Access (EMMA) to make the municipal bond market more transparent, but data is still reported in PDF format, making it costly to aggregate and analyze, and is subject to all the risks discussed above. Modernizing these disclosures could draw more investor interest in municipal bonds. Also, streamlining the disclosure process could potentially reduce the operational costs of issuing bonds.

Moreover, both the private sector and government markets are moving toward interactive data systems. The Financial Transparency Act—a bipartisan bill recently introduced to Congress—would require that all information provided to regulatory agencies be electronically searchable. The move toward interactive data systems is inevitable, so small and local government consumers would benefit from beginning the process now, working on the leading edge of the process rather than scrambling to catch up. Admittedly, it's not without effort, but the outcome, I argue, is worth it.

Data and the value of trust

When we make decisions about data, we make decisions about our values. Do we value trust—both within an organization and between an organization and the public? Do we value the time and energy of the people who work on that data? If so, we need to move toward interactive data systems.

To engender trust in our in financial institutions, we need technological tools that are inherently trustworthy. Our trust in the accuracy and integrity of our data should be well-grounded. Internally, this means that institutions can trust their own auditing processes and better communicate with each other. Externally, groups of people can look at an institution's data and trust that the institution is working in good faith and for the common good.

What's next?

Now that you have this data, what can you do with it? That will be the topic of the second blog in this series, which will discuss how interactive data can be used to create a model. This model will add another layer of value to your data and allow it to interact meaningfully with other datasets.

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About the Author
Dean Ritz headshot
Dean Ritz

Senior Advisor to the CEO, Open Data Policies and Practices

Dean Ritz is a subject matter expert in information modeling with over three decades of experience in various data-dominated domains, including artificial intelligence, expert systems, object-oriented programming, and most recently the modeling of financial information. As a Senior Director at Workiva, he applies his expertise to product strategy for collaborative work management and the management of the company’s expanding patent portfolio. His interests extend to the topics of rhetoric and ethics, with scholarly work in these areas published by Oxford University Press (2011, 2009, 2007), and Routledge (2017).

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