This dashboard was built to flag errors and quality concerns in Transparency reports submitted to the Office of the State Auditor. Our team has developed algorithms and metrics to pinpoint issues in the data that cause confusion for users of Transparent Utah. This dashboard is meant to be another useful tool for entities who submit to Transparent Utah to understand how the data they have submitted looks to the public. This tool can also help speed up the resolution of data quality issues since the visualizations and explanations can help uploaders understand how to rectify their scores.
Bad data can confuse and impair decision making. Transparent Utah data is accessed by tens of thousands of Utahns every month. The data submitted to Transparent Utah is also used by the Utah State Legislature, the Federal Census Bureau, the Office of the State Auditor, and a variety of other research and government organizations.
This section shows the data quality scores for ALL years and for ALL local government entities that submit to Transparent Utah. Each score is on a scale of 0-100%, with 0% being a poor score and 100% being a perfect score.
This section shows the data quality scores for the 2021 fiscal year and for ALL local government entities that submit to Transparent Utah. Click the "Get FY 2021 Only Scores" button to populate the score information below.
This page reports the selected entity's data quality scores. The goal is to have all the bars with a score of 100%.
"Missing Reports" is a metric that checks if an entity is missing any required Transparency reports. This is the first metric to evaluate, because if there are missing quarters/years of data, then the missing data will impact expected amounts calculated in the other scores.
Note: This score only checks missing Transparency reports. To get a reporting status for other reports, please visit the compliance report.
If you manage the financial reports for this entity, then you can improve this score by uploading your Transparency reports to https://reporting.auditor.utah.gov/. If a quarter of data did not have any transactions, then please contact one of our analysts at the Office of the State Auditor to give your entity a reporting exemption.
Contact:
"Duplicate Reports" detects if there is duplicated data in the Transparency reports (also called batch uploads) the entity has submitted to Transparent Utah.
This metric uses algorithms to flag duplicated reports. Please note that not every transaction of a quarter is checked, but rather the report's totals. Even if the entity has a score of 100% there could still be duplicated transactions that were not flagged by our algorithms.
If you manage the financial reports for this entity, then you can improve this score by correcting and/or deleting Transparency reports. Please review the detailed solution for each flag below.
If your batch is flagged as a possible duplicate, you have two options to resolve the flag:
Recreate the report with the correct posting date and fiscal year. Remember, the posting date should reflect the last date of the entity's fiscal year (e.g., 12/31 or 6/30).
If your batch has multiple fiscal years, please split up the file by fiscal year and reupload. If you need help splitting up an old file, please reach out to our team for help.
Ensure the validity of your Transparent Utah reports for the flagged fiscal years. Confirm there are no duplicate reports and that all data has correct Uniform Chart of Account codes. If there are still issues please reach out to one of our analysts so we can help determine why the AFR and TU are inconsistent. If there is a valid reason we will grant an exemption for your entity.
"UCA Validity" is a measure of how well the entity's data map into the Uniform Chart of Accounts (UCA). There are two uniform charts of accounts that are accepted:
To improve this score, you must correct the flagged/invalid UCA codes in all years of data. The primary goal is to improve your system going forward, and then we can discuss the best way to improve historical data. If you have access to historic years of data, we would like you to rebuild those reports with the correct UCA. If you do not have access to old years of data, we will work with you to find a solution. We will either correct the data for you, or grant an exemption.
Below is an explanation for each of the different types of flags/errors.
"Vendor Name %" is a metric which compares the rate of vendor, payee, and employee names that have a value assigned to them. If the transaction has a value of "Not Applicable", "Not Provided", or "REDACTED" the transaction is considered to not have "detail". While there are valid reasons to not have a vendor name, like a journal voucher, most expenses are expected to have a valid vendor name. Each entity is compared against similar sized entities to confirm whether the percentage of transactions with detail is sufficiently high enough when compared to similar entities.
This table shows a further breakdown of vendor information for each year
This table shows a further breakdown of payer information for each year. Most entities leave this field empty.
This table shows a further breakdown of employee information for each year.
This section does not contribute to the score. It is just a helpful aggregate of all years.
These scores can be improved by adding a value other than "Not Applicable", "Not Provided", or "REDACTED" to the vendor/employee name field. A new batch will have to be submitted and the older one will need to be deleted for the score to improve.
All employees must have a job title in the compensation report. Locate the batches that have employees without job titles and resubmit that batch so that job titles exist for all employees.
If you believe your entity has been inaccurately flagged or there is a legitimate reason for a lack of detail, please contact one of the analysts to grant an exemption.
"Yearly Total Change" is a metric which checks for large changes (spikes) in the year to year totals for expenditure, revenue, and payroll. There are two sections, 1) a section which checks all funds and 2) a section which does not include capital expense funds. Only section 1 contributes to an entity's score.
This section aggregates all fund types and looks for spikes. This is in contrast to the following section which compares Non Capital funds to avoid spikes due to construction.
While this section does not contribute to the score, it can help analysts detect if a spike was due to a capital expense or some other data quality issue.
This section also does not contribute to the score, it can help analysts detect if any spikes were due to an increase or decrease in student counts at a charter school.
This section also does not contribute to the score, it is used by our analysts to confirm if the totals in the payroll report match the total payroll expenses from the expense/revenue report.
The score can be improved by removing the spike of data. Common causes of the spikes are due to duplicate batches, so first confirm there is no duplicate or partial duplicate reports. If there are no duplicate batches, then investigate that year's data and check if there are any transactions with an amount that have a typo.
If you cannot determine why there is a spike please contact one of our analysts below.
If there is a legitimate reason for the spike in revenue/expense/payroll, please contact on of our analysts and we can grant an exemption for that year.
"Payroll Consistency" is a metric that identifies major changes in an employee's compensation.
Select from the drop-down list below to examine an employee's compensation. Flagged employees will be at the top of the list.
The score is improved by removing the spike for all flagged employee's compensation data. Common causes of the spikes are due to missing or duplicate batches, so first confirm there is no "duplicate" or "partial duplicate" or "missing" reports. If there are no duplicate batches, then investigate that year's data and check if there are any transactions with an amount that have a typo.
If you cannot determine why there is a spike please contact one of our analysts below.
If there is a legitimate reason for the spike in compensation, please contact on of our analysts and we can grant an exemption for that employee and year.
"Reversals" is a metric which compares the percentage of transactions that have a reversal (are negative). In Transparent Utah, both revenues and expenses are reported as positive unless there is a reversal in the General Ledger. This can cause issues since many entities have either revenue or expense negative for balance sheet calculations. This metric helps to flag any entities that may have accidentally kept data as negative while exporting from their system. Each entity is compared against similar size and government types to confirm whether the percentage of transactions with detail is sufficiently high enough when compared to similar entities.
These scores can be improved by confirming all transactions are positive unless a reversal. Then a new report can be submitted to the state reporting system.
If you believe your entity has been inaccurately flagged or there is a legitimate reason for a lack of detail, please contact one of the analysts to grant an exemption.
USBE Consistency is a metric of how well the data in Transparent Utah (TU) matches the data reported to USBE. If the totals match (within an acceptable material difference), then it is likely that the data submitted to TU is correct.
If the USBE total is higher than TU's total, then this might imply that the submissions to TU are incomplete or data is missing.
If the USBE total is lower than TU's, then this might imply that data is duplicated in TU
Ensure the validity of your transparent utah reports for the flagged fiscal years. Confirm there are no duplicate reports and that all data has correct Uniform Chart of Account Codes. If there are still issues, please reach out to one of our analysts so we can help determine why the AFR and TU are inconsistent. If there is a valid reason, we will grant an exemption for your entity.