Data Management Lessons Learned Template.xlsx
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Introduction
Data Management
What this spreadsheet contains:
The following tab is a list of financial management best practices or lessons learned pertaining to data management that federal agencies have provided to the FM QSMO. Each line item is a suggestion from an anonymous agency and includes a description of the best practice or lesson learned, and its associated pitfalls and resolution.
Why it is helpful to agencies:
Since this spreadsheet contains real-life examples that federal agencies have experienced in their recent modernization efforts, we hope that this information may help your agency avoid common mistakes and increase efficiency when planning for and implementing financial system modernizations.
How your agency can support this effort:
The FM QSMO is continously looking for additional financial management best practices and lessons learned to share with agencies. If your agency would like to anonymously participate in this knowledge sharing activity, please reach out to us at FMQSMO.fiscal.treasury.gov.
Data Management
| Topic | Category | Description | Pitfalls | Resolution | Date |
| Data Management | Data Quality | Data conversions can uncover poor data controls from legacies systems, which can cause downstream impact. | Poor data quality can slow or stop data conversions, as well as uncover potential audit issues. | Data quality should be included in the planning of a migration from a legacy system to a Core FS solution. | 10/7/20 |
| Data Management | Data Quality | Poor data quality can cause slowness in cutover processing time, if cleanup efforts are not performed on the data to remove poor data ahead of time. | Cutover times often occur during after hours or over a weekend. If data conversions occur on poor data or legacy data elements that are not needed in the new system, this can cause significan time impacts, or failures during the conversion process. | Make all efforts ahead of time to clean up data or remove elements from data being converted that is not needed. This can include data that is past its shelf life and no longer required to be actively maintained in the financial system. | 10/7/20 |
| Data Management | Data Archiving | When possible, archive as much data as possible into a data repository that is held outside of a Financial System. This can not only reduce times for converting data, but also ensure that erroneous legacy data is not being absorbed into the Financial System when it has no downstream reporting impacts. | Data that is not needed, or that is held in a legacy system should be evaluated to determine if the data is beyond retention policies. | Only convert data and import data into a new financial system if that data is still needed for reporting or for data retention policies to be held within the Core FS. | 1/26/21 |
| Data Management | Data Migration/Cutover | Reasons to avoid a year end cutover: |
possibility of there being issues affecting year end close processes cutovers often bring with it periods of Financial System being down, which can be problematic at year end systems should operate in parallel, from legacy system to new system for reporting, which is easier throughout the year than at year end
| remaining funding is often expensed during September of each year, which often means that this is a time when system processes are at peak | Managing cutover times for data migrations, data conversions, customer onboarding or system upgrades can be complicated at year end. It is ideal for agencies to select times, if possible, where transaction processing is slower and where audits or reporting windows are not in effect. | When possible, avoid mid-year cutover plans for various reasons listed out in the issue description. | 2/5/21 | |||
| Data Management | Data Migration/Cutover | Detailed step by step procedures/or a detailed cut-over plan is almost certainly a must have. Ensuring there is seamless personnel or tasks operating in sequence is vital to successfully managing a cut-over. | N/A | N/A | 2/5/21 | |
| Data Management | Data Migration/Cutover | Determine if data can be imported into the system early and converted prior to an official cutover plan. If this is possible, performing a data sweep and only collecting transactions that have occurred after a specific date in time, can vastly reduce the processing time involved in a large customer onboarding or cutover/migration. | Often the pitfalls of having to migrate and convert large amounts of data contribute to the vast amounts of time that it takes to perform a cutover. Determine whether or not integrators or developers can import legacy data prior to an official cutover and have that data stored on staging tables in the Financial System ahead of cutovers. | N/A | 2/5/21 | |
| Data Management | Data Conversion/Migration | Activities to continue: Perform mock conversions to provide the team with an opportunity to identify and correct conversion issues prior to the Production conversion | N/A | N/A | 7/1/21 | |
| Data Management | Data Conversion/Migration | Activities to continue: Provide timely information on the status of data conversion and migration activities | N/A | N/A | 7/1/21 | |
| Data Management | Data Conversion/Migration | Activities to continue: Verify that data to support critical functions is available on day one | N/A | N/A | 7/1/21 | |
| Data Management | Data Conversion/Migration | Areas for improvement: Ability to access levacy systems in order to understand the context associated with the data | N/A | N/A | 7/1/21 | |
| Data Management | Data Conversion/Migration | Areas for improvement: Focus on the clear communication of expectations for migrated data vs. historical data | N/A | N/A | 7/1/21 | |
| Data Management | Data Conversion/Migration | Areas for improvement: Provide additional lead time to allow for bureau data cleanup activities prior to mock conversion | N/A | N/A | 7/1/21 |
System Migrations and Upgrades Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Personnel & Resource Mgt Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Project Planning Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Technical Planning Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Cloud Migration Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Validation Testing Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference
Communication Financial System Provider Financial System Product Financial System Version # Topic Agency Description Pitfalls Resolution Date Reference image1.png
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