Module 2 - Documenting and Improving Data System Processes - Data System Improvement Toolkit

Sep 11, 2026

Uploaded by Pentious

Module 2 supports teams in improving data system processes through consistent documentation and stronger reporting reliability. The module guides teams to map where data reside in the system, connect data relationships that drive automated reports, and reduce inaccuracies. It also covers data quality improvement, including cleaning workflows and review checklists for missing data before reporting. Finally, it streamlines data entry by documenting collection procedures and offering best practices for moving to paperless systems.

LanguageEnglish

CategoryPresentations

FormatPDF

Pages3

Reading Time1 min

AccessFree to download

Understand and document where data are located in a system

Tool: Guide to Data Mapping

Tool: Data Map Template

Improve and document data quality processes

Tool: Guide to Data Cleaning

Tool: Example of a Case File Checklist

Tool: Example of a Missing Data Report

Document and streamline data entry processes

Tool: Data System Business Process Maps

Tool: Best Practices When Converting to a Paperless Data System

Module 2 Documenting and Improving Data System Processes Welcome to Module 2 of the Data System Improvement Toolkit! If your tribal team wants to improve the current data system processes or document existing processes to ensure they are followed consistently, this module will be helpful. It helps you to develop program policies and a procedures manual. This module addresses three actions a team interested in improving its system processes and documentation needs to do. Understand and document where data are located in a system. Many program staff use a data system with automated reports. These reports can be valuable tools but often the data generated aren’t accurate. Data mapping is the process of visually diagramming where data “live’’ in a data system. Data mapping can be a critical step to ensure reports are correct; it describes how data are connected across the system and helps you to understand which data the system uses to calculate report values. Improve and document data quality processes. A data system is only as good as the quality and completeness of the data within it. Staff struggle with identifying missing data during data reporting. These issues can result in reporting inconsistencies across the staff. Document and streamline data entry processes. Staff spend a great deal of time repeatedly entering the same collected data. Collecting data is often done inconsistently across staff. Documenting program data collection and entry processes for staff training can be helpful. The processes can be included in a policies and procedures manual. In addition, converting to a paperless data system may ease the data entry burden. | Understand and document where data are located in a system. | | | | --- | --- | --- | | Tool | Type of tool
| Description
| | 2. 1: Guide to Data Mapping | Guide
Used with the Data Map Template | This short guide provides an overview of data mapping and a step-by-step walkthrough of the process. After reading through the guide, your team can work with your data system vendor to better understand the system design before undertaking the task of mapping the system. | | 2.2: Data Map Template* | Template
Used with the
Guide to Data Mapping | Once your team has reviewed the guide to data mapping and is ready to begin the process, this template can serve as a visual guide for the system. You will likely need to change the form names to align with your program. | | Improve and document data quality processes. | | | | Tool | Type of tool | Description | | 2.3: Guide to Data Cleaning | Guide | Data cleaning is a set of processes used to improve the quality and completeness of collected data. This document is a brief overview of the data cleaning process. It describes tasks for home visitors, supervisors, and data managers before and during data reporting. | | 2.4: Example of a Case File Checklist* | Example and Template
Used with the
Example of a
Missing Data Report | Checking individual case files to determine whether assessments and other data were collected completely and on time are critical steps in making sure data is high quality. This checklist is an example a supervisor can use to review an individual home visitor file. All examples can be edited to fit the needs of the program. | | 2.5: Example of a Missing Data Report* | Example and Template
Used with Example of a Case File Checklist | Once case files have been checked for quality and completeness, this information can be summarized in aggregate across the program with a missing data report. This document is an example of a report that would be developed by a data manager or supervisor to determine which data are missing prior to reporting. | | Document and streamline data entry processes | | | | --- | --- | --- | | Tool | Type of tool
| Description
| | 2.6: Data System Business Process Maps* | Example
Used with
Technical
Assistance
Facilitation | These maps provide a

FAQs

What does data mapping accomplish in a data system?

Data mapping visually diagrams where data “live” in a system and how data are connected. It helps teams confirm that automated reports use the correct data to calculate values accurately.

How do the module tools support improving data quality?

The module describes data cleaning processes to raise completeness and quality of collected data. It also provides a case file checklist and a missing data report example to identify gaps before reporting.

How does the module help teams reduce repeated data entry work?

It recommends documenting program data collection and entry processes for staff training, which supports consistent collection across staff. It also offers best practices for converting from paper-based processes to a paperless system using laptops or tablets.

Sep 11, 2026

Uploaded by Pentious