Data integrity refers to the idea that data is reliable and accurate over the course of its life. Data quality and data security, often confused with data integrity, are both concepts that support the end goal of having data that is uncorrupted and therefore accurate for your organization. Achieving data integrity starts with having expectations of your data, systems, people, and processes and builds confidence in the software system your organization uses.
Achieving Data Integrity
- Ensure your system can store original source data by uploading attachments, such as copies of inspection reports, vendor invoices, and training certifications for staff. This eliminates the need to keep paper but maintains accurate electronic records in their original forms.
- Confirm your system has an accurate audit trail with computer-generated time-stamped records that identify data that is input by date and user and include additions and changes.
- Utilize data loading tools to insert, update or delete data that uses the application layer and therefore goes through the validation process as if a user input the data manually. Doing this produces identifiable errors and forces a user to fix the data before it is entered into the system as a mass update.
- Enforce limited access with user security by placing users in groups that have pre-defined rights, views, and ability to impact data. Less is more when it comes to allowing users the ability to see and impact your organization’s data. In the long run, this makes it easier to train on specific procedures as well.
- Document your backup and recovery options, whether you host on the premises at your organization or with a vendor in a cloud-hosted solution. Know what happens the first hour, day, and week if your data is compromised. This would include both physical compromise, such as a down server, and electronic compromise, such as from a user’s actions that did not follow a documented SOP.
- Establish processes that promote quality, eliminate redundancy, and ensure accountability. Using standard industry coding that is recognized by staff, documented workflows that support logical procedures, and limited choices in data collection help control the process.
- Train your users to input and maintain data that supports their job functions. If they are given proper education and expertise, the quality of data provided will improve and support data integrity. Provide updated documentation regularly to show ongoing support of the system.
Benefits of Achieving Data Integrity
Success in data integrity takes a coordinated effort and buy-in from the everyday user to the system administrator and requires planning, execution, and continuous monitoring. Selecting a system that helps you achieve this by creating the right workflows can mean the following efficiencies for your organization:
- Produces confidence in the end user, system users, and stakeholders.
- Offers a clear and clean audit trail for organizational accountability.
- Uses accurate reporting to make stronger decisions for future state planning.
Could you describe your data as having integrity? Many fleet organizations cannot claim that, but an upgrade in fleet management software, coupled with the above steps, can produce dramatic results.