# Doing Own Analytics Using Exported Data

In Atlas CMMS, users have the ability to export data from various modules, including Work Orders, Locations, Assets, Parts, and Meters. This export functionality allows users to obtain the raw data in a structured format, typically as a CSV (Comma-Separated Values) or Excel file. By clicking on the three vertical dots at the top right corner of each module's view page and selecting the "Export" option, users can choose the specific data they want to export.

Exporting data from Atlas CMMS provides several benefits and opportunities for further analysis and insights beyond the built-in analytics provided by the system. While the CMMS offers a range of automated analytics based on historical data recorded within the system, exporting the raw data enables users to perform their own custom analyses, create personalized reports, and gain additional insights tailored to their specific needs.

Here are some examples of how users can leverage the exported data:

Work Order Analysis:

Identify trends in work order volume, types, and completion times over different periods.
Analyze work order distribution across various assets, locations, or technicians to identify patterns or imbalances.
Calculate custom metrics, such as mean time to repair (MTTR) or mean time between failures (MTBF), based on specific criteria.

Asset Performance:

Evaluate the reliability and availability of individual assets by analyzing their associated work orders and downtime data.
Compare the maintenance costs and performance of similar assets to identify outliers or best practices.
Assess the effectiveness of preventive maintenance schedules by examining the frequency and types of work orders generated for each asset.

Inventory Management:

Analyze parts consumption patterns to optimize inventory levels and avoid stockouts.
Identify frequently used or critical parts to prioritize supplier relationships and negotiate better pricing.
Forecast future parts demand based on historical usage data and planned maintenance activities.

Maintenance Budgeting:

Develop detailed maintenance budgets by analyzing historical costs associated with labor, parts, and external services.
Identify cost trends and anomalies to pinpoint areas for potential savings or process improvements.
Allocate maintenance budgets across different assets, locations, or departments based on historical data and future projections.

Meter-Based Maintenance:

Analyze meter readings to identify usage patterns and optimize preventive maintenance intervals.
Correlate meter data with work order history to assess the effectiveness of condition-based maintenance strategies.
Develop predictive maintenance models based on meter readings and other relevant variables.

By exporting data from Atlas CMMS and performing their own analyses, users can gain a deeper understanding of their maintenance operations, identify improvement opportunities, and make data-driven decisions. This capability complements the built-in analytics provided by the CMMS and allows for more customized and targeted insights.

It's important to note that while the export functionality provides access to raw data, users should still rely on the automated analytics within Atlas CMMS for standard reporting and performance tracking. The exported data should be used for advanced analysis, custom reporting, and integration with other systems or tools as needed.

There are several other reasons why a user may need to export data from the Atlas CMMS besides conducting their own analysis. Here are a few additional use cases:

Reporting and Presentations:

Users may need to export data to create custom reports or presentations for management, stakeholders, or auditors.
Exported data can be formatted and visualized in external tools like Excel or PowerBI to generate professional-looking reports or dashboards.

Data Archiving and Backup:

Exporting data regularly serves as a backup mechanism to ensure critical maintenance records are preserved outside the CMMS.
Archived data exports can be used for historical reference, compliance documentation, or to restore information in case of data loss or system migration.

Integration with Other Systems:

Exported data can be used to integrate the CMMS with other enterprise systems, such as ERP, accounting, or business intelligence platforms.
Sharing data across systems enables a more holistic view of operations and supports cross-functional processes like procurement, budgeting, and performance management.

Collaboration and Knowledge Sharing:

Maintenance teams may need to share data exports with colleagues, contractors, or external experts for collaboration or troubleshooting purposes.
Exported data can be easily attached to emails or uploaded to shared drives for others to access and review.

Regulatory Compliance and Audits:

In some industries, maintenance records must be provided to regulators or auditors to demonstrate compliance with standards or legislation.
Exporting data allows organizations to quickly retrieve and submit the necessary documentation during audits or inspections.

Offline Access and Field Work:

Maintenance technicians may need to reference asset data, work instructions, or part information while working in areas with limited internet connectivity.
Exporting relevant data to a mobile device or printing it out ensures technicians have the information they need to complete tasks safely and efficiently, even offline.

Data Migration and System Transitions:

When an organization decides to switch to a new CMMS or merge with another company, exporting data from the current system is a critical step in the migration process.
Exported data can be cleaned, mapped, and imported into the new system to ensure a smooth transition and maintain data integrity.

Remember: The data you capture in ATLAS CMMS is a powerful asset in itself. By leveraging the export functionality and exploring the practical use cases shared on our blog, you can unlock even more value from your maintenance operations and take your asset management to the next level.