Identifying Data Gaps for Better Scheduling with Work Order Analysis

Historical work orders contain some of the most useful information necessary for planning and scheduling tasks. Analyzing historical work orders can not only help you organize future orders, but at the same time, it can help ease scheduling by identifying data gaps and missing information. Moreover, with historical work order data, you can plan costs for the future and analyze trends regarding maintenance data.

Analyzing data for better scheduling 

Calculating the estimated time required to complete a maintenance task in your EAM/CMMS system can give you a rough idea of the number of hours it would take on average to achieve a particular mission. You will know you have problems when you notice that all your tasks are set to a specific timeframe, but in reality, the actual work takes much longer to complete. This is also where prioritizing work orders come in. Based on the order’s criticality, it is either completed first or last and if a backlog does occur, it would consist mainly of low-priority work orders.

It is also useful to have a functional or process-oriented asset hierarchy. This helps scheduling tools know which assets are impacted by processes that need to be shut down for maintenance, causing the least amount of downtime for other equipment. You can also understand the actual costs of maintenance by looking at those equipment that need constant repairs.

​Finally, it is crucial that work centers and resource information is accurate. If not, scheduling will become more difficult since scheduling tools will not work. Scheduling tools within your EAM/ CMMS systems are essential in forecasting schedules for new projects and help you stay updated with recent changes in the plan. Analyzing historical work order data can also help you gain insights into previous timeframes and scheduling processes.

Optimizing work order data 

Ultimately, reviewing work orders can help you get familiar with order types, timeframes, and scheduling processes. Moreover, analyzing historical work order data over time can help you plan and assign tasks easier. To learn more about how NRX Work Order Analysis can help analyze work order data for better scheduling, click on one of our resources below, or book a demo with us to help you achieve efficient and accurate work order data.