Data Quality Analysis
The Data Quality Analysis feature helps administrators and dispatchers identify and resolve data mismatches that prevent accurate scheduling and technician assignment in Schedule Optimization.
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This is a Beta release.
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Schedule Optimization delivers efficient dispatch plans only when input data accurately reflects your operational reality. Data discrepancies such as missing skills, lack of capacity, less work orders, or overlapping events cause work orders to remain unscheduled or assigned outside SLA windows, and leave technicians underutilized. The Data Quality Analysis feature runs analysis jobs on Batch and LTP dispatch processes to identify the data quality gaps and recommend corrections.
Administrators can use the feature to audit data integrity across dispatch processes, establish data governance standards, and guide implementers in rectifying root causes before they impact future optimization runs.
The feature analyzes and generates a detailed report that categorizes findings into following areas:
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Category
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Description
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Typical findings
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Capacity vs demand analysis
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Evaluates technician availability, working hours, break settings, and resource to spot gaps between demand and capacity. It highlights where demand exceeds available technicians and where resources are underused. It also compares work order needs with assigned resources and time windows, and flags work orders that cannot be scheduled due to missing skills, resource requirements, or SLA limits.
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Technicians overbooked beyond available hours, technicians with no scheduled work.
Unscheduled work orders, work orders with SLA deadline violations, skill mismatches.
Missing mandatory technician skills, and expired certifications.
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General anomalies
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Detects data quality issues in configuration settings, technician profiles, and work order records that deviate from expected patterns or violate business rules.
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Fixed calendar entries, and unavailable days.
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Optimization objectives analysis
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Analyzes how well the completed optimization run met configured goals such as cost minimization, route optimization, or technician utilization targets. Compares input parameters against achieved output results.
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Deviation from target technician utilization percentages; higher-than-expected route distance or drive time; cost inefficiencies
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The analysis compares input data provided to the optimization engine against the output results returned by Schedule Optimization.
For each category, the tool provides specific recommendations for improving data quality. Administrators review these recommendations and guide implementation teams to update technician profiles, validate work order fields, refine territory assignments, or adjust business rules.
Use Cases
• Identify unscheduled work orders and their root cause; does the technician have the required skills, does the territory assignment match, are business hours configured correctly, or is SLA deadline impossible to meet given current capacity.
• Discover technician underutilization patterns; find which technicians have available capacity that is not being used, and determine whether missing skills, territory restrictions, or business hour gaps are responsible.
• Audit territory and skill assignments; validate that work orders are assigned to the correct territory and that technician skill sets match customer requirements.
• Compare achieved cost and route metrics against configured optimization objectives; understand whether the dispatch plan met cost, distance, or utilization targets.
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