About the On-Time Delivery dashboard

The On-Time Delivery dashboard provides comprehensive visibility into shipment delivery performance across the Shipium platform. It tracks key metrics including on-time delivery rates, transit times, and delivery accuracy across multiple dimensions such as carriers, service levels, origins, and destinations. The dashboard enables you to monitor performance trends over time, identify carriers and routes with performance issues, analyze geographic patterns, and understand how different service levels perform against delivery commitments. You can filter data by effective ship date, carrier method, origin name, and tenant name to drill into specific segments of their shipping operations.

Filters

Sections and metrics

Executive Summary

This section provides high-level KPIs (key performance indicators that summarize overall shipment performance for the selected filters.

Overall On-Time Performance

For the set of filters that have been selected, this metric displays the percentage of shipments delivered on time, calculated as the total count of on-time shipments divided by the total shipment count. The metric is displayed as a weekly trend showing how on-time performance has changed over time. You should interpret values closer to 100% as excellent performance, with performance benchmarks typically set at 90% (as shown in other visualizations on the dashboard).

Average Transit Time

For the set of filters that have been selected, this metric shows the average number of days shipments spend in transit from effective ship date to delivery. It is calculated by dividing the total time in transit days by the number of delivered shipments. The metric is displayed as a weekly trend, allowing you to identify periods where transit times increase or decrease. Lower values indicate faster delivery speeds and better operational efficiency.

Total Shipments

For the set of filters that have been selected, this metric displays the total count of shipments included in the analysis. This serves as a volume indicator and denominator for performance calculations, helping you understand the scale of data underlying the performance metrics. You should monitor this to ensure sufficient sample sizes when analyzing performance by specific segments.

Performance Trends

This section visualizes how on-time performance evolves over time, comparing actual performance against established benchmarks.

On-Time Performance (%) Over Time

For the set of filters that have been selected, this metric displays the daily on-time performance percentage as a line chart, overlaid with a 90% benchmark reference line. The on-time performance is calculated as described above, while the benchmark is a constant 90% threshold. You should interpret this visualization to identify performance trends, spot dates where performance dropped below the benchmark, and assess the consistency of delivery performance. Daily granularity allows for identification of specific problem days that may require investigation.

Carrier & Performance Analysis

This section provides detailed analysis of delivery performance by carrier and delivery status categories.

On-Time Performance by Status

For the set of filters that have been selected, this metric breaks down all shipments into three categories shown as a stacked column chart:

• On Time. Shipments delivered on the exact date, 1 day early, or more than 1 day early
• 1 Day Late. Shipments delivered exactly 1 day after the expected delivery date
• More than 1 Day Late. Shipments delivered 2+ days after the expected delivery date

Each category is calculated as a percentage of total delivered shipments. You should interpret this to understand not just the overall on-time rate, but the severity of late deliveries — a higher "More than 1 Day Late" percentage indicates more serious delivery issues requiring immediate attention.

On-Time Deliveries by Carrier

For the set of filters that have been selected, this metric displays each carrier's shipment volume (as column height) and on-time performance percentage (as data labels with conditional color formatting), sorted by shipment count in descending order. The on-time performance percentage uses color coding:

• green (>=90%)
• yellow (80-89%)
• orange (70-79%)
• red (< 70%)

You should interpret this to identify which carriers handle the most volume and how their performance compares, enabling data-driven carrier selection and performance management discussions.

Origin Performance Analysis

This section analyzes shipment performance by fulfillment center or warehouse origin.

On-Time Delivery by Origin

For the set of filters that have been selected, this metric shows a stacked bar chart for each origin (fulfillment center) displaying the proportion of on-time versus delayed shipments as a percentage, sorted by on-time performance in descending order. The chart displays "On Time Count" (shipments with EDD Accuracy Category = 'On Time') and "Delayed Count" (shipments with EDD Accuracy Category = 'Delayed') as percentages of total shipments from that origin. You should interpret this to identify which fulfillment centers consistently meet delivery commitments and which may have operational or carrier routing issues affecting performance.

Detailed Origin Performance Over Time

For the set of filters that have been selected, this metric displays daily on-time performance percentages as line charts, with one line per origin, filtered to show only the top 10 origins by shipment count. Each line tracks how that origin's on-time percentage changes day by day. You should interpret this to identify performance trends at specific facilities, compare performance across origins, and spot dates where particular origins experienced performance degradation that may require operational investigation.

Service Level Analysis

This section examines how different service levels (same-day, next-day, two-day, standard, international, etc.) perform against their delivery commitments.

On-Time Deliveries by Service-Class/Service Level

For the set of filters that have been selected, this metric shows a stacked bar chart displaying the percentage breakdown of on-time versus delayed shipments for each service level (excluding null values), sorted by service level from fastest (same_day) to slowest (international_one_to_four_week). Each bar is displayed as 100% stacked, showing "On Time Count" and "Delayed Count" as proportions. You should interpret this to understand which service levels consistently meet their delivery promises and which struggle with performance, recognizing that different service levels may have different performance expectations and customer impacts.

Service Level Performance Over Time

For the set of filters that have been selected, this metric displays daily on-time performance percentages as multi-line charts, with one line per service level (excluding null values). Each line shows how that service level's on-time percentage fluctuates day by day. You should interpret this to monitor performance trends for each service tier, identify dates when specific service levels experienced issues, and compare the stability of performance across different service commitments.

Geographic Performance Analysis

This section analyzes delivery performance by destination geography, helping identify regional delivery challenges.

On-Time Performance by Origin

For the set of filters that have been selected, this metric displays a geographic heatmap of the United States showing on-time performance percentages by origin state, filtered to states with more than 100 shipments. States are color-coded using a gradient from red (poor performance, < 85%) through yellow (moderate, ~85%) to green (excellent, ≥90%). You should interpret this visualization to identify geographic patterns in origin performance and understand which states or regions consistently ship on-time versus those requiring performance improvement initiatives.

On-Time Deliveries by Destination

For the set of filters that have been selected, this metric displays a stacked bar chart showing the top 20 destination states by shipment volume, plus all remaining states grouped as "Other", with on-time versus delayed shipment percentages. Each bar shows the proportion of "On Time Count" versus "Delayed Count", sorted by state rank and shipment count. You should interpret this to identify which destination states receive the most shipments and how delivery performance varies by destination, recognizing that some states may have geographic challenges (remote locations, limited carrier coverage) affecting performance.

Destination Performance Over Time

For the set of filters that have been selected, this metric shows daily on-time performance percentages as line charts, with one line per destination state, filtered to the top 10 states by shipment count over the last 4 weeks. Each line tracks how that destination's on-time percentage changes daily. You should interpret this to monitor performance trends to high-volume destinations, identify dates when specific states experienced delivery issues, and understand whether performance problems are isolated or systemic.

Overall On-Time Performance by Destination State

For the set of filters that have been selected, this metric displays a geographic heat map of the United States showing on-time performance percentages by destination state, filtered to states with more than 100 shipments. States are color-coded using a gradient from dark red (poor performance, near 0%) through yellow (~85%) to dark green (excellent performance, ≥90%). The visualization also includes average total time in transit days as additional context. You should interpret this to identify geographic regions where deliveries consistently arrive on-time versus areas with chronic performance issues that may require carrier strategy changes or customer expectation management.

Carrier Performance Scorecard

This section provides detailed scorecards for evaluating individual carriers and carrier service methods.

On-Time Deliveries by Carrier

For the set of filters that have been selected, this metric displays a stacked bar chart for each carrier showing the percentage breakdown of on-time versus delayed shipments, sorted by total shipment count in descending order. Each bar is 100% stacked showing "On Time Count" and "Delayed Count" proportions with data labels. You should interpret this to compare carrier performance directly, understanding both which carriers handle significant volume and which consistently meet delivery commitments, enabling informed carrier contract negotiations and routing strategy decisions.

On-Time Deliveries by Carrier Method

For the set of filters that have been selected, this metric displays a stacked bar chart for each specific carrier service method (e.g., "FedEx Ground", "UPS Next Day Air") showing the percentage breakdown of on-time versus delayed shipments, sorted by shipment count in descending order. Each bar shows "On Time Count" and "Delayed Count" as percentages with data labels. You should interpret this to drill deeper than carrier-level analysis, identifying specific service methods that underperform even when their carrier performs well overall, or vice versa, enabling granular optimization of carrier service method selection in routing logic.