Core Insights: Task Performance

Core Insights: Task Performance

The Task Performance insight digs deeper than project-level reporting to show you exactly how individual tasks are performing across your onboarding playbooks. While Project Velocity tells you that projects are running late, Task Performance tells you why — surfacing the specific tasks and steps that are consistently being completed early, on time, or late.

This is where you find the bottlenecks hiding inside your playbooks and take action to eliminate them.

What This View Shows

Task Timing Distribution Chart

The primary visualization is a diverging dot chart — a scatter-style chart anchored at zero in the middle. Each dot represents a task instance plotted according to how many days early (left) or late (right) it was completed relative to its scheduled due date.

• The left side is labeled EARLY — dots here represent tasks completed ahead of schedule, with the distance indicating how many days early.
• The right side is labeled LATE — dots here represent tasks completed after their due date, with the distance indicating how many days late.
• The center band is labeled ON TIME — tasks completed on or very near their due date.

Hover over any dot to see the specific task name, project, account, and the exact number of days early or late.

This visualization makes it immediately apparent whether your tasks cluster around on-time completion or whether you have significant outliers dragging performance to one side.

Exclude Archived Toggle

A toggle at the top of the chart lets you exclude archived tasks from the visualization. Enable this to focus your analysis on active, relevant task templates and remove noise from deprecated or historical task data.

Task Performance by Playbook Table

Below the chart, a detailed table aggregates task performance at the template level with the following columns:

• Task Name — The name of the task template.
• Source From — The type of source this task originates from (e.g., Playbook, Manual).
• Source Name — The specific playbook or source the task belongs to.
• Instances — The total number of times this task has been run across all projects in the selected period.
• Avg Deviation — The average number of days early (negative) or late (positive) this task is completed, across all instances.
• Early — The count of instances where this task was completed early.
• On Time — The count of instances where this task was completed on time.
• Late — The count of instances where this task was completed late.

Sort the table by Avg Deviation (descending) to immediately identify the tasks with the worst on-time performance — these are your highest-priority optimization targets.

Summary Stats

At the bottom of the page, five aggregate metrics summarize task performance across the entire view:

• Task Templates — The number of unique task templates represented in the current view.
• Total Instances — The total number of individual task completions included in the analysis.
• Avg Early — The average number of days early for tasks completed ahead of schedule.
• Avg Late — The average number of days late for tasks that missed their due date.
• On-Time Rate — The percentage of all task instances completed on time — your single headline metric for task execution quality.

Filters

Narrow your analysis using the filters at the top of the page:

• Date range — Define the period for which task completions are included.
• Playbook — Filter to tasks from a specific playbook.
• Owner — See how tasks perform across projects owned by specific team members.
• Account — Focus on a particular customer's projects.
• Exclude Archived — Toggle to hide archived task templates from the chart and table.

How to Use This Insight

Find Your Most Problematic Tasks

Sort the table by Avg Deviation descending to see which tasks are most consistently late. A task with a high average deviation and a high instance count is a systemic problem — it's not a one-off, it's happening across many projects. These are the tasks that deserve immediate attention.

Investigate Root Causes

When you identify a consistently late task, ask: Is it always waiting on the customer? Is there a dependency that isn't sequenced correctly in the playbook? Is it assigned to an already overloaded team member? The insight surfaces the what — pairing it with playbook review and project-level context helps you find the why.

Benchmark Your On-Time Rate

The On-Time Rate stat at the bottom is your headline KPI for task execution. Track this over time by adjusting your date range to see if the rate is improving. A rising on-time rate after a playbook change is strong evidence that the change is working.

Recognize High-Performing Tasks Too

Tasks that are consistently completed early — and have high instance counts — represent your team's strengths. They may be candidates for earlier sequencing, or examples of what great task design looks like in your playbooks.

OnRamp AI Analysis

The OnRamp AI panel on the right side of the screen automatically reviews your task performance data and highlights the most impactful findings — which tasks are dragging your on-time rate down, whether late tasks are clustered in a specific playbook, and what interventions are likely to have the biggest impact.

Ask follow-up questions like: "Which task has the worst on-time rate?" or "Are there tasks that are always late in the Enterprise playbook but on time in others?"

Explore all Core Insights views in this knowledge base for a complete picture of your onboarding performance.

]]>