Identify Tasks Ripe for Automation

Introduction

Not all tasks are worth automating. In fact, automating the wrong task can cost you more time and money than doing it manually. That’s why the first real step after process mapping is pinpointing which tasks are:

  • High-friction

  • Low-leverage

  • Repetitive

  • Error-prone

  • Not requiring creativity or nuanced judgment

These tasks are ripe for automation.

This guide will walk you through how to identify these tasks using a simple scoring framework, qualitative interviews, and a collaborative workshop format.

Why Task Identification Matters

You can't automate what you haven't defined. And not all inefficiencies are visible in dashboards.

  • Some bottlenecks live in the inbox.

  • Some are invisible but constantly repeated.

  • Others require hours of context-switching across tools.

Without a deliberate approach to task identification, teams default to shiny tool trials that solve problems no one had—or that automate tasks that barely move the needle.

The Task Identification Framework

We recommend using a 3-part framework to prioritize tasks for automation:

1. Frequency

How often does the task occur?

2. Friction

How frustrating, error-prone, or time-consuming is it?

3. Automation Feasibility

Can this task be fully or partially automated with available tools?

Formula:
Automation Opportunity Score = Frequency × Friction × Feasibility

Anything above 50 is a strong candidate. Anything above 75 is a no-brainer.

Step-by-Step Task Audit

Step 1: Interview Team Members

Ask each team member:

  • What are your most repetitive tasks?

  • What task feels like it wastes the most time?

  • What do you dread doing, but has to be done regularly?

  • Where do you often make mistakes?

These conversations reveal tribal knowledge that dashboards can’t.

Step 2: Run a Task Inventory Workshop

  • Use a shared template (Notion, Miro, FigJam)

  • List tasks per function (e.g. marketing, ops, sales)

  • Assign Frequency, Friction, and Feasibility scores collaboratively

  • Sort by score to reveal automation priorities

Step 3: Validate with Observation or Data

  • Watch how tasks are done (shadowing, screen recordings)

  • Use time-tracking tools (Toggl, RescueTime, Clockify)

  • Export audit logs or task history from project management tools

Step 4: Highlight Quick Wins

Look for tasks with:

  • High Frequency

  • High Feasibility

  • Moderate Friction

These are your low-risk, high-return automation pilots. Examples might include:

  • Assigning leads in a CRM

  • Sending onboarding emails

  • Tagging support tickets

  • Pulling weekly reports

Case Study: High-Scoring Task

Automate with: Google Analytics + BigQuery + Looker Studio scheduler or Zapier trigger

Tools That Help with Task Identification

  • Manual Audits: Notion, Airtable, Google Sheets

  • Tracking & Observation: Scribe, Loom, Screen Studio

  • Workflow Analytics: Whaly, Workato Insights, Qatalog

  • Interview Notes: Grain, Fireflies, Notion AI Summaries

Free Template:

Download the Automation Candidate Scorecard (Google Sheet)
Includes scoring system, examples, and prioritization chart.

Discovery Question to Ask Teams:

“What’s the most repetitive task your team could live without?”

AI AutomationFrancesca Tabor