---
title: "How to find slow, low-value tasks in each role"
description: "Find recurring tasks worth changing in each role. Separate effort, waiting, and repair, then check the purpose before choosing an AI function to build."
canonical: "https://scalewithsearch.com/articles/find-slow-low-value-tasks-each-role"
---
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# How to find slow, low-value tasks in each role

Ask each person to name the slowest, lowest-value task they carry. Then examine a recent example. Record active effort, waiting, review, and repair separately. Ask the person receiving the result what they use it for.

Treat the answers as the start of a study. A disliked task may protect a required decision. A slow task may spend most of its time waiting for another person. A short task may recur often enough to deserve attention.

Your goal is a short list of tasks with evidence and a proposed remedy. Avoid turning the exercise into a ranking of employees. Study how the work moves and which parts should change.

## Define value before measuring time

For each candidate task, name the result and the person who uses it. Ask what action becomes possible when the result arrives. Record the answer beside an actual completed example.

Separate necessary work from unnecessary production. A control may have value even when it creates no customer-facing artifact. A polished report may have little purpose if its recipient cannot name a decision it supports. Confirm both judgments with the responsible owner.

Use “low value” to describe a task's contribution in its current form. Do not use it as a label for a person's role or a claim that the work requires no skill.

[NIST's AI RMF Core, Map 1.4](https://airc.nist.gov/airmf-resources/airmf/5-sec-core/) calls for clearly defining business value or the context of business use. This worksheet applies that question before a build decision. Source checked October 26, 2026.

## Invite examples from every role in scope

Ask the owner, coordinator, delivery staff, and reviewers the same questions. Include outside providers when they perform a step inside the process you are studying. Keep each answer connected to its role.

Ask people what they repeatedly reconstruct, copy, chase, reformat, or correct. These verbs are prompts for finding examples. They are not proof that a task should be automated.

Let each person choose an ordinary case and an exception. Ask them to show the source material and the accepted result. Record whether the case was typical or selected because it was difficult.

State how you will use the information. The study should evaluate task design and proposed changes. Do not imply that it proves a future reduction in staffing, cost, or working hours.

## Measure a complete run

Choose a task boundary with a clear start and finish. “Prepare the weekly delivery summary from approved records” is a usable boundary. “Do reporting” is too broad for a useful comparison.

Observe a run when practical. Record timestamps or active intervals in the business's usual work log. Label remembered durations as estimates. If the observation excludes a step, say so.

Include the work before and after production. Note the time spent locating sources, resolving conflicts, preparing the output, reviewing it, and making corrections. Include the next person's repair when you can observe it.

For the later pilot, use [the output receipt guide](/articles/receipt-is-part-of-the-output) to record what ran, what stopped, and what the system produced. Compare those receipts with the observed manual process.

Keep the original observations. A summary number should point back to the runs that produced it. Do not present a single unusual case as the normal pattern.

## Separate effort from waiting

Use different columns for time spent working and time spent blocked. Name the cause of each wait. “Waiting for the manager to confirm the status” is useful. “Slow” leaves the cause unresolved.

If the task waits for information, examine how that information is requested and recorded. A clearer intake rule might be the next step. If it waits for a decision, ask whether the decision owner and required evidence are clear.

Do not assume a faster draft will change the finish time. Test the whole proposed sequence, including the same review and exception path. Use the observed result to judge the change.

The existing [AI workflow bottleneck guide](/articles/ai-workflow-bottleneck) focuses on repeated context setup. Use this study to determine whether setup is the relevant issue in your own task.

## Record repair as its own work

Ask reviewers which corrections they make repeatedly. Save the original output and the corrected version when access rules permit. Record what made the first version unusable.

Sort the reason for repair. Was the source missing, the rule unclear, the input wrong, the format unsuitable, or the decision unresolved? Ask the responsible person to verify the reason rather than inferring it from the final document.

A proposed AI function should address the verified cause. If the cause is conflicting policy, assign an owner to resolve the conflict first. If the cause is missing evidence, define the hold that prevents an unsupported answer.

Count review and repair in the proposed process. Keep them visible even when the first output looks polished. Acceptance depends on the result being usable for its stated purpose.

## Compare recurring burden without invented returns

Record frequency using a stated observation period. Distinguish observed runs from a person's estimate of future volume. Keep unusual seasonal or exception work visible instead of averaging it away.

For a planning worksheet, multiply observed occurrences by observed active effort per occurrence. Label that result as an estimate when either input is estimated. Keep waiting separate. Do not translate the result into promised savings.

Compare tasks within their context. A task with less production effort might require extensive checking. Another might be worth stopping after its owner confirms that its output is unused.

Use the numbers to ask better questions. The decision still needs a purpose, an owner, safe boundaries, and a testable alternative. No score should override an unresolved requirement.

## Work through a fictional example

Suppose a small service firm studies how its coordinator prepares a weekly update. Use this fictional workflow to plan the observation. Fill the timing columns from actual runs before comparing candidate changes.

| Part to observe | Active effort to record | Waiting to record | Question to examine |
|---|---|---|---|
| Find approved status records | Time spent locating and checking sources | Unavailable records | Are the approved sources easy to find? |
| Resolve conflicting entries | Time spent preparing the question | Manager's confirmation | Who decides which status is current? |
| Draft the update | Time spent preparing the draft | Missing confirmed inputs | Does each statement match an approved record? |
| Review and repair | Time spent checking and correcting | Reviewer's availability | Which defects recur? |

In this example, drafting is only one part of the task. A proposed function could assemble approved records and show conflicts. It would hold disputed items for the manager.

Test that narrower design against the complete current sequence. Keep review time and unresolved waits in the comparison. The worksheet does not establish how much time the change would save.

## Choose a remedy before choosing a tool

For each candidate, write the smallest change worth testing. Options include stopping duplicate output, clarifying source rules, or changing a handoff. You could use a calculation, prepare an AI-assisted draft, or assign specialist work elsewhere.

Preserve the reason. “Repeated reconstruction of approved status records” is a useful build hypothesis. “Everyone hates reporting” needs more evidence.

If judgment is the task's value, keep the decision with a person. The [manual workflow guide](/articles/when-an-ai-workflow-should-stay-manual) explains how to retain that boundary while considering assistance with preparation.

Name the person who will test the proposed change. Define the accepted result and the evidence they will inspect. If no one can review it, leave the candidate unbuilt.

## Finish with one candidate per role

Give each participating role a short summary: the task studied, evidence examined, effort and waits observed, proposed remedy, and unresolved questions. Ask the person performing the task and its recipient to confirm it.

Then compare candidates across the business. Choose one function with a clear purpose and a manageable test. Keep the other findings in the record for later decisions.

The [AI systems method](/ai-systems) begins with this study before sorting and building. To start with your own recurring task, [send the job and an example of its current output](/work).


## Related: Ownership and Migration

- [Remove the context setup step that makes AI slow down your work](/articles/ai-workflow-bottleneck)
- [When an AI Workflow Should Stay Manual](/articles/when-an-ai-workflow-should-stay-manual)
- [The Receipt Is Part of the Output](/articles/receipt-is-part-of-the-output)

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```
