Automation

Automating Approvals: Common Mistakes and How to Avoid Them

A request remains pending because no one knows who should review it. Another is approved by default even though information is missing. And when an exception arises, the team returns to email or chat to resolve it manually. If this sounds familiar, you probably do not just need a tool: you need to define the process properly before automating it.

This article answers a practical question: what mistakes should you avoid when automating approvals? By the end, you will be able to decide which parts of your workflow are ready to automate, which controls you need to retain and what information to prepare before implementation.

What approval automation is intended to achieve

The aim should not be to approve more things without review. It should be to ensure that every request reaches the right person, with the necessary information and at the right time.

An approval workflow can apply, for example, to expenses, purchases, budgets, internal documents, data changes or customer requests. The pattern is usually similar: someone submits a request, the system checks certain rules, notifies the relevant owner, records the decision and communicates the next step.

Before choosing a solution, separate three levels:

Objective: the problem you want to address, such as preventing requests from being lost or reducing unnecessary delays.
Scope: the request types, people, data, statuses and exceptions included in the workflow.
Solution: the tool or integration that will execute the rules and send notifications.

Starting with the solution usually leads to automating a confusing process. These are the most common mistakes to identify beforehand.

Common mistakes when automating approvals

1. Automating a process that no one has documented

Symptom: each person describes the process differently. It is unclear what counts as a complete request, when review begins or what happens after approval.

Cause: an attempt is made to move a way of working that depends on messages, memory or informal agreements into a tool.

Consequence: the workflow may move requests between statuses, but it does not resolve the real uncertainties. Bottlenecks, duplicate decisions and manual steps outside the system appear.

Correction: first map the current process with sufficient detail. For each request, define who creates it, what data they provide, who decides, what decisions are possible and what happens in each case. Then identify the repetitive steps that can be performed through rules.

2. Using ambiguous criteria to decide who approves

Symptom: rules appear such as “if it is important”, “if it has a high amount” or “if management reviews it”, but no one specifies what they mean.

Cause: decisions are based on context that some people know, but that has not been turned into a verifiable condition.

Consequence: the automation cannot assign the request correctly or applies a route that the team considers incorrect. It also becomes difficult to explain why a request reached one person rather than another.

Correction: turn each criterion into a specific rule. For example, define which field determines the route, which values it accepts, who can modify it and what happens if it is missing. If a decision requires professional judgement, negotiation or external information, do not force it into an automated rule: retain an identified human review.

3. Designing only the ideal path

Symptom: the workflow covers submission, approval and completion, but not incomplete requests, rejections, changes of owner or lack of response.

Cause: the design focuses on the simplest sequence and leaves exceptions for later.

Consequence: at the first unforeseen case, the team needs to intervene outside the workflow. This can break the decision record and create uncertainty about the request’s actual status.

Correction: for each status, consider what happens if something fails or changes. At a minimum, define how to request additional information, how to reject with a reason, how to reassign an approval and what to do when the responsible person cannot act. You do not need to automate every exception from the start, but you do need to decide how they will be handled.

4. Confusing a notification with an approval

Symptom: someone receives a notification, replies through another channel or does not respond, and the team interprets that situation as a decision.

Cause: the action that confirms approval and where it is recorded have not been defined.

Consequence: it is difficult to know whether the request is approved, pending or simply seen. In addition, subsequent steps may be carried out without clear confirmation.

Correction: establish an explicit action to approve, reject or request changes. Every decision must record the responsible person, date and outcome. Notifications are used to draw attention; the decision record is what allows the workflow to continue safely.

5. Allowing automation to approve sensitive decisions without limits

Symptom: the system is expected to automatically approve any request that meets initial conditions, even though the context may have changed.

Cause: every approval is treated as a repetitive task, without distinguishing between objective checks and decisions that involve judgement.

Consequence: a rule may validate a formal condition but fail to detect circumstances that require review. The problem is not automation itself, but assigning it a responsibility that it cannot assess in context.

Correction: reserve automatic approval for clear, limited and reviewable conditions. Keep human involvement where amounts, risks, exceptions, commitments or insufficient data need to be assessed. It is also advisable to define who can modify the rules and when they are reviewed.

6. Failing to define permissions and substitutes

Symptom: several people can approve without realising it, one person retains permissions they no longer need or the workflow stops when someone is absent.

Cause: responsible people have been configured as fixed names, without considering roles, team changes or substitutes.

Consequence: the process loses traceability and may become blocked. At the same time, permissions may not reflect who should actually be involved.

Correction: define which roles participate and what each one can do: create, view, approve, reject, modify or reassign. Add a substitution rule for absences and decide who reviews access periodically. Permissions are not a technical detail; they determine who can make each decision.

7. Connecting tools without reviewing the data being transferred

Symptom: a request moves from a form to a spreadsheet, email or management system, but some fields arrive empty, duplicated or in different formats.

Cause: it is assumed that the tools share the same information and meaning for each data point.

Consequence: an approval may be sent down the wrong route, create duplicate records or leave relevant data out of the decision.

Correction: document the journey of every relevant data point: where it originates, where it is stored, who can change it and what happens if it does not arrive correctly. Test cases with complete, incomplete and modified data. If there is personal or confidential information, also decide which people and systems need access to it.

8. Launching the workflow without review criteria

Symptom: the system seems to work because it sends notifications, but no one checks whether requests are resolved through the expected route or whether pending items are accumulating.

Cause: no definition has been made of how to recognise that the workflow is working or who will review incidents and subsequent changes.

Consequence: minor failures become normalised. Over time, the team may create manual workarounds and lose confidence in the process.

Correction: agree on simple review criteria before activating the workflow. For example: a complete request reaches the defined owner, a decision is recorded, rejections state what must be corrected and exceptions have a resolution path. Test the process with representative situations before using it more broadly.

How to prevent these mistakes without overcomplicating the first workflow

Start with one specific, repetitive case. Do not try to bring together every approval in the company into a single automation from the outset.

A reasonable starting point is to choose a request type with identified owners and relatively stable rules. Then write a short brief covering these elements:

What triggers the request.
What data is required to review it.
What statuses it can have.
Who approves or rejects at each status.
What rules determine assignment.
What exceptions require human involvement.
What notifications are sent and through which channel.
Where each decision is recorded.
Who maintains rules, permissions and changes.

This brief helps identify an important point: you may not need to automate the entire decision. In some cases, it is enough to automate data collection, classification, assignment and reminders, while final validation remains human.

Review checklist before automating approvals

Review these questions before configuring the workflow:

If several answers remain open, it is advisable to resolve them before choosing the tool or expanding the scope. Automation works best when it removes repetitive steps from an already understood process, not when it tries to conceal its ambiguities.

Next step

If you have a clear process but are unsure which rules to automate, which human controls to retain or how to connect the tools you already use, you can describe your automation project to AVSISTEC. This will allow you to assess the scope based on your requests, owners, exceptions and real control requirements.