Finance Automation: Where to Start When Everything Feels Manual

There’s a temptation to automate the entire finance function when the work feels manual across the board. But that isn’t always the right answer. A sensible finance automation roadmap starts by identifying where work is re-entered or put on hold, improving the process and then applying technology to solve a particular issue.

The reason for this is straightforward: no amount of automation will fix a poorly designed workflow. When details are missing, lines of responsibility are unclear, or tasks are performed in different ways by different staff, new technology can simply complicate an already unmanageable situation.

What Should You Fix Before Automating?

To automate a finance workflow, you need a clear picture of how things are done in practice. This means mapping the process in its entirety and noting what triggers it, who’s responsible for each step, the time involved and where approvals are given. It’s also worth noting where exceptions are dealt with and what causes rework.

The National AI Centre makes this point clearly: document the action, the inputs and outputs, and the person or system responsible for them. In doing so, you can spot bottlenecks and information gaps. It’s far more productive than having a list of problems with a manual process; you can see precisely what’s slowing the work down.

Take supplier invoices as an illustration. They arrive by email, are downloaded and put into a spreadsheet, sent for approval and then keyed into the accounting system after follow-up. The issue isn’t merely that the processing is manual; specific steps in the process could be improved.

Which Finance Processes Are Good Automation Candidates?

You shouldn’t assume every manual task is a candidate for finance workflow automation. The best ones are usually those with structured inputs and consistent rules, where the effort is measurable and the outcome verifiable. Examples include routine reconciliations, recurring invoice work or standard reports.

When deciding if a process is suitable, the National AI Centre recommends considering volume, repetitiveness and cost. That’s a sound way to build a roadmap: focus on the process with a problem that needs solving rather than the most advanced technology available.

What Counts As A Quick Win?

A quick win is a limited-scope improvement that reduces repetitive work without requiring an overhaul of the finance function’s technology. You might set up automatic reminders for approvers, have documents routed to the right place or flag missing data. Because the scope is narrow, adjustments can be made after measuring the result.

Simpler tools, such as templates or rule-based automation, are often preferable to complex AI solutions, as the National AI Centre suggests. There needs to be a clear purpose, though; automating something without one doesn’t improve the process.

When Does Automation Become An Infrastructure Project?

Some matters require bigger changes. If you have teams working from separate versions of the same records or data that’s inconsistent across systems, this is an infrastructure issue.

Attempting to put an automated workflow in place before you have fixed the underlying data is likely to cause problems. For instance, a management report is difficult to automate if the account codes don’t match, historical data contains numerous errors, or the required information has no reliable source.

There’s an important distinction between a quick win and a change to the infrastructure. A quick win improves a specific element of an existing process; an infrastructure change alters how information is handled throughout the finance function.

How Should You Choose Your First Automation Project?

The starting point is the process, not the technology. You can narrow the options by asking four questions:

• Is it a daily, weekly or monthly occurrence?

• Does it call for data entry, rework or chasing?

• Are the rules and steps predictable?

What are the consequences of error – delays, reporting problems or similar issues?

From there, the goal is to find those processes that are frequent and repetitive with a definite result. Avoid choosing the one that takes the most time. A complex process may need to be overhauled before automation is even feasible, whereas a smaller task provides a simpler place to begin.

What Does Accounting Automation Need From Your Data?

Any accounting automation is only as good as the quality and consistency of the data provided to it. The National AI Centre makes the point that AI requires information that’s accurate and fit for purpose. It recommends reviewing your workflows to see where technology can do the heavy lifting while retaining human oversight.

This is vital in finance since an automated system will execute a wrong rule just as quickly as a correct one.

Before proceeding, verify that you have the necessary information available, that account classifications are sound and that documents are accessible. Make sure there’s someone available to review the output and that any exceptions can be spotted.

How Should You Build A Finance Automation Roadmap?

After the initial project is complete, there’s no need to try and automate the whole workflow at once. A sensible finance automation roadmap has five stages:

1. Put the current process on paper and note the bottlenecks.

2. Remove unnecessary steps and standardise inputs.

3. Pick an area of the process where the benefit is easy to measure.

4. Run some tests on a small scale with real-world scenarios.

5. Compare it to the old way of doing things before you expand.

The National AI Centre advises this kind of structured approach, including getting input from those who’ll be using the new system. It’s a controlled move from manual work to automation, rather than treating it as simply another technology project.

What Should You Measure After Automation?

Automation isn’t an end in itself. The finance team needs to show what has improved. Look at the time to completion, approval turnarounds and processing delays. Count the manual steps and the number of tasks done without intervention. If the new workflow means fewer entries but more exceptions for staff to sort out, this may indicate the process hasn’t been improved. These figures will also inform decisions on what to tackle next.

Where Should Finance Teams Start?

When the work seems entirely manual, take a step back to understand it properly. Map it out, remove unnecessary steps and then automate the repetitive work.

A well-constructed finance automation roadmap doesn’t start with a list of software. It asks where the department is losing time and which part of the process can be made more consistent and easier to manage. In that way, you’re building around real improvements instead of adding technology to a convoluted workflow.