Drive efficiency and growth with automation

Manual processes are productivity killers. They can create reporting errors which can lead to increased compliance risk and impact many parts of your business. This post will explore how Artificial Intelligence (AI) and machine learning (ML) can reduce these risky manual-reporting processes. We’ll show how AI workflows can increase efficiencies, improve accuracy, uncover new insights, and free up your finance teams’ time for effective strategy planning.

In this article, we will cover:

1. The fix for human error
2. How algorithms can provide agility
3. Why automation offers a hassle-free workflow

Error is human, but there’s a fix for that

In the finance sector, human error creates an average of 25,000 hours of avoidable rework costing $878,000 per year, according to Gartner. Numbers like this are why the manual route is anathema to successful business practice, and why you should prioritize organizational efficiency over habit.

Foundry’s 2021 Digital Business Study, found that improving employee productivity and performance was the top objective for organizations’ digital business strategy. Easily invest in your team by freeing up some of the tasks that hold the biggest risk of errors, as these manual-entry mistakes would otherwise directly impact business performance.

“When people have to gather and process information manually from different sources, it’s inefficient, and can create errors that cause a ripple effect,” says Scott Freedman, director of marketing for Sage Intacct.

By using AI and ML-based automation, you can speed up workflows and catch costly mistakes. Automation streamlines previously manual processes to help finance teams close your books sooner, giving you more time to focus on strategic tasks. You’d be in good company, as 50% of organizations are actively researching or piloting AI and ML initiatives, according to the Foundry study. 

Algorithms and agility

By ingesting large volumes of data from financial applications across the organization, ML algorithms can gain a sense of where data should be placed and what kind of numbers are appropriate for a given field.

“For example, if someone makes a duplicate entry in an expense report, an algorithm will flag the manager,” Freedman says. Sorting out errors at this stage prevents an audit being held up down the road. The system can then automatically remind you if you need to make a decision, or approve a change, saving your employees from chasing the task manually.

You’ll find many common financial processes can be automated, and algorithms can import information from one software application into the form fields of others. Some solutions can even generate reports and send them out to stakeholders, saving you even more time. 

Private investment firm Halstatt, used the automated processes in Sage Intacct to reduce the time employees spent compiling consolidated reports, and a board book that took up to 100 hours, now takes only minutes. The company’s expense-reporting application now automatically posts journal entries and triggers check payments, lowering fees from $36 per check to less than $4.

Automation for a hassle-free workflow

Automation ensures that the data Halstatt uses is correct—and creates an audit trail to prove it. As a result, external auditors spend 2 weeks onsite rather than 6, and the company is saving $100,000 a year on fees and preparation. Overall, Halstatt’s accounting efficiency has increased 60%, giving the company the resources to create an alternative investment structure that has led to a $26 million investment.

“Automating simple procedures can save organizations staggering amounts of time and money,” Freedman says. “By eliminating repetitious tasks, you can develop strategies that drive growth.”

See how you can apply a more efficient automated workflow to your organization, with Sage Intacct.