The Essentials of Cash Flow Forecasting

Human error 

Spreadsheets are a common method of cash flow forecasting and we understand why businesses rely on them. They’re free and simple to use. That’s the assumption anyway. But given that 88% - 90% of Excel spreadsheets contain errors, that’s a scary thought. 

Creating a cash flow forecast is all about knowing the ins and outs of your finances. It’s getting down to the details and knowing everything from top to bottom about expenses, sales, loans and invoice schedules. Often, you’re sourcing this data from multiple places like ERP and CRM systems and producing complicated spreadsheets manually.

The potential for human error is high. Wrong figures and duplicate data can lead to a skewed analysis and stop you from budgeting correctly. Suddenly, you’re dipping into other revenue streams to keep your business afloat and cash flow is taking a major hit. 

Miscommunication and silos 

Gathering large amounts of financial data doesn’t happen all at once. There are various departments and decision makers that need to approve and communicate with each other. This can be made even trickier in global organizations where people are operating across different time zones and subsidiaries. All it takes is one poorly worded email or a phone conversation taken out of context and you could have another layer of complexity added to an already complex process and more time is wasted. 

Then there’s the issue of market volatility and currency fluctuation in different countries. Plus, there may be a requirement to access multiple bank accounts daily. Not only will this slow down forecasting, but it will also become harder to predict what’s happening with your cash flow. 

Lack of insight into trends and innovation 

This is the way things have always been done. Does that sound familiar to you? Well, in finance that kind of attitude is more common than you think, especially with an aging workforce of accountants who are used to using paper and spreadsheets to compile cash flow forecasts. The reality is that most accountants in big firms are baby boomers of 60 years and over with an average age of 43.

As experienced as these people are, they’re only human. Fatigue and error are to be expected from time to time when looking at pages and pages of data. Bu doing everything manually makes it harder to cross-reference historical information and highlight trends. It also makes it harder to present and adopt new innovations that can streamline cash forecasting. 

It’s also not helpful when your finance team are perceived to be ‘bean counters’ and blockers whose only role is to approve deals. In reality, finance is actively trying to protect cash flow. But unfortunately, as the saying goes, perception is reality. So, finance could be left out of decision-making by other departments and tension develops. It all contributes to slow cash forecasting, misunderstandings and negative cash flow.

We asked other experts about their take on predictive modelling and it was a big discussion point in our ‘Financial Automation & AI: Mitigate Risk to Maximize Growth’ webinar.   Leighton Weston, Global Account Director at Creditsafe, had lots of value bombs to drop about the topic.

When asked how people can make the most of predictive modelling, Leighton said, “It starts with mapping the current state of your data and deciding whether it’s good or bad. If it’s good that’s an easy conversation. If it’s bad, you have to look at ways to clean it up. And let’s take a practical example with a supplier. They might have a fantastic AAA credit score and I’ve checked them against the sanctions list. That can be automated easily. I can see where credit managers and supply chain managers earned their money in fringe cases.

But surprisingly, the fringe cases are a big chunk of work. What you don’t want is your staff looking at a financial risk report that says AAA and then looking at a blank sanctions report to do a manual review. So, then you start assessing how much time and resources you’re investing into the project. What are you going to look at in three months? What’s your desired state in six to 12 months? Knowing that timeline means you can strive for that goal.

I had a case of seeing predictive analytics work recently. A client had data on 28,000 salons and I was expecting the data to be bad. But then I matched it in a matching engine and was able to match 83% of these companies to their correct profiles immediately. It massively exceeded my expectations as I’d thought the data would only match to between 50 - 60%.”

Here’s an analogy. Your business is like a ship and healthy cash flow is the bulwark that keeps it afloat. But when you start having cash flow problems, the ship begins leaking and you need to find ways to patch up those holes. Automation will help you find those leaks much faster.  

Issues could be late payments, a low amount of capital in the business or any number of challenges that contribute to negative cash flow. Late invoices are certainly a trend that comes up a lot. The reasons for this range from a recession to a lack of due diligence from companies. And US businesses have to write off 4% of their invoices per year. While this might seem like a small number, 4% is still important cash flow that’s being lost.

We asked Sarah-Jayne Martin, Director, ICA Global AR Practice at Quadient, about how automation can help with this specific issue.

“It’s about getting in front of the problem ahead of time. There are many stages across the credit-to-cash process where there’s an opportunity. Whether that be at the initial customer onboarding and credit risk assessment or dispute management. The faster you're able to resolve the issue, the more likely it is you'll get paid.

It’s the same with regular invoice distribution. The older that invoice becomes, the harder it is to collect that money, which ultimately may end up in a write-off. So, automating that process and making sure we have consistent touchpoints with the customer is important. Instead of sending emails out all day, financial teams are now focused on customers that are truly at risk.

It’s unlikely you’re ever going to get that 4% to 0 write-offs per year. People file for bankruptcy and there’s nothing to be done about that. But with automation, you’ll be able to see customers that slip through the net and be able to plan ahead and save on write-offs.” 

Danny Wheeler from Blackline had this to say about how automation helps with improving the quality of data and identifying trends.

“On top of increased efficiency and cost savings, AI also allows finance teams to get access to the latest data. And that isn’t always the case in a manual process. This means there are far fewer wasted activities due to data not being up to date and people having to do unnecessary work. One example of this is if a customer makes a payment but the finance team can’t apply it against the invoice and process it for a few days while they work through the pile of payments that need to be processed.

In that time, the collections team have probably chased the customer again for payment or the account has been put on hold. Both cases result in wasted effort for the person chasing payment and a terrible experience for the customer, who may decide to take their business elsewhere as a result.

What’s more, automated systems can minimize human errors and inconsistencies in data processing, data analysis and decision-making. This improved accuracy can help mitigate credit risk and reduce financial losses. It also means that finance teams don’t waste time having to go back and re-do work. It also gives the business more confidence in the numbers they report on.”

Never overlook the ROI potential of automated cash flow forecasting. Research from Nvidia found AI creates more accurate business models for 43% of companies and increases annual revenue by 10%. With rich analytics and data being processed at speed, CEOs can make more informed investing and financing decisions, while hedging against downside risks. 

For one thing, financial automation is a part of digital transformation. According to Alexander Bant, Chief of Research at Gartner Finance, “Companies that drive the right digital investments have 2.7 times higher customer retention, 1.6. times higher customer satisfaction rates and 1.9 times higher average order value.”

Let’s take an example of digital transformation at work. You could have several people in financial management doing a manual cash flow forecast. Then you decide you want to automate the process. The software will give you a greater ROI in terms of time but that doesn’t mean you have to get rid of the people who were doing the manual work. They could be moved to working on more high-value, strategic initiatives that’ll provide even more ROI for the business in the future.

Another practical ROI example came from Nico McEwan, Business Development Manager at Quadient during our recent webinar. He talked about the benefits of changing from a manual paper system to financial automation.

“We were working with a manufacturing company. They were processing 20,000 bills of paper and needed to go electronic. Financial automation means all that data and approval history can be kept in one place. You aren’t relying on paper signatures and emails, which can be missed and cause delays in approving key decisions.”

Sarah-Jayne Martin from Quadient added “Ultimately, automation is an investment that delivers real improvements to working capital and the bottom line. By automating the credit application and assessment function, companies can gain better insight into risk and mitigate it effectively. This results in fewer delinquent accounts and better credit line management, which reduces exposure to financial risks. By leveraging automation in the credit risk and customer onboarding process, finance teams can streamline the process and improve the experience for both internal stakeholders and prospective customers. That’s a win-win.”