A guide to cash forecasting automation - Why it's worth automating

Regardless of the challenges, more complex cash forecasting setups can only be managed to a certain extent without automation until they become unmanageable. Usually, the breaking point is reached when your organization expands, and operations are fractured with data scattered in various financial systems, ERPs, and banks and spread among several entities. That’s usually also the moment when companies realize they need to explore the options for cash forecasting automation.

In this article, we cover some of the following topics related to cash flow forecasting automation: 

1. What is meant by cash forecasting automation?
2. Why do companies automate their cash flow forecasting?
3. The benefits of automating forecasts
4. Factors you need to consider before starting to automate forecasting
5. Different ways to automate your cash flow forecasting
6. Selecting the right solutions to start automation
   

What is meant by cash forecasting automation? 

Cash flow forecasting is unique in every organization due to different organizational structures, differing systems, or varying operational contexts, for example. Yet, typically, every organization wants to achieve the same goal: to develop reliable cash flow predictions over a specific period of time as efficiently and accurately as possible.

Cash flow forecasting automation refers to automating forecasting practices or processes to increase efficiency, improve accuracy, and lessen manual work.

How you approach automation depends on the organization’s context, such as how forecasting is currently done, existing processes, which people or entities need to get involved in the process, which systems are used, and what data needs to be included and where it's located. Once you have this figured out, you can start planning where automation could help out and what the requirements for an automation project would be.

Why do companies automate their cash flow forecasting? 

As organizations become increasingly digitalized, it’s been a trend to move away from manual processes. As such, treasury teams are also setting up their technology stacks to enable automation and improve the forecasting process. Especially so because in most enterprises, treasury plays a crucial strategic advisory role, and forecasting is a key element that weighs heavily in company-wide decision-making.

When speaking to many of our clients that have started automation projects, they tend to name the following points as to why they were convinced to automate cash forecasting processes: 

1. Minimize errors and improve accuracy 

To develop accurate cash flow forecasts, you must consolidate cash flow data from various sources, such as accounting systems, banks, and ERP systems. Without automation, this is usually done manually in spreadsheets. However, accessing each data source, collecting the information from various entities from all over the globe, and manually inputting all required data into spreadsheets is work that is very prone to errors, certainly so when several people work on it in various spreadsheets that each have interdependent formulas that can easily break.

To tackle this, automation can help with automatic data collection functionalities through system and bank integrations that enable direct data extraction from each relevant source system into a single system. This way, you can avoid the errors that are associated with working in disconnected spreadsheets.

2. Standardize processes 

In many of our client projects, a key objective is to establish uniform procedures across the entire organization. It is common for a company with multiple units to employ distinct forecasting techniques, especially when dealing with local banks and other financial systems. Furthermore, each unit typically has to manually enter or submit their forecasting figures to the group within set intervals, making it difficult for group-level teams to spontaneously access cash flow updates for each entity.

To streamline processes, it's helpful to have an automated and centralized forecasting system in place. A system can integrate with other systems and provide access to all necessary data for analysis from a single location. Additionally, if needed, this system can display relevant information to each entity in a decentralized manner.

3. Reduce manual work

Another main reason for companies to automate forecasting is that it reduces the manual work required by finance and treasury teams. For example, accessing various bank accounts, ERP systems, and accounting data and combining them to generate forecasts is very time-consuming and mundane. Instead, you can spend the time saved through automation on analyzing forecasts and business implications or other important tasks.

4. Gain instant access 

Cash flow forecasting is often performed at regular intervals. Yet, sometimes, finance or treasury teams may also need to provide unforeseen forecasts. There are many reasons for ad-hoc forecasts, but the main issue with manual forecasting is that it’s often not quick or agile enough to respond to such sudden requests that are out of the ordinary patterns. On the other hand, you can develop forecasts in minutes with the help of automation, depending on your system. That way, you don’t need to worry about last-minute forecasting requests. 

5. Support better decision-making 

Automating processes can enhance the precision of predictions, particularly when leveraging solutions such as predictive analytics. This tool utilizes historical data, trends, and various statistical models to improve forecasting accuracy over the long term. By having access to the most accurate insights, the treasury team can assist the leadership team or board in making optimized investment decisions with minimal risk.

The benefits of automating cash flow forecasts

It’s clear that there are many good reasons why you should invest in automation. But what are the main benefits that automation brings to the table? In brief, these are some of the main advantages of automation that many of our clients have experienced:

1. Increased accuracy of forecasts and less room for error due to automatically combining actual cash flows, other real-time data, and historical patterns using integrations.

2. Improved efficiency of operations by reducing the need for manual data collection and entry.

3. Real-time insights into how cash flows will affect future cash positions.

4. Automated forecasts are quicker to develop and enhance the readiness for tackling compliance with different regulators, stakeholders, or investors.

5. Automated forecasts enable faster strategic decision-making due to the quick availability of forecasts and improved accuracy.

6. Automation can provide complete transparency over group-wide cash flows.

7. It enables better funding strategies or cash pooling practices because you can quickly identify cash excess or shortages.

8. Due to automation, cash flow forecasting can be performed more frequently because it takes much less time. This boosts the speed with which companies can analyze their risk profile or make decisions on a day-to-day basis.

What do you need to consider before you start automating cash flow forecasts? 

Automating your cash flow forecasting processes does require some initial preparation. For an automation project to be successful and delivered on time, you must consider a few crucial elements: integrations must be set up, data flows between systems require proper mapping and possible file conversions, and you need to identify the suitable data that needs to be included in forecasts. It will become much easier to kick off automation work once you have done the research and have a better picture of what needs to be prepared.

 
Data required for automation 

To start the project, identify the cash flow data you should include in your forecasts and where the information is located. Usually, actual cash flow data can be derived from various places, such as bank accounts, spreadsheets, treasury management systems, accounting systems, budgeting or planning systems, or ERP systems.

It’s also good to differentiate between two data types when considering the automation of forecasts. First, there is forecasting data, such as receivables and payables, longer-term data related to planning and budgeting (forecasted revenue, currency exposure, recurring bank fees, interest, e.g.), and financing or intercompany cash flow data. Then, there is the actual cash flow data that can be retrieved from bank accounts or ERP systems directly. If you want to produce accurate forecasts, you must combine both the actual and forecasted data.

Connectivity options

Once you have identified where the data is located, it’s time to plan the integrations by involving your IT department if you haven’t done so already. As dealing with many system integrations and setting up bank connections can be a heavy burden for IT, you may want to look for a cash flow forecasting solution from a provider with experience in setting up integrations and bank connections.

Banks can typically be connected to forecasting systems through host-to-host connections, APIs, direct local connections, or the SWIFT network. ERP systems and other systems can often be connected through APIs or similar. Once you start examining tools, make sure they support your connectivity requirements. 

Different forecasting types 

You can run many distinct types of forecasting models and statistical forecasting analyses. What is good to consider is that different models require different data. For example, direct forecasts tend to be based on ERP systems and bank accounts, whereas indirect forecasts cover AR and AP to analyze liquidity positions.

Varying time horizons typically also include different elements: a short-term forecast is more based on actual data at hand, whereas longer-term forecasts can also include forecasted revenue or market trends, for example.

There are also various statistical models that you can use to run cash flow forecasts based on the data you have at hand. Examples are TBATS, Support Vector Machine, Linear Regression, Prophet, Bayesian Structural Time Series, Feedforward Neural Networks, XGBoost, and Robust Linear Regression. Each model will provide different results and some models may fit your organization better than others.

You should think of the forecasting models, time horizons, and statistical models that are right for your company as well as the required data for each of them. Good forecasting solutions can perform all these forecasting models and analyses automatically. At Nomentia, we also have dedicated consultants who will continuously help you find and develop the most suitable ways of forecasting.

Historical patterns or seasonality 

The level of detail you can achieve with a forecast differs among the various solutions on the market. But, in the end, you want to be best prepared for any scenario, so it’s good not to overlook anything.

If your business has reasonably predictable cash flow patterns over the years, looking for solutions that include cash flow data from the previous years in your cash predictions can pay off. Even if this means that you need to collect this data and put it in a suitable format, it has proven to be of tremendous value for many of our customers, resulting in increased reliability of forecasting outcomes.

Many businesses also have fluctuating cash flow patterns based on seasonality or industry indices. To some extent, these trends are still relatively predictable and can be forecasted too. There are automation solutions that can include seasonality patterns or indices and their impact on cash flows. For example, Nomentia can simulate how industry indices affect future cash flows through third-party data or analyze how different seasons impact your company’s cash flows.

Three ways to automate cash flow forecasts

There are various ways to automate forecasting, some of which require more technical expertise than others. The level of automation you can achieve depends on your chosen approach. Some methods may only automate certain stages of the process, while others can fully automate it. Ultimately, it's important to assess your resources and determine what's both practical and technically feasible. Finance and treasury professionals typically rely on the following key approaches to automate their forecasting tasks:

Partial automation through tools 

You can often partially automate forecasting processes or analysis possibilities by introducing new tools to your current processes. For example, tools can enhance visualization and analyses, automate submission management, or automate internal communication to a larger extent.

Starting with tools can be beneficial, but for more complex setups, a SaaS solution may be necessary. It's important to keep in mind that tools may have restricted connectivity options, particularly with banks. It's crucial to assess your requirements to determine if tools are adequate or if a comprehensive software is necessary.

Automation through workflows 

You can also automate administrative and mundane tasks through workflows. Either you have an in-house team that is technically capable of developing such customized workflows, or you can use one of the specialized vendors offering treasury workflow automation.

A simple workflow example could be setting up triggers to distribute emails to all contributors of a cash flow forecast with information regarding submission deadlines. Other areas where you can utilize workflows are generating automatic reports based on templates or circulating the forecasting reports to the main stakeholders on a regular basis. 

Leverage cloud-based software-as-a-service 

If you are looking to automate forecasting in its entirety, we recommend looking at cloud-based software as a service. You can only automate forecasting processes to a certain extent with tools or workflows while specialized solutions can completely automate and centralize forecasting processes.

With a comprehensive forecasting software, you can easily connect all your systems, banks, and ERPs to get a complete overview of cash across your entire organization, including different entities and bank accounts. Additionally, user management becomes simpler, as you can centrally manage user permissions with the software.

Once the software is connected to all your required source systems and banks, you can generate cash flow forecasts within minutes, allowing you to be more agile in responding to forecasting requests from various stakeholders and speeding up decision-making processes. The time saved can then be utilized for other tasks or analyzing the results of the forecasts and their business implications.

Selecting the right solutions to automate your cash flow forecasting processes 

We've written an article highlighting the top vendors and solutions for cash flow forecasting. When choosing an automated cash flow forecasting solution, it's crucial to assess its integration capabilities with your existing banks and systems, functionalities, user-friendliness, and customer service and implementation assistance offered by the vendor. For instance, vendors such as Nomentia may offer customization flexibility and involve you in the product roadmap planning to ensure it meets your future requirements as well.

Automating time-consuming processes can always benefit a business. The level of automation necessary for forecasting largely depends on the complexity of your current operations. If you work with multiple systems and banks, a SaaS solution may be the most appropriate choice. However, smaller organizations with only one bank and a limited number of systems may find a simpler tool to be sufficient. We would be more than happy to discuss the potential benefits of cash flow forecasting automation for your finance or treasury team.