For businesses juggling an ever-growing list of goals and priorities, generating a financial forecast is just one of many tasks competing for your attention. In eagerness to move onto the next pressing project, the likelihood increases that you could fall into the trap of approaching your financial forecast as a box-ticking exercise.
This approach can lead to data inaccuracies and even missed growth opportunities. Without careful planning and diligence, your financial forecasting process may neglect to consider the resources needed to validate the accuracy of the data and assumptions used, or the time to create and execute a plan to translate the results into actionable insights.
We need to approach forecasting in a way that doesn't lead to planning fatigue. The good news is that it's possible to establish a well-governed process that enables firms to predict their costs, revenue streams, and cash flows for the next 12 months with greater confidence.
Here’s a list of five steps you can take to improve the efficiency and accuracy of your financial forecasting process.
It can be tempting to dive straight into the data when preparing a forecast – but if you don’t take the time to understand the needs of the business first, your forecast may not provide the insights you're looking for. From the outset, be clear on the purpose of the forecast and how it fits within the overall business strategy so that you don’t lose sight of the big picture.
To do this, you can develop a timeline and well-defined, relevant roles and responsibilities, including a review structure. Preparing a RACI (Responsible, Accountable, Consulted, Informed)matrix can help you to identify who should be involved in the different stages of the process. Once you're clear on the purpose of your forecast and who needs to be involved, then you can move onto:
This final step is crucial to identify what worked well and what didn’t work as well, so that your process can continue to create value.
There are two key groups of stakeholders to include in your RACI matrix: the business and the board.
Involving the business in the early stages will help to gain their buy-in and encourage broader ownership of the forecast, extending beyond the finance department. Be transparent about the forecasting process and clearly communicate any changes that may affect them, such as timelines or targets, to keep everyone engaged throughout the process.
The board’s review and approval of the forecast is an opportunity for a final sense check of the assumptions underpinning your data, and to ensure the business’ long-term strategy is considered.
The forecast should also show a current view of any business risks. By demonstrating to the board how these risks are being managed, you can build trust in the reliability of the forecast.
An accurate financial model will help you to create a best case forecast by testing different scenarios. Your model should be simple and use clear formatting to guide the user, clearly separating and signalling where to find the assumptions, calculations, and outputs. These principles will save you time and, importantly, reduce the risk of error.
You can use Excel to build a robust model that adheres to these principles, but if your model is particularly sizeable or complex, a separate finance or planning, budgeting, and forecasting system might be more appropriate. Regardless of the system you use, it’s essential to plan the design of your model before putting it together, with a constant focus on the overall purpose of your forecast.
For example, if you produce a model to support long-term planning, including integrated profits and losses, balance sheets and cash flow statements, the priority of your model should be flexibility. Alternatively, if you create a budget and operational plan at cost centre level, the focus would be on detail. If you produce a short-term cash flow forecast, where the emphasis is more around speed of updating.
For more tips on increasing the accuracy of your forecasting model, read Phil Gunter-Rees' article: Improving the quality of financial forecasting.
Taking the time to understand different areas of the business can make it easier to identify each area's drivers of cost and revenue, and the assumptions underpinning them. This process may also highlight interdependencies between different business areas which could be incorporated into your model.
By consulting and involving the right people at the right time across the business, you can leverage their knowledge and expertise to ensure you base your forecast on relevant, accurate insights.
Forecasting is also an opportunity to use your new information to add or update any known risks since your previous budget or planning cycle. This helps you to accommodate the board’s risk appetite and support the business’ strategy, and gives you the information needed to monitor the risks through variance analysis.
If you have an established finance business partnering team, their knowledge of the business areas they partner with can also help you to accurately identify cost and revenue drivers and update business risks.
In May's CPD technical update, quality of data was revealed as the biggest finance analytics challenge facing firms today.
Find out more about establishing governance over your forecasting process, how to design and build a great forecast model, and forecasting applications and analytics.
A forecasting software platform may provide intuitive features, such as managed access and error-flagging, which could bring more control and efficiency to your forecasting process. Combined with the ability to deal with larger volumes and sources of data than, for example, Excel, new technology could be a worthwhile investment for your business.
Embracing the power of AI can also help to enhance your forecasting capabilities, particularly in areas such as cash flow forecasting. For example, AI can help you to more accurately discern customer payment trends and as a result, predict cash inflows with greater accuracy.
However, before investing in any new technology, it's important to first carefully assess how a new system would support the business’ short- and long-term strategic objectives. The effectiveness of any technology hinges on a thorough understanding of your business drivers and assumptions, coupled with well governed and defined data. Without these foundational elements, even the most advanced automation systems and AI capabilities could yield inaccurate or even incorrect results, compromising your decision making abilities.
It's equally vital to consider how any changes in technology will be managed by your organisation, including how the technology might interact with, or replace, any existing systems or processes. Gaining buy-in from relevant teams and primary users and providing training programmes as part of a robust transformation plan can ease the transition and maximise your team’s ability to leverage the full capabilities of your technology.
There isn't a single silver bullet that can solve all your forecasting challenges in one shot. Improving your overall forecasting process and accuracy hinges on several key considerations.
Ensuring a clear, well-governed process, supported by the business and producing quality data, is crucial regardless of technology. This fosters ownership and confidence, making the forecast a trusted basis for decision making within the business.
For more insight and guidance on how you can improve your forecasting, get in touch with Gill Ellyard.
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