The Christmas holidays are around the corner, again. A few days to make the final touches to the plans for the new year. The goals for next year are ambitious, now that the economy is picking up steam again. It is up to the financial department to determine which costs and investments are needed to achieve those goals. It often requires considerable consultation, coordination and calculation work to arrive at a realistic budget. A race against time to complete the budget before the turn of the year. Okay, but once we have that done, we are good for another year. Right?
Unfortunately, many organisations follow this train of thought. Whilst unexpected events occur inside and outside of the organisation, the financial reports continuously compare the original budgets to the actuals, month in and month out. Even though everyone already knows that the annual figures will be much higher or lower. As management information, the budget deviation does not provide any added value to the organisation. After all, how should you respond to this information? Therefore, budgets should be ‘reformulated’ throughout the year, based on a realistic forecast that takes the current situation into account.
A budget is an expression of your ambition. Your forecast is the realistic expectation, based on all the information at your disposal then and there. Are certain products selling faster than expected? Does the sales pipeline provide insufficient opportunities for the rest of the year? Do certain (risk) regions jump out? Are the dollar- or oil price rates showing major fluctuations? These are all examples of events that have a major influence on sales and / or expenses. It is only when you build proper forecast models that take this information into account, that you will arrive at real actionable information for the business!
A good financial forecast requires research and questions to be posed to the people who are closest to the client and the primary processes. The contracts that were concluded, the order portfolio, and the sales pipeline or trends in booking behaviour should be taken into account when forecasting. As a financial professional, you must also be able to carry out ‘sanity checks’ on the answers that you may receive. Collecting and checking the required information then becomes a cycle from which you continue to learn. This is certainly true when you compare your actuals to your forecast, and learn from that!
A realistic view
A financial forecast during the year allows you to say, with some degree of certainty, whether the budget will be made or not. By maintaining a realistic view of your business and the market, and not merely following management’s ambitions.
Sound familiar? Are you looking for tips on how to generate a good financial forecast? There are many, but I have listed the top 5 for you.
1. Follow the rhythm of your business
Forecasting implies that you frequently check and adjust your expectations. But how often should you do this? Preferably as often as possible, but not more frequently than needed! It’s best to increase the frequency in steps, whilst establishing the required processes and automation. First per quarter, and perhaps per month at a later stage. In some cases, it might even be helpful to forecast weekly, but that depends significantly on the dynamics of your organisation and the market in which you operate. Proper forecasting can be a time-consuming matter for many businesses, because of the complexity of the underlying business drivers. In that case, every forecast must be relevant. When you build large vessels or aircraft, it might not be very helpful to generate forecasts more frequently than once a month. On the other hand, an e-commerce businesses in a competitive market might actually benefit from this. The frequency at which you forecast should follow the rhythm of your business processes.
2. Follow the monetary flow
In actual practice, I often notice that a forecast is only made for the P&L statement. Of course, that does deliver highly relevant and usable information, but it would be great if the forecast was also converted to a properly substantiated cash flow forecast. This would give you a detailed visualisation of the cash development over the upcoming periods. This provides many businesses with very important and usable information that can be grounds for immediate action. For example, whether one should lend more, or can pay off debt sooner. Or whether more attention should be paid to receivables management, to avoid possible cash flow problems.
3. Don’t keep it (too) simple
Forecasting does not mean that you simply carry the trends through in your actuals! A good forecast requires you to dig into the underlying business drivers like products, services, clients and distribution channels. How are the various products selling? What developments are taking place with clients, and how can we influence them? What effect does the marketing campaigns have? It all starts by forecasting these business drivers. The outcomes then lead to the financial results in the P&L statement, balance sheet and cash flow statement.
Building a forecast means learning and experimenting. If you don’t analyse it, you cannot know whether it has an influence! The forecast process therefore encompasses the entire organisation. The better the people in your organisation are at conveying their insights, the more reliable the forecasts. The financial professional must therefore challenge the business to generate substantiated, feasible forecasts.
4. More detail is not always better
Digging into the business drivers does not imply that you should include every detail in your forecasts. Details that you can’t really influence, don’t necessarily have to be included in your forecast. Also, make sure that you don’t spend your time focusing on ‘guise details’. Details that often make the process significantly more complex, but don’t really make the forecast more precise. For example, like forecasting personnel expenses. You can do it based on all costs, at an individual employee level, and for all specific rules on pension and holiday pay. However, actual practice shows that a forecast based on the salary expenses and other personnel expenses, per department and / or position, is accurate enough. It works much faster and is also simpler in terms of privacy and security. A forecast that increases the accuracy by only a few percent, does not weigh up to that. A detailed forecast like that also ensures a complicated process, making it difficult to increase the frequency with which forecasts are generated.
5. Think in terms of scenarios
A good forecast shows different versions of the future. We cannot see into the future, so we must take several scenarios into account. What if the oil price spikes? What if the dollar’s value fluctuates? What will happen if the large assignment falls through? For example, you can generate three versions of a forecast, where you compare the most realistic scenario to a worst case- and best case scenario. This will be the margin if the dollar lives up to our expectations, but this will be the result if it exceeds our expectations by 5%. Another way is to work with levels of assurance. What are you 100% sure about? What are you only 85% sure about? Sometimes it might even be wise to generate what-if scenarios for specific events, so your organisation can focus on the (influenceable) events with the greatest impact. This will render your organisation much more action-oriented.
Proper forecasting requires an efficiently structured process and the utilisation of smart software for the collection, integration, verification and analysis of data. Without these prerequisites, you’ll soon notice that you spend 80% of your time collecting instead of analysing information. In that case, generating just one forecast per year will already be a substantial job. Keep in mind that the answers provided via your forecast can lead directly to follow-up questions, so fitting action can be taken. In other words, as an organisation you must also be able to perform ad-hoc analyses on all the underlying data.
The rapid developments in the field of artificial intelligence, machine learning and predictive analytics are very interesting for financial professionals. Technology that helps us retrieve smart predictions from immense volumes of data, will be within reach of all users. There are already various situations (like in the medical world) where machines that learn based on historical information can make better predictions than people. As financial professionals, we can also benefit from this! Intelligent software that helps us generate complicated what-if scenarios. Moreover, this requires significantly less time from the people in the organisation.
The transition from man to machine still requires a substantial culture change in financial departments!