Seeing the Future More Clearly: How Machine Learning Can Transform the Financial Forecasting Process
The Challenge and Opportunity
Forecasting is a key opportunity for finance to add a significant amount of value and provide strategic insight to an organization. One of the areas in which chief financial officers (CFOs) aspire to help their organizations excel is in providing forward-looking, insightful information about future revenues, expenses and cash flow to help decision-makers chart a profitable course for the company.
Developing financial forecasts that are accurate (even if never perfect) is a difficult task for a CFO’s team, and a significant forecast error has far-reaching implications for financial performance management. It is not surprising, therefore, that many CFOs and senior finance executives express frustration with traditional forecasting processes within their organizations. These processes typically suffer from the following shortcomings:
- Manual processes driven by spreadsheets that require a significant amount of time and resources to both produce and update forecasts
- Ineffective forecast models that roll forward current results multiplied by arbitrary growth factors, rather than using business drivers and data
- Models that limit the ability to do insightful scenario analysis
- Reliance on limited data sources
- Lack of integration with sales and operations forecasting
- Human and organizational bias
These challenges and inefficiencies result in an inordinate amount of time taken to develop and update forecasts, and they can lead to significant forecasting errors. More importantly, this impacts decision-makers, who have to make critical business decisions relying on information that is not sufficiently insightful, accurate or timely.
In a business environment marked by rapid change, economic uncertainty and technological disruption, maintaining the status quo with regard to forecasting is not a viable option. For finance executives seeking to improve their forecasting accuracy and processes, machine learning (ML) presents a unique opportunity to fundamentally transform financial forecasting. Machine learning technology, if implemented well, can, first and foremost, significantly improve the accuracy of forecasts, as we discuss further in this paper. In addition, these tools can be leveraged to automate forecasting models and perform computations on large data sets at high speeds. By automating the labor-intensive components of forecasting and improving predictions, analysts can focus on delivering higher value to decision-makers.
“The incredible volume of data that is managed within any organization on any given day can be overwhelming, making obsolete the traditional methods used to extract value from that data. Machine learning allows analysts to detect, identify, categorize and predict trends and outcomes, resulting in an organization that is able to effectively compete in a big data world. The potential for change that machine learning brings can fundamentally transform key business processes such as financial forecasting.”
Machine learning will transform finance, making finance operations more effective and driving transformation that will allow employees to focus on value-adding activities such as enhancing their capabilities in customer experience and delivering better results to their internal and external customers.
Protiviti research shows that the role of CFOs and finance executives continues to evolve as they are increasingly asked to be strategic partners to the business. Providing insightful, timely and action-oriented forecasting information is essential to meeting these demands. Machine learning promises to be a game changer for any finance leader looking to take forecasting to the next level.
Machine learning and artificial intelligence is an exploding area of development and the hottest technology “trend,” according to Forbes1 and others. Any finance executive seeking to transform the forecasting process should consider leveraging machine learning as a key part of producing financial forecasts: predicting future results. Financial forecasting is perhaps the one area where Finance can help drive the most value within an organisation and have direct impacts on revenue, profitability and shareholder value. Improving the ability to produce more accurate forecasts more quickly can help Finance partner with the business to exploit opportunities to improve top-line revenue growth, course-correct overspending and improve cash flow, among many other things. The machine learning solution can aid the finance function and the business in seeing the future more clearly by helping to reduce forecasting error. While no forecast is as good as hindsight, the margin of error can be narrowed significantly, and any forecaster should not forego the opportunity.