In dynamic markets, many companies struggle to anticipate developments and generate precise financial forecasts. As a result, companies are often forced to publish ad-hoc disclosures, revising turnover or profits downwards.
“Ad-hoc disclosures can cause dramatic losses of company and shareholder value and weaken trust in the capital markets.”
Your expert for questions
Dr. Frauke Schleer-van Gellecom
Finance Transformation – Predictive Excellence
at PwC Germany
Tel.: +49 69 9585-6740
PwC recently conducted an analysis of forecasting study in collaboration with the Justus Liebig University of Giessen. Forecasting is becoming increasingly important: the analysis showed that a DAX company with average market capitalisation (€40 billion) must expect ato losse of €158 million after issuing a profit warning. Share prices are considerably more volatile for companies forced to issue profit warnings than they are for companies which can avoid doing so.
Profit warnings also affect stock market stability; it has been proven that particular terminology in ad-hoc disclosures (e.g. “weaker than expected”) negatively affects investors’ trust in a company’s forecasting ability and its general performance.
“The cause of a deviation from the budget can be identified throughwith a clear understanding of the drivers behind it, or by using knowledge gained with using machine learning. Above all, this ultimately enables us to avoid profit warnings, which only occur because we’re looking at past data.”
Data-driven tools using artificial intelligence (AI) are a useful preventionpreventative measure for companies. AI-based analyses are more accurate than manual predictions, and they also offer an objective and efficient methodans of forecasting.
This reduces both unexpected variations and the need to publish ad-hoc disclosures, resulting in increased confidence among investors. Value is important to companies, and so they strive to gain a competitive advantage – especially in uncertain times. On average, data-driven forecasting tools offer a financial gain of between €70 million and €85 million over five years for a typical listed company in Germany.
Modern forecasting tools exploit the potential of AI and machine learning to produce more accurate forecasts. Using data-driven approaches to forecasting offers many benefits:
“Data-driven tools make an important contribution to increasing forecast quality and improving process efficiency. They enable companies to avoid profit warnings and protect value.”
We will support you in answering these questions, and we’ve also developed a predictive excellence platform based on our Forecast Engine. This tool has proved its worth in drastically increasing forecast accuracy compared to manual approaches, and in identifying relevant value drivers and early warning indicators.
Click here to read more about our predictive excellence platform based on the PwC Forecast Engine.