Non-deal
Predictive analytics to understand price drivers
We used predictive analytics to understand key price drivers for a fair value review of a business.
We worked with a prominent player in the beef supply sub-sector of the agriculture industry to review the fair value of its business. Our valuations team was engaged to review the model used to determine the business’s fair value and required support in terms of assessing the validity of the underlying assumptions. Given the role that the price of its produce played in this review, it was key that an accurate forecast was obtained.
The challenge
Given that the prices of the client’s products were a key input into the forecast, we required an independent assessment of these inputs. This included an accurate forecast for beef, weaner and maize prices. Through the market research performed, there were two credible sources that provided different perspectives on the forecast prices. However, management formulated its own view of the forecast prices, which was incorporated into its fair value model.
In order to perform a robust assessment of management’s fair value, we had to generate our own opinion on the respective forecast prices. Ultimately, we needed to understand which macro-economic drivers influence these prices in order to forecast them.
The outcome
We sourced GDP, CPI, agricultural output consumption, agricultural production indexes, herd size and composition data, among other data inputs, to identify which parameters have a significant correlation with the respective price inputs.
We ran a correlation test using our data analytics capabilities to understand which parameters showed a high level of correlation to the input prices. These parameters were then used in a multiple regression analysis which was also performed using data analytics tools, the output of which was used to forecast the respective prices.
This analysis was triangulated against other forecasts produced by credible sources to validate the accuracy of management’s input. This resulted in a more robust assessment of management’s valuation.
