regression analysis is a mathematical method used to understand the relationship between a dependent variable and an independent variable. Results of this analysis demonstrate the strength of the relationship between the two variables and if the dependent variable is significantly impacted by the independent variable. When there is a discrepancy between actual sales and predicted sales, it is key to analyze what happened and why it happened. This discrepancy should be treated as an investigation. Review the data used for the regression analysis, including the input variables and their sources, to ensure accuracy. Check for any anomalies or outliers in the data that could have influenced the results. Assess the assumptions made during the regression analysis to verify their validity. External factors are another analysis that needs to happen. See if the competition improved, economic conditions shifted, or if the market needs to be attacked a different way. Internal factors also need to be taken into consideration, with new ideas as to marketing, pricing strategies, or new product launches.

In order to communicate the discrepancy to the audit manager, there has to be an honest and clear explanation of the methodology used in order to come up with the analysis. Explain how the predictions were established, either through historical data or assumptions, and reiterate that predictive analysis is subject to inside and outside factors that can change certain situations. Clearly state the observed deviation between predicted and actual sales, and express the commitment to investigate and address the issue.

When it comes to suggestions, Encourage cross-functional collaboration between sales, marketing, operations, and finance teams to gather diverse perspectives and insights for a more comprehensive analysis. Also, establish and create an atmosphere of always improving, and always finding areas where the team as a whole can improve on for large discrepancies not to happen again.