How do you resolve discrepancies in your variance analysis?

1 Check your data quality

The first step to resolve discrepancies in your variance analysis is to check the quality and accuracy of your data. Data quality issues can arise from various factors, such as human errors, system errors, missing data, outdated data, or inconsistent data. To avoid these issues, you should ensure that your data is collected, validated, and stored in a consistent and standardized manner, using reliable and secure tools and methods. You should also perform regular data audits and reconciliations to verify and correct any errors or inconsistencies in your data.

2 Analyze your variance drivers

The next step to resolve discrepancies in your variance analysis is to analyze the drivers or causes of your variance. Variance drivers can be classified into two types: controllable and uncontrollable. Controllable drivers are those that you can influence or manage, such as operational efficiency, pricing strategy, or marketing campaigns. Uncontrollable drivers are those that you cannot control or predict, such as market conditions, customer behavior, or external events. To analyze your variance drivers, you should use various methods and tools, such as ratio analysis, trend analysis, or variance decomposition, to break down your variance into its components and identify the factors that contributed to it.

3 Adjust your budget or forecast

The third step to resolve discrepancies in your variance analysis is to adjust your budget or forecast accordingly. Depending on the nature and magnitude of your variance, you may need to revise your budget or forecast to reflect the changes in your assumptions, expectations, or performance. For example, if your variance is due to a temporary or seasonal factor, such as a holiday or a weather event, you may not need to adjust your budget or forecast significantly. However, if your variance is due to a permanent or structural factor, such as a new competitor or a regulatory change, you may need to adjust your budget or forecast substantially. To adjust your budget or forecast, you should use realistic and reliable data, assumptions, and scenarios, and communicate your changes and reasons to your stakeholders.

4 Implement corrective actions

The fourth step to resolve discrepancies in your variance analysis is to implement corrective actions to address the issues or opportunities that your variance revealed. Corrective actions can be preventive or corrective. Preventive actions are those that aim to prevent or reduce the occurrence of negative variance in the future, such as improving your processes, controls, or systems. Corrective actions are those that aim to correct or improve the current situation of negative variance, such as increasing your sales, reducing your costs, or enhancing your customer service. To implement corrective actions, you should set clear and measurable goals, assign responsibilities and resources, and monitor and evaluate your progress and results.

5 Report your variance and actions

The final step to resolve discrepancies in your variance analysis is to report your variance and actions to your stakeholders. Reporting your variance and actions is important to provide transparency, accountability, and feedback to your stakeholders, such as your management, investors, or customers. Reporting your variance and actions can also help you gain insights, learnings, and recommendations for your future budgeting and forecasting activities. To report your variance and actions, you should use clear and concise formats, such as dashboards, charts, or tables, and highlight the key findings, explanations, and implications of your variance and actions.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?