What is variance analysis?

Variance analysis is a valuable tool that enables businesses to gain key insights by comparing predicted financial outcomes with actual outcomes.

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This quantitative approach can have a number of benefits, including enabling businesses to maintain control of their operations through the accurate identification of discrepancies between what was predicted and what occurred.

Identified variances can be favourable and unfavourable; for example, a favourable variance would be seen if raw materials costs were lower than predicted but an unfavourable variance would be seen if the reverse were true.

What are the benefits of conducting variance analysis?

As this Forbes article explains, adopting a data-driven mindset is essential for all businesses looking to remain competitive in today’s crowded markets.

Variance analysis can be used to:

1. Improve planning, as it can help decision-makers to establish more accurate budgets.
2. Monitor success, as it can make identifying areas for improvement easier.
3. Establish benchmarks for success.

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Even greater benefits can be seen when variance analysis is conducted on a regular basis, as this provides even more data that can be used to inform strategic and operational decisions.

How is variance analysis conducted?

It can be advantageous to work with a data analysis company, such as shepper.com/, and leverage their professional expertise; however, here is an overview of what variance analysis includes:

1. Identify key metrics

Before the analysis process can begin, it is important to identify the metrics and variables you are going to analyse, such as labour costs, sales, and materials.

2. Data collection

Next, all relevant data must be pulled from your records. There are automation tools available that can improve the accuracy of this process and ensure efficiency.

3. Variance calculation

At this point, the comparison process can begin. You will start to see which variances were favourable and which were unfavourable. Your identified metrics should be applied here to identify where improvements can be made in the future.

4. Report

Your findings should be collated into a variance analysis report, detailing why each variance occurred, its impact, and how you can learn from its occurrence moving forward.

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