There are a variety of ways by which you can assess your business’ overall financial health and success. By utilising data analytics and performing variance analysis, you may become aware of business practices or decisions that need to be amended. But, many times, most businesses have a hard time conducting variance analysis because data is in many places, running analytics hasn’t yet been optimised to glean useful insights, and manipulating the data takes too much time.
We’ll outline what variance analysis means, the ways in which you can carry it out smarter so it is more useful and how automation tools can help perform the work for you so that you can use variance analysis to a greater advantage.
Variance analysis is a method of assessing the difference between estimated budgets and actual numbers. It’s a quantitative method that helps to maintain better control over a business. When using variance analysis, one best practice is to review variances on a trend line so that you can readily pinpoint any dramatic shifts. Once you find anything that is suspect, variance analysis can help you to investigate the reason behind the big difference in what’s planned and what happened financially.
During a reporting period, you can sum all variances to see if your business is over or under-performing. When you notice a significant shift in the variance trend line, then you can become aware of dysfunction and work to resolve it. But, where do you begin and how can you pinpoint what’s causing the variance? This is where automation can help to assess the data points and highlight the issues.
The variance analysis that you choose to focus on will depend on the type of business you operate. The reason for variances also are dependent on certain factors, like:
Variance analysis provides organisations with a lot of benefits, including:
Variance analysis becomes an integral part of an organisation’s information system. Not only does it help to regulate control across departments, but it also provides a running tab of what can be realistically expected versus what occurs.
Variance analysis is used to assess the price and quantity of materials, labour and overhead costs. These numbers are reported to management. While it’s not necessary to focus on every variance, it becomes a signalling mechanism when a variance is salient. In this way, management can rely on variance analysis to help to improve the company’s overall performance or process improvement protocol.
More importantly, variance analysis plays a significant role in decision-making and how managers approach tasks and projects. When performed correctly and consistently, it can help to keep teams on the right path to achieve long-term business goals. However, many businesses fail to reap the benefits of variance analysis because it has to be performed consistently and promptly to work.
To accurately forecast future revenue or costs, it is necessary to have organised data from history. This calls for automation solutions such as SolveXia that can store all data in a centralised location and can automatically be pulled, manipulated and transformed into insights for decision-making. When your financial team is being pulled in so many directions and spends time on low-value time-consuming data entry and repetitive tasks, then variance analysis can easily fall by the wayside. A data automation tool can maximise your team’s productivity by pulling data from various sources, providing real-time analytics and reports to key stakeholders.
Let’s take a look at how this works in a real-world scenario with a sample of variance analysis.
A business uses variance analysis to find there is a $50,000 variance in one of its cost centres.
To determine how and why this happened, it requires further variance analysis to understand if the difference came from price changes or a difference in the quantity of materials being used. Maybe it is a growing trend or a one-off event. It could also be erroneous data entry. Either way, if the company aims to keep costs low and operate at its maximum efficiency, then it’s necessary to have these results immediately to help manage future operations.
For accurate variance analysis, data must be correct to reflect what happened. With automation, you will be able to quickly link up all your data systems and compare historical data with current data without human interference and the system will highlight what has since changed allowing the business to find the source of the issue fast and understand quickly if it is a cause for concern, or if there is a risk or opportunity in the business.
With these variance analysis examples in mind, there are some key terms to remember when performing your own analysis and to better understand its purpose. Take a look:
Here’s a look at the most common types of variance that occur within organisations:
This is the difference between what you expected to use and what you used, multiplied by the cost of the materials. You can calculate this with this formula: (the actual unit used - standard unit usage) x standard cost per unit.
This helps companies determine if they are using more materials than they actually need to be. With this variance known, companies can adjust their purchase orders from suppliers and reduce waste.
This is a measure of how well you utilise labour relative to what you expect to need. The variance is calculated by (actual hours - standard hours) x standard rate.
With this number in mind, companies can assess how efficiently their labour is being used and if the pricing is a good fit for the business’ needs.
The difference between the actual fixed overhead expense and the budgeted overhead expense. Since this is supposed to be a fixed amount, it shouldn’t vary so much from the budget.
If the variance is high between the budget and the actuals, it signals room for improvement in which the company can revisit its budget plans. It’s useful to more accurate budget allocation to see if more money can go to different places for the business to function more effectively.
Take the actual price paid for raw materials and subtract the standard cost times the number of units used.
Same as above, but with labour instead of products. Take the actual price paid for a direct job, subtract the standard cost and multiply by the number of units used (wages).
Subtract the standard variable overhead cost per unit from the actual cost incurred. Then, multiply the remainder by the total unit quantity of output.
This is the difference between how many hours were worked versus what was budgeted for the work. It is calculated by standard overhead rate x (actual hours - standard hours).
Not every organisation will focus on the same variance calculations. Depending on your service line and business goals, you will choose what variance analysis makes the most sense to track to ensure you are maximising efficiency and minimising costs.
From all we know, there is a lot in favour of using variance analysis to help control business and manage finances well. However, there are challenges to variance analysis.
Variance analysis is based on numbers and data. When you have data spread out across spreadsheets and in different records within an organisation, then compiling and assessing data becomes tricky and timely. One of the challenges with variance analysis from the get-go is the timeliness of reporting, so this is where automation tools can come in to maximise efficiency.
Automation tools such as SolveXia help to benefit variance analysis by providing:
Managing a business comes down to measuring inputs and outputs. By keeping track of budgets and actuals, you can utilise variance analysis to flag any significant fluctuations from what was otherwise expected.
You can leverage automated software solutions like SolveXia to help store and manage data and information. These tools also help businesses thrive by maximising productivity and lowering costs. Automation solutions can quickly collect, transform and process mass amounts of data in seconds, relieving your team of having to perform time-consuming data entry and manual manipulation. With all data stored and centralised, you can standardise processes and automate workflows to reduce errors and adhere to compliance. There’s a lot you can accomplish when you include automation solutions into your day-to-day workflows. Stakeholders, customers and employees all reap the benefits of automation solutions.
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