For enterprises, variance is the difference between the expected cash inflows or outflows and the actual cash inflows or outflows. In other words, it is the difference between the forecasted cash position and the actual cash position of an enterprise at a given time. This variance can be expressed as a positive or negative number, indicating whether the actual cash inflows or outflows were higher or lower than expected based on the forecast.
Variance is an important metric for enterprises to track as it helps understand how accurate your cash forecasts are and whether you need to adjust your financial plans or take corrective actions. By analyzing variances in cash forecasting, enterprises can identify areas where you are overspending or underperforming and take necessary steps to improve your cash flow and financial performance.
Different types of variances can occur in cash forecasting due to various reasons such as changes in market conditions, customer behavior, operational issues, and timing issues, among other factors. These variances can impact both sales revenue and expenses. By understanding the underlying causes of these variances, companies can make necessary adjustments to their forecasting models, mitigate risks, and improve their overall financial performance.
Broadly, variances can be classified into two major categories:
Materials, labor, and variable overhead variances include price/rate variances and efficiency and quantity variances. Price/rate variances show the differences between industry standard costs and actual pricing for materials while efficiency variances and quantity variances refer to the differences between actual input values and the input amounts specified.
Overhead variances include volume variances and budget variances. Volume variances are differences between actual fixed overhead costs applied and budget fixed overhead costs. Meanwhile, budget variances indicate the differences between actual and budgeted amounts.
Budget variances can be divided into two subgroups: expense variances and revenue variances. Expense variances are all about costs and are easier to control and streamline. That’s why we tend to focus on them more during variance analysis. Revenue variances, on the other hand, are more unpredictable and harder to measure. But they’re also really important because they can help you find ways to improve business processes, increase revenue, and reduce costs. By analyzing revenue variances, you can find opportunities to make your business more efficient and valuable in the long run.
Let’s say that your enterprise sells widgets, and you’ve projected that you’ll sell $1 million worth of widgets in the next quarter. However, at the end of the quarter, you find that you’ve only sold $800,000 worth of widgets. That’s a variance of $200,000, or 20% of your original plan. By analyzing this variance, you can figure out what went wrong and take steps to improve your sales performance in the next quarter. Here, variance analysis becomes the vital tool that enables you to quickly identify such changes and adjust your strategies accordingly to manage your financial performance and optimize cash forecasting.
Variance analysis helps you identify the difference between your planned or expected financial outcomes and what actually happened. It’s like checking if you spent more or less than what you planned to spend. This helps you understand where you went over or under budget and why. It’s important because it allows you to monitor your financial performance, identify trends, and make informed decisions about future planning. By using variance analysis, you can stay on track with your financial goals and improve your bottom line over time.
During times of market uncertainty, your enterprise experiences unexpected changes in revenue, expenses, or other financial metrics. The tightening financial conditions are expected to cause the global economy to grow sluggishly, at a rate of 1.6% in 2023, as per JP Morgan’s 2023 Market Outlook. In such cases, one of the most important tools in your financial management toolkit is variance analysis.
Variance analysis basically helps you see how your organization is doing financially and take proactive actions to reduce risks and improve results. It allows enterprises to compare their forecasted cash flow with their actual cash flow, and to determine the underlying causes of variances, such as changes in market conditions, customer behavior, or operational issues. By performing variance analysis, enterprises can gain valuable insights into their cash flow performance and make informed decisions about how to respond to unexpected changes in the market.
For example, if a company identifies that its actual cash inflows are lower than expected due to a decrease in sales revenue, it can take steps to reduce costs or adjust its pricing strategy to maintain profitability. Similarly, if a company identifies that its actual cash outflows are higher than expected due to unexpected expenses, it can adjust its budget or seek alternative financing options.
The fundamental formulae for collecting the data required for variance analysis are relatively straightforward. There are two basic formulae for calculating variance: positive convention and negative convention.
Positive convention measures variance as a positive value, indicating a negative variance. In positive convention, negative figures show that actual figures are under budget, indicating a positive variance. Let’s take a look at the formula for positive convention:
Actual Spending – Budgeted Spending = Variance
Negative convention calculates negative variances as negative values and positive variances as positive values. Here’s the formula for negative convention in variance analysis:
Budgeted Spending – Actual Spending = Variance
Both conventions are acceptable, as long as they are applied consistently. However, obtaining actual figures for a variance is only the first step – contextual analysis is crucial for gaining actionable insights.
For example, if a CPG company has a budgeted purchase order of $10,000$10,0000 for packaging materials from a supplier but ends up spending $12,0000 in a quarter, they could be concerned since they are over budget by 20%.
However, the overage is only $2,0000 in a budget that might measure in the millions. This presents an opportunity for investigation (are there any inefficiencies in the packaging process? Can the enterprise negotiate a better price with the supplier, or consider alternative packaging materials?). This also poses an opportunity to adjust future budgets to optimize the enterprise’s financial performance. While it may not be a major financial emergency, it still warrants attention to ensure optimal cash flow management.
Let’s take a look at the top 4 benefits enterprises can reap by conducting variance analysis for cash forecasting:
Variance analysis helps identify discrepancies between actual cash inflows and outflows and the forecasted amounts. By comparing the forecasted cash flow with actual cash flow, it is easier to identify any discrepancies and take corrective measures.
Conducting variance analysis allows for a review of past forecasts to identify any errors or biases that may have impacted accuracy. This information can be used to refine forecasting techniques and improve future forecasts.
Understanding the reasons for variances can provide valuable insights that can help improve financial decision-making, which is critical in a volatile market. For example, if a variance is caused by unexpected expenses, management may decide to reduce expenses or explore cost-saving measures.
By analyzing variances, companies can identify areas where cash management can be improved. This can include better management of accounts receivable or accounts payable, more effective inventory management, or renegotiating payment terms with suppliers.
It can be difficult for treasurers to create low-variance cash flow forecasts for enterprises, especially with traditional variance analysis methods that typically involve spreadsheets, due to the large amount of data involved. Moreover, relying on manual variance reduction approaches can lead to a high variance and can be time-consuming, labor-intensive, and expensive, thus, delaying the much-essential decision making.
Amid turbulent market conditions, as companies prepare for the latter half of 2023 and 2024, enterprises’ finance chiefs are recommending various enhancements to improve decision-making. The most commonly mentioned improvements are the adoption of digital technologies, AI, and automation, and the enhancement of forecasting, scenario planning, and consistency in measuring key performance indicators, as per Deloitte CFO Signals Survey.
This goes to show the significance of adoption of advanced technologies, such as AI, for companies preparing for uncertain markets. Here’s how AI takes variance analysis to the next level – AI-based cash forecasting software helps in variance analysis by taking additional steps to improve the accuracy of the cash forecast by 90-95%. It compares cash forecasts to actual results to check for variances, aligning the forecast with other horizons such as monthly, quarterly, and yearly forecasts, thus, ensuring that the forecast is accurate across various scenarios. AI also analyzes the accuracy of cash forecasts through a line item analysis across multiple horizons, and makes tweaks to the algorithm through an AI-assisted review process. Finally, AI fine-tunes the forecast model and enhances the data as needed to achieve the desired level of forecast accuracy.
Artificial intelligence (AI) can help you generate low-variance cash flow forecasts. It automates data collection from past cash flows, including bank statements, accounts receivable, accounts payable, and other financial transactions and integrates with most financial systems. This data is evaluated to detect patterns and trends that can be utilized to anticipate future cash flows. Based on this historical analysis and regression analysis of complex cash flow categories such as A/R and A/P, AI selects an algorithm that can provide an accurate cash forecast.
Several leading enterprises turn to AI for variance analysis and thereby ensure accurate cash forecasting. It compares forecast, budget, and actual data to improve accuracy by identifying the key drivers.
Here are some of the key benefits you can achieve by conducting variance analysis with AI in cash forecasting:
AI can deal with large volumes of data quickly, accurately, and consistently. This can improve the accuracy of your cash forecasts and reduce the risk of errors that may occur from manual data entry or human bias. AI simplifies your cash flow analysis by deep diving into and analyzing a vast amount of data coming in from multiple sources, including historical cash flow data, market trends, and economic indicators, in real time. Thus, it provides instant insights into cash flow variances. This can provide a more comprehensive analysis of cash flow variances, allowing you to identify trends and patterns that may not be apparent through manual analysis.
With AI at its core, cash flow forecasting software can learn from industry-wide seasonal fluctuations to improve forecasting accuracy. AI-powered cash forecasting software that enables variance analysis can also create snapshots of different forecasts and variances to compare them for detailed, category-level analysis. By offering such comprehensive visibility, it helps you respond quickly to changes in cash flow, take corrective action as needed, and manage your enterprise’s liquidity better.
With real-time analysis and more comprehensive insights on cash forecasts, AI can help you make faster, more informed decisions about cash flow management. This can help organizations respond quickly to changes in cash flow and take corrective action as needed. This is particularly important during times of market uncertainty when cash flow patterns can change rapidly and unexpected events can occur.
AI can automate the reporting of cash flow variances, providing regular reports that highlight trends and patterns. By automating the reporting process, organizations can save time and resources that would otherwise be spent on manual reporting. This also ensures that reporting is consistent and accurate, eliminating the potential for human error. With regular, real-time reports on cash flow variances, you can stay on top of your enterprise’s cash flow management and identify areas for improvement to maximize your financial performance.
HighRadius’ AI-based Cash Forecasting Software is the perfect solution for enterprises looking to improve their cash forecasting process and achieve the above-mentioned benefits. Here are the cash forecasting solution’s key features that can help you reduce variances in cash forecasting and achieve accurate cash forecasts:
In a rapidly evolving business landscape, market uncertainties and disruptions can have a significant impact on an enterprise’s financial stability. That’s why having a robust cash flow forecasting system with AI at its core to conduct variance analysis is crucial.
By analyzing large volumes of historical and real-time data, AI-powered cash forecasting software can provide accurate insights into cash flow variances, enabling enterprises to respond quickly to any changes in the market and empowering finance leaders to make informed decisions. It can also learn from industry-wide seasonal fluctuations to provide more accurate cash flow forecasts.
With AI in the cash forecasting process, including variance analysis and scenario modeling, enterprises can better manage their liquidity during times of market uncertainties and prepare themselves for the future, where accurate cash flow forecasting will be critical to their success. It can be a game-changing factor to give you a competitive advantage, improve your enterprise’s financial stability, and help you make data-driven decisions that can help them thrive in the long run.
Standard costing refers to the process of establishing estimated (standard) costs for products or services based on expected levels of input costs, labor costs, overhead costs, and other factors. Variance analysis, on the other hand, is the process of comparing actual costs to standard costs to identify variances, or differences between the expected and actual costs.
The three main sources of variance in an analysis for cash forecasting are timing variance, amount variance, and category variance. Timing variance refers to differences in cash flow timing compared to the expected timing, while amount variance is the difference in the actual cash flow amount compared to the expected amount. Category variance refers to differences in the actual cash flow for a specific category compared to the expected cash flow.
P&L (profit & loss) variance analysis is the process of comparing actual financial results to expected results in order to identify differences or variances. This type of variance analysis is typically performed on a company’s income statement, which shows its revenues, expenses, and net profit or loss over a specific period of time.
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