An Example Of An Analytical Procedure Is The Comparison Of

The comparison of financial data, whether it's across different periods, against industry benchmarks, or between actual results and budgeted figures, stands as a cornerstone of analytical procedures. These comparisons, far from being simple exercises in arithmetic, offer invaluable insights into a company's financial health, operational efficiency, and potential risks. In auditing and financial analysis, understanding and applying these comparative techniques are essential for identifying anomalies, trends, and areas requiring further investigation.

Understanding Analytical Procedures

Analytical procedures are evaluations of financial information made by a study of plausible relationships among both financial and nonfinancial data. They range from simple comparisons to complex analyses using advanced statistical techniques. The primary purpose of these procedures is to identify fluctuations or relationships that are inconsistent with other relevant information or that differ significantly from expected values.

Key Objectives of Analytical Procedures:

Enhance the auditor's understanding of the client's business and industry.
Identify areas of potential risk by highlighting unusual fluctuations or unexpected relationships in financial data.
Provide evidence supporting the financial statements by confirming management's assertions.

The Power of Comparison: A Detailed Look

The comparison of financial data is a fundamental analytical procedure that involves examining the relationships between different pieces of information to uncover patterns, trends, or anomalies. This can be done in several ways, each providing a unique perspective on the company's performance.

1. Comparison of Current Year Data with Prior Year Data

This is one of the most common and straightforward analytical procedures. By comparing current year balances or ratios with those of previous years, analysts can identify significant changes that may warrant further investigation.

Purpose: To identify trends and unusual fluctuations in financial performance over time.
Example: A sudden increase in sales revenue compared to the previous year could indicate successful marketing campaigns, increased market demand, or, potentially, aggressive revenue recognition practices. Conversely, a significant drop in gross profit margin might suggest rising costs of goods sold, pricing pressures, or inventory obsolescence.
Analysis: When performing this comparison, it's crucial to consider factors such as changes in accounting policies, economic conditions, and industry trends that may explain the fluctuations.
Limitations: This method assumes a degree of consistency in the company's operations and external environment, which may not always be the case.

2. Comparison of Actual Data with Budgets or Forecasts

Comparing actual financial results with budgeted or forecasted figures helps assess the accuracy of management's projections and identify areas where performance deviates from expectations.

Purpose: To evaluate management's ability to plan and control operations, and to identify areas of unexpected performance.
Example: If actual sales revenue falls significantly short of the budgeted amount, it could indicate overoptimistic sales forecasts, ineffective marketing strategies, or unexpected competitive pressures. On the other hand, if actual expenses exceed the budgeted amount, it could point to cost overruns, inefficient operations, or inadequate budget controls.
Analysis: When analyzing these variances, it's important to distinguish between controllable and uncontrollable factors. For example, a variance due to unexpected changes in commodity prices may be beyond management's control, while a variance due to inefficient labor utilization may be addressable through operational improvements.
Limitations: The effectiveness of this comparison depends on the reliability and accuracy of the budgets or forecasts used. If the budgets are unrealistic or based on flawed assumptions, the comparison may not provide meaningful insights.

3. Comparison with Industry Averages or Benchmarks

Comparing a company's financial ratios and performance metrics with industry averages or benchmarks provides insights into its relative performance and competitive position.

Purpose: To assess how a company performs relative to its peers and identify areas where it may be lagging or excelling.
Example: If a company's current ratio is significantly lower than the industry average, it could indicate liquidity problems or inefficient working capital management. Conversely, if its profit margin is higher than the industry average, it could suggest superior operational efficiency, effective cost control, or a strong brand reputation.
Analysis: When making these comparisons, it's essential to consider factors such as the company's size, business model, and geographic location, as these can significantly affect its performance relative to industry averages. It's also important to use reliable and comparable industry data sources.
Limitations: Industry averages are just that – averages. They may not reflect the specific circumstances of a particular company or the nuances of its business. Also, obtaining accurate and comparable industry data can be challenging.

4. Comparison of Financial Data with Non-Financial Data

This involves examining the relationships between financial and non-financial data to identify unusual patterns or inconsistencies.

Purpose: To provide a more comprehensive understanding of a company's performance by linking financial results to operational activities.
Example: Comparing sales revenue with the number of customer complaints could reveal issues with product quality or customer service. Analyzing employee turnover rates in relation to profitability could highlight potential problems with employee morale or management practices.
Analysis: This type of comparison often requires a deeper understanding of the company's operations and industry, as well as access to relevant non-financial data.
Limitations: The availability and reliability of non-financial data can vary, and the relationships between financial and non-financial data may not always be straightforward.

5. Ratio Analysis and Trend Analysis

These techniques involve calculating and analyzing financial ratios over time to identify trends and potential problems.

Purpose: To assess a company's financial health, performance, and risk profile using a variety of financial ratios.
Example: Monitoring trends in liquidity ratios (e.g., current ratio, quick ratio) can provide early warning signs of potential cash flow problems. Analyzing trends in profitability ratios (e.g., gross profit margin, net profit margin) can reveal changes in operational efficiency or competitive pressures. Examining trends in solvency ratios (e.g., debt-to-equity ratio, times interest earned) can indicate changes in a company's financial leverage and risk.
Analysis: Ratio analysis should be performed in conjunction with other analytical procedures and a thorough understanding of the company's business and industry. It's important to consider the limitations of each ratio and to interpret the results in context.
Limitations: Ratios are only as good as the data used to calculate them. They can be distorted by accounting manipulations or unusual events. Also, ratios provide a snapshot of a company's financial condition at a particular point in time, and may not reflect its long-term performance.

Steps for Performing Comparative Analytical Procedures

To effectively utilize comparative analytical procedures, follow these steps:

Determine the Suitability of the Procedure: Evaluate whether a comparative analysis is appropriate given the nature of the account, the availability of data, and the assessed risk of material misstatement.
Define the Expectation: Develop a precise expectation of what the account balance or ratio should be. This expectation can be derived from prior periods, budgets, industry data, or non-financial information.
Identify Significant Differences: Compare the recorded account balance or ratio with the expectation. Identify any significant differences that exceed a predetermined threshold.
Investigate Significant Differences: Investigate the reasons for significant differences. This might involve discussing with management, reviewing supporting documentation, or performing additional analytical procedures.
Evaluate the Results: Assess whether the explanation for the difference is reasonable and consistent with other audit evidence. If not, consider the implications for the financial statements and the audit opinion.

Illustrative Examples of Comparative Analytical Procedures

To further illustrate the application of comparative analytical procedures, consider the following examples:

Example 1: Analyzing Sales Revenue

Procedure: Compare monthly sales revenue for the current year with the corresponding months in the prior year.
Expectation: Sales revenue is expected to grow by 5% per month, based on historical trends and industry forecasts.
Finding: Sales revenue for June is 20% lower than the prior year.
Investigation: Discuss with management to understand the reason for the significant decline in sales. Possible explanations include a slowdown in economic activity, increased competition, or a product recall.
Evaluation: Evaluate the reasonableness of management's explanation and consider whether additional audit procedures are necessary to verify the accuracy of sales revenue.

Example 2: Analyzing Cost of Goods Sold

Procedure: Compare the gross profit margin for the current year with the prior year.
Expectation: The gross profit margin is expected to remain relatively stable, given consistent pricing and cost structures.
Finding: The gross profit margin has decreased from 40% in the prior year to 35% in the current year.
Investigation: Investigate the reasons for the decline in gross profit margin. Possible explanations include increased raw material costs, lower selling prices, or inventory obsolescence.
Evaluation: Assess the impact of the decline in gross profit margin on the financial statements and consider whether additional disclosures are necessary.

Example 3: Analyzing Accounts Receivable

Procedure: Compare the days sales outstanding (DSO) ratio for the current year with the prior year.
Expectation: The DSO is expected to remain relatively stable, given consistent credit policies and customer payment patterns.
Finding: The DSO has increased from 30 days in the prior year to 45 days in the current year.
Investigation: Investigate the reasons for the increase in DSO. Possible explanations include a change in credit policies, slower customer payments, or an increase in overdue accounts.
Evaluation: Assess the implications of the increase in DSO for the collectability of accounts receivable and consider whether an allowance for doubtful accounts is adequate.

Common Pitfalls to Avoid

While comparative analytical procedures are powerful tools, it's important to be aware of common pitfalls that can undermine their effectiveness:

Relying Solely on Data: Analytical procedures should not be performed in isolation. They should be integrated with other audit procedures and a thorough understanding of the client's business.
Using Unreliable Data: The accuracy and reliability of the data used in analytical procedures are critical. Ensure that the data is properly sourced and verified.
Failing to Investigate Significant Differences: It's essential to thoroughly investigate any significant differences identified during analytical procedures. Don't simply accept management's explanations without further verification.
Setting Inappropriate Expectations: The expectations used in analytical procedures should be reasonable and well-supported. Avoid using unrealistic or overly optimistic expectations.
Ignoring Qualitative Factors: Analytical procedures should consider qualitative factors that may affect financial performance, such as changes in management, regulatory changes, or economic conditions.

The Scientific Explanation

The effectiveness of comparative analytical procedures is rooted in basic statistical principles and economic theory. The underlying assumption is that financial data is generally predictable and follows certain patterns. By comparing data over time or across different entities, analysts can identify deviations from these patterns that may indicate errors, fraud, or other unusual events.

Regression Analysis: More sophisticated analytical procedures may involve regression analysis, which is a statistical technique used to model the relationship between two or more variables. This can be used to predict expected values and identify outliers.
Time Series Analysis: Time series analysis is another statistical technique used to analyze data points collected over time. This can be used to identify trends, seasonality, and cyclical patterns in financial data.
Benford's Law: Benford's Law is a mathematical principle that states that in many naturally occurring sets of numbers, the leading digit is likely to be 1 more often than any other digit. This law can be used to detect anomalies in financial data that may indicate fraud or errors.

FAQ: Comparative Analytical Procedures

Q: What is the difference between analytical procedures and substantive tests?

A: Analytical procedures are used to evaluate financial information by studying relationships among data, while substantive tests are used to verify the accuracy of individual account balances or transactions. Analytical procedures are often used to identify areas of potential risk, while substantive tests are used to obtain direct evidence about the fairness of the financial statements.

Q: When should analytical procedures be performed during an audit?

A: Analytical procedures should be performed during all phases of an audit:

Planning Phase: To understand the client's business and identify areas of potential risk.
Substantive Testing Phase: To obtain evidence supporting the financial statements.
Final Review Phase: To assess the overall reasonableness of the financial statements.

Q: What are some examples of non-financial data that can be used in analytical procedures?

A: Examples of non-financial data include:

Number of employees
Square footage of retail space
Number of website visitors
Production volume
Customer satisfaction ratings

Q: How can technology be used to enhance analytical procedures?

A: Technology can be used to automate many aspects of analytical procedures, such as data extraction, data analysis, and report generation. Data analytics software can also be used to perform more sophisticated analyses, such as regression analysis and time series analysis.

Q: Are analytical procedures required by auditing standards?

A: Yes, auditing standards require auditors to perform analytical procedures during the planning and final review phases of an audit. Analytical procedures are also encouraged during the substantive testing phase.

Conclusion

The comparison of financial data is a powerful analytical procedure that provides valuable insights into a company's financial health, operational efficiency, and potential risks. By systematically comparing data across different periods, against budgets, or with industry benchmarks, analysts can identify anomalies, trends, and areas requiring further investigation. When performed effectively and with a thorough understanding of the client's business, comparative analytical procedures can significantly enhance the quality and effectiveness of financial analysis and auditing. The key lies in not just performing the comparison, but in understanding the "why" behind the numbers, and using that understanding to drive informed decisions.