Financial analysis is an important tool that gives an overview of an organization’s financial wellbeing and helps inform strategic decisions. It helps financial advisors review company performance, sustainability, and growth by using foundational tools like income statements, balance sheets, and cash flow statements to do various calculations.
In today’s data-driven world, financial advisors are expected to make compelling, fact-based suggestions supported by analytics. The surge of technology and data available to businesses makes the role of financial advisor indispensable to the organization. After all, someone needs to be trusted to make heads or tails of sales, supply, demand, overhead costs, and other variables. Financial analysis is at the core of this work, enabling financial advisors to support decision makers and promote healthier business practices overall.
Financial analysis is the process of evaluating a company’s key financial statements to help make business projections or review historical performance. Financial analysis can be used internally to review a company’s performance or externally for investors evaluating an opportunity.
Financial analysis typically involves examination of three main documents:
Calculations are often done in a tool such as Causal. It’s faster and travels better than an abacus. Financial analysis is useful because it can not only be used to make projections and guide future decisions, but can also be used to compare a company’s prior performance, track growth, and compare against competitors.
Conducting a financial analysis requires working across teams to collect data, set goals, and execute calculations. The analysis is carried out internally by the finance department and shared with executives to help them make better business decisions. Financial analysis may also be used to assess the worthiness of projects or investments with ratios such as net present value (NPV) and internal rate of return (IRR).
There are many types of financial analysis (which can be used in combination) to paint a full picture of an organization’s finances. They include:
Often used for competitive analysis to see how your financial status compares, vertical analysis shows a snapshot of one period in time. With this method, you divide elements of the income statement by revenue to calculate a percentage.
Here you capture the company’s ability to generate cash and how it’s spent over time.
The ability to generate revenue from assets shows leaders where they may be able to get more output from machinery, staff, and other resources.
Analyzing growth over a period of time, such as year-over-year growth, helps businesses scale and invest without overextending.
Comparing multiple years of financial data to calculate a growth rate, the intent of this calculation is to see how the business itself has changed at a macro level over time. Any spikes or dips can lead to trends and causality that can be further examined to reduce risk or capitalize on opportunities.
With leverage, you’re comparing financial metrics to equity. A debt-to-equity ratio is one example.
Analyzing the balance sheet, liquidity represents a company’s ability to pay short-term invoices and expenses. The main goal here is to ensure that your business maintains an appropriate level of cash. It’s a good measure of a company leveraging its assets effectively while paying it bills on time.
Assessing how a company generates profits with metrics like gross margin and EBITDA. This analysis may also be used to assure investors of good financial standing.
Assessing risk-adjusted rate of return, such as dividend yield, capital gain, etc.
Here you’re analyzing the value of a business. There are many methods to do this, and it’s up to the analyst to determine which works best.
These are just a few of the most common financial analysis models, but there are many others available to help you understand the numbers behind the business. Every business is unique and has different priorities when it comes to analyzing finances. Financial advisors should approach analysis with key performance indicators (KPIs) and business needs in mind.
It’s an understatement to say that financial analysis is important. Staying ahead of the numbers is what keeps the doors open and enables strategic growth. It’s critical to keep your analysis current. Things change too fast and radically to rest on old statistics and models. Here are best practices you can incorporate into your financial analysis to produce the best data possible.
It’s easy to make mistakes when working with large amounts of financial information. Being organized with calculations and having multiple people double check your work prevents mistakes. Putting calculations on auto-pilot and trusting them blindly is a fast-track to bad outcomes. It’s also crucial to think logically about the outcome of calculations and consider how they compare to previous results. If a calculation seems off, run it again.
Keep in mind that your analysis is only as reliable as your data. Before running any calculations, scan for any numbers that seem off compared to other financial statements and previous quarters. Large spikes or dips could be cause for concern. Ensure that everyone in the organization understands how important accurate data keeping is to running a functional business and encourage them to do their part.
Seasonality or cash management practices could play part in which financial analysis strategies are important to your company. For example, many retailers see large sales spikes around holidays. This may affect historical trends, cash flow analysis, and much more.
The data is never as straightforward as it seems, so know how your business operates to “play the curve.” For example, some companies carry large accounts receivable balances because they extend credit to customers. With this in mind, you should track metrics like average collection period to gain a better understanding of expected income.
It’s often helpful to visualize data with tables, charts, and graphs – which we at Causal happen to have by the truckload. Using the right data platform helps you catch mistakes thanks to easy-to-read dashboards and spreadsheets. It also makes it easier to explain the results of your analysis to executives and stakeholders.