Building Your Financial Analysis - An Overview
One of the big questions I often get asked is, "What should a financial analysis look like?" To provide an overview, financial analysis involves reviewing any statements you have received and making a note of any significant changes. It's also important to include historical comparisons and industry comparisons, depending on the information available to you.
In your analysis, you should model potential solutions while discussing the assumptions made along the way. The focus should generally be on profit, but you should also consider revenue and costs and how they interact. Additionally, the measures you use should align with the organisation's maturity.
Another critical aspect is to conduct a sensitivity analysis of the forecasted numbers. This allows you to build expected scenarios, such as best-case and worst-case outcomes. A situational analysis essentially examines the existing financial statements to identify major changes and utilises ratios to compare the firm on various metrics, like profitability, solvency, cash conversion cycles, and overall value.
Breaking it down will help you understand the financial situation better. You can also start comparing historical data to industry benchmarks through ratios and other comparative calculations. Remember, there are three types of analysis:
- Horizontal analysis: Compares figures between two years.
- Trend analysis: Looks at data over three or more years.
- Vertical analysis: Examines relationships within a single year.
It's often beneficial to express statements as a percentage of sales, making it easier to identify trends in comparative analysis. Considerations in this analysis include:
- Liquidity and cash flow: Do you have enough funds to cover expenses?
- Profitability: How much profit is being generated?
- Stability: How stable are the organisation’s finances?
- Growth: Where does growth lie—profits, revenue, equity, or assets?
- Efficiency: How effectively is the organisation utilising and managing its assets?
Gaining a clear understanding of these areas and comparing them to competitors is essential.
One note to remember is about Compound Annual Growth Rate (CAGR). CAGR smooths out growth trends over time, making it particularly useful for comparisons. You can apply CAGR to various metrics beyond just profit, including investments, sales, and customer satisfaction.
When creating your model, it’s vital to estimate revenues and costs based on financial and industry benchmarks. Ensure that the scale matches the size of the organisation or event you're targeting, and that the impact is significant enough for your audience to take notice.
Finally, we’ll delve deeper into financial measures in future discussions. Initially, profitability metrics can include Return on Investment (ROI), Net Present Value (NPV), break-even analysis, and payback periods.
When considering costs, it's important to differentiate between incremental costs, one-time costs, and ongoing costs. Breaking these costs into categories will help everyone understand the financial implications as your solution progresses. Additionally, you should analyse revenue by evaluating the percentage increase or profitability, depending on the context.
To illustrate these concepts effectively, using a visual format such as a graph can be beneficial. For instance, you could create a graph that depicts profit alongside the assumptions made throughout the process, demonstrating how these align with various Environmental, Social, and Governance (ESG) measures that the concerned company values.
It's also crucial to conduct a sensitivity analysis. This involves evaluating expected, best, and worst-case scenarios to see how each might look. Presenting an optimistic projection is essential, but it's also vital to acknowledge that outcomes may vary; they could be lower or higher than expected.
When addressing risk, focus on strategies for mitigating potential issues in both the worst-case and best-case scenarios. Ensure you explain to your client how to manage the consequences of unexpected success, as achieving high performance can bring unique challenges. This is where a sensitivity analysis can be particularly advantageous.
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