Identifying trends in financial data is a crucial skill for corporate finance professionals, especially when it comes to deal execution performance metrics. Trends can reveal patterns, opportunities, risks, and insights that can inform strategic decisions and actions. But how do you spot and analyze trends in financial data? Here are some tips and techniques to help you.
The first step is to select the data sources that are most relevant to your deal objectives, industry, and market. For example, if you are evaluating a potential acquisition, you might want to look at the target company's financial statements, industry reports, competitor analysis, and customer feedback. You should also consider the quality, reliability, and timeliness of the data sources, and avoid using outdated or inaccurate information.
The next step is to use the tools and methods that best suit your data and your goals. Depending on the type, size, and complexity of the data, you might use different software, techniques, and models to process, visualize, and interpret it. For example, you might use Excel, Power BI, or Tableau to create charts, graphs, dashboards, and reports. You might also use statistical methods, such as regression, correlation, or trend analysis, to identify relationships, patterns, and outliers in the data.
Depending on the size of your data, especially in a small and midsize company, I've always found Excel to be the best tool for data analysis due to its almost limitless functions and ability to manipulate quickly. These days combining Excel with ChatGPT and other LLM's to produce VBA Coding and Excel formulas, the power of Excel is unlocked even further.
The third step is to look for changes and patterns in the data that indicate trends. Changes can be positive or negative, gradual or sudden, consistent or erratic, and can reflect various factors, such as growth, decline, seasonality, volatility, or anomalies. Patterns can be linear or nonlinear, cyclical or random, and can show how the data behaves over time, across segments, or in relation to other variables. For example, you might look for trends in revenue, profitability, market share, customer satisfaction, or operational efficiency.
The fourth step is to compare and contrast the data to gain more insights and perspectives. You can compare the data to different benchmarks, such as historical data, industry averages, competitor performance, or projections. You can also contrast the data to different scenarios, such as best-case, worst-case, or alternative outcomes. For example, you might compare and contrast the target company's financial performance to its peers, or to your own expectations and assumptions.
In my experience comparing data to different benchmarks requires deep understanding of both datasets. An individual should know if either set includes outliers that should be first stripped out to provide for a more apples to apples comparison.
The final step is to explain and communicate the trends you have identified and what they mean for your deal execution. You should be able to summarize the main findings, highlight the key implications, and provide recommendations or action steps. You should also be able to communicate the trends clearly, concisely, and convincingly, using visual aids, narratives, and evidence. For example, you might use a slide deck, a memo, or a presentation to share your analysis and insights with your stakeholders.
By following these steps, you can identify trends in financial data and use them to enhance your deal execution performance metrics. Trends can help you understand the past, present, and future of your deal, and enable you to make smarter and faster decisions.