Nowadays, there is no shortage of data and information. In fact, the challenge comes when we need to collect and analyze large amounts of datasets to identify opportunities for business improvement. One way to do so is known as trend analysis. Following trends, you will be able to interpret past accounting data to predict and inform your decisions. Let’s find out how trend analysis is used in company accounting and how alternative data for trend analysis can be leveraged to improve this process.
What is trend analysis?
Trend analysis is the process of collecting and analyzing past data. It is used on quantitative or numerical data from different periods of time with the purpose of identifying patterns (or trends) that help you make future decisions. The numerical data is usually plotted on a chart and it helps you understand how the past performance could impact the future.
Why is trend analysis important in accounting?
Trend analysis is used in accounting to help you forecast the future direction of your business. It is also one of the easiest analysis methods available as you can visually represent the data. Also, trends can be expressed in percentage terms, which is less time-consuming and easier to make comparisons between different businesses.
Trend analysis is also popular because you do not need to have advanced accounting knowledge to use it. It is user-friendly and extremely flexible, so you can paint the broader picture of a given company – including its financial performance, operational performance, and efficiency. This is why trend analysis is one of the most popular ways of presenting company data.
Benefits of trend analysis
Trend analysis is a popular method among investors and business professionals. Apart from being user-friendly, it does not require advanced accounting knowledge. Analysts can use this method to compare two or more companies in a specific period, identify the industry average in a given period, and more.
In short, one of the main benefits of trend analysis is that it makes it easier for you to identify the strengths and weaknesses of a given company and compare them to another firm in the same industry. As a result, you can identify opportunities for improvement.
Next, trend analysis is employed to analyze the financial performance of a given firm over a longer period. Based on this, management can understand the evolution of a company and make decisions for the future, adjusting processes and finding opportunities to improve current operations.
Another crucial financial indicator is a firm’s liquidity. Trend analysis allows you to understand the company’s position relative to its peers. You can analyze short-term liquidity, long-term solvency, and others using financial ratios.
Finally, trend analysis identifies the profitability of a company over a given period. This can be done using a wide variety of accounting data and different financial ratios, depending on your objective. Some examples include the net profit ratio or the gross profit ratio. Revenue growth may also be a good indicator if the company is a startup or operates in a capital-intensive industry.
Use cases of trend analysis
When using accounting data, trend analysis can be employed to meet different objectives. As a business manager or owner, trend analysis of your financial statements helps you discover trends or inconsistencies and make appropriate decisions.
For example, if your expenses are in an uptrend, or they have been increasing for the past months, it may indicate an error, such as double-booking the expenses, or you may need to adjust operations and ensure that you lower your business costs. Trend analysis helps identify errors or mistakes, so it’s a great tool if you want to make sure your financial statements are correct before sharing them with the intended audience.
Additionally, investors widely use trend analysis to identify opportunities. Due to its flexible nature, trend analysis is also used with share price data, not only financial data. It can be used to analyze the entire stock market, a given industry, or even predict when the market will turn bearish or bullish. Trend analysis is a method of identifying patterns and a common component of technical analysis when used to identify financial assets, so you can move with the trend and capitalize on these changes.
Some other examples include:
- Examining revenues to identify why they decline or increase;
- Examining expenses and identify reasons for spikes or errors;
- Check whether there are unusual expenditures in a given period that might require further attention;
- Forecast financial data for decision-making processes, including revenues, expenses, and others.
How alternative data enriches trend analysis in accounting
Accounting data is considered traditional data – what investors and business professionals have always used to make informed decisions. However, the expansion of the internet has created a nascent but booming industry – the big data industry.
Using alternative data collected from social media, sensors, and web-scraping cannot replace the use of traditional data – its purpose is to enrich your current datasets and help you obtain a granular insight into your chosen business.
Alternative data can enrich your trend analysis using accounting data in several ways, depending on your objectives. For instance, if you want to understand the firm’s profitability over a period of time, you can use foot traffic data to identify increases in customer numbers. Also, you can identify how concentrated these customers are, how quickly they pay or how much they pay (by using credit card data), and how they feel about your business (by using social media data).
Summary
Accounting data has always been powerful. Yet, the adoption of alternative data when it comes to business and investment transforms everything, allowing businesses and individuals to understand all the complex forces behind the company’s performance and its future viability. Sophisticated investment managers are already using alternative data to improve the quality of their decisions, and business professionals must stay on top of their competition and satisfy their stakeholders by including various alternative data sources in the management process.
