Even though time elapses and the past remains unchangeable, you can still work on the future. And for businesses, this is where data analytics comes to play.
Data analytics involves taking a set of raw data and examining it for beneficial conclusions. Data is everything that involves historical records, researches, insights into the industry, etc. Information is scattered. On the other hand, data is an organized and structured form of info. Over the years, experts have realized the significant benefits of utilizing data to forecast trends and future happenings.
How Does Accountancy Involve Data Analytics?
The modern forms of traditional professions such as doctors, accountants, engineers, etc., are now quite altered. With the advent of new technological findings and extensive research, the roles performed by these professionals now got revolutionized. They do not merely include the basics but expand on a broad range of skills. For example, the merger of science and technology has now made it imperative for doctors to own rudimentary technological know-how.
On the other hand, accountants are now not merely record keepers. They also assist in evaluating situations and making strategic decisions. They are more involved in the broader context of business workings instead of just focusing on creating reports and statements. With this, there has also been an increase in newer qualifications that help individuals take up more advanced accountancy roles such as data analytics. One of the more modern accountancy qualifications includes the master’s in accounting or MACC degree, which grooms individuals on various skill levels.
Each business function can utilize data to its advantages, such as strategy, marketing, and accounting. If you are wondering about the application of data analytics in particular business divisions, here we have a list. It includes the types of data analytics and their application in the accounting field.
● Descriptive Analytics
As the name suggests, descriptive analytics define a scenario. They tell you what happened in a certain timeframe or a specific situation. If we talk from accountants’ perspective, we will realize that accountants most commonly work around descriptive analytics. They have to report past figures and numbers for viewing by the management and other stakeholders. They record data and present it in a form that makes it easier for other people to review it. Most information in a business is raw and scattered. Accountants are responsible for sorting it out and creating reports and statements that are easy to go through and understand.
They are also responsible for providing the top management with figures that help them make long- term strategic decisions. Since they hold all data and info, they can quickly answer questions for the top management. For example, making the half-yearly or yearly financial statements for public viewing, or the sales schedule for the past five years for the board of directors. These reports help assess how the past periods performed in terms of different factors such as revenue, sales, expenses, etc. And this is how descriptive analytics has the most application in accountancy.
● Diagnostic Analytics
While descriptive analytics explain a scenario, diagnostic analytics breaks it down further. The former answers the ‘whats’ of a situation, whereas the latter answers the ‘whys.’ For example, a recent dip in sales may worry the directors. They may ask the accountants to perform a yearly comparison and see if it is a seasonal trend. On the other hand, conducting variances between the forecasted figures and the actual numbers is also one of the accountants’ primary tasks. They need to perform variance analysis to ensure business activities are going as planned. All of this requires diagnostic analytics. You take a set of data and compare it or further dissect it to examine the driving factors.
● Predictive Analytics
Businesses need to forecast the expected outcomes to plan well. And predictive analytics come in very handy in such a situation. It takes the descriptive and diagnostic analysis results and pushes it ten steps further. It utilizes past figures and trends, examines the reasoning of these fluctuations, and then based on this knowledge, devises a future forecasted plan for the business.
Predictive Analytics is usually complicated and often requires higher levels of skills. However, companies now are very particular about planning, budgeting, and forecasting, so it is also one of the most effective analysis forms. It is also one expertise that makes you stand out among the pool of professionals and may help you bag a good job.
● Prescriptive Analytics
The last type of data analytics is prescriptive. It involves recommending what a business needs to do to solve a problem. Let’s say, based on past data and external industry factors, what makes your consumers come back to buy from you again? Prescriptive analytics is detailed and often requires the use of complex computerized algorithms and software. Accountants can use prescriptive analytics to solve a financial problem, such as comparing and assessing different capital spending options based on investment analytics.
Conclusion
Data analytics is a new high in business management. It involves the use of information to make better, more informed organizational decisions. It breaks down into four types, with each having significant applications in the accountancy field. If you aspire to build a thriving accountancy career, owning extraordinary data analytics skills is critical for accounting success.
