Today, many organizations are working hard to adopt a fully data driven mindset to grow their businesses and enhance the services they provide to customers. Like most other industries, analytics will be a critical game changer for those in the financial sector.
Data analytics is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. It leads to many other technology disruptions such as IoT, Machine Learning, AI across all business sectors.
Though many organizations are beginning to disrupt their analytics landscapes by gathering immense volumes of data assets, these companies are at varying levels of Big Data maturity. In many cases, these initial data projects lead business stakeholders to a very simple question: “How can this data help us solve our business problems?”
As customer volume increases, it dramatically affects the level of services offered by the organization. Existing data analytics practices have simplified the process of monitoring and evaluation of organizations, including vast amounts of client data such as personal and security information. But with the help of Big Data, organizations can now use this information to continually track client behavior in real time, providing the exact type of resources needed at any given moment. This real-time evaluation will in turn boost overall performance and profitability, thus thrusting the organization further into the growth cycle.
Identifying more areas where Big Data resources can be utilized most efficiently involves the alignment of business cases and technological capabilities, which reveals opportunities for improved business processes.
Professional bodies around the globe has been engaged on researching this emergent concept and one of those; ACCA has published a well calibrated article on Big Data which can be accessed on this link:
But why is this important? And what does it have to do with accounting and finance profession?
Accountants use data analytics to help businesses uncover valuable insights within their financials, identify process improvements that can increase efficiency, and better manage risk.
Here are a few examples:
Auditors, both those working internally and externally, can shift from a sample-based model to employ continuous monitoring where much larger data sets are analyzed and verified. The result: less margin of error resulting in more precise recommendations. Some firms have already started implementing this into practice.
Accountants who assist, or act as, investment advisers use big data to find behavioral patterns in consumers and the market. These patterns can help businesses build analytic models that, in turn, help them identify investment opportunities and generate higher profit margins.
Four types of data analytics:
To get a better handle on big data, it’s important to understand four key types of data analytics.
1. Descriptive analytics = “What is happening?”
This is used most often and includes the categorization and classification of information. Accountants report on the flow of money through their organizations: revenue and expenses, inventory counts, tax collected. Accurate reporting is a hallmark of solid accounting practices. Compiling and verifying large amounts of data is important to this accurate reporting.
2. Diagnostic analytics = “Why did it happen?”
Diagnostics are used to monitor changes in data. Accountants regularly analyze variances and calculate historical performance. Because historical precedent is often an excellent indicator of future performance, these calculations are critical to build reasonable forecasts.
3. Predictive analytics = “What’s going to happen?”
Here, data is used to assess the likelihood of future outcomes. Accountants are instrumental in building forecasts and identifying patterns that shape those forecasts. When accountants act as trusted advisers and build forecasts, business leaders grow increasingly confident in following them.
4. Prescriptive analytics = “What should happen?”
Tangible actions — and critical business decisions — arise from prescriptive analytics. Accountants use the forecasts they create to make recommendations for future growth opportunities or, in some cases, raise an alert on poor choices. This insight is an example of the significant impact that accountants make in the business world.
Why accountants make excellent data scientists?
Accountants have outstanding technical skills. Accountants are used to aggregating information to create a picture of an organization that summarizes the details contained in each transaction. Working with descriptive analytics, predictive analytics, and prescriptive analytics comes more easily to people who already possess excellent quantitative skills.
Accountants are natural-born problem solvers. The jump from descriptive and diagnostic analytics to predictive and prescriptive analytics requires that one shift from an organizational mindset to an inquisitive mindset; a shift from stacking and sorting information to figuring out how to use that information to make key business decisions. Accountants are experts at making this jump.
Accountants see the larger context and business implications. The true value of data analysis comes not at the point when the data is compiled, but rather when decisions are made using insights derived from the data. To uncover these insights, a data scientist must first understand the business context. Not only do accountants understand this context, they live it on daily basis.
There is no pause on the influx of big data and data analytics into the accounting profession. Its happening and at an unprecedented pace. To survive and thrive, we better need to equip ourselves with required skill-set, upgrade our approaches and lead the organizations to prepare for the upcoming challenges.
ABOUT THE AUTHOR:
Imtiaz Ahmad is a young qualified Finance Professional from ICAEW & ACCA and an aspirant CEO with 14+ years of experience; worked for a diversified range of industries in Pakistan and Middle East. He is a seasoned Coach, Mentor, Counselor and Teacher in Accountancy and Finance profession too. He has 500+ students who got qualified ACCA, CA and CMA to his credit, in different countries around the globe.