Avinash is a Management Accountant for the past seven years with an MNC and is hailed as one of the most competent employees. A person whose analysis and strategies are quite appreciated by those at the helm of the company. But things have started going a little awry off late. Avinash is facing some roadblocks in his work process. Suddenly there seems to be a lot of external data available, which is a good thing, but he doesn’t seem to understand what to do with so much data!  

The evolving role of Management Accountants

With changing times, the role of management accountant is also evolving. The traditional management accounting role involved financial decision making, budgetary control and profitability analysis. However, today the role involves enterprise performance management, driving profitability rather than just analysing it. A major portion of management accounting now also involves Business analytics and using terabytes of available data to do the descriptive and predictive analysis. For ages Management accountants have utilized enterprise system for report making, however, they now need to leverage it for more analytics oriented use.

How can management accountants use Business Analytics:

The functions of Management Accounting can be divided into three broad heads: (1) Cost Accounting (2) Performance Measurement (3) Planning and Decision Making. Cost Accounting makes use of internal data. Performance Measurement also uses data which is available internally. Only external data will be used for benchmarking the performance. Lastly planning and decision making involves data from cost accounting and performance measurement as well as external data which is also “non-financial” and available in a haphazard manner.

Source: Impact of Business Analytics and enterprise system on Management Accounting. International Journal of Information systems (25):35

The good news is, Business Analytics can be utilized for all the three functions. Descriptive and Diagnostic analytics is useful for cost accounting, both descriptive and predictive tools can be applied to performance measurement, and all three tools, descriptive, predictive, and prescriptive can be used for planning and decision making. Let us see how:

  • Descriptive Analysis

The descriptive analysis offers an answer to “What happened”. This analysis provides a solution in a pre-determined manner. For example, reporting client revenue for the previous year or conducting financial ratio to compare RoI on historic performance using visualization and text mining tools.

  • Diagnostic Analysis

Diagnostic Analysis offers an answer to “How did it happen?” This involves conducting root-cause analysis and utilizing data to test a hypothesis. For example, if there is reduced number of orders by a particular client in the previous year, the Diagnostic analysis will get to cause as to how and why it happened. Not just this, it will also try to bring out solutions to stop such occurrences.

  • Predictive Analysis

Predictive Analysis answers “What will happen in future and when”. This involves the art of forecasting. To predict the future occurrence of a particular event, the analyst needs to build a model or algorithm for identifying the various necessary components. For instance, an automobile manufacturer can collect terabytes of data on the performance of its internal parts, and build a model to predict the possibility of failure of the components and plan its maintenance work beforehand. The tools used for prescriptive analysis are genetic algorithms, log regression, time series regression and Monte Carlo simulations.

  • Prescriptive Analysis

Prescriptive analysis answers “How can I make it happen?” Diagnosis and prediction are useless without recommendations or suggestions as to how to bring about improvement. Sure, it might require some experimentation, but this will help us to further understand the most appropriate course of action. Tools such as Machine Learning can help to come up with the optimal solution to the problems based on time, quality, and revenue versus cost.

Conclusion: Data analysis forms a basis for rational decision making

This is an age of Digital Information revolution. If Management Accountants fail to keep pace with changing times, they will put their company’s operating performance at risk. It may also lose its competitive edge. Management Accountants need to shun their discomfort surrounding data and adopt a model which suits the culture and demand of their organisation’s working style. The strategy should also be congruent to the Management Information System of the company. It doesn’t have to be as complex as it is always feared. Application of Business Analytics will help Management accountants to make the unbiased judgement. There will also be less of personal opinion, biases and irrationality. Decisions should be based on facts and diligent analysis aimed at maximization of stakeholder value.