Artificial intelligence (AI) is no longer a pipe dream, and robotic process automation (RPA) is already here and displacing blue-collar workers and professionals alike. Those in the management accounting profession aren’t immune from the threats. There can be no doubt that some job functions performed by management accounting and finance professionals will become completely automated. At first, it will be the routine rules-based tasks that are no longer performed by humans, but don’t underestimate the possibility of higher-level tasks becoming part of the domain of these advancing technologies. The threats that come from the loss of job responsibilities open the door to opportunities, but only for those with the right skill set and mind-set.
Robotics and AI aren’t the only challenges. The rate of data generation doubles every two years, and Big Data is top of mind for many finance leaders. Big Data is just that, big—too big, in fact, for traditional database management systems. Also, the data increasingly comes from unstructured formats, gleaned from multiple sources including mobile phones, the internet, the Internet of Things, radio frequency ID, and digital cameras. Analyzing these vast troves of data can reveal patterns relating to human behavior. This data can be a strategic asset if the right tools are used in a disciplined way. The challenge is leveraging all this data to drive business success. Examples include ranking customers based on their likelihood of paying, estimating customer churn, optimizing inventory levels using POS (point of sale) data, identifying spam, detecting fraud, targeted marketing, cross-selling recommendations, and identifying root causes of damages and quality issues.
At the same time, today’s finance teams are charged with both creating and preserving value. Senior financial leaders increasingly need to apply their analytical and business skills to more strategically oriented organizational issues. The ever-expanding level of data collection, combined with the processing abilities of AI, will generate exponentially more analysis. Using business analytics to leverage AI as “augmented intelligence” can help unlock that value. It’s up to the individual to add the insight that helps create value.
What skills will be needed? Business analytics has many facets. Descriptive analytics tell us what happened, and diagnostic analytics tell us why. Predictive analytics uses statistics, data modeling, real-time data, and machine learning to detect trends for forecasting. Prescriptive analytics goes a step further, ranking the trade-offs of different courses of action and making a recommendation for a specific action. Here’s where the tools of scenario modeling and optimization algorithms are used. The underlying assumption when using this enhanced information is that the company will gain a competitive advantage if it can anticipate the future better. Management accountants do a good job of describing and diagnosing, but we can do better with predictive and prescriptive analytics.
Data analytics is a way of thinking, viewing business problems from a data perspective, using structured analysis and data-based decisions. An art as well as a science, it includes data mining, predictive modeling, and data visualizing. Data mining involves examining large databases to generate information and extract patterns. Data integrity, security, and quality are critical. Data governance is the science of managing the availability, usability, integrity, and security of data. An important aspect of data analytics is fitting the right model to the data. With predictive modeling, you build a model to estimate the future. Regression is one example of predictive modeling. Data on its own is pretty useless until you format it in a way that reveals actionable insights. Communicating the results in a clear, visual way is imperative. You want to tell a compelling story and encourage the user to explore further.
Business analytics aims to create actionable insight. It gives you the ability to react quickly to an increasingly complex, volatile, and competitive environment by exploring past business performance. Business analytics is all about quantifying business issues and making decisions with more accurate and fact-based data. The purpose of this enhanced analysis is to make better business decisions, something many professionals with the CMA® (Certified Management Accountant) certification have been doing since 1972.
This enhanced analysis can help you understand customers better, increase revenue, reduce costs, and manage risks. Analytics must be anchored in strategy, providing insights to develop competitive advantage and enabling a company to earn a higher return than the competition. Because competitors catch up, new competitors enter the market, consumers are fickle, styles change, and supply chains dry up, companies need to constantly focus on creating and sustaining competitive advantage. Analytics can help unlock the insights that can lead to actions to create value, but how do accounting and finance professionals develop those skills?
The CMA certification may be the answer. CMAs are already doing data analytics, and business analytics skills enhance the business insight required to create value and competitive advantage. They play an important role in defining the business problem to be solved, analyzing alternatives, interpreting the results, ensuring the integrity of the data, testing the reasonableness of the results, communicating the results, and making and/or implementing the decisions. Management accountants don’t have to be data scientists, but they do need to be able to ask the right questions of data scientists and to work with augmented intelligence. CMAs can partner with data science experts to communicate recommendations to senior business leaders.
Data analytics should be integrated with the key management accounting functions of planning, performance management, risk management, and decision support. Analytics is an enabler of effective insight to drive robust plans, risk dashboards, and better decisions, leveraging data to generate insight and driving value along the entire value chain.
The CMA program’s focus on planning, analysis, and decision support aligns closely with the skills that management accounting and finance professionals will need in the future. The exam covers forecasting techniques such as regression analysis, expected value, sensitivity analysis, and Monte Carlo. It also covers more traditional descriptive and diagnostic analytics, such as financial ratios and variance analysis. Also, strategic planning will become even more important in the future as the pace of change quickens. CMAs can earn the CSCA® (Certified in Strategy and Competitive Analysis) certification to add a strategic perspective to their skill set.
Anticipating and adapting to change as well as absorbing continuous learning are imperative in today’s business environment. Companies and individual management accountants have to realize that automation and AI are here and will only become more common more quickly in the future. Embrace these changes, and take the opportunity to develop the skills that will set you apart so that you can harness this new technology. Someone has to manage all those robots in accounting. Why not you? If you aren’t certified, earn the CMA and learn more about data analytics through education and training. If you are a CMA, earn the CSCA!
December 2017
