Data Analytics for Management AccountantsBy
Following a data-driven approach can optimize results for your organization.
At the beginning of the COVID-19 pandemic in the spring of 2020, the governor of the state of N.Y., Andrew Cuomo, conducted daily press briefings presenting data analytics dashboards to summarize the disease’s spread rate in the state. He declared that “data-driven policy works” because analytics were used to develop guidelines for the state’s COVID-19 management policy to reopen the state’s economy.
Management accountants can also develop data-driven analysis to gain insight and valuable business intelligence that supports decision making and adds value to their organizations. As Chris Mishler, a past chair of IMA’s Technical Solutions and Practices Committee, says, “Data analytics skills are a critical pathway for management accountants to know the right questions to ask and how to get the answers their organizations need to succeed.”
DATA ANALYTICS POWER
Data analytics can play a vital role in management accounting because the data pool for analysis may be much larger than the data available for financial accounting. This provides broader opportunities for analysis because data isn’t restricted to externally reported financial information contained in U.S. Securities & Exchange Commission 10-K filings. Management accountants can be creative because they can customize analysis and dive into both financial and nonfinancial data collected by their organizations to support better decision making across the organization. The insights provided by analysis facilitate the discovery of sources of operational efficiency or inefficiency. In today’s hypercompetitive world, having ready access to this information allows the company to realize more profit and increase operational efficiency.
Once data is analyzed, it’s important to present it in a clear and meaningful way. Use data visualization, or dataviz, to present the analysis. Dataviz is the presentation of information in graphic or pictorial form, such as dashboards, interactive reports, and interactive presentations (see, for example, Figure 1). Mishler says, “Some of the biggest ‘Wow!’ moments from my internal or external customers have come from insights and recommendations drawn from data analytics and related visualizations.”
Dataviz grabs the user’s attention because of the clarity of the information depicted through charts and graphs. They allow the human brain to see very large amounts of complex data in a visual format and comprehend it much faster than by reading a spreadsheet. And the use of color highlights and contrasts data differences. It’s possible to drill down into the underlying detail. Dataviz tells the data’s story through pictures.
A major challenge in data analytics is using reliable and accurate data. The fact that it was extracted from an enterprise resource planning system is no guarantee that it’s analysis-ready. Beware of how bad data—garbage in, garbage out—can sabotage analysis. Data may be corrupt, incomplete, and inaccurate and need cleansing—the process of identifying and correcting data errors prior to performing analysis. Include management accountants in the data collection and data scrubbing process because they understand their organization’s information and can evaluate data quality. Delegating this function to the information technology department is risky because the team members may not have the same understanding of data’s nuances, how to choose the right data, and how to analyze it.
Avoid the risk of drawing the wrong conclusions from the analysis. Plan the analysis, identify its objectives, and carefully review the results. Finally, don’t forget to establish data analytics internal controls and governance procedures to safeguard data. After all, data is an asset.
Another issue according to Gartner (gtnr.it/2ITeO3z) is dark data, data that is collected by an organization in the normal course of business but isn’t used for analytics. This may lead to overlooked analytics opportunities because the organization may not understand the data’s value. It may also mean that unnecessary data is retained, adding data retention costs.
Andrew Urbaczewski, associate professor of data analytics at the University of Denver’s Daniels College of Business and distinguished visiting professor at the United States Air Force Academy cautions CFOs to resist buying the latest data analytics technology. He advises instead asking the right business questions and then obtaining the tools required to answer those questions based on a company’s needs.
MASTER DATA ANALYTICS TOOLS
Upskilling management accountants to equip them with data analytics skills pays huge dividends for companies. Mishler suggests that management accountants must add data analytics skills to their portfolios to provide strategic decision-making support to their organizations’ stakeholders. Success is measured by connecting data in meaningful ways.
According to Mishler, learning about the applications of data analytics tools makes management accountants smarter about their organizations and positions them to act as trusted advisors. Asking and answering the right questions and using the right data and tools place management accountants in a powerful role that adds value to the organization. Follow Governor Cuomo’s example and adopt a data-driven policy for your organization. Remember, the right numbers and analysis don’t lie.
The opinions included are those of the author and not necessarily those of the U.S. Air Force Academy, the U.S. Air Force, or any other federal agency.
The IMA Data Analytics & Visualization Fundamentals Certificate™ was launched recently to support developing these skills. Co-developed with the University of Illinois’s Gies College of Business, it includes four modules: Becoming Data Driven, Visualizing the Present and Predicting the Future, Applying Data Analytics and Visualization, and a final assessment.
21.5 hours of CPE