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Management Accounting Applications

Management accountants use their knowledge and expertise to support business planning, controlling, and decision making (Garrison et al., 2018). In their Managerial Accounting book, researcher Garrison et al. (2018) said that “the most basic managerial skill is the ability to make intelligent, data-driven decisions” (p. 4). The amount and types of data that are generated each day continue to accelerate, thus, the possibilities to use Al for management accounting are significant. Al technology can assist management accountants with data analysis to generate insights, improve decision-making, increase productivity, and enhance operational performance.

Manufacturers with a large number of long-term assets are also exploring ways in which Al can enhance operations and improve profitability. A study from McKinsey found that Al technologies can optimize production processes that traditionally rely on human operators’ experience, intuition, and judgment (Charalambous et al., 2019). McKinsey worked with a cement company client to integrate Al to install real-time asset optimizers by capturing millions of lines of data from hundreds of process variables and analyzing said data using advanced analytics tools. The study found that profits improved within a few weeks of implementation. After eight months, the Al-enabled asset optimizer improved operational performance by 11.6% versus the analog processes (Charalambous et al., 2019). In short, the introduction of Al improved results without requiring capital-intensive equipment upgrades.

Al has also been used to support decision-making and enhance operational performance in the parcel delivery industry. In Japan, for example, a surge in online shopping and a shortage of drivers has strained the parcel delivery industry (Tsukimori, 2020). In response, Japan Data Science Consortium (JDSC) developed its own Al patentthat analyzes household electricity data to calculate whether someone is likely to be home during the package delivery period. The idea was simple: When electricity usage is high, someone is likely to be home to receive a package, effectively avoiding the added costs and time associated with re-delivery of the package. Based on a pilot study conducted in 2018, the rate of re-deliveries was reduced by 90%.

The analysis produced by Al could be incorporated into a balanced scorecard (BSC). The BSC consists of an integrated set of performance measures that include four perspectives that are directly linked to the company’s strategy: (1) financial, (2) customer, (3) internal business processes and (4) learning and growth (Kaplan & Norton, 1992).

From a financial perspective, management accountants would become responsible for capturing the costs associated with Al initiatives to ensure cost-effectiveness. Additional financial performance indicators, such as RO1 and other profitability measures, could be tracked. From the customer handling perspective, managers could track satisfaction through surveys after implementing Al initiatives. Managers could also measure how the percentage of customers changes (decreasing, increasing, or staying the same) after Al implementation. From the internal business processes perspective, managers could track whether their organization has improved key business processes by addressing the following kinds of questions: Are standard cost variances decreasing because of using Al? Is the service delivery time decreasing? From the learning and growth perspective, managers could monitor how the company leveraged Al to change and improve its competencies. For example, are employees being adequately trained on how to fully take advantage of all the benefits of Al in their respective responsibility area?

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