Traditionally, the accounting function's role is always viewed as that of a steward, the control centre for the organisation, rather than the catalyst for enterprise growth. The term 'back office' is often used to describe the operating nature of accounting function. So in today's volatile global business environment, the key challenge for accounting function is how to lead the enterprise in its growth strategies while ensuring effective risk management and stewardship of the enterprise. With complexity and data proliferation, increasingly the CEO and the board turn to accountants to help make sense of data, to help cut through this complexity, and to provide more informed analysis on the business and its operation. The opportunity for accounting function is if it can generate the insights that help make better corporate decision making, while continuing to ensure effective control of the enterprise, its reputation as a catalyst for growth will be guaranteed. To do so, traditional accounting departments may have to transform themselves into 'intelligent accounting functions'. Intelligent accounting functions run their operations as cost effectively as possible, leveraging technology to reduce finance operating costs; strengthen stewardship and control so as to establish a solid foundation to support growth.
This SMU-X course offers an experiential learning opportunity that allows students to translate classroom knowledge and theory into practical solutions for real organizations. Through this student consultancy project, students learn how to solve complex business problems with guidance from the faculty and project sponsor mentors, from problem definition to final client presentation - while simultaneously testing their skills in real world settings. The course will focus on examining accounting processes and applying data-driven analytics and insights so as to identify and create accounting delivery efficiencies.
The course aims to achieve the following objectives:
- Real-world problem solving through student consultancy project
- Apply classroom learning and research to real-world challenges in order to envision solutions for an intelligent accounting function
- Understand the changing role of finance function
- Understand how to simplify, streamline and harmonize essential finance processes to create a leaner, more efficient finance function
- Learn how to use a data visualization tool
- Experiential and peer-learning
- Active mentoring by faculty and project sponsors
- Learn how to handle uncertainty in a project
The Deloitte project focused on exploring the changing roles of auditors and examined ways to simplify, streamline and harmonise essential audit process with Artificial Intelligence (AI). Students had to envision how the future of audit and the profession may change as the traditional roles are transformed with AI, to become more efficient, strategic and catalytic. Requiring audit, AI and business knowledge, coupled with active mentorship from the course instructors and Deloitte representatives, students researched and recommended accounting processes that could be simplified and streamlined, which include rethinking how structures and skills could evolve within the audit profession.
Students designed an efficient business intelligence tool that succinctly presents the company's key performance indexes and other relevant data points crucial to the organisation's management and the various business unit for better decision making.
Aspiring to expand the business further regionally with specific challenging targets, Seng Hua Hng (SHH) commissioned the SMU students to build in-house data analytics capability to help the company achieve its strategic goals. SHH previously would rely on ballpark estimates to make key strategic decisions such as to determine annual production capacity. The key challenge of utilizing ballpark estimates was the lack of accurate demand forecasting on a periodic basis and the absence of important financial information that would support the risk assessment of expansion into new foreign markets. Students also leveraged on predictive analytics to find valuable insights such as expansion plans for both domestics and overseas, new product introduction possibility and better estimation of future financial targets.
The SGX project is focused on the process of collection of data from both mainstream and social media sources, in efforts to help investors stay on top of the latest industry developments. Students devised a standard operating procedure that helped to reduce total man-hours and improve the process accuracy of SGX's systems over time.
Students recommended a suitable methodology to measure members' engagement score, using the existing data available and propose additional data points relevant to track engagement. Students also developed a predictive tool to identify the profile of their members who would be most prone to dropping out.
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