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Controllers are responsible for understanding and explaining how their companies are performing financially. To succeed today, they need strategic, technological and analytical skills that go beyond traditional compliance and reporting. Controllers should deliver real-time insights — quickly, reasonably and often at a granular level — to help enhance decision-making and improve business processes.
This shift from transaction processing to strategy requires the right technology. By automating processes, leveraging cloud ERP and digital platforms, and adopting innovations like artificial intelligence (AI), controllers can boost productivity, help reduce costs and demonstrate value. At the same time, these efforts can improve their teams’ work-life balance and set themselves up for continued career advancement.
If finance modernization offers so many benefits, why aren’t organizations further along in deployment? One reason can be budget. It’s often a chicken-or-egg scenario. Finance transformation can be a cost-saver in the long term, but how much should an organization need to invest to realize those savings? Controllers may be required to work within financial constraints — or with systems that were deployed without their input.
Nonetheless, controllers may have opportunities to act.
The finance function is well suited to take advantage of several forms of innovation, including automated workflows, visualization tools, AI and now generative AI (GenAI). As GenAI continues to evolve, controllers should seize the opportunity by learning how it can enhance their overall plans for finance modernization. For example, many companies are exploring using GenAI data mining contracts, providing initial flash reporting and developing forecasts.
For employees, it may be an opportunity for upskilling, particularly for those who are early adopters. It can also help increase efficiency and free up time for staffers to complete higher-level tasks.
Key to this effort is defining proper governance and oversight. Take time to learn about Responsible AI practices to weave them into your plans. Think of existing risk management functions as the starting point for these practices. Responsible AI should be end-to-end — starting with assessing and prioritizing use cases on both value and risk — and carrying through the AI lifecycle, including output validation and performance monitoring.
Staffing challenges are a perennial concern for controllers. While finance modernization can help address these concerns, embarking on a transformation brings its own challenges. Employees are often skeptical of change, and they may even perceive new tech as a threat. You can show them that transformation can significantly improve their experience by resolving long-standing issues that teams have been struggling with for years.
The key to navigating this paradox? Building trust. Maintain open communication about your organization’s plans and reasons for change. Inspire, don’t impose, by fostering a culture around innovation that makes work more effective and engaging.
To build engagement, identify change champions who can help motivate others, prioritize upskilling and develop ambassador programs with incentives to help drive adoption. Throughout, pay close attention to staff resourcing and intervene swiftly to avoid burnout or cover areas requiring attention. Carefully consider how to align roles with evolving tasks, rewarding strong performance along the way.