Transformation at many organizations is technology-focused, but controllers and CAOs are finding that much more needs to change.
Finance departments agree on transformation but differ on how and which finance areas to enact change. Transformation at many organizations is technology-focused, but controllers and chief accounting officers (CAOs) are finding that much more needs to change.
While there is broad agreement on the need to transform finance departments, organizations differ on how to enact change and which areas of finance to target. Transformation at many organizations is technology-focused, but controllers and chief accounting officers (CAOs) are finding that much more than just technology needs to change.
While technology is an enabler of transformation, its impact depends greatly on the people and processes surrounding it, making governance, culture, and change management key considerations. The pressure to transform also does not preclude the need for strong business cases—with many technologies promising the world but delivering far less, leaders must clearly demonstrate the value of initiatives to secure appropriate buy-in and investment. Return on investment (ROI) on new technologies, particularly automation, often has a long timeline given the high up-front costs, or is difficult to quantify in terms that will convince decision-makers. Nevertheless, with new technologies steadily gaining traction and leaders increasingly recognizing the need to transform to stay competitive, controllers are poised to radically alter their organizations in the coming years.
Given how closely KPMG works with many of the world’s leading organizations, we have distinct insights into how finance leaders are approaching these topics. Below are five areas that corporate controllers and CAOs are focused on as they undertake transformation at their organizations.
Transformation and its challenges
The word “transformation” is thrown around so much that in some ways it has lost its true definition. A good approach to finance transformation is to first set a vision for the desired end state. Once that vision is set, its various parts can then be examined (e.g., the people, technology, reporting, digital organization structure, etc.) and an organization can gauge how far it is from where it wants to be. Closing that gap, or the difference between the current state and desired end state, is what is commonly referred to as “transformation.” Achieving the vision often involves “mini t” transformations of small, incremental improvements that combine for a more comprehensive “big t” transformation.
Controllers and CAOs are all-in on finance transformation but know that it won’t be easy. First, there are the technological barriers that leaders must overcome as they move their organizations into the digital age. As more tools and technologies become available, organizations must carefully consider how to leverage solutions for operational efficiencies in a tight labor market. Considerable efficiency gains can be found on the back-office side; however, doing so can require systems rationalization and standardization so things like legacy systems and technical debt don’t hold an organization back.
Technological challenges are not the only hurdles that finance leaders face. To sustain efficiency improvements, automation is a key lever, but ROI for automation can be difficult to justify since up-front investments can take longer to recoup. Particularly when replacing low-cost work, the price tag of transformative applications such as automation can be a deterrent to adoption. For this reason, as organizations pilot solutions, strategies must involve prioritization and comfortable ROI thresholds for potential implementations.
Beyond ROI considerations, leaders also face administrative challenges when trying to initiate transformation. In some instances, organizational structures may require multiple levels of managerial approval to accomplish simple implementations, leading to longer timelines and discouraging innovation. Change management is necessary to ensure that organizational structures align with new technologies, and that sufficient adoption occurs.
Buy-In and the business case for transformation
Making the business case for thorough transformation is often complex due to the difficulty of defining and measuring ROI. In some circumstances, projects are creating new capabilities or are borne out of vendor support issues, making the business case simpler than comparing ROI to existing solutions. In other cases, substantial transformations like live ERP systems will necessitate investments with distant ROI to make gains in long-term efficiencies. Even when the business case is more straightforward, the scope of transformation means achieving buy-in and consensus is often difficult. However, transformation demands action, and organizations cannot always wait for consensus before creating a vision and moving forward.
That said, the business case for finance transformation is typically crucial to securing buy-in from senior leadership. Some executives have attempted to drive senior buy-in through smaller changes with more immediate returns, while other officers have found their leadership more patient. The latter can especially be the case in privately held organizations—with no common stocks or analysts following organizational activity, there is less urgency at top levels around rapid returns.
Some organizations are increasing their use of shared services as a means of transforming processes and functions. Shared services functions offer value throughout the enterprise, but their responsibilities across business areas can make their impact hard to establish in terms of the broader organization. Demonstrating the efficiency afforded by a shared services approach is helpful when reporting to the CFO since it eases buy-in in the financial function, but business leaders in other areas may be reluctant to let go of tasks that are sensible for a shared services team to handle.
The people side of transformation
Alongside any technology transformations must come changes to the processes and people that interact with those technologies. Working from a project-oriented mindset can limit the scope of change and cause cultural issues around resource reduction. To address this, leading controllers and CAOs typically approach transformation with a broader, function- or organization-wide mindset in terms of both the change itself and the intended benefits. This change in mindset is essential to initiate more profound financial transformations.
Many finance professionals, particularly early career talent, are capable with technology and have an active interest in their own roles becoming digitally enabled. Meeting these expectations are crucial, as opportunities to work with digital solutions and develop valuable technology skills—effects of transformation—can be used to attract talent, both externally and internally. Maintaining a center of excellence for automation within finance has also become more viable as tools improve usability, making reskilling more straightforward than was the case with previous forms of technology. Upskilling for existing resources on finance teams can help develop skill sets internally while also encouraging a transformation-motivated culture.
Automation can help free up resources, eliminating tedious workloads and improving efficiency, but concerns around resource reductions can impact culture and transformation timelines if they are not addressed. Dedicated transformation teams make it easier for officers to communicate the need for changes and the potential benefits of automation strategies to manager-level personnel. Engagement in the design process gives employees a sense of agency that can improve buy-in to continued automation implementation. Establishing “on ramps” and “off ramps” on projects provides top talent with opportunities to be actively involved in transformation, keeping them engaged and developing, while also bringing fresh perspectives.
Automation and the close process
Artificial intelligence (AI) and predictive analytics are bringing controller and accounting functions closer to fully automated close processes. Most organizations are early in this process, using tools to support analyst activities like compiling reports rather than handle booking entirely independently. Anomaly detection can be a key use case for leveraging AI, as this can track close and preclose processes to highlight errors or identify trend outliers before bad data is ingested.
The distinction between true AI and robotic process automation (RPA) implementations isn’t always cut and dried, but RPA in the data collection process can alleviate manual efforts even if true AI capabilities are not enabled. Efforts to establish RPA processes often target areas rife with repetitive work, such as accounts payable and portions of the close process. Finding ways to make simple, quick forays into RPA can demonstrate the possibilities to employees, increasing their enthusiasm and engagement. In addition, this focus has the additional benefit of potentially reducing headcount if effective RPA ultimately helps organizations avoid rehiring for vacant roles.
Finance officers recognize the importance of identifying processes suitable for RPA before pursuing more robust automation implementation. Examining close processes to identify inefficiencies and reduce complexity can make it easier for teams to handle in the short term while also preparing their organizations for future automation implementations. While 100 percent automated end-to-end close processes may not be feasible in the immediate future, focusing on that goal at the outset of transformation efforts can help establish a strong framework for future developments.
Centralization and governance
Standardization across process ownership has become a priority as leaders move their respective finance organizations forward. Broader digital enablement and automation depend on clear governance to ensure consistency and uniformity. For some, digital centers of excellence (COEs) can be a useful approach for governance in RPA transformation efforts, as these groups can work throughout the organization to identify new use cases, monitor implementations, and create visibility for cultural change. At larger organizations, multiple COEs across regions allow for clearer insights into problem areas for standardization, particularly when paired with citizen-led data transformation through tools like Alteryx and Power BI.
Citizen-led approaches have inspired skepticism in some executives, but some organizations have seen success with a mixed model, incorporating on-the-ground input while keeping governance within control for standard-setting and internal audit collaboration purposes. On the other hand, the individual activity involved in citizen-led development can cause key person dependencies due both to skill sets and independent implementation.
Ownership of RPA implementations can be complex to establish when developing global business services centers. In the past, RPA has been used in limited capacities to solve niche problems, and ownership was often left with IT. As RPA has become more broadly utilized, though, there is a trend towards ownership remaining with the function that will use the tools. As such, many organizations have centralized ownership in the finance function, with IT still providing a measure of support.
Successful transformation will look different for every organization—companies have different starting points and different destinations. The journeys will be similar, however, as every controller and CAO will need to take a multiprong approach that considers the many people, processes, technologies, and organizational structures that transformation touches. The roadmap is complex and far from easy, but with a view of the various facets, leaders are equipped to bring effective, lasting change to their organizations.
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