By Jacob Goldberg
While many financial management (FM) organizations have a moonshot goal to transform themselves, they are swamped managing the workload day-to-day to meet operations, while ensuring legal and regulatory compliance. In addition to this regulatory burden, financial management and operations are support functions, not revenue-driving, bringing additional pressure to reduce costs. Pressures of compliance and cost-efficiency often result in lower strategic investments for planning and transforming FM operations for the future.
To address these forces, FM organizations should invest in robotic process automation (RPA) to automate tasks that are repetitive, rule-based, and manual labor-intensive.
RPA’s Role in Optimizing Business Process.
Many processes within an FM origination could be improved by reviewing the tasks through an RPA lens. Common indicators that a process is suited for RPA include repetitive steps, a low level of complexity, and/or a set of clearly defined rules. FM analysts should be trained to identify these indicators and help determine through additional review if the process is suited for automation. In this review process, the FM analysts and automation subject matter experts (SMEs) will perform a cost-benefit analysis, alternative solution evaluation, and prioritization to determine if the process is suited for automation. While there are many tools that can assist in process optimization, RPA is quickly becoming one of the most impactful tools.
RPA is a software that allows users to develop automations (referred to as bots) to assist in performing business functions. These bots can follow complex business rules, mirroring tasks normally performed by a staff member. Some of the most common use cases include reading spreadsheets, data entry, reconciliations, navigating websites, extracting data from PDFs, and generating reports. By performing these tasks through a front-end interface, in the same way a human would, bots require no modifications to current systems. Historically we’ve seen many FM analysts learn Excel macros to automate tasks, which is a strong indication that they already have the technical mindset to make learning RPA easier.
RPA is perfectly suited to transform the FM approach with its seamless integration and ease of use. FM analysts will be able to identify opportunities for RPA in their own tasks with some introductory training. After completing basic training, FM analysts can develop bots independently, with supervision from SMEs, or by asking dedicated RPA developers to create a bot for them. During this identification process, users should target business processes with the highest ROI when comparing time savings to bot development time. As these bots are put into production, the amount of time spent performing routine tasks will decrease for the FM analyst. This saved time can then be reallocated into deeper analytical tasks, such as forecasting.
Empowering the Workforce to Innovate
In order to implement RPA within an organization, one needs buy-in from the workforce and to ensure the FM analysts are stakeholders in the process. FM analysts should have no fear that a bot will eliminate their jobs, rather that bots will elevate the quality of their jobs. FM analysts should be given opportunities to develop bots themselves, which can be further facilitated by a proper governance structure. With buy-in from the workforce, the likelihood of a successful RPA implementation is much higher and will provide additional benefits as described below.
Employees should be given opportunities to develop creative solutions for their roles. In the tech world this is commonplace, but in more traditional organizations, such as FM organizations, this level of freedom isn’t always ingrained in their culture. New employees are trained to perform tasks by their predecessors, and innovation is frequently discouraged, following the adage: “If it isn’t broken, don’t fix it.” This mindset limits growth and needs to be re-evaluated. It should also be recognized that this exploration doesn’t always end in success, but there is still value gained in the journey!
Automation at Scale
When introducing RPA within an organization, a governance framework should be put into place. This governance typically comes in the form of a Center of Excellence (CoE). The key to a successful governance approach is modeling the structure of the CoE to suit the needs of the organization. Some organizations may prefer to develop a CoE that maintains total control of the RPA process, whereas other organizations may prefer designing a CoE that enables the rest of the organization in the RPA journey. A CoE can also be used to implement internal controls and risk management strategies, which are of particular importance within an FM organization. Whichever model is chosen, a thoughtfully developed CoE should help enable a coherent approach to RPA implementation without stifling innovation or decreasing engagement.
As highlighted in the previous entry in this series (Measuring Impact During Transformational Journeys), benefits can be derived from the journey, even if the end results didn’t serve their original goal. In RPA, there are several additional benefits outside of the speed and efficiency that a bot can offer. Employees who are given an opportunity to work hands-on with RPA are learning a new set of skills that are transferable beyond RPA. These skills include critical thinking, process optimization, problem decomposition, and many others. Additionally, employees who are working on engaging tasks are less likely to seek employment elsewhere. RPA helps in retention by providing an opportunity to develop new skillsets, work on developing bots, and remove redundant tasks from their responsibilities.
Guidehouse has helped many clients implement RPA, including an FM division of a government agency within the intelligence community. This organization is responsible for providing documentation for auditors to sample and make changes to the FM process to address auditor findings. Guidehouse created a series of three bots to automate the most time-consuming steps of the six-step auditor request process:
This early warning of an auditor’s findings gives our clients the opportunity to transition from reactive to proactive decision-making. Implementing these bots has saved our clients thousands of hours, improved accuracy, and decreased turnover.
The success or failure of an RPA implementation should be measured through several different levels, including at the process level, workforce level, and organizational level. At the process level, ROI can be calculated by comparing the number of hours it will take to develop the bot and the number of hours the bot will save over the expected life cycle of the bot. Not all bots will be successful, but it’s important to recognize failures quickly, and move on to the next candidate for RPA. At the workforce level, the measurement isn’t as straightforward as ROI, but still measurable. Workforce leadership can measure employee satisfaction and improvement through metrics such as decreased turnover, exit interviews showing less dissatisfaction, and surveys. At the organizational level, RPA provides the opportunity to perform more value-added and forward-looking functions. But with proper guidance from organizational leadership, this time savings should be re-invested back into the company. In the real-life example provided above, the bots provided our clients a significant time savings, which they re-invested into preparing for future audit samples. To implement changes on this scale requires a general shift in mindset, not just for this client, but across all FM originations. FM needs to shift from reactive to proactive, and RPA is a tool that can help achieve that vision.