Making the Business Case for Robotic Process Automation (RPA)

Robotic process automation (or RPA) is a technology that mimics actual user behavior via software robots (bots) to automate high-frequency deterministic business processes. It enables organizations to integrate those tasks into enterprise systems, including ERP, CRM, and industry-specific software, without writing complex integration code.

RPA has become a key tool in the ongoing digitalization of business processes, extending the concept of automation to a range of scenarios that would otherwise require human labor or intervention. The main benefits of deploying RPA are as follows:

• Reduced process times and costs. Using an RPA solution can reduce the time taken to execute a process and improve throughput. Compared to a human operator, an RPA bot can work without breaks and operate on a 24/7 basis. The combination of better throughput and reduced labor costs can reduce the overall cost of running the process. A global BPO company applied RPA to 14 core insurance processes involving 120,000 case transactions per month and built 27 robots to automate parts of those processes. In doing so, it reduced the cost of each process by 30% on average.
• Increased productivity. RPA solutions can free up human operators to focus on higher-value work, expanding the team’s overall productivity. The human operator can trigger a bot as required to assist in performing a task (described as attended operation), or the bot can execute the entire process without intervention, either to a preset schedule or triggered by logic (described as unattended mode). A national public sector organization created 120 bots to automate elements of 25 accounting processes, including maintaining financial journals and materials pricing. This saved 18,000 person-hours annually and reduced the cost of the processes by 15%.
• Improved quality. An RPA solution can consistently execute a process, avoiding human error. It also enables greater traceability of a process for regulated businesses, with all activity stored in a log. A global FORTUNE 500 technology company was undertaking a digital finance transformation, which included using RPA to automate the creation of previously manual journal entries for intercompany cross-charges. The automated solution did away with human-generated inaccuracies and generated 50% productivity gains. It also meant that the process was fully auditable.
• Improved customer experience. Organizations are increasingly looking to RPA to help improve customer experience. A bot can handle many basic incoming customer requests, and by improving responsiveness and avoiding long wait times, can increase customer satisfaction. A UK-based Hospital Trust used RPA to integrate patient self-service kiosks with the National Program of IT (NPfIT) patient Administration System (PAS). This increased the proportion of patients using the self-service kiosks to 51%, improved patient satisfaction, and led to a 50% improvement in staff efficiency.

As RPA solutions have evolved, they have incorporated new capabilities to broaden the scope of processes to which they can be applied, including:

• Process discovery and task mining
• Intelligent Document Processing (IDP)
• AI/ML assisted decision automation, image recognition, and NLP

RPA solutions apply to a wide range of scenarios and can automate many basic and repetitive tasks that a human might carry out in both front- and back-office processes.
Many processes are now fully digital, and with the addition of advanced capabilities including IDP and ML, RPA can support many different types of horizontal and industry vertical processes, for example:

• Processing invoices
• Reviewing mortgage applications
• Checking customer details
• Generating sales quotations
• Triaging insurance claims
• Handling customer information requests
• Generating management reports
• Posting financial journal entries
  Processing delivery requests in retail

In many scenarios, RPA provides a tactical halfway house between continuing to operate a manual process and redesigning or refactoring the process in a way that avoids manual steps altogether. This may involve using traditional integration middleware or increasingly the use of cloud-based integration Platform as a Service (iPaaS) solutions. However, creating integrations of this type will require professional developer time, and may not be cost justifiable for the given scenario. This is why picking the right target for RPA is so essential.

There is also an increasing overlap between RPA, workflow, and Business Process Management Software (BPMS) solutions, and many organizations are combining them with AI/ML capabilities to extend the scope of automation across an end-to-end process.

Finally, business process outsourcing (BPO) can be another alternative to consider for high-volume processes. BPO has commonly been applied for back-office processing in areas including finance and HR, using labor arbitrage in offshore locations to reduce the overall cost of a business process. Increasingly, RPA will be used by BPO providers as part of their cost reduction strategies.

The costs that should be factored in when implementing an RPA solution are as follows:

• Solution License Costs. License costs are a complex issue for RPA since many vendors have pricing models based on the number of bots in use or the volume of automated transactions. Since the scope and scale of a bot (and the task it undertakes) can vary widely, this makes it difficult to predict and govern costs and compare one vendor with another.
• Infrastructure Costs. Under on-premise deployment, users will have to install and maintain the underlying infrastructure.
• Implementation Costs. Deploying an RPA solution into an organization will typically involve professional services, either from the vendor or a third-party provider.
• Management Costs. RPA is considered to have a relatively high overhead for management and governance. This will involve both day-to-day administration, and aspects such as security and compliance.
• Training Costs. Training will be required for business users, development teams, and administrators.

RPA is often a short-term solution to avoid more complex integration or software development. But it is important to understand that RPA will do little to improve an inefficient business process. So, organizations must assess whether RPA is the right solution for a business requirement or whether process redesign is a better answer in the long term. Additional risks that should be considered as part of the business case for RPA, include:

• Lack of strategy. Plowing headlong into RPA without a broader strategy is a recipe for disaster. Many organizations underestimate the need for a strategic approach and the business change management necessary to support and enforce it.
• Scaling challenges. Although it’s easy to implement RPA tactically, scaling up (for high volume processes) and particularly scaling out (to extend automation more widely) has proved problematic for many organizations.
• Lack of standards. Standards in the RPA world are underdeveloped, hampering interoperability between RPA vendors and between RPA and other solutions.
• Lack of measurement. As with any process improvement initiative, it’s vital to have clear metrics and a baseline to measure the outcome and the value created. Building metrics into an RPA deployment should be relatively straightforward, but organizations often neglect to capture and baseline.

Used in the right places, RPA has strong potential to assist an organization in digitizing its processes. However, there is ample scope to create disarray, and it’s crucial to view RPA as a tool with a specific role in digital business improvement initiatives and plan the appropriate use cases carefully.

For individual use cases, RPA can certainly deliver value to a pilot project within 90 days, and can be used to prove the model within that time frame. The key is to do this alongside broader strategic planning. To achieve this, we recommend the following 30/60/90 Plan:

• 30 Days: Planning and process identification. Develop an overall plan for automation, and its role within your digital strategy. List key processes and identify feasibility for and benefits of automation. Create a core team for automation projects. Select one or two processes as automation pilots.
• 60 Days: Design and development. Undertake in-depth analysis of pilot processes. Train business users and development teams. Design target pilot processes and develop initial automations. Test then deploy. Build a more detailed project plan.
• 90 Days: Scaling and optimizing. Use feedback from pilots to optimize your approach. Develop a plan for scale out. Develop and communicate governance processes. Expand the core team and consider a center of excellence. Preparatory work is essential to understand which processes are suitable for RPA and the business changes necessary to implement a solution. Organizations should challenge themselves by asking whether, in the long term, they need to re-engineer the business process to which RPA is being applied.