RPA Driven Transformation: Identifying the Next Automation Opportunity

In the last few years, robotic process automation (RPA) has been a key focus area for more and more Fortune 500 firms. Sustained interest and significant resources have been invested in deploying RPA solutions, mapping and re-engineering processes, and restructuring organizations. Financial returns are a key driver, with expectations of a 1-2-year turnaround in invested capital.

The initial RPA programs were driven by individual business owners working in silos, with a wide variation in standards and technologies across the enterprise. Later, as the technology gained traction, a need to regulate, harness (lessons) and improve the overall reliability of the RPA projects were realized. This was achieved by setting up dedicated centers of excellence (COE). These COE(s) offered a wide range of services including governance, operating model and the enforcement of developmental and architectural standards and reporting.

Businesses have procured, designed and deployed RPA processes for the past couple of years. Today, they face a new set of challenges and lessons that require a “shift” in identifying RPA opportunities and deployment solutions.

Key Challenges

Benefits management: Most RPA business cases traditionally promised 1-2 year return cycles with high levels of automation across selected processes. These business cases were often defined much before the actual design, build and deployment of the bots. Consequently, factors such as system dependencies, ongoing bot support costs, process variations, task level details and actual cycle time(s) were often overlooked leading to inflated benefits and aggressive break-even periods. Post deployment of the bots, organizations realized that the automated processes still require human effort to manage exceptions and other unplanned scenarios. This has significantly reduced the expected savings and pushed out the break-even period.

Capacity utilization: The dedicated use of bot licenses by lines of business due to inefficient design – and driven by business and compliance requirements – has led to a situation where a large number of bot licenses remain under-utilized for significant periods of time; leading to inefficient use of infrastructure and increases in cost overhead.

Organizational change: RPA use cases are often selected without a complete understanding of the current process. There is an absence of reliable process metrics with an incomplete understanding of process steps, technology constraints and human skill dependencies. There are unrealistic expectations regarding organizational change, such as changes in current roles and responsibilities and reductions in overall team size. In retrospect, organizations have realized that they need to retain staff so that they can continue to support process variations and exceptions – including tasks that cannot be automated. Additionally, there are gaps in training and development, leading to delays in organizational restructuring (roles, sizing, etc.). These delays have led to cost overruns and increased resistance among team members, as well as among leadership in supporting or sponsoring any follow-on work.

The challenges above need to be addressed immediately if firms aspire to improve and automate processes while leveraging existing infrastructure (licenses, processes and bots). These challenges can be resolved by revisiting the key strategic components of the automation program as outlined below.

Our Recommendations & Solutions

Business case: The key to program success starts with clarity in business drivers, planning for known and unknown dependencies, and reliable estimates that can help set expectations. The business case definition should include ongoing support costs, transition costs, retained human labor costs and overhead costs, including opportunity costs.

Non-financial case: While a majority of RPA opportunities tend to be “value” driven, it is advisable that businesses start considering additional benefits. These include reduced time-to-market, improved user experience and better compliance, while allowing to provide differentiated offerings in the market.

Multi-Technology solution: RPA as a stand-alone technology has several limitations. Most leading RPA products are unable to manage multiple and complex rules, transform data, orchestrate large workflows, perform analytics or take on advanced automation technologies such as optical character recognition (OCR) and machine learning. As next steps, organizations should now assess opportunities that involve a mix of RPA and other re-engineering and automation techniques and technologies. This will help automate processes and tasks that involve considerable human effort such as reading and processing information, making rules and experience-based decisions, and managing multiple human-system interactions.

BOT management: The utilization of bot infrastructure in several firms currently does not meet expectations. There is a strong case for reusing bots across processes wherever feasible, and, approved by business, technology and risk teams. This would involve building and maintaining a bot catalog that can help provide a consistent and updated definition and profile of existing bots. The updated catalog will help the existing governance and program management processes to facilitate decisions on bot sharing, scheduling, risk and controls management, as well as information security.

Governance model: Enterprise-wide transformative programs often require joint effort and planning by disparate organizational functions. Specifically, automation programs impact a diverse set of functions such as business, IT, HR, training, procurement and facilities. It also impacts current contracts with software vendors, system integrators and BPO partners. The center of excellence should be empowered and sponsored by business leaders. This will help in rolling out novel initiatives that focus on higher capacity utilization, improved and predictable returns on investment, and enhanced service offerings.

The recommendations outlined above have been implemented at several of our clients’ businesses with promising results.

For a fund management firm, we successfully automated complex processes involving multiple systems, human decisions, human system hand-offs and interfaces that were considered unviable. The firm is now using a mix of technologies including data automation (workflow, virtualization and dashboards) and RPA to automate processes across operations (reporting, self-service, etc.)

In a telecommunication firm, RPA was recently used in collaboration with customer service and workflow management solution to deliver a seamless experience for agents and customers across order management processes, allowing for quicker turnaround and fewer costs. The automated process supports a global customer base with customized support based on customer tier, region and product.

While each industry vertical and firm is unique, the considerations and recommendations outlined are applicable to most firms and scenarios. These recommendations can help organizations venture into areas left out due to process, technology, organizational and financial constraints. It would also help organizations to innovate and provide differentiated products and services at reduced costs, thus disrupting existing industries and evolving newer business models.