RPA Programs Stumble to Be Mainstream in Financial Services
Only 20% of Organizations Are Confident They Can Measure the Impact of RPA Roll-Out and 70% Claimed It Was Hard to Get Productivity Data Covering People and Robots
Financial services companies looking to exploit Robotics Process Automation (RPA) are finding it difficult to progress deployment beyond proof of concepts because established measures of performance do not provide the precision to be confident of delivering the potential business benefits.
This is according to research conducted across 50 North American mid to large-scale financial services organizations by ActiveOps, a leading provider of digital operations management solutions.
RPA is autonomous software programmed to follow rule-based tasks just as a human would. The difference is that robotic decision making and outcomes are predictable, consistent, and 100 per cent accurate.
Julian Harper, CEO, North America, ActiveOps, stated: “Many financial service organizations are making significant commitments to shareholders and customers based on efficiency gains through new digital processing technologies. These findings highlight an increasing concern that roll-outs and investments are being limited by the capability to orchestrate and optimize work and resources effectively. According to the research only 20% of organizations feel confident in their ability to measure the impact of RPA technology across complex diverse functions where robots are impacting on small parts of multiple human activities.
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Key findings include:
- 45% of financial services organizations questioned are running 10 or more robots in their operation.
- When asked how they measured the productivity of robotics, unsurprisingly perhaps, 90% of those who responded stated that it was based onnotional FTE hours saved – calculated from the activities of the robot doing tasks quicker than a human. I.e. measuring the theoretical effort saved, not the actual staff time able to be used elsewhere because of the reduction in human effort through RPA.
- Also, interestingly 48% of the sample stated that they saw variances into robotics performance – something not anticipated when preparing business cases
- 70% of the sample stated that is was not easy to get productivity data on their robots in isolation – even without the complexity of overall productivity involving human and digital processing systems.
Mr Harper continued: “RPA deployment is now progressing beyond ring-fenced pilots that can be tested outside the conventional IT and delivery operations functions. Companies are now encountering the challenges of operationalizing the technology such that it makes a genuine and meaningful difference to business outcomes. In delivery operations these means a whole new set of requirements in measurement and management processes to optimize human and RPA capacity with the processing work available. Organizations have to anticipate work and balance capacity to new levels of precision, and the winners will not be the number of robots deployed, but the organization which makes them work the hardest.”
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The following is a four-step checklist of operational control necessary to be confident to consolidate savings across delivery operations. Any organization embarking on an RPA journey without these capability within their operations is likely to be struggling to make it to the mainstream – or incurring a high level of risk based on travelling in hope.
- A common and consistent framework for quantifying work and capacity across delivery operations independent of the specialism or function involved – typically hours of work and hours of time, measured within / by day as a minimum.
- Define and operate productivity measures accurate and valid for an individual within a day (ideally an hour).
- Operate a proactive deployment process operating daily and weekly to manage marginal capacity between teams or resource pools.
- Establish a numerate process for setting, planning and then controlling actual use of time realized from RPA deployments
“RPA offers opportunities for radical improvements across a range of cost, quality and service outcomes but any organization can buy software licenses – the differentiation comes from their application and like the first industrial revolution, new delivery technologies need equally new management processes. Our survey highlights significant constraints on the anticipated ROI that may not be appropriately managed in many organizations today” concluded Mr Harper.
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