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New Independent Study Reveals Why Not All Software Robots Are Created Equally

 

By Leslie Willcocks

Robotic Process Automation (RPA) continues to be a growing success story. In 2016, RPA alone experienced a 68 percent growth rate in the global market, with 2017 maintaining this momentum. Some reports have even predicted a US$ 8.75 billion market by 2024. However, merely investing in RPA is not an instant recipe for growth.

In “Service Automation Robots and The Future of Work” (2016), my colleague Mary Lacity and I highlighted successful RPA deployments and how organizations were achieving triple wins for their shareholders, customers, and employees alike. We continued tracking these developments in 2017 and also noticed something different — many less successful journeys. In practice, it appears that automation success is far from guaranteed. Wider reports provide anecdotal evidence of between 30 to 50 percent of initial projects stalling, failing to scale, being abandoned or moving to other solutions. Our most recent research has examined in detail both successful and more challenged automation deployments. It turns out that service automation — like all organizational initiatives that try to scale — can be fraught with risk. We’re seeing 41 specific risks that need to be managed in eight areas: strategy, sourcing, tool selection, stakeholder buy-in, project execution, change management, business  maturity and an automation center of excellence.

One of the key risk areas is tool/platform selection. Because of the hype and confusion in the RPA marketplace, clients risk choosing the wrong tool(s), too many tools, or bad tool(s). By early 2018, over 45 tools or platforms were being sold as “RPA” and over 120 tools were being sold as some form of cognitive automation. Because the space is relatively new to many clients, it’s difficult to assess the actual capabilities and suitability of these tools. Clients must be wary of hype and “RPA washing”.

In our new report on Benchmarking the Client Experience, we extensively polled clients at Blue Prism on the results they’ve been getting by integrating RPA into existing business processes. In order to get the most valuable feedback, we set the bar high in requesting client assessments of the Blue Prism RPA platform on the following criteria: scalability, adaptability, security, service quality, employee satisfaction, ease of learning, deployment speed and overall satisfaction. From our qualitative research into process automation, these emerged as the most critical and essential characteristics and requirements for a successful enterprise-grade RPA implementation.

The overall level of satisfaction with the Blue Prism platform was extremely high in our survey. Respondents reported a 96 percent overall satisfaction rate, with 79 percent of respondents ranking Blue Prism’s platform a six or seven on a seven-point Likert Scale. Based on our 25-year research history into process improvement initiatives (BPM, shared services, outsourcing, six sigma, etc.), these are extremely high RPA satisfaction levels. Our research into IT and Business Services outsourcing finds only 20 percent of vendors getting “world class” performance, 25 percent getting good performance, 40 percent “doing OK”, while 15 percent experience poor outcomes. The record on IT projects also continues to frustrate. The most recent (2017) Standish Group CHAOS report found only a third of IT projects were successfully completed on time and on budget over the past year – the worst failure rate the Standish Group has recorded.

What, then, accounts for the impressive 96 percent overall satisfaction rate with Blue Prism?

Our observation is that not all RPA offerings are the same. The capability of RPA software depends greatly on the origins and orientations of the supplier. If designed as a desktop assistant, many RPA tools experience problems with scaling, security and integration with other information systems. Other RPA vendors offer RPA which is effectively a disguised form of what we have described as a “software-development kit,” needing a lot more IT development by the in-house team or the RPA vendor than first imagined, and incurring unanticipated expense, time and resources. True enterprise RPA, however, is designed from the start with a platform approach, to fit with wider enterprise systems. This might make it more expensive initially, and require more attention in the first few months of trial, but true enterprise RPA platforms have proven to be an investment in success later in the deployment cycle, when compared to other RPA software that tends to run into real problems.

Our qualitative research also suggests that some RPA tools are not easily scalable, especially those based on a recording capability, or requiring a lot of IT development. This occurs because some RPA tools are not designed as configurable service delivery platforms that can be integrated with other existing systems. These also need a lot more management involvement than clients and their vendors often expect. Many clients, moreover, do not put in place the necessary IT, project and program governance (rules and constitution, who does what, roles and responsibilities), and often do not use built-in tools that contain technical governance.

This, of course, is not the whole story. An RPA and cognitive skills shortage is already upon us. This means that retained capability and in-house teams are sometimes not strong enough – a situation not helped by sometimes skeptical senior management under-resourcing automation initiatives and not taking a strategic approach. Consultants are also hit by skills shortages and cannot always provide the support necessary — this is also true with business services outsourcing providers. We are also finding that clients often do not give enough attention to stakeholder buy-in and change management. Given these emerging challenges, the Blue Prism client satisfaction level are very notable indeed.

To download the report, click here.

Leslie Willcocks is Professor in the Department of Management at the London School of Economics, and co-author, with Mary Lacity, John Hindle and Shaji Khan, of the Robotic Process Automation: Benchmarking The Client Experience (Knowledge Capital Partners, London).