The recent release of IEEE 2755.1—2019 Guide for Taxonomy for Intelligent Process Automation Product Features and Functionality supports companies and users in the growing process automation product space. Yet, there is still a good deal of confusion around Intelligent Automation (IA), often referred to as the “fourth industrial revolution.” This new and rapidly changing technology field comes with implementation and scale challenges that businesses need to fully understand to achieve success.
Intelligent Automation is a decision to embark on a journey to do things differently, bringing design thinking, task automation, and eventually prescriptive analytics together to fundamentally transform a part of a business’s structure. It should be noted that the marketing of Intelligent Automation can often be misleading, implying that once a proof of concept is done and a pilot process running, it is smooth sailing from that point forward. That is simply not the case.
Today, while numerous enterprises have proven there is value in adopting Intelligent Automation, many are struggling with scale. Drawing on experience, it’s useful to share identified “stall points” hindering implementation and scaling of an effective IA program. Identifying and addressing any one of the following 12 potential stall points can help avoid having to bring an IA program to a halt.
Design Authority
Design Authority is a key foundational element that leverages decades of software development experience into a resilient and robust framework. Enshrining your automation within a rock-solid Design Authority provides the standardization required for a bot production program to scale successfully. Design Authority allows for code reusability and system controls, as well as code review and release management, and provides a strong foundation for growth.
Effective Execution
While a Design Authority supports optimized production, there also needs to be consistency in execution, according to set standards. As automation is driven across thousands of business processes globally, an efficient execution mechanism becomes critical. Automation is, in reality, digital labor that is contributing to business operations. The roles and responsibilities of IT, the automation Center Of Expertise (COE), Design Authority and the business need to be clarified and governed.
Governance
Governance dovetails neatly with Design Authority and the COE. Effective execution will be determined by how well all coalition partners across the ecosystem work together. This includes demand management, as well as maintenance and control. Well-established governance procedures will provide corporate leaders with the confidence that the expanding automation program is managed by appropriate checks and balances.
Automation anxiety and cultural roadblocks
Automation anxiety is very real and must be tackled head-on. There is often excitement at first, where everyone believes to be in a supportive environment. Yet, natural human behavior is a familiar theme in major change programs and reflects many of the same concerns that any organizational change brings with it around fear, uncertainty, and doubt. Automation can create an additional set of concerns around job security.
Underestimating the benefits of automation
Establishing an effective set of metrics is key to gaining support for expanding an automation rollout. A common mistake is to focus only on cost benefits resulting from a specific process “fix.” Certain values, however, like risk reduction or defect elimination, cannot be measured in the same way as cost productivity, so defining not just a broad range of measures but also the different methods of measurement is key.
Keeping audit out of the loop
An effective strategy is to engage a consult audit partner as an automation program builds. Using a risk and control expert that is neither part of your internal nor external audit team can be very helpful. The cost of ignoring audits can be severe. Late in the day, for example, auditors could potentially tear apart the whole automation lifecycle process, questioning the very fundamentals of the automation configurations a program is built on.
Lack of an automation strategy
Most organizations don’t have automation strategies in place, although almost all operate with business and IT strategies. The lack of an automation strategy becomes a real hurdle to scalability. Without a strategy, an automation program will likely remain an “initiative,” stuck as a tactical solution.
Procuring with a limited view
Automation should not be treated as standard IT procurement. Automation is first and foremost a business tool and should be evaluated as such. However, while a business can sign off on the initial proof of concept, a scaled implementation costs significantly more and involves effective procurement.
Supporting adoption through change management
As automation is deployed across the organization, supporting the program through robust Change Management is critical, as it encompasses three kinds of change that need to be managed: people, systems, and processes. In effect, Change Management, or the lack thereof, can represent up to three distinct stall points.
Automation as an investment
A common mistake is for automation products to fall under the IT umbrella and its acquisition to be monitored through the lens of traditional IT procurement. Because automation is first and foremost a business tool, automation should be recognized as digital labor that is managed by the business—not a piece of software implemented by IT.
Security concerns
Organizations must include the well-established security processes of enterprise applications into the automation program. While the automation platform application is secure, how a particular automation is built might introduce new risks. The key is to “bake” enterprise-level controls and security into the automation platform so that IT and audit are satisfied on all counts. This is of particular importance in adhering to GDPR compliance.
Tracking true metrics for cost control
It’s key to demonstrate the total program yield against the cost of deployment. Organizations still operating via a traditional Waterfall methodology will find themselves easily stalled by the multiple, time-consuming, and tedious steps involved. In contrast, an Agile methodology links return on investment to every enhancement based on a pre- and post-implementation time-and-motion study measure, where every enhancement has a clear metric on hours returned to the business.
Conclusion
To overcome IA “stall points, a growing pool of expertise is becoming available. Tool providers can be useful to a point, but there is also marked value in seeking out automation process experts who understand the entirety of what makes for a successful IA program. Other relevant stakeholders, such as automation industry analysts who study successful programs and peers in other organizations where implementations are more advanced, are also good resources.
As corporations tap into these external partners, they need to figure out how to optimally engage with them to determine the direction they take–whether in standing up to their own COE and internalizing automation capabilities; outsourcing; or something in between.