The intricacies in doing business has increased in recent years. Uncertainties in the macro environment, from political to technological shifts, have given rise to a challenging business climate where organizations compete to differentiate. New and innovative ideas are essential to keep up with disruptions and improve business outcomes. Automation of manually intensive processes in service industries is a lucrative option to save human efforts, minimize errors, and reduce operating costs.
Automation projects typically start on a positive note. However, as organizations go deeper in the implementation phase, challenges crop up, which sometimes lead to failure of the project. Is automation really that tough to manage? The answer is a definite ‘no’ if we avoid some of the common pitfalls.
An automation project, following either traditional waterfall model or agile methodology, is subject to certain risks that can derail the project or pose challenges in completion. Identifying the top risks and applying ways to mitigate them effectively without affecting project schedule or stakeholder relationships leads to successful automation implementation.
Automation and its core
There are three levels of automation:
- Basic desktop automation - such as macros or local automation
- Tool based scalable robotic process automation
- Intelligent automation which is self-learning and cognitive in nature
Most organizations have already achieved level 1, which run in the form of macros with their own limitations. At level 2 and 3, when tool-based automation is undertaken, challenges arise
Top risks in robotics implementation
Robotic automation implementation is not a standalone deployment unlike traditional application development and deployment. It is heavily dependent on the process, applications, and the technical infrastructure on which these applications are hosted, and how robots interact with these applications and process flow. Hence, risks arise from the system environment and affects the governance model.
Risks in assessment
The objective of automation is to gain financial benefits in the form of reduced human resources, or simplified processes. A gap between the efforts for automation and the benefits derived is a major challenge. For example, an activity that is performed at lesser frequency, or has very few people working on it will not give expected benefits or derive ROI from automation. In other scenarios, processes selected for automation have limitations such as shorter cut off times, need for manual judgement, or misjudged volumes, which make automation implementation complex and some-times, not feasible.
Risks in technological infrastructure
Technological infrastructure includes the setup - physical desktops, VMs, VDI/Citrix - and each of them is only compatible with certain automation tools. Hence, selection of the right infrastructure setup is a challenge. Non-compatibility of an automation tool can lead to wastage of efforts in a project. Another common environmental issue is frequent changes in underlying applications in robotic deployments. Unplanned and sudden changes can stop a robot. Few applications have dynamic controls, which can change at some intervals and affect robots. In banking environments, availability of data is a major challenge too.
During RPA deployment, data availability and technological environment mismatches are the major issues related to technology infrastructure, followed by issues in application infrastructure, application dynamism, and non-compatibility with automation tool.
Multiple stakeholders are involved in the automation of a process – For e.g. one team finalizes the requirements, while another performs testing, and the end user is completely different. This leads to challenges of expectation mismatch and rework. It is always preferred to have one single team throughout all phases of project to give and test automation requirements.
Attrition leads to a lack of continuity and affects the automation project with respect to quality and timely delivery. Considering availability of resources, some clients prefer automation projects to run on staff augmentation model-wherein they hire automation resources for a temporary period. The challenge here is delivery quality, lack of support from senior technical resources, and project management. Typically, such projects encounter issues post going live and are unstable in nature.
Overall, the major risk contributors in robotic implementation are infrastructure (64%), followed by assessment (19%), governance (12%) and resources (5%) – (Figure 1).