Artificial intelligence, analytics, and automation, while offering transformative potential business value, need an integrated approach across data, processes, and technologies. When deployed in isolated use cases at task-automation levels, they do not scale and provide their expected transformational impact on end-to-end process outcomes.
Any major business process—from supplier selection and materials procurement to human resource management and finance functions—has multiple integrated workflows that span organizational units such as HR, finance, and operations. The sub-processes and workflows within each end-to-end business process include many tasks, some of which are fairly stable and structured with standard operating procedures and minimal variances. These simple processes are usually the low-hanging fruits for automation, and businesses can significantly improve their efficiency and accuracy with technologies like robotic process automation. But some functions and processes involve complex tasks that rely more on human experience, knowledge, and skills and involve loads of exceptions and variances in decisions and actions; these cannot be automated using deterministic and pre-coded static tools and technologies.
A number of key observations and qualitative customer interactions emerged from the survey we conducted with AntWorks.
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