Automation as a key driver of renewed business productivity has been much talked about. It’s a key expectation for businesses (and their employees) on their transformation towards becoming an Intelligent Enterprise.
However, there are many hurdles towards automating various aspects of a business’ operations, due to some of the limitations found in last generation tools:
- Rather than streamlining tasks requiring human supervision, additional steps are added to existing processes, creating opportunities for errors and increases in processing times. Existing automation tools often focus on tasks being completed – but as we know, business processes are made up of many tasks and interdependencies, each of which need to be addressed and orchestrated to truly automate a process.
- Automations, that rather than being ‘set and forget’, require as much (or often more) time being spent in configuration as underlying processes or data structures change during the growth or transformation of a business
- Automation development still requiring relatively deep technical expertise. This has compounded the two issues above in the past – stretched development resources becoming compromised with respect to the time spent on overhauling existing automation deployments, architecting & implementing new automations and then having to discover how processes and related tasks / interdependencies actually work.
Three key developments are now being integrated within automation technology, to improve both the effectiveness and efficiency of automation initiatives.
Dubbed Hyperautomation, vast new opportunities for businesses to improve front and back end process are now being unlocked through the following developments:
- Machine Learning bringing intelligence to automations. By leveraging the insights from data generated through the conduct of different tasks, as well as underlying corporate data, automations can be made much for effective and efficient through automations being able to dynamically address different issues as they occur – for example, an unforeseen process change, that would otherwise need to be resolved with the assistance of a developer, can be sensed and solved by these new automation technologies. This improves the experience provided to business users, end customers and of course developers also.
- Process Mining providing insights into how businesses really run. During projects to really explore different processes with customers, it’s often the case that the issue is ultimately decoupled from where people think the problem lies. Process mining allows for insights as to how the different steps within a process run with detailed metrics, providing transparency as to the “average” of a process, but also the extremes. It’s these insights that allow for the development of truly robust automations.
In conjunction with Machine Learning and Process Mining, the incorporation of Low/No-Code technology within automation tools will support this Highway to Hyperautomation across businesses. Low/No-Code technology, where people without any programming experience can develop software using simple interfaces, will allow those employees such as business process owners that know and operate business processes most closely to develop new automations as needed. This will supercharge the uptake of these technologies, assisting companies in their transformation initiatives.
SAP has released exciting new solutions that address each of these hyperautomation drivers – from Intelligent RPA, available as part of the Business Technology Platform, to the innovative SAP Ruum solution, allowing frontline workers to develop and deploy automated workflows using low-code functionality. In conjunction with our Spotlight and recently acquired Signavio Process Mining technologies, the highway to hyperautomation is here!
This article originally published on Linkedin.
