Introduction – 5 for Friday
Welcome to our latest edition of 5 for Friday. In this edition we’re discussing what’s next for Robotic Process Automation (RPA).
RPA has been popular for several years now and many organisations have adopted the technology to automate previously manual processes. Although not universally successful, RPA has, for a lot of organisations, delivered significant operational benefits and savings. Performing high levels of often mundane and repetitive work previously done by the human workforce but now performed by the new digital workforce.
As with most technologies, what it does, how it does it and even who provides it continues to evolve.
What’s next for Robotic Process Automation (RPA)
In this article we discuss 5 areas where the world of RPA is evolving. Are you evolving with it?
1. Intelligent Process Automation
Intelligent Process Automation (IPA) extends Process Automation through the use of Artificial Intelligence (AI).
AI enables process automation to go beyond rules based automation and the requirement for structured data. It enables the processing of unstructured text (for example, in documents and emails), more intelligent interactions with people (e.g. chatbots), visual processing (images and video), to make decisions based on analysing high volumes of data and by learning from human actions. This capability both extends the reach of the digital workforce and also augments what the human workforce can do through assisted automation and virtual assistants.
Increasingly AI capabilities are being built into RPA platforms as well as being made available through off the shelf and customisable cloud services.
2. End to End Process Automation and Transformation
Many organisations began their automation journey by automating tasks. With tasks typically being operations that were previously performed by individuals or teams within a particularly department e.g. invoice processing within Finance. For organisations that had teams of people performing the same tasks, automating these tasks enabled RPA to deliver significant operation savings. When organisations automated these tasks they generally took the ‘as-is’ task/process definition and tweaked it to enable it to be performed by a robot (digital workforce).
The above approach enabled successful organisations to achieve fairly rapid results and a reasonable to good level of return to the organisation. Having automated these types of high volume tasks though the organisation needs to evolve its approach to further scale out the digital workforce and to enhance the benefits it delivers. A key way to do this is to look at end-to-end business processes and to take a truly transformational approach to how the organisation achieves the desired outcomes that process is expected to deliver. This transformation should be based on redesigned business processes that are optimal for both a digital workforce as well as the human one, overcoming historic assumptions around what people do and the traditional silo based organisation structure. Enabled organisations to operate in ways that are truly customer focussed and operationally optimal rather than constrained by the way “it’s always been done”.
3. Citizen Developers
Many of the RPA vendors have actively been promoting the concept of ‘Citizen Developers’. Where members of operational teams are empowered to automate their own processes rather than having to rely on automation being performed by a separate Centre of Excellence (CoE). Some call this democratising RPA. The objective is to enable more of the organisation to contribute towards automation, reducing the bottleneck on the CoE, increasing the level of automation across the organisation and enabling automation of individual / smaller team tasks that previously wouldn’t have justified the investment of CoE time.
Some organisations have already achieved success with this broadening of the automation team. It does generate challenges though. The RPA vendors have invested significantly in tools to simplify process capture and automation creation, even automating some aspects of this. Creating robust, reliable automations though still require a structured approach and a level of technical understanding that is typically only found in a small proportion of the operational team. Governance is also important in order to manage time, ensure quality and to maintain automations (see also operating at scale).
4. Platforms and Integration
RPA platforms are continuing to evolve, originally built around UI automation they have, and continue to be, enhanced to provide capabilities traditionally considered in be in the scope of other solutions e.g., low/no-code platforms, business process management, process mining, enterprise integration and even customer engagement. These improved capabilities, such as simplified API based integration, enable these platforms to overcome some of the issues with UI automation such as achieving real-time performance at scale.
There are also now many more RPA platform vendors, whether standalone platform vendors or as RPA capabilities added to enterprise business applications (SAP, Oracle etc). This more competitive marketplace has created new licensing/pricing models, lower cost options, new cloud delivery models, and even the flexibility to utilise more than one vendor platform. This flexibility, could, for example, mean utilising an alternative solution for assisted automation than is being used for centralised unattended automation.
Large organisations in particular might need to consider how they continue to evolve what they can achieve with automation without becoming totally dependent on one vendors platform.
5. Operating at Scale
Operating at scale can be a challenge. For some, the initial challenge is being able to find enough good automation opportunities to scale out beyond the initial low hanging fruit (see points 1 – 4 above which help with this). For others, the challenge is around maintaining automations. Unfortunately, not all automations are robust, platforms, systems and data evolve, and processes need to change as the business does. Many CoEs have had to increasingly allocate resource towards support and maintenance as their number of automations scale out and the criticality of the automation platform to successful operation increases. This can then, in turn, constrain the ability to continue to scale out.
Consider refactoring automations to enhance stability and maintainability. Take the opportunity to modularise automations to reduce duplication and the volume of ‘code’ under support. Perhaps even consider replacing some UI automations with API based integrations. The cost of the automation platform can quickly become high (licensing & run-time environments) when automations are created without considering how they will run efficiently i.e., with minimal bot run-time and concurrently with many other processes. Utilise the available production performance data to optimise process implementations freeing up capacity and reducing costs.
If you’re not yet at scale, now is the time revisit how you approach automation. Consider aspects such as maintainability, performance and future change as processes are designed and implemented. Don’t just focus on implementing a functional as-is automation as it can often come back and bite you!
We hope you’ve found this article interesting. If you have any questions about any aspect of this article or need any insight, inspiration or problems overcome then please get in touch at email@example.com. Our mission is to help organisations realise the full potential of intelligent technologies such as the evolving world of RPA.
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