CW Developer Network

Sep 11 2019   4:47PM GMT

RPA series: delaware – the road to ‘smarter’ RPA

Adrian Bridgwater Adrian Bridgwater Profile: Adrian Bridgwater

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This is a guest post for the Computer Weekly Developer Network written by Simon Harbour, UK Technology Lead, delaware.

The company… delaware consulting works to create ERP and ICT solutions and services applying the ecosystems of its main business partners, SAP and Microsoft. 

TechTarget defines Robotic Process Automation (RPA) is the use of software with Artificial Intelligence and Machine Learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform — these tasks can include queries, calculations and maintenance of records and transactions.

Harbour writes as follows…

One of the core uses of RPA today is in aiding Enterprise Application Integration (EAI) processes.

RPA helps simplify and streamline activities within the enterprise through the integration of legacy applications and is especially useful when there are no specific APIs in place to facilitate the integration. Key differentiators over more traditional integrations include speed of implementation; equivalent added value; lower costs; integration with BPM tools, and high levels of adoption by end users thanks to the use of low-code development platforms.

RPA is also being used extensively today both internally to streamline IT operations and, externally, to automate manual tasks and help organisations on their digital transformation journey. In an internal context, keeping the lights on and systems ‘fed and watered’ are typically repetitive tasks that are ideal candidates for RPA automation, especially where the right API doesn’t exist due to aging legacy systems. RPA can provide quick, point solutions to solve high-volume process automations.

Recurrent monitoring

We have seen RPA used to improve recurrent operation monitoring processes, thereby helping reduce mistakes and processing time.

In an external context, RPA tools are one component of the integration within the digital strategy toolbox and are often complemented by other tools like business process management software (BPMS) and process mining tools when attempting to automate and streamline processes.

One area where RPA helps in this context is in addressing improved customer service. It is increasingly used in conjunction with workflow management and other software tools to enhance customer experience and ensure every customer interaction is guided to the best channel for a specific/individual case.

Most organisations believe that providing multiple channels for customers to interact through will deliver a better experience. In reality, this often leads to confusion, delays and frustration. By guiding customer interaction to a specific channel based on the issue type, we have seen a reduction in errors, subsequent and repeat issues and a significant increase in reported customer experience.

RPA with OCR

Looking ahead, the future looks bright for RPA. The world is evolving quickly, with collaboration being an increasingly central element. Combining forces brings new opportunities.  Vendor communities are great vehicles for strong collaboration that facilitate both knowledge-sharing and accelerating progress. The area of optical character recognition (OCR) is a good example of this. Some RPA vendors are building their own tools while others are focused on integrating existing solutions. Both work and deliver a higher added value to the bots.

So where does RPA go next?

With a customer move towards a best-of-breed approach in terms of application landscape, cross-platform interconnectivity becomes a priority, especially in terms of data governance, stewardship and compliance.

In addition, operational excellence requires short and agile roadmap implementations; customer excellence requires a customised approach within standard processes – and RPA provides the vehicle to get there.

Smarter RPA

The most significant move, however, is towards smarter RPA. Even if this is still work in progress, RPA software vendors are either developing their own machine learning capabilities or leveraging the capabilities of more established platforms such as Google, Amazon and Microsoft. An interesting focus on the horizon is Artificial General Intelligence (AGI), in the words of the AGI Society, ‘an emerging field aiming at the building of “thinking machines”; that is, general-purpose systems with intelligence, comparable to that of the human mind.’

The future of RPA will see lots of change. The nature of some of this is uncertain but one thing is clear: we are moving inexorably closer to smarter RPA.

Harbour: the RPA future is bright.

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