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Driving Digital Transformation with an efficient RPA-AI operating model

December 13, 2018 - Aditya-modi


To stay competitive in today’s era, enterprises across the world are increasingly turning to emerging technologies to drive digital transformation. Those who fail to adopt digitization of their processes are replaced by those who leverage the emerging technologies successfully. Digital transformation fulfils aspirations of enterprises like Improved operational efficiency, higher productivity and enhanced customer satisfaction. While a broad range of technologies have emerged to achieve this, automation technologies, specifically Robotic Process Automation (RPA) has been proven impactful.

RPA technology tools are relatively cheap and fast but Enterprise Architecture (EA) professionals need guidance on building an effective RPA strategy with AI capabilities to deliver long-term value to an organization.

Robotic Process Automation – The Need

In a recently commissioned study by Forrester Consulting, ‘Automation Shapes Digital Transformation’, the best RPA operating model practices delivering long-term value to stakeholders were explored. With over 300 executives from enterprises of different scale and sizes across industries and world, the survey captured the automation journey of enterprises from initiation to implementation, then scalability with focus on challenges with controlling and operating RPA. In the study, it was found that while there are various drivers that determine the need to implement RPA in an organization, lowering cost was the top initial driver. RPA lowers costs by replacing humans performing low value tasks. It was also determined that enterprises employ digital workers to improve employee experiences. Taking over routine tasks enables employees to focus on more strategic work and helps reduce time-to-market with products, adding a positive impact on employee experience.

Over the years, RPA has proven to be beneficial in functions such as finance & accounting, human resources, supply chain, logistics, manufacturing and customer support. In the study, ‘Automation Shapes Digital Transformation’, almost 74% of respondents said that RPA made a huge impact in functions such as finance and accounting, whereas the least was seen in logistics (23%). Apart from operational functions, RPA has helped enterprises taste success in business functions too. Rule-based tasks such as complaints handling, onboarding and reporting have seen the most success with RPA.

Robotic Process Automation – Implementation Challenges

With so many functional benefits, it is clear that RPA is a robust solution to automate simple and repetitive tasks. Yet there are so many such tasks on a day-to-day basis that companies can easily drown in the ocean of what RPA can automate. In spite of multi-tenancy options with cloud and on-premise models to reduce RPA operating costs, 9 out of 10 firms struggle. 81% of firms say their total cost of bots’ ranges from $15k to $25k per bot.

Implementation of RPA is also often seen as a tedious and challenging task. Firms struggle with governance when deploying RPA. 65% seek RPA solutions providers that are able to control and operate for them. Assessments to determine the best application and poor governance cost firms extra. Adding to this is the risk of poor governance, higher compliance risk, ensuring robust security against data leak control, data privacy breaches, along with getting management buy-in.

Key to RPA implementation success

In order to overcome implementation challenges, it is important to build an assessment model to guide the process of RPA selection and feasibility. It’s essential to formalize the operating model early in the RPA journey and to guide the process of RPA selection:

Traditional RPA frequently relies on desktop-based tools that replicate the work of a person to complete a task. With this, licensing costs can quickly spiral out of control as automation is scaled across the company. However, the vast majority of respondents reported the TCO of a bot to be anywhere between $15,000 to $25,000 (81%). Only 18% reported the TCO to be more than $25,000 per bot.

It is imperative to establish a strong central governance process to ensure standardization across the enterprise, and to ensure that the enterprise is prioritizing the right opportunities. It is also important that IT is informed of, and represented within, the governance process. Enterprises are always on the look-out for additional control points for Bot Design and maintenance, almost 55% said controlling operations and 53% ensuring business continuity and creating governance standards to be the major requirements.

A strong RPA implementation team would bring together an operator who knows the tasks, an RPA expert who knows what can be automated and a business owner who knows how often the task is performed overall and what is the gain of automating it. To build an enterprise wide capability, RPA’s ability to support multichannel communication and interactions, the ability to determine intent based on aggregated interactions, NLP, reporting and analytics, Machine learning capability and ease of upgradation is said to have convinced many enterprises to change their opinion about RPA.

Lastly, RPA should not be seen as the be all, end all of enterprise digital transformation efforts. It should be considered as only a part of a wider range of automation solutions.More important is to understand what processes should be automated and which should be left untouched. This demands a strong process mining capacity as the starting point.EdgeVerve provides platform capabilities spanning entire automation journey. The award-winning automation platform, AssistEdge identifies automation opportunities, draws business process maps and variations and helps companies increase employee productivity, process accuracy, reducing turnaround time and operational costs. Acclaimed for its RPA Analytics and AI Integration capabilities by Forrester, AssistEdge caters to multiple roles and industries. Enabling enterprises to span the entire gamut of automation continuum from deterministic through predictive to cognitive automation, it leads the way to a wider range of enterprise benefits.

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