Opinion: What is real intelligent automation?

Opinion: What is real intelligent automation? Don is CTO at Pegasystems and responsible for Pega’s platform and customer relationship management (CRM) applications. He has 20 years’ experience delivering enterprise software solutions for Fortune 500 organisations, with a focus on digital transformation, mobility, analytics, business process management, cloud and CRM. Don has led enterprise software implementations and provided technology and architecture consulting to senior business and technology executives from Fortune 500 organisations, including American Express, Citibank, JP Morgan Chase and BP. Don holds a BS in Physics and Philosophy from Boston College.

Intelligent automation reduces costs, improves efficiency and allows businesses to initiate change through technology. When applied to business operations or customer services, it has proven to be an invaluable piece of technology as it improves productivity thus saving time in the process with quicker responses. With intelligent automation, manufacturing giant Siemens has driven 10 times faster processes at a tenth of the cost.

However, some software vendors place commodity AI-like OCR or image recognition combined with robotic process automation (RPA) under the same umbrella as intelligent automation. Others label intelligent automation as just smart robots when in reality there is much more to it. The following three themes are essential to acquiring intelligent automation:

A customer-centric business architecture

It is key to have a business architecture that operates from the centre-out, instead of top-down or bottom-up. This way, businesses can start their technology structure in a customer-centric format that focuses on solely the customers’ needs. This format is preferable to adopting a top-down approach, as a technology foundation developed from the top-down around front-end channels can lead to siloes, which increases the costs and can also be time-consuming. This method requires changes made to the architecture to then be updated onto each channel, whether it be mobile applications, contact centres, or chatbots etc. because each one is hardcoded and independent from the others, it would need to be done in this manner. Likewise, a platform built from the bottom-up – from databases, mainframes, ERP systems, etc. is just as problematic, as they are also built around siloed products, not end-to-end customer journeys.

A centre-out business architecture captures the micro-journey – processes needed to reach each outcome, for example, like applying for a loan or resolving a billing inquiry. It further ensures that there are clear and consistent stages an organisation must incorporate for every customer query or case, and also that these variables are accessible to each employee working in any channel. For example, if a customer were to contact a company’s customer service line, the representative will be able to view information about the status of the customer’s query, regardless of which channel they used. By breaking down siloes, relevant and accurate information can be provided quickly to customers, and fewer gaps in customer service will eliminate delays to improve satisfaction. 

Unlike the top-down approach, in the event that a change is made to a microjourney, this will be automatically reflected across all channels, thus ensuring that there are fewer errors made which increases the level of customer satisfaction and by extension, customer loyalty. American Express implemented a centre-out approach and saw customer satisfaction triple as well as a 10 percent increase in cardmember spending.

Case management and AI 

Combining the decision-making capabilities of AI with case management is crucial to getting work completed. If AI can be likened to a brain – doing the thinking, case management is like a muscle, because it makes each step happen. For example, email bots can quickly comprehend the reason, sentiment and data in a customer query using natural language processing. With case management, the issue would be automatically resolved or it would be routed and flagged to the right employee based on the level of priority and urgency.  

A low-code approach

Finally, a model-driven, low code environment breeds the effective collaboration of both business and IT in the development process, as the use of visual forms of software helps technical and non-technical staff to work together smoothly. Moreover, all work is documented, versioned and auditable so that processes can be managed and traced.

By referring to one single information hub, business and IT teams can see all the parts making up an application, and each visual form. This allows workers to design each micro-journey, identify customer personas for each one and highlight the channels they’ll use to interact with them. Plus, all the systems and data necessary at each stage of each process can also be decided.

Fast deployment, fast results

By applying a centre-out approach to intelligent automation, organisations can achieve faster deployment and faster results. For companies to achieve real intelligent automation, a single unified platform that combine AI, robotics, and case management needs to be implemented to plan customer outcomes. Agile platforms that enable businesses to easily adapt in times of change is the key to success in a constantly evolving environment. Businesses have the means to retire poor technology and inefficient processes by investing in intelligent automation. Those that do will achieve greater results at a lower cost while delivering a boost in customer satisfaction.

(Photo by Robina Weermeijer on Unsplash)

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