Intelligent Automation — Bringing Together The Best Of RPA And Human-Like Cognitive Tech

Banwari Agarwal

Banwari Agarwal

CEO – F&A, BFSI and IA

Intelligent Automation (IA) — or Intelligent Automation (IA) for short — takes digital process transformation to an all new level. Indeed, it makes the actual reinvention of knowledge work possible.

Combining a new generation of cognitive technologies that mimic human capabilities to solve complex, end-to-end business challenges, IA represents an evolution in process automation that requires minimal — or zero — manual intervention.

With Intelligent Automation, organizations can improve customer and employee experiences, enhance operational compliance and manage a multitude of workflows with greater speed, transparency, consistency and efficiency.

In essence, IA results in creating a technology-based digital workforce that works hand-in-hand with the human workforce to get the job done. Applications and use cases have spread quickly, often delivering up to a 60% impact on business efficiency.

But how does IA work? Can it be integrated with existing IT systems? And what do you need to know before deciding when — or how — to intelligently automate?

Bringing Intelligence to Process Automation

IA goes far beyond simple rules-based, mechanist robotic process automation (RPA). Instead, new technologies like natural language processing, speech recognition, computer vision, and machine learning (ML) are  used to replicate the capabilities of human work — not just automate it.

 

Intelligent Automation — Bringing Together The Best of RPA and Human-Like Cognitive Tech

 

Machines with AI and ML cognitive intelligence can process vast amounts of structured and unstructured data with the ability to analyze, understand and learn on the go. This “smart” automation rests on algorithms that can train on vast data sets. The result? Competitive advantages that can dramatically elevate business value, scale operations and boost ROI in ways never seen before.

 Intelligent Automation can…

  1. Standardize Processes and Increase Efficiency
    Automation tools supported by smart technologies can help standardize systems while processing complex data and responding to operational deviations to reduce functional errors for consistent and reliable performance.

  2. Enable Scalability and Boost Productivity
    Automating intelligently across an IT infrastructure provides greater system-wide agility and flexibility for growth and adapting to changing business needs. Workflow integration and enhanced monitoring eliminates bottlenecks to increase productivity.

  3. Save Time and Money While Reducing Error and Risk
    Reducing — or eliminating altogether — the human effort cuts the time consumption and costly mistakes inherent in manual operations, which account for about 80% of production errors and up to 70% of all electronic equipment failures.

  4. Improve EX and CX
    Workers unencumbered by mundane, repetitive tasks are freed to concentrate on more intellectually challenging projects. Intelligent automation can improve systems that make employees’ work lives simpler and more fulfilling. For customers, IA helps deliver immediate services which, in turn, boosts customer retention and increases overall customer satisfaction.

  5. Ensure Process Compliance
    IA can help protect records, secure data privacy, and ensure compliance with government, legal, and financial regulations using tools which consistently maintain workflows without deviation or mistake.

Organizations that automate intelligently are also seeing exponential improvement in their business objectives and KPIs. The Sutherland Global Services Robility solution has helped businesses achieve:

  • Profitability improvements of up to 9%

  • Revenue upsides of 16%

  • Employee satisfaction and CSAT improvements of 18 points

  • Reductions in total cost of operations of up to 30%

The “Nuts and Bolts” of IA

Infrastructures incorporating Intelligent Automation bring together RPA and cognitive intelligence using three different types of human-capability mimicking systems. Each plays its part in helping to solve complex problems and improve interactions between customers and employees.

  • Systems that “think,” “see” and “hear” — making decisions autonomously when they encounter variances

  • Systems that “learn” — executing highly dynamic, non-rules-based processes while making optimal adjustments when environments change

  • Systems that “do” — replicating, repetitive rules-based human actions

Sutherland applies all three types of systems with AI and ML technologies, including computer vision, cognitive automation and autonomous robotics integrated with third party cognitive services from Google, Microsoft and others.

Computer vision involves robots with intelligent eyes that can recognize screen elements through contextual relationships. They accurately identify and classify objects then react to what they “see” just as humans do to bring unrivaled accuracy and precision to automation.

 

Intelligent Automation — Bringing Together The Best of RPA and Human-Like Cognitive Tech

 

Cognitive automation uses language detection, unstructured data extraction and sentiment analysis that enables robots to extend automation to knowledge-based processes that otherwise couldn’t be covered. They not only automate unstructured content, but also interpret content and apply rules.

Autonomous robotics creates collaboration between both attended and unattended robots, which is monitored and managed for optimizing end-to-end workflow automation with centralized work queues.

The Right Path to IA

But before they can boost ROI through IA, organizations must first identify what — and where — their needs reside, understand how emerging cognitive technologies will impact their chosen systems and have a plan of attack for implementation. The biggest challenge to getting Intelligent Automation right is figuring out how to integrate these technologies with people and processes in a way that augments the current IT environment.

Unfortunately, poor understanding of needs and improper planning can stunt transformation from the start. In fact, our experience indicates that more than half of automation implementations fail to meet objectives and are considered complete failures.

 

Intelligent Automation — Bringing Together The Best of RPA and Human-Like Cognitive Tech

 

Often IT projects approach IA from a discrete task automation point looking to save money by updating siloed, disparate systems. Others struggle with choosing the right automation product, proof of concept, putting together the right change management strategy or identifying processes and making them work at scale. Different automation processes deliver different types of outcomes, and failing to define success criteria or insufficient planning without aligned business expectations leads to higher risk of  failure.

Leaders should keep these key elements in mind when considering IA implementation:

  • Determine the specific needs and identify the appropriate processes for automation

  • Understand the technology, its capabilities and whether it can deliver on expectations

  • Create a holistic strategy aligned with specific goals and a clear project scope with a roadmap for  future development and scalability

  • Choose the right vendor or partner to help outline and execute the project

Partners including Sutherland offer AI developers who can fix key areas that need improvement by examining a company’s organizational capabilities and undertaking a gap analysis. In some cases, existing systems and processes need to be altered or stripped down to incorporate AI. It may also take time to integrate legacy systems with new AI technologies. However, time and costs are quickly recouped as ROI increases with greater productivity following implementation.

Realizing the Potential of Automation

The benefits of implementing IA are well documented, and each manually operated process offers an opportunity to realize gain through digital transformation. Moreover, opportunities for creativity and innovation compound when human capital is freed to drive greater business results.

Identifying operational needs, aligning them with clear business outcomes and developing a strategy with the right technologies and a roadmap for future scalability highlights the path to IA.

 

Intelligent Automation — Bringing Together The Best of RPA and Human-Like Cognitive Tech

 

Collaboration with a partner established in service and technology can fast-track the process by designing and implementing customized solutions and guiding organizations through the challenges of implementation. They can show not just how to do a task with reduced headcount, but also how to scale across the entire value chain of processes with greater speed, better quality and higher productivity for better business outcomes.

By discovering the right ways to apply cognitive technologies at each step in the transformation journey, your business innovates, strengthens a posture of ever-learning and delivers — at scale — more value to customers than ever before.

If you would like to learn more about how the right cognitive tech can be applied to the automation of your business’s operations, let’s talk.