Since the first mainframes were installed in the late 1950s, process automation has been a much sought after objective in the corporate world. Automation has created a massive worldwide industry in hardware design and software development.
Automation and computerized processing have also become a source of fascination in the public imagination: Think 2001: A Space Odyssey, The Terminator, and other dystopian fantasies. But visions of a world dominated by machines conveniently overlook how difficult it is to replicate true human intelligence.
Nevertheless, some forms of intelligence are already here. Today’s smart-thinking businesses are looking hard at what’s called intelligent automation. Advanced forms of process automation—supported by digital data and complex analytical algorithms, and enabling step-changes in the performance, agility, and competitive capabilities of a range of businesses.
Evolving automation technologies are empowering their operators to emphasize their uniquely human capabilities to think creatively, prioritize tasks, solve problems, and interact with clients, partners, and co-workers in smarter, more productive ways.
Now more than ever, business leaders need to understand the abundant opportunities enabled by intelligent automation and chart the best path forward. Intelligent automation is evolving from systems that do to systems that think, learn, and, ultimately, adapt.
Robotic process automation (RPA) is the starting point on the intelligent software automation continuum. This is the stage at which entities do. The concept is compelling: non-programmers hard-code business rules into software that can be triggered to execute processes previously only performed by humans. RPA technology is flexible, secure, scalable, low-cost, and easy to master compared with traditional business process management systems. It can be applied to any rules-based, multi-application activity.
But while RPA systems work only with structured inputs and hard-coded business rules, automation technologies can also think. They can introduce logic, allowing programs to make decisions autonomously when they encounter variances in the processes they execute. Natural language processing is an example: Smart phones and call centers can interpret spoken or written communication and translate it into executable actions.
Systems that learn can analyze vast amounts of dynamic and unstructured input, and execute highly dynamic and non-rules-based processes. Such machine learning can have various applications: it can improve the diagnostic capabilities of medical imaging systems, for example; it can enable online retailers to create highly-individualized catalogs, and can enhance the ability of software companies to test for security vulnerabilities in future releases of applications.
Today, it’s do-think-learn. By mid-2017, this model will shift to think-learn-adapt. Systems that adapt will be characterized by their ability to modify themselves or optimize performance depending on changes to their environment, to divert or defend themselves from security threats, and to interact more seamlessly with other systems and the people they serve and support.
Starting the Intelligent Automation journey
To help chart a path toward adopting intelligent automation, organizations should consider these approaches:
- Think big and scale fast: Automation needs to be recognized as a top strategic initiative across the enterprise. An experienced executive can assume the role of automation leader, responsible for accelerating adoption of intelligent automation simultaneously across the IT and business operations.
One life sciences organization we work with established a team to identify processes ripe for automation. Those separate processes—complaint management, invoice processing, and report generation—allowed the team to explore first-hand the capabilities of RPA, natural language processing, machine learning, and intelligent image conversion. The team developed a 12-month automation roadmap with more than three dozen process areas across different functions.
- Leverage partner expertise: Strong partners can quickly assess and take advantage of game-changing but little-known intelligent automation technologies, often offered by small, emerging vendors. For one global financial services company that deployed intelligent automation across large-volume, rote, and rules-based processes in its market research and supply chain operations, we benchmarked vendor technologies, validated product capabilities, and supported design, testing, and deployment.
- Automate on-demand: To reap the rewards of intelligent automation without becoming an automation expert, one healthcare payer implemented an as-a-service solution to quickly and accurately process out-of-network claims, relying on Cognizant’s intelligent automation platform to perform process automation, and apply intelligent algorithms for handling exceptions based on analyzing past transaction data. Intelligent agents eliminated a backlog of 8,000 claims in just five days, at 99% first-pass accuracy. Today, the solution handles every out-of-network claim for this provider—not only determining who should be reimbursed, but completing documentation to ensure the health plan pays the right party for every claim.
Do. Think. Learn. Adapt.
A wait-and-see stance is not an option when systems that do, think, and learn are already helping your competitors reposition themselves for the “fourth industrial revolution.” New technologies are fusing the physical, digital, and biological worlds, affecting all disciplines, economies, and industries, even challenging ideas about what it means to be human.
The adaptive realm will see an even greater degree of interaction and partnership between humans and the software “robots” that augment our work and personal lives. Organizations that start the journey will experience the benefits of process acceleration, greater efficiency, quality gains, and optimized work teams—collaborating, creating, and improving results like never before.
Has your organization considered intelligent automation? What challenges have you had to overcome? If you are wondering how to get started, drop me a line.
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