It’s no longer good enough to just be digital or even phygital – it’s now time to hyper automate!
The world of digital transformation and generally management consulting is very vast and increasingly saturated with people promising to deliver on massive organizational change who often miss the mark. The main issue is not that these consultants are delivering bad work, it’s often that the organization itself lacks what’s necessary to continue with the momentum that these highly paid snipers command.
At the organizational level, going to a DIGITAL FIRST strategy, through to Robotic Process Automation (RPA), getting into real machine intelligence (read AI) wields a great path toward hyper automation. Savvy CIOs will tell you: Digital transformation doesn’t come in a box — or a cloud. “It’s like most tech trends that get hyped up and overused,” as it’s become more mainstream, says Genpact CEO Tiger Tyagarajan, who advises enterprises on digital strategy.
So mainstream, in fact, that 40 percent of all technology spending will go toward digital transformations, with enterprises spending in excess of $2 trillion through 2019, according to IDC. But what, exactly, is that money funding? Replatforming on new technologies is critical. Forrester Research, for instance, recommends a disruptive approach to transformation that includes everything from incremental improvements to moonshot approaches.
But what does it all mean?
Digital transformation marks a radical rethinking of how an organization uses technology, people and processes to fundamentally change business performance, says George Westerman, MIT principal research scientist and author of Leading Digital: Turning Technology Into Business Transformation. Digital transformation, which Westerman says should be led by the CEO, requires cross-departmental collaboration in pairing business-focused philosophies with rapid application development models.
Such sweeping changes are typically undertaken in pursuit of new business models and new revenue streams, driven by changes in customer expectations around products and services.
“Customer expectations are far exceeding what you can really do,” says Westerman. “That means a fundamental rethinking about what we do with technology in organizations.”
Digitalization and automated processes, intelligent software applications, and smarter machines are fundamental tenets to building an enterprise hyper-automation framework. Though Hyper automation may sound smooth and manageable in theory, its execution is severe and complicated, and no wonder one can find statistics on how 50% of the Automation project fails.
May it be a ground-up or top-down initiative Hyper automation requires consideration of a set of technologies across digitization, artificial intelligence, and connectivity. Hyper automation requires envisioning a complete end to end automation wherein processes are intelligent, machines are assistants, and procedures are capable of self-optimizing. However, this may sound like a far fetched scenario companies such as Amazon.
Many others have achieved some degree of success in several business areas, including merchandise returns, order fulfillment, and procure to cash. Other examples are companies like rocket mortgage which have capitalized early-stage hyper-automation to build an on-demand pull style adjudication and risk management processes, which potentially save consumers several hours from otherwise working with cumbersome mortgage application. The legacy applications required to pull together documents and data from various systems both at consumer and enterprise end and decisions had to travel across desks and hands by the time a final approval informed to the customer. By this time, the consumer may have already decided, lost interest, or even chosen a competitor who might be just a little faster than the incumbent.
Accelerated process agility and optimization
Reduce capital RPA and Other Automation deployment related costs
Avoid automating broken processes and redundant silo’s efforts and thus project failures
Uncover hidden digital value of enterprises with compounding returns
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