Companies regularly explore new IT technology investments, and upon discovering the promise of new advances, quickly make their way to their traditional comfort zone: the knee-jerk reaction of leveraging technology only to reduce operating expenditures (usually starting with the CIO’s budget). This is increasingly true in the case of one of the newest technologies to enter our “technosphere,” known as Robotics Process Automation (RPA). Simple downward pressure on IT labor costs often generates a “CFO-friendly” return on investment (ROI) that justifies the business case for new technologies such as this. This is a “business of IT” pattern that repeats itself all too often as CIOs seek the tools necessary to modernize their company’s technology footprint, and their associated competitive enablement.
This thinking misses the mark.
Technology is one of the most powerful conduits available to enhance the experience of our true “customers” – the employee population, those employed to sell, deliver, manufacture and administer – who depend on technology to do their jobs more effectively. By extension, our “customer’s customer” and their experience can be directly correlated to technology enablement decisions! So, do we really win by only taking out cost, or do we win by empowering the workforce to be more effective and drive the top line? In the case of RPA, automating IT-related processes and systems will reduce labor costs. However, we quickly realize that the most significant impact of this very promising technology is on improving employees’ ability to do their jobs better. This, in turn, enables the competitive edge that differentiated customer experiences require.
We live in an economy where almost everything we do in the workplace is technology enabled, spanning all sectors from service through manufacturing. Yet still, IT systems and software remain complex. Even though we’ve been engineering software for 40-plus years, it is still a flawed process (imagine if we built bridges the way we engineer software!). Use of RPA as a technology to remediate the inevitable technology faults helps us to instantaneously execute fixes at machine speed. This minimizes the mean time to restore, which ultimately enhances the end-user experience of IT’s true customers.
Robotic Process Automation technologies can be transformational.
RPA use cases and applications are infinite – it’s mind-boggling. RPA is enabled by several artificial intelligence-based component technologies, and extends well beyond fault remediation. To get started with automating IT-related processes and systems, understanding the differences between scripting, orchestration and robotic process automation is good way to begin the ultimate journey:
- Techniques such as scripting (and macro-routines) are often as diverse in their structure and syntax as the engineers that created them; this makes scripting a brittle solution that defies standardization by its very nature and remains tightly coupled to a specific component of technology that it services.
- Orchestration introduces both structure and syntax and often involves participation and decision making on the part of the technology that is being orchestrated. Hence, the infrastructure itself becomes an active participant and collaborator – for instance, by publishing its configuration information that is then consumed by the orchestrated process. This characteristic makes orchestration “smarter” and so it can be loosely coupled to the technology that it supports.
- RPA has a unique ability to be aware and adapt to changing circumstances, exceptions and new situations. It can manipulate data, trigger responses, initiate new actions and communicate with other systems autonomously. RPA is built on machine learning (a base component of AI) which makes it the “smartest” and enables a wide variety of use cases, building on its own knowledge and determining what to do, where to do it and when to do it.
Historically, the worry around large-scale scripting and even orchestration has traditionally been that if your automation doesn’t have the knowledge of what-where-and-when, to do it or not do it, you’re in no-man’s land and at risk of actually breaking more than you fix. However, the integration of orchestration and machine learning, which both fundamentally underpin RPA, is a way to ensure that you know when to initiate an orchestrated task, where and which one.
Will RPA and “AI-like” software just fizzle out again as AI has in the past?
The open source community, academia such as MIT, and industry giants such as Google and Facebook are all actively contributing the core technology components driving RPA advancements, as well as the cognitive and AI computing space. As the open source community continues to become the prevalent contributor of technology advancement, we are beginning to see a number of start-ups entering the marketplace. These start-ups leverage machine learning, RPA and cognitive computing, and apply these technology advancements in commercial software and services. We’ll see more start-ups emerge out of stealth mode in the very near future.
This will benefit organizations that are adept in capitalizing on start-up technologies. The organizations who successfully leverage RPA and cognitive computing create better experiences for their employees and clients and also drive increased revenues, while the rest find it increasingly harder to compete in the evolving marketplace. That’s a glimpse of what the current path looks like today, the “haves” and the “have nots.” What will alter this scenario is the broad impact of open source, the API economy and SaaS, where a whole new community of start-ups and venture capital firms begin to invest in this space aggressively enough until the technology becomes fully ubiquitous, commonplace and generally available to all.
To empower the workforce by improving the customer experience, do we need to first make the case for cost savings, to entice our leadership to buy in and take the leap of faith? Can we change our current mental model to one that emphasizes building a more effective workforce to drive revenue up, rather than simply drive cost down? Can we transform our corporate belief system to where if revenue goes up, cost cutting becomes less of a problem and would in turn improve the effectiveness and morale of the workforce, further contributing to increased revenue and margin?
In the IT industry itself, across the major players, there is statistical evidence that 17-22 percent of the activities (incidents/requests) are being addressed using advanced automation. That’s estimated to go at least as high as 40 percent in the next three years, according to IT industry analysts. A doubling of automated fulfillment events in the next three years…is this a new expression of Moore’s Law, whereby processing speed doubles every two years?
Regardless of your choice of technology strategy, RPA, cognitive computing and AI are all still dependent on the data that you have, generate and consume. Not a day should go by that organizations, departments and functions do not pay attention to the quality of their data and their ability to collect, aggregate and interpret it.
Nor should a day should go by when CIOs are not promoting the idea that employee job satisfaction is at least as good an argument for RPA adoption as the potential for reducing labor costs. Satisfied, productive employees stay loyal and drive more top line revenue. This saves on the cost of employee and customer churn and disruption to the organization. As to the initial costs of new technologies, including RPA, the old saying remains true: You can’t cut your way to prosperity.
What are your thoughts on RPA? Post a comment or question here!