#2 - How the Future of Work Evolved Over the Years
Bi-weekly newsletter series highlighting the stories and experiences of technologists, startups, and entrepreneurs who change the future of work through #RPA (#RoboticProcessAutomation), #IntelligentAutomation, #ArtificialIntelligence (#AI), #ProcessMining and the broader # futureofwork automation technologies.
We will cover how a technology area within the Future of Work space impacted and changed our lives. For the second article, I'd like to introduce the "Evolution of the Future of Work" from the early 2000s until today, and a little glimpse into the #future.
The future of work is defined as many things; the augmentation of robots and AI into our daily work and tasks, the transformation of how you do monotonous and repetitive tasks, and where you do your work. As technology and time progress, the three pillars defined below still lead to transforming our work life. Each is tied to one another and pioneered the creation of this market and the evolution of RPA:
Technology – How the technology and product landscape has evolved for customer success and created new opportunities for people.
Customer Journey – How the organizations and users have adopted the advancements in technology.
Career and Opportunities – The inception of new roles and careers within the industry has created new jobs and modified existing ones.
Think of this as a circular path that starts with the product and technology to solve a current problem that the people face; later, the technology is adopted by the user and customers who implement it and find gaps to strengthen the customer journey. The critical component it leads to is the growth of new careers and opportunities, which employ thousands of people (including myself).
As we set our clocks back to the 2000s, process automation started to solve problems in outsourcing work. As more companies in the US and Europe developed a dependency on shared services and outsourcing, their focus on higher efficiency and faster work increased. A new technology called RPA came into the scene. RPA imitates a user’s interactions on a desktop and other capabilities and arrives at the perfect time to meet the demand of this specific customer base.
As automation took over tasks, it faced scrutiny, and a popular claim was that “robots are taking over jobs.” While the field started to create more jobs and helped remove repetitive and mundane tasks from people’s daily lives, the perception of automation moved from a substitute for our work to an augmentation of our work. The impact of automation on our daily work lives shifted the focus to better customer and employee experiences as benefits and value drivers.
Let’s jump into the time machine to reveal what was going on at the time.
THE EARLY 2000s - The Time of Inception
Most of the outsourcing and shared services firms were executing tasks via Citrix. Citrix automation introduced a vital gateway to complete tasks cross-borders via Virtual Machines. One of the critical features to accomplish this was advancing and leveraging Computer Vision and Optical Character Recognition (OCR) and triggering the robots at a specified time and date. However, there were no orchestration and scheduling capabilities to execute the robots at certain times, and reliability and security were the top concerns for adopting solutions.
Phil Fersht, Founder and Chief Analyst at HFS, coined the term “Robotic Automation” at first in a blog post in 2012 about the dawn of a type of outsourcing that involved processes and technology. Even though the term was coined in the early 2010s, the RPA firms Blue Prism, UiPath, and Automation Anywhere were founded in 2001, 2005, and 2003. It is important to note that Process Mining Manifesto was authored much later in 2011. As the industry views the process orchestration with Process Mining and RPA as a single entity now, back then, both approaches were just getting started.
The increased reliance on Business Process Outsourcing (BPO) and Shared Services drove the attention to labor arbitrage savings with effectiveness and efficiency for back-office functions. As early adopters began to work together on how automation applies within their organizations, IT developers took on another “software tool,” fueled by prioritizing the technology-first approach compared to a process-first.
The barrier to entry for anybody interested in learning to build automation robots was still really high due to the costly training materials and educational content. The content was not free, and there were no forums, online courses, and YouTube videos that could enable developer communities for RPA.
2017 & 2018 – The Time of Adoption
This was when I entered the RPA market as a generalist consultant. At the time, there were not many distinctions in roles for a Business Analyst and RPA Developer. Instead, the companies and the Center of Excellence (CoE) combined the two functions under one umbrella. As the industry and the requirements changed over time, it became apparent to split the responsibilities to allow more flexibility and success for the projects. The RPA ecosystem continues to grow, including the orchestration and scheduling capabilities and much more robust executions in UI-based automation techniques with Computer Vision. In addition, other capabilities began to take root, including Intelligent Document Processing and enhanced process documentation generation. Even though building a reliable, stable, and robust automation robot required extensive C# and VB.NET coding capabilities, the technology was introduced to the market as a “drag-and-drop” and “anyone can do it” low-code-no-code application. The programs provide a canvas to build process flows by adding activities; however, democratizing the technology and enabling the citizen developers were still way out in the future.
The first customers were piloting their RPA Journeys by targeting back-office functions for automation due to the business process outsourcing heritage of the technology. The automation was being sold to customers internally for headcount reduction and time-saving.
The fear of robots replacing humans was at its peak as the market still needed to be educated on how the technology is best used and deployed. Robotic-Process-Automation (RPA) software was too narrow and did not address every stage of an automation transformation program, including; pipeline targeting and generation, RPA Analytics, testing, and debugging. As customers continued to adopt the technologies, some failed to meet their value and ROI targets. As RPA was sold as magic and a low-code-no-code solution, the businesses quickly realized that the effort to build robots was much higher. Customers' failures due to overinflating the value, the technology’s capability, and limited services businesses that knew how to build robots triggered a bad customer sentiment for RPA. It raised the question of who is the right person, team, and company to make these robots. As the RPA-pure-play consulting firms emerged in the market to meet and fill this gap, proficiency and expertise became tough to find. This was when RPA Developer certifications and unique methodologies defined and designed by the pure-play consulting firms became the vital components as a base standard for deployments.
One of the most impactful changes that happened at the time was the introduction of the first open, free and accessible online training by UiPath. It allowed UiPath to acquire a developer base much quicker than the competition and helped close the product feedback loops faster and at a higher volume. As more people learned how to deliver and use the product stack, the more companies started to develop an understanding of the technology and why they had not been successful before.
2019 & 2020 – The Time of Scale & Growth
The technology-first approach at the time led to products getting adopted before developing a deep comprehension of the process and underlying process impacts. Therefore, business cases and benefit realization metrics and targets built for these processes had limited scope and accuracy in forecasting the value generation and ROI. In early 2019, HFS Research released a dataset that showcased the barriers to applying robotic process automation (RPA) in organizations worldwide in 2017. 41% of the customers said that the lack of clarity on the business case was the leading reason they chose not to move forward, followed by 30% of “It will be built into enterprise software platforms in the next five years; we’ll wait.”
RPA platforms moved away from being automation tools to Intelligent Automation platforms. I remember attending the UiPath Forward in Vegas and Automation Anywhere’s product launch at NASDAQ. I saw UiPath adding Process Mining and Task Mining capabilities via two acquisitions; ProcessGold and StepShot, respectively, and Automation Anywhere adding advanced Intelligent Document Processing with IQBot and cloud-based automation capabilities. This year also marked the broader acquisitions, with Microsoft snapping up Softomotive and IBM acquiring WDG.
The recognition of the lack of accurate business cases and targeted automation led to investments in the analysis stage of the automation programs. We have also moved away from BPO-based metrics like decreased FTE hours, average handling time, and other labor arbitrage savings to metrics like improved customer and employee experiences. This resulted from investments focusing on front-office automation solutions where the robots interact with employees via GUI and user interfaces that can be built within, now called Intelligent Automation Platforms. The term “Human-in-the-loop” was heard as part of the front-office enablement. As RPA companies made investments in the analysis stage of an Intelligent automation transformation, we have also seen the Machine Learning capabilities growing, enabling Data Science teams to participate within the RPA CoEs and integrating the algorithms built to be used in a workflow automation solution.
As technology improved via new product development and acquisitions and customers started to adopt the new offerings, the enterprise programs were forced to think differently about process prioritization and targeting. With the ecosystem continuing to grow and expand across the departments of an organization, the RPA community was no longer about the people who build automation robots. The roles and responsibilities continued to expand from generalist roles to dedicated Business Analysts, RPA Developers, Solutions Architects, Machine Learning Engineers, and Intelligent Automation Leads, including the introduction of Chief Automation Officers.
Free training, accessible forums, and YouTube videos democratized information and knowledge capital. The requirements for coding skills were seen to be less important than the understanding of the process and Low Code/No Code. The community brought the scale the industry needed as it welcomed a wide range of backgrounds and skilled professionals.
2020 to the Future
RPA is no longer just RPA - the evolution of automation grew from RPA to Intelligent Automation and now Hyperautomation, including many areas of transformation. This created new startup companies that build integrations with workflow and process automation companies, enabling further robustness in execution
The ecosystem continues to grow with the inclusion of:
Low Code / No-Code Application and Robot Development
Process Discovery - Process and Task Mining
Citizen Development
Test Automation
RPA Analytics Ecosystem
Advanced Intelligent Document Processing
Machine Learning
Fully orchestrated end-to-end automation where Process Mining feeds the transactions live and triggers RPA robots and AI/ML embedded into RPA to make smarter process decisions. This year also marked the growth of “automate the automation” activities. Drag-and-drop, easy-to-use activities allowed the early stages for the democratization of process automation technologies, enabling business users to build task-focused automation rather than process-focused automation. In the early 2020s, citizen development became a vital ingredient of the automation adoption across the organizations, automating report generations, invoice scanners, timesheet submissions, improving the supply chain with intelligent automation, and much more.
Now, if we were to think about what’s ahead of us based on the experiences and learnings we had in the past, it is not hard to imagine that some tools
we use today had time to break through the dogmas and stagnant ways of doing things. We do not question using PowerPoint, MS Excel, or Gmail. However, our work requires us to leverage these tools to be successful, effective, and efficient. One, for example, will be expected to work efficiently by “not writing an invoice by hand” but instead submitting it in a digital and structured format. Removing redundant steps and activities within your work will be expected as part of the job. By not accepting how things were always done before, the expectation of building automation and solutions to improve your work with technology will be the crucial ingredient for any job moving forward. It makes one ponder just how many different productivity tools we utilize during our day job now.
The Evolution of RPA Webinar held by Alex Dixon , Director of Industry Solutions from UiPath and Alp Uguray, Senior Solutions Expert at Ashling Partners
