In the 70’s and 80’s business systems were focused on data capture and information organization. It was all about the paperless work place. This phase of automation reduced the amount of time spent searching for information as well as accessing information in an enterprise – “The TPS System”. The data capture phase created organized silos of data and started the integration phase where data was shared across silos to avoid the labor of duplicate data entry. In the late 80’s and 90’s systems architects started to design systems with core attributes that were common across different functional modules. For instance, healthcare had a common Patient Administration System (PAS) whose attributes were used across different clinical disciplines (Lab, Rad, Pharm, etc.).
Then there was the Y2K phase where the sins of the past had to be corrected. The thought of first-generation systems lasting into the next century or beyond created a demand for IT development resources that was truly a once in a lifetime event. Moving on.
The first decade of the 21st century continued integration to reduce data replication and introduced the concept of Service Oriented Architecture (SOA) and the Data Access Layer (DAL) to gain access to “systems of record” or sometimes referred to as the “source system”. Many classically architected data warehouses still utilize SOA and the DAL methods to share data within the organization.
The next phase that started to emerge in the first decade of 2000 was Business Process Management or Orchestration. Platforms such as Microsoft’s BizTalk, Nintex, and Sharepoint’s workflows supported by Windows Workflow Foundation, and many commercial business process management platforms were introduced to the market. The first decade of the 2000’s was focused on clinical or business best practice pathways to create a repeatable process for measurement. This stage in the evolution created operational / experiential data to measure and analyze the steps in the process. The measurement phase gave analysts a way to change pathways and improve processes by disclosing and correcting bottlenecks in a process flow.
The second decade of the 2000’s brought the beginning for automating workflows through user friendly workflow automation products bolted on to document management systems. Then, an entire Business Process Management industry was created to automate document workflow through an enterprise. Perceptive, Kofax, Hyland and many others captured enterprise market share by automating the workflow of moving scanned documents through an enterprise. Aside from commercial Business Process Management Systems, Application Architects were designing and developing custom workflow solutions through SOA systems integrations and custom application development. But wait, the evolution, continues.
In 2015 Robotics Process Automation (RPA) platforms (i.e. UiPath, Blue Prism, Automation Anywhere and others) started to appear in the market. These platforms empowered solution developers and technically capable business analysts to configure business process automation. Gartner’s report on Robotic Process Automation states “RPA is still relatively small market with a total revenue of slightly less than $850 million in 2018. However, RPA is the fastest-growing software subsegment ofﬁcially tracked by Gartner, with year-on-year growth of over 63% in 2018.”
Now we are seeing RPA platforms incorporate Artificial Intelligence and Machine Learning. Nintex acquired an AI platform EnableSoft, and many Commercial RPA companies have announced their product roadmap to integrate or incorporate Artificial Intelligence and Machine Learning technologies. The stated vision of many of the RPA platforms is AI and Robotics Process Automation driven enterprise and personal assistant Bots for the worker. The personal Bots complete routine and mundane tasks such as pulling and distributing reports, documenting personal time and attendance information and sifting through unwanted email. This gives the worker more time to focus on strategy or the value stream of the organization.
Now Bot, if you could just work this weekend, “that would be great.”