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Over the past few decades, Digital Transformation has been a key strategic focus for most business entities, primarily aimed at improving their productivity and efficiency, and, more importantly, effectively managing the growth aspect of the business. After successfully implementing strategies such as outsourcing, leveraging low-cost locations, and optimizing business processes, the focus has now shifted to “profit maximization,” “customer satisfaction,” and having a direct impact on “business metrics.” With Intelligent Process Automation moving from a “concept” to a “reality,” it is now well-positioned to take center stage in any Digital Transformation Strategy.
Over the past few decades, Digital Transformation has been a key strategic focus for most business entities, primarily aimed at improving their productivity and efficiency, and, more importantly, effectively managing the growth aspect of the business. After successfully implementing strategies such as outsourcing, leveraging low-cost locations, and optimizing business processes, the focus has now shifted to “profit maximization,” “customer satisfaction,” and having a direct impact on “Business metrics.” With Intelligent Process Automation moving from a “concept” to a “reality,” it is now well-positioned to take center stage in any Digital Transformation Strategy.
When used together, the following technology levers create unique solution patterns that help businesses achieve their objectives in a more advanced and efficient manner.
Although process standardization and optimization remain the primary step in any Business Process Transformation, the role of technology in accelerating the process cannot be underestimated. Automation tools like Automation Anywhere and UiPath offer their proprietary process mining engines based on artificial intelligence. These Process Analyzers have an in-built analytics engine that continuously captures data from process recorders and creates a comprehensive process map, including all possible exceptions. This map can then be used to improve operational efficiency. In some cases, the Process Analyzer even generates the screen level process design and RPA product code. If RPA technology and AI algorithms start leveraging the output of the Process Analyzer, the benefits of self-trained bots could be realized in the near future.
Each organization is unique and has its own set of constraints and needs, making it crucial to subject any analysis to a Process Assessment Framework designed specifically for that organization. This framework typically includes three key steps: data collection, prioritization, and detailed functional/technical assessment. By following this process, an organization can gain a comprehensive understanding of its processes and identify areas for improvement that are tailored to its specific needs and constraints.
Enterprises frequently face challenges in strengthening their automation pipeline and quantifying the potential benefits of automation. We leverage our industry experience and business process assessment framework to conduct design workshops with key stakeholders, helping business teams to develop a clearly defined automation pipeline and a data-driven business case. Our goal is to support enterprises in overcoming these challenges and realizing the full potential of automation in their operations.
Robotic Process Automation (RPA) refers to an IT layer that interacts with existing IT applications by using “Software Robots” that imitate the way human agents interact with the system to execute any business process. RPA technology can be successfully applied as long as the interaction rules with existing IT applications can be defined. This means that all business processes that are manual or repetitive in nature, have high volumes, and defined business rules are ideal candidates for automation.
While productivity / efficiency improvement is one of the key direct benefits of RPA Technology, there are many other significant benefits which makes it even more interesting for both Business and CIO organizations,
What a BOT can do?
……… and much more!
Optical character recognition (OCR) is one of the earliest technologies used for extracting information from documents, and it has since advanced significantly with the integration of sophisticated image processing and AI-based algorithms. When combined with business domain-specific rules, these technologies can provide unique solution patterns that help businesses automate more at a reduced cost.
Each organization is unique and has its own set of constraints and needs, making it crucial to subject any analysis to a Process Assessment Framework designed specifically for that organization. This framework typically includes three key steps: data collection, prioritization, and detailed functional/technical assessment. By following this process, an organization can gain a comprehensive understanding of its processes and identify areas for improvement that are tailored to its specific needs and constraints.
In general, there are three types of documents: structured, semi-structured, and unstructured. Structured documents include those with pre-defined templates such as ID cards and government forms. Semi-structured documents, such as invoices and purchase orders, have multiple formats but present the same information. Unstructured documents, such as contracts, do not have a defined format.
Artificial intelligence technology has been around for decades, but in recent years, its evolution has accelerated, and it has become capable of solving real business problems. With the help of advanced AI algorithms, large amounts of data, and the continuous focus of major IT players, the technology is now slowly moving from concept to reality. Here are a few areas of interest from a business process automation perspective:
Natural language processing (NLP) – Extracting meaningful data from unstructured documents, such as legal contracts and stakeholder queries, is becoming increasingly important in the process automation landscape. This capability allows businesses to automate more complex tasks and improve operational efficiency. The utilization of this capability is increasingly being expanded to various language translation and sentiment analysis scenarios
Computer Vision (CV) – The ability to extract significant information from images opens up an entirely new realm of automation, which includes various examples such as signature matching, face recognition, product mapping, and defect identification.
Advance Analytics – With the aid of machine learning algorithms and predictive analytics, enterprises can predict future trends, recognize potential opportunities, and arrive at informed decisions. Consequently, leveraging this technological advantage, businesses are now shifting their focus towards cross-selling and up-selling opportunities, rather than solely focusing on basic process automation.
Chat platforms like Office communicator, Facebook messenger, WhatsApp, and others have been in existence for a long time, and the industry has successfully utilized the technology for their day-to-day human interactions. However, the real power of these platforms has been realized with their evolution into virtual agents. These agents have the capability to interact with business applications and extract meaningful data from language text.
This solution pattern has opened up a new world of opportunities for process automation, such as responding to stakeholder queries (customers, vendors, partners, employees, etc.) based on business application data, and tracking sales workforce, to name a few great examples in this area.
Digitalization forms the backbone of any business process automation. This involves large-scale digitization strategies, such as ERP implementation, as well as the need for smaller applications catering to specific use cases within process areas. Examples of such applications include leave management, purchase order management, conference room booking, and limited workflow management. Integrating these applications with the overall IT landscape through RPA can further enhance process efficiencies.
These platforms enable the development of applications with minimal coding or without coding at all. These platforms have been gaining traction in recent years as they enable businesses to build applications more quickly and cost-effectively than traditional software development methods. While no-code/low-code platforms offer several advantages, such as increased speed of application development, reduced costs, and greater accessibility, they may also have some limitations. For example, the platforms may not be suitable for complex applications that require custom coding, year-on-year license cost, dependency on platform Vendor, and obviously platform specific constraints.
The rapid development of technology, coupled with a focused approach from the IT industry, has resulted in a range of incredible solution patterns that are capable of solving almost every possible use case related to business process transformation. Over the past few years, the industry has witnessed exponential growth and evolution of Robotic Process Automation (RPA) into Intelligent Process Automation (IPA) technologies.