How Intelligent Process Automation is Revolutionizing Enterprise Operations

Are you tired of spending valuable time and resources on repetitive tasks? Do you wish for a more efficient way to handle routine business operations? Look no further! The rise of business process automation, utilizing intelligent automation technology, is revolutionizing how businesses conduct their operations.

By seamlessly integrating artificial intelligence (AI) and natural language processing (NLP), intelligent automation systems can effectively understand and engage with human language. This makes such systems ideal for streamlining workflows, reducing costs, and enhancing productivity. In this era of digital transformation, it’s time to embrace the power of intelligent automation and take your business operations to the next level.

What is Intelligent Process Automation?

Intelligent process automation (IPA) is an innovative technology that combines robotic process automation (RPA), process mining, intelligent document processing, analytics, and AI. It is a highly efficient tool for business process automation, capable of thinking, learning, and adapting autonomously. IPA is also known as hyper-automation, intelligent automation, or digital process automation.

IPA combines several AI technologies like computer vision and cognitive automation, along with machine learning (ML) and RPA. It has been a game-changer for many industries, such as automotive manufacturing, pharmaceuticals, life sciences, healthcare, and insurance. With IPA, businesses can automate complex decision-based processes that previously required human intervention. With IPA, businesses can cut operational costs, improve efficiency, and quality, and offer better employee and customer experiences. It’s an essential technology for organizations that want to stay ahead in this constantly evolving digital landscape.

Components of Intelligent Process Automation

Intelligent process automation is a critical business tool to streamline processes and eliminate inefficiencies. A holistic approach to intelligent automation comprises five key components that companies can prioritize to achieve this objective:

1. At the core of intelligent automation, artificial intelligence (AI) stands as the initial building block. AI focuses predominantly on cognitive tasks, encompassing optical character recognition (OCR), NLP, ML, and intelligent character recognition (ICR). The amalgamation of intricate algorithms with ML empowers businesses to analyze structured and unstructured data on scales previously deemed unattainable. As AI advances, it will play an integral role in efficiently processing progressively intricate data, thereby establishing a knowledge base that proves invaluable for comprehending historical events and predicting future trends.
2. The second component of intelligent automation is robotic process automation (RPA), which automates repetitive, rule-based procedures using user interface automation or integration with business systems. RPA bots can emulate human interaction and undertake back-office duties that require minimal critical thinking. More intellectually taxing tasks can be assigned to AI or human resources to expedite its completion.
3. The third component of intelligent automation involves adopting lean programming principles to assess all business processes, including sub-routines and tasks, and identifying positive and negative performance levels. The goal is to reduce the duration of non-value-adding activities, eliminate redundancies, and improve the efficiency and precision of critical production or service delivery processes. This exercise often involves substituting human involvement in non-essential functions with AI or RPA. This is commonly referred to as ‘workflow automation’ or ‘business process automation’.
4. The fourth component of intelligent automation involves adopting specific technological solutions to overcome challenges or address inefficiencies. Enterprises must exercise caution in adopting tools and integrating them into their operations to avoid having independent teams operating in silos, thereby creating visibility, data sharing, and collaboration issues.
5. Lastly, it is worth noting that data is a crucial factor in the success of organizations today, and the fifth component of intelligent automation focuses on leveraging this resource. In the life cycle of intelligent automation, data (including internal performance and metric data) is the fuel that feeds all other components, processed through RPA and AI software. As a result, data collection tends to be constant and large-scale, requiring compliance and governance measures to ensure transparency, trustworthiness, and accessibility. Automation and intelligent data handling are critical to extracting value from data efficiently, accurately, and within reasonable timeframes. This creates a loop where AI, innovative/predictive analytics, and automation can scale data operations while enhancing the data, further optimizing business operations through ML.

Intelligent Process Automation vs Robotic Process Automation: Key Differences

In spite of its usefulness in enhancing work efficiency, automation has its limitations. Robotic process automation, which is process-centric, is best suited for mundane and rule-based tasks that don’t require human intelligence — for example, downloading invoices or tabulating lab results. While RPA can simulate human work actions, it doesn’t possess intelligence. It operates solely based on the structured data fed into it and follows a predefined set of instructions.

In contrast, intelligent automation, or intelligent process automation, utilizes multiple technologies, including RPA, to simulate human intelligence. With advanced algorithms and ML, IPA can analyze large volumes of data to identify patterns and make inferences and conclusions. It can also communicate with humans using NLP and diagnose business processes to improve them through process mining. Moreover, unlike RPA, IPA can handle exceptions and self-manage through unforeseen scenarios for which it was not scripted. It can learn and adapt to data and events in real-time, making adjustments to adapt to changing environments, a feature RPA lacks.

One of the most significant differences between RPA and IPA is that IPA can operate in unstructured environments, allowing it to streamline supply chains by identifying potential bottlenecks before they happen. For instance, it can be used to improve customer service capabilities by interpreting what a customer wants and providing services at a more innate level rather than directing them to a specific web page or prompting them to answer frequently asked questions with template answers.

While RPA suits rule-based tasks, IPA transforms automation by simulating human intelligence and operating in unstructured environments. IPA incorporates RPA and other technologies like NLP, ML, IDP, and process mining to diagnose, improve, and automate business processes. This makes it a more human-like and adaptive solution than RPA.

Impact of Intelligent Process Automation on Different Industries and Services

Intelligent automation has been transforming industries for several years now. From the initial stages, when machines replaced humans on assembly lines, to the current state of AI, RPA, and cognitive algorithms, IA has evolved into a sophisticated tool that mimics human reasoning and behavior. With the growth of data flows, digital transformation, and practically unlimited computing power, intelligent automation has dramatically changed how humans and machines interact.

Deploying intelligent automation can prove to be a multifaceted undertaking that demands a holistic approach encompassing a knowledge base, effective governance, appropriate toolsets, meticulous analytics, ongoing refinement, and a stable IT ecosystem. Intelligent automation can be implemented in nearly every industrial sector, creating a new generation of hardware and software robots that perform cognitive and physical tasks. These systems handle and analyze large volumes of data, identify discrepancies, verify accuracy, acquire knowledge through experience, adjust to modifications, and make informed judgments.

Some of the significant use cases of intelligent automation include:

1. Commerce: Implementing intelligent automation can result in increased sales, heightened customer engagement, and reduced costs. Retailers invest heavily in it, and examples of intelligent automation in commerce include online and offline shopping guidance, improved warehouse logistics, transaction security, data-driven planning of supply and delivery, and hands-free checkout.
2. Manufacturing: Intelligent automation has triggered industrial revolutions such as Industry 4.0 and 5.0. Physical and digital robots perform many operations, replacing or supplementing humans through automated factory floors, automated workflows, predictive analytics, and machine vision.
3. Intellectual property: The importance of AI in managing intellectual property cannot be overstated. In particular, algorithms powered by AI and ML have a significant impact on research by enhancing the precision and efficiency of data retrieval, as well as resolving ambiguities.
4. Insurance: Intelligent automation helps insurance service providers automate data management and rate calculations. Intelligent automation solutions help insurance companies address problems such as manual entry of voluminous data, low scalability of processes, and poor time effectiveness.
5. Logistics and transportation: Intelligent automation solutions can create a holistic ecosystem that includes route optimization, supply planning, and predictive maintenance.

Key Benefits of Intelligent Process Automation

Intelligent process automation offers many benefits, including improved efficiency, cost-effectiveness, quality enhancement, heightened productivity, and increased customer satisfaction. It promotes innovation, encourages employee engagement, and establishes modern and resilient operating models that empower businesses to effectively anticipate and navigate change. By leveraging intelligent process automation, companies can achieve successful digital transformation, positioning themselves ahead of the curve in a dynamically evolving business environment. Here are the primary advantages that organizations can experience by integrating intelligent process automation into their business operations:

1. Enhanced operational efficiency: Intelligent process automation reduces manual, time-consuming back-office tasks, allowing employees to focus on high-value tasks. This leads to improved employee and operational efficiency.
2. Greater cost savings: Intelligent process automation modernizes legacy systems and streamlines workflows and business processes, leading to increased cost-savings for companies.
3. Increased productivity: By empowering employees to build unique solutions to close gaps and enhance team collaboration, intelligent process automation helps improve productivity.
4. Business continuity: With the capability to keep businesses aligned with evolving technologies, providing additional business value over time, intelligent process automation ensures seamless business continuity.
5. Innovation and employee engagement: As new working methods emerge, intelligent process automation inspires innovation and employee engagement.
6. Creates effective digital customer journey maps: Automating business processes with intelligent automation platforms creates effective digital customer journey maps.
7. Increases customer satisfaction and loyalty: By meeting changing customer demands, intelligent process automation increases customer satisfaction and loyalty in these fast-changing times.
8. Builds modern and resilient operating models: By facilitating the creation of modern and resilient operating models, intelligent process automation empowers organizations to withstand the test of time and innovate in their industry.
9. Enables businesses to anticipate change: By helping businesses anticipate and forecast change, intelligent process automation keeps the company sustainable even in times of change.

Build an Intelligent Automation Strategy with Hexaware

Enterprises worldwide are embracing digital transformation to streamline their operations. Intelligent process automation has become a crucial factor in this transition, enabling businesses to shift from manual to digital operations. However, a complete business process transformation requires a digital way of working, which encompasses advanced technologies such as AI, ML, and NLP.

Hexaware’s Intelligent Process Automation Services (HIPAS™) offers a strategic solution that enhances efficiency and the bottom line by deploying intelligent process automation. HIPAS™ leverages various technologies, from robotic process automation to AI technologies like cognitive OCR, ML, NLP, speech recognition, and image analytics, to achieve digital business process transformation.

Process automation has become critical for businesses aiming to increase productivity, achieve process efficiency, enhance customer experience, and optimize costs. Hexaware’s intelligent process automation approach focuses on executing the entire lifecycle of the customer’s digital transformation journey through a robust framework that spans three phases – automation consulting and advisory, development, and deployment, and bot support using the leading automation platforms in the industry.

Hexaware’s strategic engagement in the customer’s process automation journey involves an end-to-end implementation model. Hexaware collaborates with customers to design and establish an intelligent automation center of excellence with a suitable governance model, well-defined roles and responsibilities and evangelizes the concept of intelligent process automation adoption across the enterprise. Hexaware’s tool-based process assessment and discovery are enabled through partnerships with leading process and task-mining products.