How can RPA improve knowledge management and sharing in professional services?

Robotic Process Automation (RPA) uses software robots to automate repetitive tasks by mimicking human interactions with computer systems. It operates at the user interface level, streamlining processes without requiring changes to underlying technology. For complex scenarios which involve reading unstructured text from email we can integrate rpa with ai model using NLP ( natural language processing) to extract the meaning data. Similarly for extracting data from images or unstructured pdfs

In the financial sector, RPA is a game-changer, enhancing efficiency & reducing costs. In the fast-paced financial world, where data processing and repetitive tasks are integral, RPA automates routine tasks, reducing costs and errors. It facilitates seamless integration between systems, ensuring smooth information flow across departments. A key advantage is RPA's ability to revolutionize knowledge management by automating data processes, empowering professionals to focus on strategic decision-making. This fosters a culture of collaboration and knowledge-sharing, streamlining processes and creating a dynamic decision-making environment. RPA contributes to the financial sector's resilience and adaptability in an ever-evolving landscape.

With recent advances in Artificial Intelligence (AI), Robotic Process Automation (RPA) has evolved, incorporating co-pilot tools for more efficient automation development. These AI-driven tools act as collaborative partners, assisting developers in designing and refining automated workflows. Furthermore, the integration of AI-based decision-making enhances the RPA's capabilities, enabling it to make more sophisticated and adaptive decisions, thereby improving effectiveness and flexibility in automated operations. This synergy between RPA and AI represents a significant advancement, empowering organizations to achieve higher levels of intelligent automation and operational efficiency.

By implementing RPA in professional services, organizations can create a more efficient and collaborative environment, leading to improved knowledge management and sharing practices.

Days of standalone RPA mimicking human interaction is going down,We require systems that can evolve and provide a significant outcome to business. Interoperability of RPA systems are critical in conjunction with other IT systems and humans

From my experience while going through different case studies for RPA will help one to introspect the AS-IS process optimize them and on top of it automating this might result in a double whammy of efficiency and cost saving.

RPA fosters collaboration and knowledge sharing by streamlining workflows and maintaining up-to-date information. This comprehensive approach cultivates efficiency and ultimately boosts productivity and decision-making.

RPA implementations usually have a very positive side effect of standardizing processes. This usually comes before RPA gets implemented, if the people implementing it know what they're doing. So, as processes get standardized, it becomes easier to share them between people within the organization. Also, they usually need to be properly described and documented in order to be automated, which, in turn, also means better knowledge sharing.

One of the benefits I have observed when introducing RPA is the ease if sharing information across key stakeholders in a normalized format. RPA is an excellent tool for processing structured data, from different sources, to produce output in different formats. Combine this with some good practices to distribute the results in a schedule and you will have implemented a simple way of standardizing views to potentially complex data. This is an excellent value with measurable benefits

RPA can help analyse the learnings and bring out best practices. For reducing delivery time, easy access to knowledge is the key. Rediscovery of knowledge is directly related to increased project timelines. Effective Knowledge Management with Intelligent Automation capabilities can help delivery teams and business users, both. RPA with AI capabilities is the solution here. It will help users have easy access to best practices to be followed and to Professional Services team to overcome any know Issues or problems and avoid any delays in project delivery due to this.

RPAs have been playing an increasing role in managing IT environments and applications. This is in addition to automation of business processes. Some of the use cases for IT services automation with RPA include: 1. User Onboarding 2. Access management 3. File Management 4. System Housekeeping tasks 5. User deactivation / deletion In IT services realm, most of these use cases are developed and implemented for systems which need these tasks to be automated via Graphical User Interfaces and usually do not have alternative integration channels like APIs or remote shell access.

Some of the most frequent processes to automate are processing documents (such as invoices or customer queries and forms), or generating documents (such as agreements, contracts, order confirmations, various reports, etc.).

We used RPA to perform consistency checks on consolidated financial statements, and the routine even posted corrective entries into the system before sending us an execution report. The robot did in 5 minutes what a human did in 3 hours before. Thanks to this approach, we were able to reduce the time it took to produce consolidated accounts by 12 times and improve quality. But the greatest benefit was that my team’s brains were 100% dedicated to analysis and no longer to data manipulation: much more rewarding for them.

Intelligent Document Processing (IDP) Documents from suppliers (invoices, delivery notes, order confirmations, etc.) or from customers (orders, forms, etc.) can be processed automatically here. A comparison with a third-party system such as ERP makes sense. Archiving and posting in various systems ultimately takes place. E.g. in storage in a DMS, booking in ERP, etc.

RPA can be utilized in both attended processes, involving human interaction, and unattended processes, such as data collection. In the present context, with hyperautomation techniques, it can be composed of various specialized technologies for each activity, expanding its versatility. RPA finds application in both front-office and back-office processes, catering to business users as well as IT routines. Its applicability spans across diverse sectors of the economy, showcasing its adaptability to a wide range of use cases.

1. Efficiency in processing 2. Reproducibility of outcomes given same inputs 3. No rework 4. Productivity enhancement 5. Data sanctity 6. Process compliance 7. Stringent controls Above are few but not complete benefits we can get with RPA.

Poka Yoke ! Huge cost advantage in terms of removal of rework - supports resource optimisation and in turn promotes Sustainaility!

RPA in professional services offers time and cost savings through task automation, improving accuracy and data quality. It enhances operational efficiency, scales easily, and ensures compliance. Professionals benefit from reduced mundane tasks, focusing on value-added activities and strategic decision-making. RPA's adaptability to legacy systems and data analytics capabilities contribute to a better customer experience, employee satisfaction, and strategic agility. Overall, it transforms service delivery by optimizing processes and increasing productivity.

- Efficient Knowledge Capture: RPA can automate the process of capturing knowledge from various sources, such as documents, emails, and websites. It can extract relevant information, categorize it, and store it in a centralized knowledge base. - Enhanced Knowledge Accessibility: RPA can automate the retrieval and dissemination of knowledge within professional services organizations. It can quickly search and retrieve relevant information from the knowledge base, making it easily accessible to employees. - Standardized Knowledge Sharing. - Improved Knowledge Collaboration

Among its key benefits, RPA offers cost reduction, freeing up time for teams to focus on higher-value activities, minimizing operational errors, enhancing efficiency, providing increased visibility, and standardizing processes for better auditability. Notably, RPA has become more accessible to business users, enabling them to create automations independently without heavy reliance on IT teams. This democratization of automation empowers business users to leverage RPA tools for process improvements and efficiency gains.

Applied RPA improves productivity, consistency and accuracy at a user level by enacting the user-computer actions that are both UI and API based. The true potential of such a platform is realised when it is extrapolated at the enterprise level. This can be achieved when we build an ecosystem with platforms including RPA, APA, AI, Process Mining and ingest it in to an end to end process (say P2P, O2D etc) across the line of business and industries.

A journey into RPA should begin by identifying automation candidates, preferably mature processes with well-defined rules that demand significant operational time from the team, allowing for a robust Business Case. However, it's crucial to evaluate various tools in the market based on their benefits, capabilities, costs, and management aspects. Governance and operational considerations should also play a pivotal role in the decision-making process, ensuring a comprehensive approach to successful RPA implementation.

Begin by identifying tasks that are repetitive, rule-based, and data-intensive for automation. Choose a suitable RPA tool that aligns with your business needs and goals. Train employees on the use and maintenance of RPA bots. Continually monitor and optimize the RPA processes to ensure they deliver the expected benefits.

Selecting a right platform and processes are key to success. A clear strategy is crtical to embed RPA into an organization's journey. Selecting the right tool enables an organization to scale up RPA by fully utilizing in app modules without complexities and need for third party integration in the future. Therefore the tool must be reviewed comprehensively prior to procurement. Starting with a POC to scale up gradually and, selecting simple tasks automation first before end-to-end automation will allow the organizations to deploy RPA faster with increased success. Complexities can be addressed subsequently for full automation. This approach enable the stakeholders to witness the value thereby interest is increased by building trust.

The article offers solid guidance for those looking to implement RPA in professional services. However, it is suggested to further emphasize the importance of internal training to ensure that staff can make the most of the technology. Additionally, it is essential to emphasize the need for an agile and adaptable approach, as technology and organizational needs can change over time. Overall, it is a valuable resource for those looking to leverage the benefits of RPA effectively in professional services.

It is very important to set realistic goals for RPA programs. Key stakeholders sponsoring the program and also the users of RPA platform need to be aware that RPA is designed to mimic human actions and hence such programs lie at the lowest rung of the cognitive systems. While it is possible to integrate AI/ML models to bring enhanced capabilities w.r.t. decision making and data analysis, it is very important to optimize the processes being automated before implementing automated bots. It has been seen that as is automation of processes and iterative enhancement thereon may yield much better results.

Applied RPA improves productivity, consistency and accuracy at a user level by enacting the user-computer actions that are both UI and API based. The true potential of such a platform is realised when it is extrapolated at the enterprise level. This can be achieved when we build an ecosystem with platforms including RPA, APA, AI, Process Mining and ingest it in to an end to end process (say P2P, O2D etc) across the line of business and industries.

While RPA offers numerous benefits, it's important to manage change effectively, as the introduction of bots can impact workforce dynamics. Businesses should also consider data security and privacy implications, ensuring that the use of RPA aligns with legal and policy requirements. Regular maintenance and updates are crucial to keep the RPA tools efficient and effective.

***Automate Repetitive Tasks*** With the help of RPA a lot of repetitive tasks get automated. As a result this creates a lot of capacity for professionals to have knowledge sharing sessions and discussing strategies. Also by combing AI Ml with RPA, it helps to collect data from multiple sources and doing analysis on it. This way it's helpful to keep knowledge management intact with the newer version of data coming every time. Best example is of automating incident management tools in which by automating the incident allocation, it helps to tag them to the respective knowledge base.

An RPA can never be an E2E solution to automate a process. More often than not, RPA is a stop gap automation solution that can interact with multiple systems to automate repetitive tasks. One major drawback of RPA is that it cannot handle exceptions which have to be dealt manually. While RPA is a great tool for handling repetitive tasks and freeing up productive time, we should not rely only on RPA for process digitization. Take a step back by assessing the process E2E and evaluate options for digital tools which provide solutions for entire workflow digitization. This will help improve process health and unlock productivity in the long run.