[Webinar] Explore the origins, current state, and future of RPA

https://youtu.be/wdzpBcrwbc4

Radiant has tracked RPA solutions for over a decade and has been part of its evolution. Chandra Alluri shall discuss its origins, share insights on its current state, and how it will morph in the future to alleviate the pain points in software engineering and IT & Business operations. Connect with us to learn how our RPA solutions can help you!


Reporting Solution for Fortune 500 Clients

Reporting Solution

Radiant delivered numerous reporting solutions across the globe, including Fortune 500 clients. One of our clients in financial services must audit the various clients' financial statements, analyze the reports, and assess the risk. The process involves numerous manual steps, aggregating the data from multiple disjointed and discrete systems in various formats, including spreadsheets and flat files.

Our Solution

Radiant built the custom reporting solution with the following five critical foundational components:

  • Security & Regulatory Compliance: Highly confidential data must be stored and managed securely.
  • Efficiency / Productivity: The solution should focus on simplicity allowing the BVI workforce to be more efficient and productive.
  • Data Entry / Collection: Transactional & Historical Data must be aggregated from multiple sources and various formats.
  • Workflows & API Based Open systems: Should enable multiple levels of decisions & allow to interact with legacy & lateral systems.
  • Flexible Reporting and scalable solution: The solution should be dynamic and allow flexible reporting in addition to the canned reports. In the future, it can access multiple systems.

 

 

 

Radiant has built a flexible and straightforward solution that has the following primary layers:

  • The data layer enables the data ingestion from various sources, catalog the data and search the required data elements by different users. The solution initially started aggregating the data from 4 primary sources and expanded to dozen-plus resources from other divisions.
  • Reporting / Visualization layer to enable canned reports as well as user-configurable reports.
  • Security & Compliance layer to comply with SOC2 and other national standards.

Benefits

  • The solution allowed 100+ users to access canned reports and build custom reports to their needs.
  • The majority of the manual steps were removed in the reporting process.

 


Robotic Process Automation for a Large Financial Services Client

Case Study: Robotic Process Automation (RPA) for a Large Financial Client

Radiant helped one of its financial services clients with process automation using industry-leading RPA tools. The factors that lead to effective automation of repetitive business process are:

  • Understand and analyze business processes and their bottlenecks through lean six-sigma principles.
  • Document and map process steps by applying proper queuing methods.
  • Automate steps locally using relevant scripting utilities.
  • Comply with role-based access controls along with system and data controls.
  • Enable users to create their bots through script-less automation tools.

A large financial services organization is transforming its securitization process that impacts the entire secondary mortgage industry.  Three large financial services institutions and a governing body required quality reporting on a program’s progress to have a common understanding, track and monitor the issues and make informed decisions from time to time. It was a three-year-long, half-a-billion-dollar program.

The quality reporting data has to be obtained from all three participating organizations that use five different tools: Two instances of HP ALM, Rally Dev, IBM Clear Quest, and Service Now. These tools support their custom processes and configure very differently, which resulted in the following challenges:

  • How to deliver meaningful reports to all three organizations and the governing body?
  • How to generate consistent, reliable, and timely reports?
  • How to secure a way of reporting with proper controls in place so that underlying data is not exposed to the outside world? It can have a devastating impact on markets.
  • How to absorb the changes and generate new reports at more frequent intervals?

Our Approach:

Radiant solved the problem in the following systematic steps:

Process / Data Normalization – We studied and analyzed the existing business processes of 3 different organizations and how the tools are configured in support of them. Since the business processes are tied to their other internal supporting processes, they cannot be changed without impacting the business. Hence, we developed a mechanism to fetch data from feeding organizations into a shared repository, which involved writing VBA macros, SQL scripts, and Python Programs that made seamless connections to all the tools in different organizations.

Six-Sigma Analysis to understand process bottlenecks – We analyzed and timed the 32-step process that took 4.5 hours to generate one weekly report to eliminate bottlenecks and reduce error-prone areas.

Automated Manual processes – Error-prone tasks were further automated to improve the accuracy of reporting and reduce the time taken to generate the report by 70%

Implemented Blue Prism to support more processes, implement controls to processes, support more processes, and support more intervals.

Summary

The Quality reporting is consumed by 300 stakeholders, including executives and decision-makers, and is carried out every day since February 2017 without a break, including holidays and furloughs of the client. Reporting errors are a rare scenario. New reports can be developed, implemented, and stabilized within a week. The necessity to support the late-night and weekend reporting was significantly reduced. This mechanism was humming along with process optimization and the implementation of Blue Prism.

The critical factors to success come with an in-depth understanding of business processes, applying engineering methods to optimize the processes, using the right tools and technologies such as python, SQL scripts, VBA scripts to automate small steps in the processes, documenting business rules for manual steps, tuning to the culture of an organization, securing infrastructure, establishing controls, and the ability to configure the RPA tool so that new processes can be easily supported.

Benefits / Facts

  • Manual errors in reporting were eliminated. However, controls were introduced to avoid data errors, but some manual checks are still required for foolproof reporting.
  • The Manual Steps involved in the process were reduced to 3 from 32.
  • The number of people required to support the reporting was reduced by 80%, from 15 resources to 3.
  • The number of reports increased to 20 with the same bandwidth of 3 resources.
  • The need for off-peak support was eliminated.

We learned how to leverage the culture, technology stack, and infrastructure of an organization to implement Robotic Process Automation. Please contact us to discuss our RPA expertise.

 


Digital Network Assistant Chatbot for a Large Telecom Client

Digital Network Assistant Chatbot for a Large Telecom Client

A large telecom client’s primary objective of this project is to help 10,000+ Network and Technology specialists across the globe ranging from circuit engineers to field operators who manage extremely complex provisioning, troubleshooting, and maintenance workflows under significant time pressure with a Digital Network Assistant.

The functional goals of this solution are: (1) Improved self-service capability, (2) Simplified information search, and (3) Easy Troubleshooting. Technical solution must enable users through a conversational interface on Web, Mobile, and Instant messaging platforms, and the Digital Network assistant must be available 24X7.

The functional scope of work of this project encompassed:

  • Use the conversational interface to assist users in handsfree mode
  • Integrate with multiple AI / ML platforms such as Google’s Dialog Flow, Amazon’s AI, etc.,
  • Enable creation of multiple Bots or multiple instances of the same Bot to serve different groups across the globe
  • Build an interface where business users without the technical background can create new intents and train the Bot with new skills

The technical scope includes:

  • Building a platform to centrally manage the data, intents, skills to avoid conflicts and redundancy
  • Building AWS infrastructure to manage and support Bot lifecycle
  • Building the components and action handlers to fetch the corresponding data and display the information through an interface
  • Building CI/CD pipeline to quickly develop, test, and deploy the new skills into production
  • Building a user interface to help business and operational users to develop and train the Bot with new skills with code-less development architecture

The operational scope includes:

  • Mining the skills of different groups and understanding the frequency of the usage
  • Prioritizing the skills for development and quantifying the benefits
  • Queuing the skills for development into Sprint Backlogs
  • Training the new users on how to leverage Chatbot in their day to day tasks

Our Solution:

A chatbot is a tool to retrieve information and generate human-like conversation. It is mainly a dialog system aimed to solve/serve a specific purpose. To accomplish this goal, it needs an interface where the user needs to request dialog or keyboard; it needs NLP service to understand and interpret the command; it needs action handlers to connect with applications and retrieve the information so that the Bot can respond to the request. Also, it requires secured connections; authentication and authorization; store the data, dialogs, intents; orchestration services to synchronize requests from different users; messaging platforms from where users can make requests; and channels of service.

A Chatbot requires an interface to integrate with and all the plumbing to connect and retrieve the information on the surface. Hence designing and building the framework is essential to implement Chatbot to serve its purpose.  The following figure illustrates the Chatbot framework.

 

 

The solution was built on the following best practices:

  • Decouple the dependency between User Interface and NLP Backend – Every NLP comes with its own interface. It is in an organization’s best interests to develop its own interface and access NLP service through APIs. This helps easily changing the NLP service without much hassle.
  • Save the intents and dialogs within the local database – This improves the performance and keeps it independent of the service provider.
  • Design for multiple Bot Instances – Enterprises may either use one instance to cater to different business lines or use different instances with different names. Hence it is better to design for multiple instances.
  • Develop different services – When different Chatbot instances are required, it is important to develop different services for Training, Testing, etc., to comply with multiple versions of different instances easily.

Benefits:

  • Our solution reduced the time taken to complete the provisioning research tasks from 20 minutes to less than 3 minutes
  • Our solution helped users to train 180+ skills in a period of 90 days, which resulted in significant productivity
  • For the financial year 2019, our solution saved $13M

 


Choosing the Robotic Process Automation (RPA) platform

Once the business case for Robotic Process Automation (RPA) implementation is approved and a decision is made to move forward, the next step is to understand RPA platforms available and find the right partner who can assist in the transformation. As discussed in the first article in this series, the combination of technological and business factors will help select the RPA platform.

The following are key features to keep in mind:

  • Intuitive GUI and easy-to-use drag and drop interfaces – The platform should have a visually enabled integration development environment (IDE) for developing integration flows by navigating an application or data source. This enables non-technical (business analyst) users to leverage robot designers to interact with live applications as they build out a process.
  • Rich analytical suite – The platform should have the ability to analyze a large amount of data and provide meaningful insights on trends and process bottlenecks to make informed decisions.
  • Script-less automation – The platform should allow business users with limited or no scripting knowledge to automate their business processes with minimum guidance from implementation teams to be more creative in automating their business processes.
  • Process structured and unstructured documentation – The platform should have cognitive capture capabilities to recognize machine-print characters, hand-print characters, checked boxes, bubbled fields, barcodes, signature images, etc. The platform should be able to integrate with scanning solutions.
  • Integration with the environment - The platform should integrate with other systems through web-service calls or APIs and easily interface with different data integration methods. The RPA platform should also integrate with legacy systems.
  • Batch processing - The platform should enable batch processing and schedulers to maximize the servers computing power and leverage scheduling so that work can be done over evening hours or weekends when more computing power may be available or limited network traffic.
  • Automatic data validation – The RPA platform should provide data validation capability to ensure high data quality levels and provide better feedback through machine learning algorithms. The platform should allow us to configure rules and set thresholds for automatic data validation.
  • Audit tracing – The RPA platform should allow critical activities to be auditable and traceable to satisfy regulatory and compliance requirements.
  • Versatile robot automation – RPA robots interact with virtually any legacy enterprise applications or modern business systems, web site, portal, database, and content (e.g., PDFs, Excel, …). Data is extracted, processed, and passed between applications, websites, portals, and databases, while business rules and logic apply throughout the workflow.
  • Management console –Role-based administration governs the functions that allow secure, granular control over integration projects, access rights & viewing of integration flow results. Active Directory or other directories should be able to leverage for authentication and authorization.
  • Automated process discovery – This process can record, map, and analyze business processes, applications, and activities performed by employees, allowing organizations to pinpoint top time-saving automation opportunities.
  • Unattended robots – Robots can schedule to run at a specific time or be executed by a user. A robot publishes with Java/.Net APIs or as a RESTful services interface that another application can then call. Robots can also schedule or initiate other applications, such as case management, business process applications, or any application via APIs.
  • Supports multiple data sources and types - All kinds of application environments and data sources are supported, including websites, portals, enterprise systems, legacy applications, Excel, Email, XML, JSON, CSV, and SQL.

Critical Success Factors

The following steps are critical to succeed in choosing the RPA platform.

Expertise – Success of RPA implementation often hinges on business process re-engineering, lean six-sigma process improvement knowledge, and intelligent automation. Hence having the right partner with a mix of all these skills and abilities eases planning, prioritization, and implementation.

Empower users – Organizations that rely on implementation partners to automate business processes are often not successful. We suggest training, upskill, and enabling users to automate their processes with minimum help from solution providers.

Lean governance – Business process automation should adhere to all the compliance, regulatory, and security requirements. Managing the implementation with checks and balances and prioritizing processes based on ROI should be governed appropriately. Best practices, libraries with reusable functions, and other coding standards manage the CoE model. Knowledge sharing across different business lines can better manage using communities of practice.

Agile management – Although business processes can automate in no time, we found managing the entire process following agile principles yields better results. Whole automation activities should adhere to enterprise methodology.

Metrics and measurement – We have observed organizations inflating robots' ROI, leading to mistrust and confusion among stakeholders. Hence the governing body should set proper guidelines and define agreeable metrics so that productivity improvements and other benefits can be accurately captured and reported.

Continuous monitoring and improvement – The process metrics must continuously analyze for further improvements.

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About Radiant

Radiant specializes in delivering meaningful and measurable technology solutions that help customers navigate and succeed in the Digital Transformation journey. We have been helping our clients for nearly a decade in this journey in several ways: UI/UX modernization, Legacy modernization, Cloud migration, Business Process Automation, Platform modernization, etc., using a wide range of technologies and development methodologies. Through this experience, thought leadership, and conviction, Radiant formed the following four guiding principles to support our customers on their digital transformation journey:

  1. When we consider customer needs, Radiant considers all stakeholders: executives driving strategy, employees executing work, and engaging customers.
  2. Radiant knows that maintaining a competitive edge is not only about connecting with customers in new and innovative ways, but it’s also about continuously keeping them engaged.
  3. As companies embark on the digital transformation journey, it’s imperative for them to keep pace with the technological curve, at the same time quickly and efficiently integrating new systems, processes, culture, and customer experiences into all areas of the enterprise.
  4. Radiant knows that digital transformation is a disruptive shift, and it requires using the right technology effectively to help ensure business continuity as the enterprise transforms.

Connect with one of our experts at Radiant to learn more!


The Evolution of Robotic Process Automation (RPA)

Radiant Digital has over twenty years of experience, helping customers re-engineer their business processes. This article is the first in a two-part series on business process automation. In this series, we will discuss the evolution of Robotic Process Automation (RPA), how to begin your automation journey, and how to promote success.

Evolution of RPA

Operational efficiency is a powerful strategic lever for organizations seeking to reduce costs and improve customer and employee satisfaction. Over the last three decades, human resources' value has become the common denominator in the equation to enhance operational efficiency. As such, organizations have limited options, such as 1) shifting resources to more economical locations; 2) outsourcing work to other organizations or partners; 3) offshoring work to other countries; and 4) offshoring work to partners.

Just-in-time management techniques, geographical time advantage, increased availability of skilled resources, globalization, and favorable trade pacts have favored these approaches. Organizations have enjoyed the results for nearly two and a half decades. However, several factors force companies to look for alternatives or supplement outsourcing models that provide additional efficiencies. These factors include rapidly advancing digital technologies, cybersecurity threats, populism, increased outsourcing costs, tax laws changes, and knowledge loss through the aging workforce.

Recently, digital enterprises have increasingly focused on a business process automation strategy to increase operational efficiency further. Robotic Process Automation (RPA) tools propelled this change and yield the following key advantages:

  • Cost-effective: RPA solutions are relatively economical, and return on investment is very high
  • High velocity: Business processes can be automated and deployed into production swiftly
  • Codeless automation: Advancements in technology and RPA solutions allow business users to automate with little coding experience
  • Enhance human capabilities: RPA will take laborious and tedious tasks from humans and will allow them to focus on high-value activities.
  • Minimal disruption: RPA solutions can quickly augment humans in the existing processes with minimum disruption
  • Complex task execution: in some cases, RPA solutions with advanced capabilities (e.g., machine learning, OCR) can perform complex tasks more accurately than humans.

Where to begin? A good beginning makes a good ending.

The first step in realizing the benefits of RPA is to decide where and how to begin implementation. The best possible candidates for RPA should choose via a decision and scoring framework. For example, a decision framework might include process attributes such as:

  • Stability: Processes stable with limited variation are optimal candidates for automation as they yield quick returns and require little maintenance.
  • Repetitiveness: A candidate process should include repetitive tasks to realize the exponential value of RPA.
  • Documentation: Processes should document sufficiently such that all the stakeholders can agree and provide sign-off.
  • Structure: Processes structured with a clear decision and action criteria are more comfortable with automating.

Certain types of processes that usually don’t require human intervention are definitive candidates for RPA. Exemplar candidates include:

Swivel-chair processes are tasks that require users to refer to multiple systems to retrieve data. For example, some network operation users need to access various systems, pull up data, and compare them using various screens before responding to customers. So, checking equipment purchases and delivery status, which takes on an average of a week for fulfillment, is a repeatable task by hundreds of customer service representatives across the organization. This well-structured and documented process has matured to offer consistent customer service. Hence, the operations that involve swivel-chairing are the best candidates to pilot RPA. When the process is automated, the user’s expertise and knowledge become invaluable in validating and optimizing the process.

End-user computing processes, for example, in financial or health services, workers are often required to provide updated information to customers—e.g., computing insurance premiums, generating an amortization schedule based on daily market changes, or developing new risk models. End-users typically build these models in their choice of tools, pull data from secure sources, and analyze outcomes based on market trends. The process of removing data from source systems, conditioning, and formatting data to feed into the model doesn’t change frequently. RPA can automate this repeatable process so users can focus on value-added activities such as modeling and analyzing data.

HR operations - HR operational activities have been the same for a long time for many organizations. Digitization forces HR departments to harness social media for talent acquisition and use SaaS platforms to accomplish various activities.  However, operational activities are still cumbersome, as they involve many manual steps. For example, prompting employees to submit timesheets, running background checks, and on-boarding are simple activities but require multiple prompts and sometimes require a soft nudge. RPA bot can easily accomplish these steps and free up time for more human activities. Since these are age-old stable processes, they are also relatively easy to automate and earn good returns on RPA.

Enterprise reporting – Large programs require reporting to be done with data compiled from multiple tools. No matter how advanced tools become, as programs and organizations evolve, they don’t meet all reporting requirements. For example, we had to pull data from seven different tools across three organizations to report the program status accurately. This process has nearly 35 steps that took 4.5 hours each day to aggregate, condition, and format data to compile multiple reports. For the program that runs at jet speed, reports with a data lag of 24 hours are pretty stale. Using the RPA bot, we have automated the entire process and brought the total time to less than 30 minutes, and this automation allowed us to generate reports as often as required. These are great candidates for RPA as they provide instant visibility to key stakeholders and decision-makers.

Manual / Paper Processing – Many organizations still use large amounts of paper received via faxes or manual submissions to fulfill a business need. It requires a lot of time and is prone to errors as the manual operators input data into other processing systems. RPA platforms, with their ability to scan and learn using advanced technologies, can become very handy in accelerating the business process and significantly reducing errors while assisting and relieving the burden to employees to focus on high-value functions.

The success of RPA adoption by different organizations largely depends on where and how they start. As discussed above, once organizations get the hang of it, results lend themselves to further the case of automation.

Our next article in this two-part series will dive deep into critical success factors and hitching RPA bots with Chatbots to make it even more powerful. Connect with one of our experts at Radiant to learn more!