Robotic process automation framework - The implementation of Robotic Process Automation in Business Processing Outsourcing Organizations

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research and CRMDigital transformation is the digitalization of earlier analogue machine and material processes, service operations, and organizational tasks to aggregate new value for clients and employees. There is an increasing number of organizations that are taking advantage of digital transformation, competing in the market of the digital economy. The advances of the global market in competitiveness trigger organizations whose ambition is to distinguish themselves to develop more efficient and effective processes, delivering distinctive services or products to their consumers. When the Business Process Outsourcing (BPO) processes are automated with Robot Process Automated (RPA), the organization can raise cost efficiency, acquire efficiency advantages, and increase their rank in the market. Additionally, when repetitive and tedious activities are automated, human employees have time and opportunity to enhance their cognitive judgment, creative thinking, and social skills. This research approaches the steps that lead to the elaboration of a framework that can be adopted in BPO processes, aiming to help in the knowledge of which processes are typical in BPO, and which of those processes can be fully automated, semi-automated or cannot be automated with Robotic Processing Outsourcing. Afterwards, are revealed the assumptions that were the base of the artifact elaboration, following the description of each component and stage that constitute the framework. Lastly, it is referred the validation of the framework by experts and the discussion of the obtained results, conclude the utility of the artifact as support to the automation of BPO with RPA

TRANSLATING ROBOTIC PROCESS AUTOMATION IN SOCIAL WORK: ASPIRATIONAL CHANGES AND THE ROLE OF TECHNOLOGY

Automated decision-making using Robotic Process Automation (RPA) is increasingly found in public- supported social work. This study analyses two cases in which RP A was implemented and disseminated in social work in Sweden. The first case took place in a Swedish municipality; the second case took place in a project conducted by the Swedish national agency for municipalities. These cases involve translations of aspirational changes related to RPA in decisions on social assistance. The study uses Actor-Network Theory to highlight organizational areas and issues in social work that must be addressed when RPA is implemented and disseminated. The study’s research questions are the following: What are the leading actors ́ ideas about aspirational changes related to RPA in decisions on social assistance? What is the role of technology in this context? The study revealed some similar aspirational changes in the two cases related to change management and maximization of services. Variations were found in other aspirational changes for RPA such as the issue of trust in applicants and the role of caseworkers. The study points to the need to increase applicants’ use of, and facility with, information technology. The formulation of “a why” behind these changes is important for caseworkers’ future role and use of discretion

Investigating the factors driving adoption of RPA in South African banking: a qualitative analysis

Background: Studies have shown that the traditional banking sector is under threat from digital banks and financial technology (fintech) organisations that can operate with a lower cost base and respond to the market faster. In response to this threat, leading banks have implemented Robotic Process Automation (RPA) to reduce costs and simplify operations. The adoption of RPA has, however, proven to be challenging as in many cases the impact of automation technology implementations is perceived to affect the livelihoods of staff who work in banks. Within the South African banking context, there is a particular sensitivity to factors that impede employment and labour unions are deeply involved in protecting workers. Objective: While there is research on RPA implementations, it is limited in the banking context. Further, there is currently little to no RPA adoption research specifically in the South African banking context. This study seeks to investigate the factors that drive RPA adoption in South African banks. Method: This study has used the Technology-Organisation-Environment (TOE) framework, extended with Institution Theory, as a lens to structure an approach in organising RPA adoption factors in an extensive literature review on the phenomenon. Thematic analysis was used to analyse the interview data that was collected. Themes were aggregated and organised by the TOE perspectives to create structure throughout the study. Results: The findings were that the adoption of RPA in South African banks is driven by the expected benefits of RPA which are achieved when well-suited processes are targeted, an effective operating model for the program including business and IT personnel, with the right skills. A well-designed change program is critical for RPA adoption in banks. South African banks are also working closely with the trade unions and are, on the whole, following best practices when automating parts of their workforce's roles by ensuring that they are given the opportunity to work on more engaging tasks

The Intersection of Robotic Process Automation and Lean Six Sigma Applied to Unstructured Data

While new Artificial Intelligence (AI) technologies gain traction in the workplace, there seems to be more buzz around these newer advances, including Robotic Process Automation (RPA), than more established process improvement techniques such as Lean Six Sigma. This praxis research uses Lean Six Sigma as a framework for effectively deploying these emerging technologies, a challenge for 86% of companies (Ernst & Young, 2021). This research is applied to one of the legal industry’s most resource intensive processes – eDiscovery in the environment of a Big 4 accounting firm that provides services to corporations and legal professionals alike. Electronic discovery (also known as e-discovery, ediscovery, eDiscovery, or e-Discovery) is the process of identifying, collecting, producing, and presenting electronically stored information (ESI) in response to a request for production in a law suit or investigation. ESI can include any type of electronically stored file and commonly includes emails, documents, databases, media files, social media, and web sites. The lifecycle of eDiscovery has been defined by the Electronic Discovery Reference Model (EDRM) as having the following phases: Information Governance, Identification, Preservation. Collection, Processing, Review, Analysis, Production, and Presentation. To move through the phases of the EDRM historically requires a significant investment in time, technology, and human resources. This project had its origins as an automation effort driven by the technical advances in RPA solutions. However, RPA became a tool for to enable the program – not the solution itself. The DMAIC framework (Define, Measure, Analyze, Improve, Control) of Lean Six Sigma laid the foundation for a more wholistic analysis of the EDRM including the identification of processes that required revision prior to their automation. The Define phase identified the resource intensive strain moving through the EDRM causes corporations, vendors, and litigators. Through the measure phase, an opportunity to provide better results faster, and therefore cheaper was quickly identified. Through the analysis, several unnecessary handoffs, extraneous processes, and general bottlenecks in the process were refined. Through the Improve phase, automation played a significant part in realizing the efficiencies identified in the analyze phase. Finally, the controls phase not only put these improved processes into place but also quantified the value of ensuring these procedures were thoroughly deployed. This research is organized using the DMAIC framework to articulate the process for completing the research, the gains and efficiencies made throughout the analysis, and to measure the impact and success of the overall program enhancements. The impact of this project is measurable not only in the reduction of defects as defined by Lean Six Sigma, but also a significant improvement in time required to complete these processes. Even more satisfying, these efficiencies have a measurable, financial impact that has currently been realized north of $5 million USD in one year alone. This impact led to the solution becoming a finalist for an industry award where it was presented to over 3,000 industry professionals. Furthermore, the reduction and automation of manual, tedious tasks have also led to more enriching work for resources

Promotion of an industry : trends and expectations of digital transformation in the Hungarian business services sector

In this paper, we explore the current trends of and future expectations for digital transformation projects in Business Service Centres (BSCs) in Hungary. We carried out fifteen interviews with senior technology experts and executives in three Hungarian based BSCs of multinational parent companies to examine individual transformation projects. We also used quantitative data from large-scale surveys on the sector to get an overview of general practices. We reviewed the use of advanced technologies like robotic process automation, predictive analytics, chatbots, and artificial intelligence. We found that BSCs had mostly The consequences automated massively repeated processes and that this automation had liberated employees for more creative tasks. of this transition are threefold: (1) BSCs can reinforce their position as business partners of their global parents, (2) creative assignments are more attractive for prospective and current employees in a labour market characterized by a shortage of suitable personnel, (3) employees usually do not fear the possibility of job loss due to automation and digital transformation

Embracing Automation: Boosting Productivity and Efficiency in the Tech Sector

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThis project explores the implementation of process automation within a tech company to streamline and optimize the Sev ABC Rota process, which involves the manual handling of critical support tickets. The current manual system poses challenges such as data entry errors, time consumption, and delays in system updates, necessitating the urgent need for automation. Power Automate, along with connectors like Excel, Outlook, Teams, and SharePoint, is utilized to automate the Sev ABC Rota process. The automation includes creating and updating data in a SharePoint list, removing engineers from the daily queue, sending email notifications, and creating a Teams group chat. The choice of Power Automate is based on its no-code functionality and compatibility with Microsoft connectors, ensuring simplicity, time savings, and increased productivity. The paper discusses the benefits and challenges of process automation and automated workflows, emphasizing their impact on productivity, cost reduction, accuracy, and customer satisfaction. Various metrics and assessment techniques, including cycle time, throughput, error rates, cost savings, and customer satisfaction, are proposed to evaluate the effectiveness of automated workflows. Additionally, emerging trends in automation, such as the combination of cognitive technologies, adoption of intelligent automation, cloud computing, and low code/no-code platforms, are discussed. The importance of change management and employee engagement in successful automation implementation is highlighted, emphasizing the need for a culture of ongoing learning and collaboration. Overall, this paper provides insights into the implementation and evaluation of process automation in the tech industry, offering a roadmap for organizations seeking to enhance efficiency and optimize operations

Innovation, Artificial Intelligence in Contingent Work-Force Management

In recent years, the global use of contingent workers is rapidly increasing despite the increasing quantity of artificial intelligence applications in business. The question is "how these companies leverage the use of artificial intelligence to enhance contingent workforce's management?". The ideal goal of this paper is to develop a purely conceptual application of innovation, artificial intelligence (AI) adjacent to contingent workforce management(CWM). The researcher used qualitative information gathered from various authors and observations to reinforce the usage of AI. One of the critical tools to integrate with contingent workforce management for reduction of time spent on human resource administrative tasks is AI. There must be a transformation of thinking, accepting positive organizational change, utilization of technology and openness to new technology to foster  AI. Along with that, integrating contingent workforce management with AI reduces risks and costs, increases efficiency and quality of work. Innovation and Artificial intelligence have been used in five pillars performance of contingent workforce management to mitigate the challenges associated with it.In recent years, the global use of contingent workers is rapidly increasing despite the increasing quantity of artificial intelligence applications in business. The question is "how these companies leverage the use of artificial intelligence to enhance contingent workforce's management?". The ideal goal of this paper is to develop a purely conceptual application of innovation, artificial intelligence (AI) adjacent to contingent workforce management(CWM). The researcher used qualitative information gathered from various authors and observations to reinforce the usage of AI. One of the critical tools to integrate with contingent workforce management for reduction of time spent on human resource administrative tasks is AI. There must be a transformation of thinking, accepting positive organizational change, utilization of technology and openness to new technology to foster  AI. Along with that, integrating contingent workforce management with AI reduces risks and costs, increases efficiency and quality of work. Innovation and Artificial intelligence have been used in five pillars performance of contingent workforce management to mitigate the challenges associated with it

A Framework for Artificial Intelligence Applications in the Healthcare Revenue Management Cycle

There is a lack of understanding of specific risks and benefits associated with AI/RPA implementations in healthcare revenue cycle settings. Healthcare companies are confronted with stricter regulations and billing requirements, underpayments, and more significant delays in receiving payments. Despite the continued interest of practitioners, revenue cycle management has not received much attention in research. Revenue cycle management is defined as the process of identifying, collecting, and managing the practice’s revenue from payers based on the services provided.This dissertation provided contributions to both areas, as mentioned above. To accomplish this, a semi-structured interview was distributed to healthcare executives. The semi-structured interview data obtained from each participant underwent a triangulation process to determine the validity of responses aligned with the extant literature. Data triangulation ensured further that significant themes found in the interview data answered the central research questions. The study focused on how the broader issues related to AI/RPA integration into revenue cycle management will affect individual organizations. These findings also presented multiple views of the technology’s potential benefits, limitations, and risk management strategies to address its associative threats. The triangulation of the responses and current literature helped develop a theoretical framework that may be applied to a healthcare organization in an effort to migrate from their current revenue management technique to one that includes the use of AI/ML/RPA as a means of future cost control and revenue boost