Ohjelmistorobotiikasta älykkäisiin automaatioihin

Älykkäiden automaatioiden käyttäminen on tullut teknologian kehittymisen myötä mahdolliseksi organisaatioille. Älykkäiden automaatioiden avulla organisaatioiden on mahdollista parantaa työn tehokkuutta sekä työntekijöiden kokemaa työn mielekkyyttä. Tässä työssä tutkitaan, miten älykkäitä automaatioita on mahdollista ottaa käyttöön mahdollisimman tehokkaasti. Tutkimuksen tavoitteena on koota yhteen parhaita käytäntöjä, jotta älykkäiden automaatioiden käyttöönottoprosessi sujuisi organisaatioilta jatkossa mahdollisimman sujuvasti. Tutkimus toteutetaan systemaattisena kirjallisuuskatsauksena. Tutkimusaineistoksi valikoitui kaksikymmentä julkaisua, joiden perusteella tutkimusongelmaan ja tutkimuskysymyksiin vastataan. Tutkimuksen teoriaosuus keskittyy ohjelmistorobotiikan ja älykkään automaation käsitteiden määrittelemiseen. Kirjallisuudesta selvisi, että älykkäät automaatiot ovat ohjelmistorobotiikan ratkaisuita, joihin on yhdistetty tekoälyyn liittyviä kykyjä, kuten esimerkiksi jokin koneoppimisen malli. Tutkimuksessa havaittiin myös, että ohjelmistorobotiikkaa on tutkittu paljon, mutta siihen liittyviä älykkäitä automaatioita melko vähän. Tutkimus osoittaa, että älykkäiden automaatioiden käyttöönottamista kannattaa tarkastella ainakin teknologian, organisaation ja sen ihmisten näkökulmista. Teknisen näkökulman mukaan älykkäitä automaatioita kannattaa ottaa käyttöön vaiheittain, siirtyen yksinkertaisemmista automaatioista kohti monimutkaisempia edistyneemmän tason automaatioita. Organisaatioiden kannattaa siis kehittää osaamistaan esimerkiksi tavallisia ohjelmistorobotteja toteuttamalla ennen älykkäisiin automaatioihin siirtymistä. Ihmisten näkökulmasta prosessissa kannattaa keskittyä ja panostaa viestintään. Organisaation näkökulmasta on tärkeää kehittää yhtenäinen, koko organisaation laajuinen automaatioiden hallintamalli, joka mahdollistaa niiden tehokkaan hallinnan ja ylläpidon. Tulokset voivat jatkossa auttaa älykkäitä automaatioita käyttöönottavia organisaatioita, sillä tutkimus kerää aiemmin hajallaan kirjallisuudessa olleita hyviä käytäntöjä yhteen. Tutkimus toteutetaan systemaattisena kirjallisuuskatsauksena. Tutkimusaineistoksi valikoitui kaksikymmentä julkaisua, joiden perusteella tutkimusongelmaan ja tutkimuskysymyksiin vastataan. Tutkimuksen teoriaosuus keskittyy ohjelmistorobotiikan ja älykkään automaation käsitteiden määrittelemiseen. Kirjallisuudesta selvisi, että älykkäät automaatiot ovat ohjelmistorobotiikan ratkaisuita, joihin on yhdistetty tekoälyyn liittyviä kykyjä, kuten esimerkiksi jokin koneoppimisen malli. Tutkimuksessa havaittiin myös, että ohjelmistorobotiikkaa on tutkittu paljon, mutta siihen liittyviä älykkäitä automaatioita melko vähän. Tutkimus osoittaa, että älykkäiden automaatioiden käyttöönottamista kannattaa tarkastella ainakin teknologian, organisaation ja sen ihmisten näkökulmista. Teknisen näkökulman mukaan älykkäitä automaatioita kannattaa ottaa käyttöön vaiheittain, siirtyen yksinkertaisemmista automaatioista kohti monimutkaisempia edistyneemmän tason automaatioita. Organisaatioiden kannattaa siis kehittää osaamistaan esimerkiksi tavallisia ohjelmistorobotteja toteuttamalla ennen älykkäisiin automaatioihin siirtymistä. Ihmisten näkökulmasta prosessissa kannattaa keskittyä ja panostaa viestintään. Organisaation näkökulmasta on tärkeää kehittää yhtenäinen, koko organisaation laajuinen automaatioiden hallintamalli, joka mahdollistaa niiden tehokkaan hallinnan ja ylläpidon. Tulokset voivat jatkossa auttaa älykkäitä automaatioita käyttöönottavia organisaatioita, sillä tutkimus kerää aiemmin hajallaan kirjallisuudessa olleita hyviä käytäntöjä yhteen

Robotic process automation and artificial intelligence in industry 4.0 : a literature review

aking into account the technological evolution of the last decades and the proliferation of information systems in society, today we see the vast majority of services provided by companies and institutions as digital services. Industry 4.0 is the fourth industrial revolution where technologies and automation are asserting themselves as major changes. Robotic Process Automation (RPA) has numerous advantages in terms of automating organizational and business processes. Allied to these advantages, the complementary use of Artificial Intelligence (AI) algorithms and techniques allows to improve the accuracy and execution of RPA processes in the extraction of information, in the recognition, classification, forecasting and optimization of processes. In this context, this paper aims to present a study of the RPA tools associated with AI that can contribute to the improvement of the organizational processes associated with Industry 4.0. It appears that the RPA tools enhance their functionality with the objectives of AI being extended with the use of Artificial Neural Network algorithms, Text Mining techniques and Natural Language Processing techniques for the extraction of information and consequent process of optimization and of forecasting scenarios in improving the operational and business processes of organizations.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

The Assessment of Robotic Process Automation Projects with a Portfolio Analysis: First Step - Evaluation Criteria Identification and Introduction of the Portfolio Concept

RPA’s (Robotic Process Automation) usage in organizations has rapidly increased in recent years; as a result, companies have developed high expectations from this technology. However, according to Ernst & Young (E&Y), 30-50% of observed RPA projects initially fail and reveal several risks, which lead to investment losses. Consequently, the RPA project is prematurely retired, and the company is back to the manual process. This premature retirement is mainly because of wrong process selection and the not sufficient company automation (RPA) maturity. Therefore, this paper will introduce the concept of an RPA Portfolio, which will assess the complexity of business processes with a company’s automation (RPA) maturity. The RPA Portfolio is a new innovative concept to simplify and visualize the business process selection for RPA projects, and will help to introduce successfully the right RPA projects

Introspection on the Research Avenues of Robotic Process Automation as a Service (RPAaaS)

One of the newest business and technology developments is cloud computing, where several users approach the Cloud to complete various tasks. Cloud RPA is a technology that uses robotic process automation on Cloud-native using artificial intelligence. RPA-as-a-service: an automation software or bot that any user with an internet connection can use in the Cloud. It is an automaton self-service in cloud drag-and- drop actions and different GUI as a user-friendly software service. Cloud RPA ensures users automate any process via the Internet on the Cloud and can access it in their browser. RPA enables an intelligent agent to replicate typical manual decisions, such as rule based, well-structured ones involving vast amounts of data in a digital system, and eliminate operational errors.&nbsp

Robotic Process Flexibilization in the Term of Crisis: A Case Study of Robotic Process Automation in a Public Health Department

Due to the pandemic, institutions of the health sector, especially public health departments, are facing major challenges in managing their processes. In a constantly changing environment, new and existing processes have to be adopted or implemented in the shortest possible time, while the process volumes to be managed are constantly increasing. In our article, we use a case study to show how the concept of “flexibility by design” can be influenced by RPA in the sensitive environment of healthcare and how exactly flexibility in process execution can be achieved with it. As a result, we show that RPA can positively implement or enable three of the six realization options from the concept. In addition, the concept was supplemented by two aggregated theoretical dimensions, namely “Response” and “Range,” which summarize the supporting conditions for a process flexibilization with RPA. In the article, we thereby show how exactly RPA can complement existing processes in a healthcare environment and thus, serve to subsequently make rigid process models more flexible

Análisis Cuantitativo del Cambio de un Proceso Semi-dirigido a Uno con Asistente Digital Cumpliendo el Estándar de Calidad 5-Sigma en la Facturación de las Empresas Públicas de Medellín

La exigencia del mercado de tener un mejor desempeño en los indicadores de Calidad, reducir los errores que se presentan en este proceso y el aumento de las facturas que se generan mes a mes llevaron a la Unidad de Facturación a buscar herramientas como la inteligencia de negocios, la analítica y la robótica, aplicando BPM (Business Process Management) para mejorar las tareas de la actividad de revisión de la Calidad de la Facturación. Este proyecto de investigación busca establecer la diferencia cuantitativa de la eficiencia y eficacia de la revisión de la calidad de la facturación en EPM, cumpliendo con el estándar 5- Sigma, comparando las variables de tiempo y costos. El proyecto busca información para la toma de decisiones en la mejora generada por la transición de una operación manual a una con Automatización Robótica de Procesos. Se realiza una comparación de las actividades de análisis y se formulan las variables cuantitativas para hacer el cotejo de las dos herramientas analizadas, presentando los resultados obtenidos y haciendo recomendaciones de gestión del proyecto. Es necesario tener un indicador de calidad de máximo 230 errores por cada millón de facturas emitidas. Los participantes en este proyecto son la directora del proyecto; Rosalba Pacheco Higuera y el estudiante; Sergio Armando Valencia Castañeda. La investigación se desarrolló bajo una metodología cuantitativa que permitió comparar los recursos utilizados para realizar las tareas de revisión de la Calidad de la Facturación entre un proceso semidirigido y otro automatizado con RPA, respondiendo a las diferencias entre la eficacia, eficiencia y efectividad de ambos casos. La realización de las tareas de generación de PDF dentro de la revisión de la Calidad de la Facturación en EPM con un asistente digital RPA y Qlik Sense tiene un beneficio de más del 80% respecto a las tareas de un proceso semidirigido con EXCEL y Qlik View. Se concluyó que una actividad realizada de forma autónoma es más eficiente y eficaz que la misma actividad realizada asistida por un equipo de operarios y que mediante la reingeniería de las tareas realizadas se obtuvo una mayor eficiencia.The market demand to have a better performance in the Quality indicators and reduce the errors that occur in this process, and the increase in invoices that are generated month by month led the Billing Unit to look for tools such as the business intelligence, analytics and robotics, applying BPM (Business Process Management) to improve the tasks of the Billing Quality review activity. This research project seeks to establish the quantitative difference of the efficiency and effectiveness of the invoicing quality review in EPM, complying with the 5 - Sigma standard, comparing the variables of time and costs. The project seeks information for decision-making in the improvement generated by the transition from a manual operation to one with Robotic Process Automation. A comparison of the analysis activities is carried out and the quantitative variables are formulated to make the collation of the two tools analyzed, presenting the results obtained and making project management recommendations. It is necessary to have a quality indicator of maximum 230 errors per one million invoices issued. The participants in this project are the project manager; Rosalba Pacheco Higuera and the student; Sergio Armando Valencia Castañeda. The research was developed under a quantitative methodology that made it possible to compare the resources used to carry out the Billing Quality review tasks between a semi-directed process and another automated with RPA, responding to the differences between the effectiveness, efficiency and efficacy of both cases

Improving business processes with RPA technologies

A Robotic Process Automation (RPA) é uma tecnologia inovadora que utiliza robots em formato de software para automatizar tarefas repetitivas e melhorar processos empresariais. Esta investigação aprofunda-se nas suas vantagens e desafios, realçando o seu papel no aumento da produtividade, melhoria da precisão, redução de custos e no progresso da experiência do cliente. Apesar destes benefícios, a implementação do RPA enfrenta desafios, incluindo a necessidade de manutenção contínua e o potencial deslocamento de empregos humanos. A investigação integra uma Revisão Sistemática da Literatura (RSL) com a metodologia Investigação-Ação. A RSL apresenta os benefícios e os desafios do RPA, as suas abordagens de implementação e o seu impacto presente na literatura atual. A Investigação-Ação seleciona quais são os processos adequados para automatização e destaca a seleção e análise de processos enquanto etapas cruciais nas atividades de melhoria de processos. Adicionalmente, a investigação detalha as complexidades envolvidas na seleção, redesenho e otimização de processos para ajustar a distribuição de recursos humanos em tarefas que requerem um nível elevado cognitivo. Ao adotar RPA, é possível melhorar a eficiência e reduzir taxas de erro, possibilitando que outros recursos sejam alocados a atividades estratégicas e de valor acrescentado. Esta investigação, também apresenta um método para a seleção e redesenho de processos, essencial para uma implementação de RPAs. Por último, proporciona a aplicação de RPAs em ambiente real, podendo servir enquanto modelo para organizações que pretendem implementar esta tecnologia, melhorando o seu desempenho e mantendo competitividade no atual panorama de constante mudança.Robotic Process Automation (RPA) is an innovative technology that utilises software robots to automate repetitive tasks and enhance business processes. This research delves into the advantages and challenges of RPA, emphasising its role in increasing productivity, improving accuracy, reducing costs, and elevating customer experience. Despite these benefits, RPA implementation faces challenges, including the necessity of continuous maintenance and the potential displacement of human jobs. The study integrates a Systematic Literature Review (SLR) with Action Research methodology. The SLR defines the primary benefits and challenges of RPA, its deployment approaches, and its impact on business process tasks in the current literature. In contrast, Action Research selects the optimal business processes for automation and highlights the importance of process selection and analysis as crucial steps in business process improvement activities. It addresses the complexities of choosing, redesigning, and optimising business processes to maximise human resource allocation towards high-cognitive tasks. By adopting RPA, companies achieve enhanced process efficiency and reduced error rates, allowing staff to dedicate more time to strategic, value-added activities. The research presents a robust framework for process selection and business process model redesign, essential for successful RPA implementation. Furthermore, this research offers critical insights into RPA's application in a realworld environment, serving as a valuable resource for organisations intending to implement this technology, improving operational performance and sustaining competitiveness in the ever-changing business landscape

Implementation of intelligent process automation (IPA) based clinical decision support system for early detection and screening of diabetes : this thesis is presented in partial fulfilment of the requirements for the degree of Master of Information Sciences in Information Technology, School of Natural and Computational Sciences at Massey University Albany, Auckland, New Zealand

Diabetes mellitus has become a leading cause of disease-related deaths in the world. Once an individual is diagnosed with diabetes, a series of processes will be required to keep the blood sugar regular and help avoid hyperglycemia and hypoglycemia. Self-Management of diabetes is complex and involves constant glucose monitoring, diet management, care, support, exercise, and insulin management. These processes are expensive because they require detailed record-keeping of medications, activities, and a timely report to doctors to assist them in making an informed decision that will subsequently help the patient heal. Other challenges include the high cost of treatment, lifestyle changes, education, lack of medication adherence, and treatment plans. Our approach is to adopt the Early screening technique and detect the risk of diabetes unobtrusively. Early screening is a technique that can help detect Type 1, 2 diabetes and achieve preventive care according to the guidelines set by WHO and recommended by the American Diabetes Association (ADA). Unobtrusive systems allow a doctor to screen for diabetes while he is unaware. We followed the Design Science Research model (DSRM) and started by using systematic literature review (SLR) guidelines to search the most popular journals limiting the results tied to studies that discussed the screening and detection of the risk of diabetes. We reviewed the architecture, features, and limitations of the various tools and technologies using the following classification: Continuous Glucose Monitoring Systems (CGMS), Flash Glucose Monitoring Systems (FGMS), and the Unobtrusive Systems. In addition, under the unobtrusive system, we studied the Child Health Improvement through Computer Automation (CHICA) system. While there is evidence that supports its benefits and usefulness, we found some required enhancements from the literature in the areas of decision support systems, data entry automation, and flexible integration with other systems. The artefact built during the development phase is an Intelligent process automation (IPA) system that can be implemented within the health sector for early screening and detection of diabetes unobtrusively. Developing this artefact will allow us to understand the possible issues and challenges of implementing an automation process in a medical institution. We evaluated the artefact using a mix of quantitative and qualitative methods. This method allowed us to answer the research questions and understand the value of automation to medical practitioners. The value includes speed, reduce cost, and error while safeguarding the lives of the medical professional on active duty. The results show that the system can enhance patient-doctor interaction, reduce patient wait time, and optimize the glucose monitoring process. However, there were challenges such as cost of implementation, training of staff, and the increased workload within the system. In addition, potential challenges identified include fear of job loss and aversion to change during implementation within the hospital. This study has also allowed us to understand the integration of robotic process automation with machine learning within the healthcare sector. We hope that this study will contextually position IPA within the technological stack of health care institutions and add to the body of knowledge on this subject

Towards Intelligent Robotic Process Automation for BPMers

Robotic Process Automation (RPA) is a fast-emerging automation technology that sits between the fields of Business Process Management (BPM) and Artificial Intelligence (AI), and allows organizations to automate high volume routines. RPA tools are able to capture the execution of such routines previously performed by a human users on the interface of a computer system, and then emulate their enactment in place of the user by means of a software robot. Nowadays, in the BPM domain, only simple, predictable business processes involving routine work can be automated by RPA tools in situations where there is no room for interpretation, while more sophisticated work is still left to human experts. In this paper, starting from an in-depth experimentation of the RPA tools available on the market, we provide a classification framework to categorize them on the basis of some key dimensions. Then, based on this analysis, we derive four research challenges and discuss prospective approaches necessary to inject intelligence into current RPA technology, in order to achieve more widespread adoption of RPA in the BPM domain