Forced to provide results consistent results to shareholders the organizations turned to Robotic Process Automation (RPA) in order to tackle the following typical challenges they face: (1) Cost reduction, (2) Quality increase and (3) Faster processes. RPA is now considered the next big thing for the Shared Services Centers (SSC) and Business Process Outsourced (BPO) around the world, and especially in Central and Eastern Europe. In SSCs and BPOs the activities with the highest potential for automation are in finance, supply chain and in human resource departments. This means that the problems these business are facing are mostly related to high data entry volumes, high error rates, significant rework, numerous manual processes, multiple not-integrated legacy systems and high turnover due to repetitive/low value added activities. One advantage of RPA is that it can be trained by the users to undertake structured repeatable, computer based tasks interacting in the same time with multiple systems while performing complex decisions based on algorithms. By doing this, the robot can identify the exceptions for manual processing, remove idle times and keep logs of actions performed. Another advantage is that the automated solutions can work 24/7, it can be implemented fast, work with the existing architecture, cut data entry costs by up to 70% and perform at 30% of the cost of a full time employee, thus providing a quick and tangible return to organizations. For Romania, a key destination for SSCs and BPOs, this technology will make them more competitive, but also will lead to a creation of a series of high-paid jobs while eliminating the low-input jobs. The paper will analyze also the most important vendor providers of RPA solutions on the market and will provide specific case studies from different industries, thus helping future leaders and organizations taking better decisions.

Purpose: The purpose of this paper is to analyse the influences of different types of knowledge and their inherent dynamics on the effectiveness of the decision-making (DM) process. Knowledge dynamics (KD) is envisioned through the lens of the knowledge fields theory while effective DM process is objectivised via organisational appreciation and reward, higher business performance, sustainable partnerships and managerial satisfaction with previous achievements.Design/methodology/approach: A questionnaire-based survey was conducted with 275 middle managers from companies operating in the business consulting field. The conceptual and structural model was tested using the partial least squares structural equation modelling technique.Findings: The study advances novel insights into the significant positive influences of various knowledge fields on KD on the DM process within real-life business environments. Even though rational knowledge exerts a noteworthy effect on DM, its influence is exceeded by the KD, which proves that integrating emotional and spiritual knowledge in the decisional equation may become a pivotal input to making good managerial decisions regardless of the level of regulation and standardisation in the field.Research limitations/implications: The research relied on threefold knowledge fields as predictors for the DM process, thus providing a starting point for the development of more complex models.Originality/value: The study emerges as a groundbreaking approach via the integration and application of the knowledge fields theory within a more comprehensive and empirical outlook on the DM process. Simultaneously, it places DM beyond the unidimensional outcomes of rationality and intuition by urging its intricate and interactional nature.

Robotic Process Automation (RPA) is going into a “maturity market”. The main vendor providers surpassed USD 1 billion in evaluation and the research they are launching these days on the market will change again radically the business landscape. It can be seen already what is coming next to RPA: intelligent optical character recognition (IOCR), chat-bots, machine learning, big data analytics, cognitive platforms, anomaly detection, pattern analysis, voice recognition, data classification and many more. As a result the top vendors developed partnerships with the main leading artificial intelligence providers, such as: IBM Watson, Microsoft Artificial Intelligence, Microsoft Cognitive services, blockchain, Google etc. On the business part, the consulting companies who are implementing the RPA solution are moving from developing Proof-of-Concepts (POCs) and Pilots to helping clients with RAP global roll-outs and developing Centre of Excellences (CoE). As a result, the experiences gathered so far by the author on this kind of projects will be tackled also in this paper. In this article will we will present also some data related to automation for different business areas (eg. Accounts Payable, Accounts Receivable etc) and how an assessment can be done correctly in order to decide if a process can be automatized and, if yes, up to which extent (ie. percent). Moreover, through the case studies we will provide (1) how now the RPA is integrated with Artificial Intelligence and Cloud, (2) how can be scaled in order to face hypes, (3) how can interpret data and (4) what savings these technologies can bring to the organizations. All the aforementioned services made Robotics Process Automation a very powerful tool since a year ago when the author did the last research. A process that was mainly not recommended for automation or was partially automated can be now fully automated with more advantages, such as: money, non-FTE savings and fulfillment time.

Setting Up a Robotic Process Automation Center of Excellence

The widespread access to the Internet has undoubtedly changed the way businesses handle their processes and interact with their customers. With the surge of new devices, business models, technologies, and platforms, alongside social media growth and innovative advertising, it became easier to transition from employment to entrepreneurship. The paper aims to assess the public perception of digital entrepreneurship, with a focus on its barriers, drivers, and expectations for the future. The results show that there is a slight agreement with a digital business being easier to establish compared with a traditional one. The driving forces behind starting a digital business are recognized, and the digital environment is considered essential for business growth in the following years. With some exceptions, there are no significant differences between age groups, genders, relationship statuses, levels of education, and/or occupations when rating the barriers, drivers, and expectations for the future of digital entrepreneurship.

Innovative digital technologies, together with new sustainable practices, push for new business models and skillsets, pressuring companies to adapt to external change in order to gain competitive advantage. Higher education institutions could offer support. More than 20% of university graduates in the European Union study “business, administration or law”, with some of them being future top-level managers and entrepreneurs. This paper aims to provide an understanding of the factors shaping business students’ perspectives and decisions in the modern business landscape. It reunites their career preferences, personality characteristics and knowledge regarding technology’s utility for business and compares them between two cohorts (i.e., first year bachelor students and second year master students). The results of an online survey with a sample of 154 respondents show that business students’ entrepreneurial intention is influenced by their entrepreneurial confidence, their boldness when considering risks, as well as by being further along their educational journey. While almost 80% of business students are daring, oriented toward results and confident in their entrepreneurial abilities, and around 50% would feel most comfortable having their own business, approximately half of first year bachelor students and 14% of second year master students tend to be “not sure” regarding how eight out of ten modern technologies mentioned in this paper (i.e., robotic process automation, big data, artificial intelligence, computer vision, industrial robots, internet of things, virtual reality, enterprise resource planning) could improve a company’s innovation and performance.