Background/Objectives: To describe about the importance of big data analytics in healthcare, discuss the advantages and methodologies, describe examples provided in the literature, briefly discuss the challenges, and offer conclusion. Methods/Statistical analysis: A survey on methods that supports healthcare value by reducing cost at the same or better quality using big data techniques. Findings: Right procedure to guide the beginners of medicine and enhance Research and Development productivity in discovery, development, and safety in healthcare. It delivers the needed outcomes for each patient using evidence-based care, while ensuring safety. Improvements/Applications: Various approaches discussed can be applied in different fields of healthcare analytics in order to obtain sustainable answer for morbidity cases and also provide a better decision support system saving lives at lower costs.

Need, Application and Characteristics of Big Data Analytics in Healthcare-A Survey

Managers can only recognize a problem if they are fit to identify it as such, and successfully act on it only if they understand what causes it and how to adapt to it. One area that is hard to both understand and manage successfully is that of innovation. Due to inherent aspect of novelty, managing innovation entails a large portion of uncertainty. Moreover, in an increasingly complex business environment innovation is an area that has become essential for a firm’s success. The ability to successfully identify and mitigate problems related to the firm’s innovation efforts is consequently paramount for firms’ long-term success. It would consequently be of large importance for organizations to possess tools and frameworks that aid them in identifying issues and guide them through the uncertainty of innovation. The purpose of this report is to develop a tool that acts as a management system that facilitates managerial understanding of innovation as well as be used as a basis for decisions and facilitate communication regarding the topic. Thereby supporting organizations in strengthening their innovation capabilities. This was done through an abductive research, including a theoretical review of previous literature, as well as 38 interviews at Ericsson. A conceptual model of innovation capabilities was developed by combining these two sources. The model was subsequently developed into an assessment tool which was applied on a single product department of Ericsson. The purpose of this application was to evaluate current innovation capabilities and support upcoming efforts, as well as verify the utility of the proposed assessment tool. The resulting assessment tool consists of six individual elements, each with influence of the innovation capabilities of a firm. System theory is integrated into the assessment tool, meaning that all elements must be taken into consideration when it is applied. The elements are divided into two separate categories called Doing the right things and Doing things right. Doing the right things consists of two elements, Organizational intelligence and Innovation strategy & vision. These elements are presented as central due to their fundamental necessity in developing additional elements. Surrounding elements are Resources, Processes, Values and Organizational structure describing the ability for Doing things right. The assessment tool also includes a way to create a goal and an action plan to reach this goal based on the initial assessment.

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Proposing a tool for assessment of innovation capabilities through a case study at Ericsson

The transition from speech as the dominant service to data services has led to new trends in telecommunication business, and therefore the need to adjust legacy metrics and KPIs (Key Performance Indicators) that aims to point out the effects of these changes. In this paper, we give the development trends of new KPIs by which the telecommunications companies more accurately scaled the use of services and income generated from data driven services. Special attention was paid to the situation of the market in Bosnia and Herzegovina and the need for monitoring the trends in this area.

The evolution of metrics in modern telecommunication environment

The transition from voice to data services has led to new trends in telecommunication business, and therefore the need to adjust legacy metrics and KPIs (Key Performance Indicators) that aims to point out the effects of these changes. In this paper, we give the review of development trends of new KPIs that provide greater insight into the use of data based services, as well as estimating the share of revenue that is obtained from these services. The importance of customer segmentation and correlation with KBOs (Key Business Objectives) is discussed. Special attention was paid to the situation of the market in Bosnia and Herzegovina and the need for trends monitoring in this area.

Development trends of telecommunications metrics

The telecom industry is phasing towards a business model which is more data centric, as the industry sees a decline in its legacy services. As a result of this shift, the legacy metrics and KPIs which were once used to scale and understand respectively the performance of the industry need to evolve as per needs of the new environment to provide a more accurate picture of the industry as it undergoes a business transformation. As a result of shift from voice to data there is a change in the business trends in the telecom industry which in turn necessitates the need for new Key Perfomance Indicators to measure the performance of the telecom industry. So the objective of the paper is to study the changes happening in the telecom industry due to the shift of voice from data and the effect of this shift on the telecom business trends. The paper attempts to come up with new key performance indicators which will help the telecom managers' scale the usage and revenue generated by data services more accurately.

G. S. Jayendran

Papers

Transforming Telecom Business: Scaling the Shift Using Predictive Analytics