Key Performance Indicator

This study evaluates the effectiveness of a performance-focused methodology for engaging multidisciplinary, frontline healthcare teams in making behavioural changes that improve patient care and health system efficiency. Results include significant declines in average length of stay in hospital and waiting time for surgery, and a dramatic increase in early patient ambulation. Performance-focused methodology using key performance indicators, targets, measurement, and ongoing feedback, supported by non-monetary incentives, can quickly improve healthcare outcomes.

ABSTRACT Purpose – Ensuring compliance with food safety legislation and market requirements is one of the key issues facing the poultry meat industry. The purpose of this paper is to analyse how a pre-requisite programme (PRP) and key performance indicators for food safety can be developed in the poultry meat supply chain. Design/methodology/approach – The first stage of the research involved an examination of literature, which was conducted using desk research. The second stage includes a discussion on food safety management systems in primary production and the development of food safety plans with an associated PRP. Findings – Effective food safety management systems in primary production are critical to supplying food which is safe and wholesome. In order to manage food safety effectively measurable indicators of performance should be developed. These will provide data on the suitability of the food for sale, the effectiveness of the food safety management system and any potential areas of weakness which in turn will drive continuous improvement. Originality/value – This study is of benefit to the broiler industry in the further development of quality assurance standards and business improvement models.

This paper presents an extensive review on the services, six-sigma, and application of six-sigma in services. In order to improve service quality focus on service process is necessary. Six-sigma is a philosophy which also concentrates on the improvement of ...

Supplementary Cluster Activities constitute an important organisational part within the structure of the German Cluster of Excellence “Tailor-Made Fuels from Biomass” at RWTH Aachen University, because they focus on the entire clusters efficient networking process and successful strategic cluster development. As research teams from different scientific fields collaborate, the strategic management of interdisciplinary processes becomes necessary to enhance scientific cooperation. Therefore, amongst other measures of cluster development, a Balanced-Scorecard-Approach is implemented to measure the performance of the entire Cluster of Excellence. With the annual implementation of the Balanced-Scorecard-Approach, crucial key performance indicators have been collected, compared and analysed for the strategic management of the Cluster of Excellence, to facilitate innovation activities through adequate measures.

Monitoring business activities using Business Intel- ligence (BI) tools is a well-established concept. How- ever, online process monitoring is an emerging area which helps organizations not only plan for future im- provements but also change and alter their current ongoing processes before problems happen. In this paper, we explore how monitoring process perfor- mance can help evolve process goals and require- ments. We elaborate an approach that uses the User Requirements Notation (URN) to model the goals and processes of the organization, and to monitor and align processes against their goals. A BI tool exploit- ing an underlying data warehouse provides the Key Performance Indicators (KPI) used to measure the satisfaction of goals and process requirements. Feed- ing this information into the URN modeling tool, we can analyze the consequences of current business ac- tivities on desired business goals, which can be used for process and business activity alignment thereafter. We illu...

As the complexity of commercial cellular networks grows, there is an increasing need for automated methods detecting and diagnosing cells not only in complete outage but with degraded performance as well. Root cause analysis of the detected anomalies can be tedious and currently carried out mostly manually if at all; in most practical cases, operators simply reset problematic cells. In this paper, a novel integrated detection and diagnosis framework is presented that can identify anomalies and find the most probable root cause of not only severe problems but even smaller degradations as well. Detecting an anomaly is based on monitoring radio measurements and other performance indicators and comparing them to their usual behavior captured by profiles, which are also automatically built without the need for thresholding or manual calibration. Diagnosis is based on reports of previous fault cases by identifying and learning their characteristic impact on different performance indicators. The designed framework has been evaluated with proof-of-concept simulations including artificial faults in an LTE system. Results show the feasibility of the framework for providing the correct root cause of anomalies and possibly ranking the problems by their severity.

This paper presents a framework for assessing the impact of the data collection process on the validity of key measures in reliability. The quality of data is affected by many organisational and behavioural factors. The aims of developing this framework are to (1) identify inputs/steps that have the most significant impact on the quality of key performance indicators such as MTTF (mean time to failure) and MTTR (mean time to repair), (2) identify ‘weak’ links in the data collection process, and (3) identify potential remedial actions. Development of this framework will assist the understanding of assumptions used in reliability calculations and improve the quality of underlying data and the data collection process. Consequently, this is a vital step in the continued development and use of data based decision-making models for reliability assessment.

Enterprise Resource Planning systems have been introduced to support the efficient and effective execution of business processes. In practice, this may not fully succeed. This also holds for inventory management (IM), part of the sub-field within logistics termed supply chain management. By analyzing the IM business process, eleven potential benefits are indicated. Next, by using a Business Intelligence approach, key performance indicators (KPIs) are selected to measure the performance of sub-processes. Putting this together yields an IM framework that is used to obtain a generic, coherent picture of IM processes in different organizations. The proposed framework is tested using experts’ opinions and two case studies. The experts’ comments yielded a list of top-10 KPIs. The case study results show that some of the potential benefits are also observed in practice. Future research may reveal that comparable performance improvements are possible in other ERP domains based on similar measurement frameworks.

In the pharmaceutical industry, systems for improving operational effectiveness and efficiency are becoming more and more popular. In this paper, developments in the industry’s improvements in operational effectiveness and efficiency have been analyzed. A holistic model is presented which builds the basis for the presented study results. The study includes data gathered from pharmaceutical production sites in surveys in 2004 and 2009. The analysis is divided according to the four sub-systems: Total Productive Maintenance, Total Quality Management, Just-in-Time, and the Management System. For each sub-system, key performance indicators and associated elements (practices and instruments) from 2004 to 2009 are investigated. The data indicates that the industry did make continuous steps towards “Excellence in Operations” between 2004 and 2009. Pharmaceutical companies took control over their former low asset utilization and managed to improve the efficiency of their quality systems; however, they are still far away from having any kind of “continuous flow”, smooth production scheduling or make-to-order manufacturing. It can be said that most of the companies are still working on the effectiveness side rather than focusing on the efficiency side.

Cost overrun in the field of project construction is still a global issue, and it is a challenge to seek for solution from various scientific discipline including information technology. This thesis aims to design a business intelligence application model for analyzing the cost of construction project to provide follow-up information as quickly and as early as possible to assist the executives to make valuable business decisions. This case study was prepared through literature reviews, interviews, and direct observation to obtain overview of the business processes in the construction company. The modeling of BI application which can be successfully developed using agile methods is very effective in addressing the change. This case study found that the application of business intelligence which provides information on key performance indicator (KPI) can assist the executives of the company to make decisions quickly and precisely, thus improving the performance of the project, especially in the cost control.

The purpose of this study is to develop key performance indicators to measure performance of academic staff in private higher learning institutions in Malaysia. Universiti Tenaga Nasional is chosen as the case study. This paper discusses the development of Key Performance Indicator (KPI) based on Balanced Scorecard. Focus groups were used to come up with the operational performance indicators through a series of workshops, meetings and discussions. 14 key performance indicators were developed under 5 main headlines, teaching and supervision, research and innovation, publication, consultancy and services. A questionnaire was then designed to rate the favourability of the chosen KPIs. Analysis were done using Fuzzy Conjoint Model.