Process performance indicators in project pre-design stage

Traditionally performance in construction is measured based on the iron-triangle - time, cost and quality. In recent years indicators have been developed to include the measurements of other aspects of project performance. The main shortcoming of these however is that most of them are lagging indicators and hence are of little use for controlling the performance during the projects. This paper reviews the existing key performance indicators, their types, use and shortcomings. The paper describes a proposed conceptual framework for developing performance indicators for the pre-design stage, of which the briefing process is an important part. In this framework a process mapping methodology is suggested to identify the main activities that take place in the pre-design phase, the dependencies between them and the stakeholders involved. Initial investigation of the proposed framework has shown that it is a viable model that has already helped in identifying the relevant processes of the pre-design phase and the related indicators

A combined sensitivity analysis and kriging surrogate modeling for early validation of health indicators

To increase the dependability of complex systems, one solution is to assess their state of health continuously through the monitoring of variables sensitive to potential degradation modes. When computed in an operating environment, these variables, known as health indicators, are subject to many uncertainties. Hence, the stochastic nature of health assessment combined with the lack of data in design stages makes it difficult to evaluate the efficiency of a health indicator before the system enters into service. This paper introduces a method for early validation of health indicators during the design stages of a system development process. This method uses physics-based modeling and uncertainties propagation to create simulated stochastic data. However, because of the large number of parameters defining the model and its computation duration, the necessary runtime for uncertainties propagation is prohibitive. Thus, kriging is used to obtain low computation time estimations of the model outputs. Moreover, sensitivity analysis techniques are performed upstream to determine the hierarchization of the model parameters and to reduce the dimension of the input space. The validation is based on three types of numerical key performance indicators corresponding to the detection, identification and prognostic processes. After having introduced and formalized the framework of uncertain systems modeling and the different performance metrics, the issues of sensitivity analysis and surrogate modeling are addressed. The method is subsequently applied to the validation of a set of health indicators for the monitoring of an aircraft engine's pumping unit

Defining Process Performance Indicators: an Ontological Approach

It is increasingly important to evaluate the performance of business processes. A key instrument to carry out this evaluation is by means of Process Performance Indicators (PPIs) as suggested in many methodologies and frameworks like, for instance, COBIT, ITIL or EFQM. As a consequence, it is convenient to integrate the management of PPIs into the whole business process lifecycle from its design to its evaluation. in this paper, we focus on the definition of PPIs as a necessary step to achieve that integration. Unfortunately, current proposals are not able to specify several usual types of PPIs, specially those related to data, and are not well designed to enable the automated analysis of PPIs at design-time. in this paper, we present an ontology for the definition of process performance indicators that overcomes this issue, explicitly defines the relationships between the indicators and the elements defined in a business process modelled in BPMN, and enables the analysis of PPIs at design-time. Furthermore, this ontology has been validated by means of several real-world scenarios

State Budget Challenges and the Scourge of Poverty

Performance Measurement is necessary in order to support the implementation of a Continuous Improvement approach within a company. Performance Measurement has been a subject of increasing interest for researchers and practitioners. The questions addressed in the literature especially evolved from “what” to measure to “how” to measure. The present thesis follows this evolution by exploring how companies can successfully implement Performance Measurement. The thesis follows a parallel research design including a literature review and a case study. From one side, a literature review aims at explaining the main theories behind Performance Measurement, such as the concept of Performance Measurement System, as well as giving some recommendation for its implementation. On the other side, an empirical case study, conducted in a construction industry company, presents a practical implementation of Performance Measurement including some of the indicators dashboards built in several factories and departments of the company. The results of this case study are also supported by several interviews conducted at different steps of the implementation with the different actors involved. Then a theoretical verification is conducted by comparing the theory from the literature review with the empirical results from the case study. It especially allows to verify some recommendations as well as to identify a few gaps. The results of this study can be seen as a set of verified recommendations in order to successfully implement Performance Measurement within a company. These recommendations come from the comparison between theory and practice and they are divided in three main parts: the Key Performance Indicators identification, the Performance Measurement System design, and the practical implementation of Performance Measurement. Regarding this last part, five key success factors (e.g. perceived benefits of performance measurement, top management commitment) and five barriers (e.g. time and effort required, human behaviour) have been verified. Moreover, some Performance Measurement issues are discussed, such as the reduction of the complexity, the potential gaps between local approaches and global consistency, as well as the concept of organisational learning. Finally, the thesis identifies three kinds of trade-offs (e.g. accuracy of the data and cost of collection) that need to be considered when implementing Performance Measurement

The Integration of Cleaner Production Indicators on the Environmental Performance Measurement System for the Indonesian Natural Rubber Industry

This study aims to identify the priority of the cleaner production implementation and integrate it in the design of a comprehensive environmental performance measurement system for natural rubber industry in Indonesia. Prioritizing the cleaner production on the production process of natural rubber is based on the case of 10 Indonesian crumb rubber companies using the Analytical Hierarchy Process. The comprehensive environmental performance measurement system in natural rubber industry, i.e. in crumb rubber industry, starts from the selection of key environmental performance indicators (KEPI) using the fuzzy independent preference evaluation method. The environmental performance measurement model is developed to assist users in evaluating the comprehensive environmental performance and condition of the key indicators. The weighting for each of the KEPI is performed by means of the expert choice software. The environmental performance measurement model is designed in the form of a environmental scorecard with traffic light facilities which can provide recommendations based on the performance achievement status of each KEPI. From the results of the model verification in the case of crumb rubber industry, several indicator statuses were found "not good", i.e. on the index of raw materials, solid waste load, water conservation, energy conservation, and environmental innovation indicators. The environmental performance ranking model is designed to evaluate the comprehensive environmental performance in different companies or at different assessment periods

Using a Responsive Survey Design to Innovate Self-Administered Mixed-Mode Surveys

Implementing innovations in surveys often results in uncertainty concerning how different design decisions will affect key performance indicators such as response rates, nonresponse bias, or survey costs. Thus, responsive survey designs have been developed to better cope with such situations. In the present study, we propose a responsive survey design that relies on experimentation in the earlier phases of the survey to decide between different design choices of which - prior to data collection - their impact on performance indicators is uncertain. We applied this design to the European Values Study 2017/2018 in Germany that advanced its general social survey-type design away from the traditional face-to-face mode to self-administered modes. These design changes resulted in uncertainty as to how different incentive strategies and mode choice sequences would affect response rates, nonresponse bias, and survey costs. We illustrate the application and operation of the proposed responsive survey design, as well as an efficiency issue that accompanies it. We also compare the performance of the responsive survey design to a traditional survey design that would have kept all design characteristics static during the field period

Marine safety and data analytics : vessel crash stop maneuvering performance prediction

Crash stop maneuvering performance is one of the key indicators of the vessel safety properties for a shipbuilding company. Many different factors affect these performances, from the vessel design to the environmental conditions, hence it is not trivial to assess them accurately during the preliminary design stages. Several first principal equation methods are available to estimate the crash stop maneuvering performance, but unfortunately, these methods usually are either too costly or not accurate enough. To overcome these limitations, the authors propose a new data-driven method, based on the popular Random Forests learning algorithm, for predicting the crash stopping maneuvering performance. Results on real-world data provided by the DAMEN Shipyards show the effectiveness of the proposal

Performance Indicators Analysis inside a Call Center Using a Simulation Program

This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key case at the time where the events analyses could be executed. This article comes to the conclusion that Simulation is a completely suitable instrument to accomplish its purpose since it could be adequate to demonstrate, for the call center taken into consideration principally that: (a) it is feasible to reduce the agent contingent; (b) reasonable variations on the demand design can impact very much the key performance indicators of the Call Centers’ project; and (c) it is feasible to increase the service level if a combined handling format is followed

Performance Indicators Analysis inside a Call Center Using a Simulation Program

This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key case at the time where the events analyses could be executed. This article comes to the conclusion that Simulation is a completely suitable instrument to accomplish its purpose since it could be adequate to demonstrate, for the call center taken into consideration principally that: (a) it is feasible to reduce the agent contingent; (b) reasonable variations on the demand design can impact very much the key performance indicators of the Call Centers’ project; and (c) it is feasible to increase the service level if a combined handling format is followed