Coordinating and Evaluating of Multiple Key Performance Indicators for Manufacturing Equipment: Case Study of Distillation Column

There appears to be confusion regarding how to conduct a comprehensive benchmarking study, especially one on labor productivity. This paper details a six-step procedure for conducting a labor productivity benchmarking study. The procedure addresses the questions of how, who, and why. The procedure is illustrated using three case study projects. A labor productivity study has several unique features. First, the objective must be precisely defined. A study of labor productivity can be done for many reasons, and the purpose must be clearly defined because the objective influences subsequent decisions involving protocols. Procedures for how the study will be conducted to assure valid comparisons must be developed. Next, the key performance indicators (KPIs) must be determined and a procedure must be established for evaluating multiple KPIs. Labor productivity is unique in that there is no single KPI that can be used to define best performance. Multiple KPIs are proposed and procedures are developed. O...

Transportation infrastructure supports economic growth and quality of life for citizens. Optimal operation and maintenance of transportation infrastructure, such as bridges, is a trade-off between multiple Key Performance Indicators (KPI) such as reliability, availability, costs, environmental impacts, and safety (probability of life and limb). Some KPI’s are codified which may allow for a uniform evaluation. Other KPI’s are more difficult to define and evaluate. The use of Unmanned Aerial Vehicles (UAV) for inspection purposes maximise availability and minimise costs as well as user safety (bridge users as well as inspection personnel). Significant experience from 3 recent bridge-related inspection projects: The Öresund Bridge (cable-stayed bridge between Denmark and Sweden), The Faroe Bridges (one being a cable-stayed bridge – both located in Denmark) and The New Little Belt Bridge (suspension bridge in Denmark), has been obtained. The paper present key findings in relation to integration of UAV-supported inspections.

PurposeThis paper aims to present a simple and innovative fuzzy methodology-based lean performance measurement system (L-PMS) for an Indian automotive supply chain. The paper also enlightens the influence of coronavirus disease 2019 (COVID-19) on supply chains and the practical implications of the unprecedented disruptions on the performance measurement systems.Design/methodology/approachThe L-PMS is divided into three phases. In the first phase, the key performance indicator (KPI) list, as deemed fit by the organization, is prepared using literature and suggestions from the case organization. The list contains 61 KPIs measuring 24 performance dimensions in seven functional areas of the supply chain. In the second phase, the KPI performance data (actual, best and worst) are collected using the enterprise resource planning (ERP) system. In the last phase, the leanness score of the case organization is calculated at four levels – KPI, dimension, functional area and overall organization.FindingsThe overall leanness score of the case organization is 60%. The case organization uses KPIs from all seven functional areas, but it needs to improve the number of KPIs in administration and supplier management functional areas. The case organization uses only quantitative KPIs. However, the performance dimensions at the middle level are adequate. The leanness level of the case organization in different areas is highly variable (ranges from 45% to 91%).Research limitations/implicationsThe major limitation of the study is that the case study is done at a single organization.Practical implicationsThe managers at the different levels of the hierarchy can use the lean performance measurement score to leverage the better performing areas/dimensions/KPIs and improve poor performing areas/dimensions/KPIs. The lean performance measurement at functional area level can help leadership to give responsibility to different people for the improvement of leanness with respect to different dimensions/functional areas. The disruptive impact of COVID-19 should clearly be understood by the managers to make appropriate decisions based on the severity as measured at different levels.Originality/valueAccording to the authors' best knowledge, this is the first lean performance measurement application at the four hierarchical levels (KPI, performance dimension, functional area and overall organization).

In response to large-scale health crises, emergency healthcare infrastructure projects (EHIPs) have been implemented to provide healthcare services rapidly. However, few studies have systematically explored the success of these projects. This study aims to assess the success of EHIPs throughout the whole life cycle using a cloud matter-element model (CMEM). Considering multiple performance indicators that measure the success of EHIPs, a hierarchy model of the project success index is proposed through eight rounds of Delphi surveys. This model comprises 10 key performance indicators (KPIs) that are most appropriate for measuring the success of EHIPs and 20 quantitative metrics aligned with these KPIs across the life cycle. Based on the hierarchy model, the CMEM is applied to evaluate the success of EHIPs, which effectively addresses the fuzziness and randomness inherent in the Delphi process. Two cases were then utilized for verifying the practicality of the proposed project success assessment model. The findings demonstrate that the CMEM-based assessment offers not only significant flexibility but also high accuracy, robustness, and scalability. The CMEM-based assessment seamlessly integrates numerous incompatible indexes and their characteristic values, without being limited by the number of evaluation indexes. Further, sensitivity analyses are conducted to test the robustness of the assessment model and its results. These analyses confirmed that the CMEM is a robust, reliable, and adaptable tool for assessing the success of EHIPs. Theoretically, this study should set an exemplar of aggregating the performance measurement with emergency management and healthcare systems, facilitating an efficient response to major crises. It also provides a novel approach to evaluating multiple-criteria decision-making problems. Practically, this study should enable project management teams to identify and improve weak areas, ensuring continuous success in the EHIP-related domain.

Problem Management (PM) is one of the components in the Information Technology Infrastructure Library (ITIL) Service Support area. The primary focus of Problem Management is to identify causes of service issues and commission corrective work to prevent recurrences. To address this practice and make it more effective, the project tends to identify the specific Key Performance Indicator (KPI) for    Problem Management process in a Malay owner company named as Mesiniaga Berhad. The identification of Problem Management KPI is based on the previous research which is using ITIL as a framework. The interview session has been conducted in Mesiniaga with Problem Manager working at that company with more than 10 years’ experience in Problem Management process. The method of    interview is using qualitative approach which is using the design question with the lists of KPI. The expert will select or decide which KPI are related with the current report in Mesiniaga. The result showed that 6 KPIs are related and come out with analysis on how the outcome of KPI behavior matched with the Incident report in Mesiniaga. To enhance on how the identification of KPI, instead of using manual to capture the Problem Management KPI, the automation of selected KPI from Incident to Problem Management can be       implement in the systems. Most technologies are intelligent enough for data analytic to decide which suitable KPI of Problem          Management follow the current business and client environment. Â

A thermal performance standard for residential buildings in warm climates: Lessons learned in Brazil

Diversified and complicated manufacturing sites make optimal scheduling of production lines difficult. Under current manufacturing processes, it is almost impossible for schedulers to consider all the constraints of production processes. A strategy of simulation-based advanced planning and scheduling (APS) is employed to overcome difficulties that interfere with satisfactory on-time delivery and commitment to the current status. In simulation-based scheduling, key performance indices (KPIs) are important for selecting optimal dispatching rules in scheduling. In cases involving complex processes, in which the identification of appropriate KPIs is limited to selection among existing KPIs, KPIs should be chosen and modified carefully to optimize process management and to reflect all of the existing constraints of production. However, the existing methodologies for modifying KPIs are misplaced in complex manufacturing environments such as job-shop processes. We propose a new method to design and select appropriate KPIs that meet the characteristics of any given process, and verify with empirical analysis whether or not the KPIs meet requirements from experts of production lines.

PurposeThe purpose of this paper is to present a comprehensive survey of workplace productivity key performance indicators (KPIs) used in the office context. Academic literature from the past 10 years has been systematically reviewed and contextualized through a series of expert interviews.Design/methodology/approachThe authors present a systematic review of the literature to identify KPIs and methods of workplace productivity measurement, complemented by insights semi-structured interviews to inform a framework for a benchmarking tool. In total, 513 papers published since 2007 were considered, of which 98 full-length papers were reviewed, and 20 were found to provide significant insight and are summarized herein.FindingsCurrently, no consensus exists on a single KPI suitable for measuring workplace productivity in an office environment, although qualitative questionnaires are more widely adopted than quantitative tools. The diversity of KPIs used in published studies indicates that a multidimensional approach would be the most appropriate for knowledge-worker productivity measurement. Expert interviews further highlighted a shift from infrequent, detailed evaluation to frequent, simplified reporting across human resource functions and this context is important for future tool development.Originality/valueThis paper provides a summary of significant work on workplace productivity measurement and KPI development over the past 10 years. This follows up on the comprehensive review by B. Haynes (2007a), providing an updated perspective on research in this field with additional insights from expert interviews.

In this chapter, we will underline the importance of the key performance indicators (KPIs) computation for power plants' management. The main scope of the KPIs is to continuously monitor and improve the business and technological processes. Such indicators show the efficiency of a process or a system in relation with norms, targets or plans. They usually provide investors and stakeholders a better image regarding location, equipment technology, layout and design, solar and wind exposure in case of renewable energy sources and maintenance strategies. We will present the most important KPIs such as energy performance index, compensated performance ratio, power performance index, yield, and performance, and we will compare these KPIs in terms of relevance and propose a set of new KPIs relevant for maintenance activities. We will also present a case study of a business intelligence (BI) dashboard developed for renewable power plant operation in order to analyze the KPIs. The BI solution contains a data level for data management, an analytical model with KPI framework and forecasting methods based on artificial neural networks (ANN) for estimating the generated energy from renewable energy sources and an interactive dashboard for advanced analytics and decision support.

KPI-Based Approach for Business Process Improvement

BackgroundThe objective of this study was to describe aspects of case study herds investigated by the Department of Agriculture, Fisheries and Food (DAFF) in which animal welfare incidents occurred and to identify key performance indicators (KPIs) that can be monitored to enhance the Early Warning System (EWS). Despite an EWS being in place for a number of years, animal welfare incidents continue to occur. Questionnaires regarding welfare incidents were sent to Superintending Veterinary Inspectors (SVIs), resulting in 18 herds being chosen as case study herds, 12 of which had a clearly defined welfare incident date. For each study herd, data on six potential KPIs were extracted from DAFF databases. The KPIs for those herds with a clearly defined welfare incident date were studied for a consecutive four year window, with the fourth year being the 'incident year', when the welfare incident was disclosed. For study herds without a clearly defined welfare incident date, the KPIs were determined on a yearly basis between 2001 and 2009.ResultsWe found that the late registration of calves, the use of on-farm burial as a method of carcase disposal, an increasing number of moves to knackeries over time and records of animals moved to 'herd unknown' were notable on the case farms.ConclusionFour KPIs were prominent on the case study farms and warrant further investigation in control herds to determine their potential to provide a framework for refining current systems of early warning and prevention.

Purpose. This research aims to investigate how small and medium-sized enterprises (SMEs) can strategically leverage key performance indicators (KPIs) to enhance their performance and competitiveness in the dynamic business landscape. Through a multifaceted research methodology, including secondary data analysis, case studies, comparative analysis, and future trends analysis, the study seeks to address the specific challenges faced by SMEs and provide actionable insights for optimizing performance through KPI utilization. Results. The findings of this research reveal the intricacies of SME performance challenges, ranging from financial constraints to operational complexities. Through a comprehensive examination of theoretical foundations and real-world case studies, the study demonstrates successful strategies used by SMEs in effectively utilizing KPIs. The comparative analysis identifies patterns and distinctions in KPI deployment across industries, enriching the understanding of tailored approaches. The forward-looking future trends analysis anticipates advancements in data analytics, artificial intelligence, and technological tools that will shape the landscape of SME performance measurement. Scientific novelty. This research contributes to the field by offering a nuanced exploration of challenges faced by SMEs and the transformative potential of KPIs within their unique operational environments. The comparative analysis and future trends exploration add a novel dimension, providing a forward-looking perspective on the evolving landscape of KPI utilization in SMEs. The research pioneers an investigation into emerging technologies and methodologies, positioning itself at the forefront of anticipating future trends in SME performance measurement. Practical value. The practical value of this research lies in its provision of actionable insights for SME leaders, policymakers, and researchers seeking to enhance the resilience and competitiveness of SMEs. By synthesizing theoretical foundations with real-world examples, the study offers practical guidance on addressing challenges and optimizing performance through KPI utilization. The exploration of tools, technologies, and future trends equips SMEs with the knowledge needed to navigate the intricate business landscape effectively.

This study aims to evaluate the effectiveness of the Key Performance Indicators (KPI) method in assessing employee performance at CV Pustaka Tiga Mandiri. The research utilizes a qualitative approach with interviews, observations, and documentation as the primary data collection instruments. Employee performance evaluations at this company heavily depend on achieving targets set through KPIs, which serve as benchmarks for the success of individuals and departments in reaching the company’s strategic goals. The findings indicate that the implementation of KPIs at CV Pustaka Tiga Mandiri has a significant impact on employee performance, particularly in the marketing department. Employees who meet their targets receive better performance evaluations and additional incentives, while those who fail to do so are issued warnings to improve their performance. Performance evaluations also affect compensation, with salary deductions applied to employees who are absent without valid reasons. The implications of this study highlight the importance of implementing an objective and data-driven performance appraisal system to enhance productivity and efficiency within the organization. The study also demonstrates that using KPIs as an evaluation tool can help the company identify areas needing improvement and provide a solid foundation for managerial decision-making. The originality or novelty of this research lies in the application and evaluation of the KPI method within the context of a local company, which is still relatively uncommon in Indonesia. This study contributes to the understanding of how KPIs can be effectively used to improve employee performance in medium-sized enterprises.

The goal of our research and experiments is to find the definitions and values of key performance indicators (KPIs) in unstructured text. The direct access to opinions of customers served as a motivating factor for us to choose Twitter data for our experiments. For our case study, we have chosen the restaurant business domain. As in the other business domains, KPIs often serve as a solution for identification of current problems. Therefore, it is essential to learn which criteria are important to restaurant guests. The mission of our Proof-of-Concept KPI discovery tool presented in this paper is to facilitate the explorative analysis taking Twitter user posts as a data source. After processing tweets with Stanford CoreNLP toolkit, aggregated values are computed and presented as visual graphs. We see our tool as an instrument for data discovery applicable, for example, to define new qualitative and quantitative KPIs based on the values found in the graph. The graph represents a complete view of aggregated data that corresponds to the search results according to the user-defined keywords, and gives easy access to detailed data (tweets) that, in its turn, leads to better understanding of the post context and its emotional coloring.

<p><span>This paper introduces and proposes an approach in goal-oriented requirements elicitation process that using Key Performance Indicators (KPIs), in information system enhancement process. KPIs can be used to control and reduce user requirements problems caused by personal interests of users in requirements elicitation process. An information system enhancement project for a distribution company has been used as a case study to demonstrate this approach. The case study shows that the requirements can be elicited from the organization goals and current information system condition rather than from user requirements. This approach also showed that KPIs have been able to control some user requirements that have difference point of view with high level stakeholder requirements. Compared with the previous research, IT goals and KPIs are more easily identified in the enhancement process rather than through development of a brand new information system.</span></p>