Analysis Of Key Performance Indicators Research Articles

Visualization and analysis of key performance indicators for agricultural cold supply chain in Indian context using fuzzy DEMATEL approach

PurposeThis study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.Design/methodology/approachThe KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.FindingsThe findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.Research limitations/implicationsTo connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.Originality/valueThe presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.

Analysis of Key Performance Indicators during and Post the Covid-19 Pandemic (Case Msmes in Indonesia)

This study aims to identify the Key Performance Indicators (KPI) of each of the internal and external environmental factors used to measure the performance of Micro, Small, and Medium Enterprises (MSMEs) during and after the COVID-19 pandemic. The population in this study are the owners and managers of MSMEs in Banyumas Regency in December 2020 and 2021. The data analysis technique uses the Mc-Nemar Test Method. The results of the study indicate that KPIs which include production; GMP Good Manufacturing Practices; quality control; Brand; packaging; labeling and intellectual property; marketing; Financial management; capital literacy; Human Resources; character; Relevant agencies, and permits to measure MSME performance during and after the COVID-19 pandemic. These KPIs contain implementation in the short term (during the COVID- 19 pandemic) and medium or long term (post-COVID-19 pandemic). This study proves that KPIs relevant to measuring short-term performance are very important to develop a model for the recovery of MSME performance during the COVID-19 pandemic. Relevant KPIs to measure the performance of MSMEs in the medium or long term are very important to determine the post- COVID-19 recovery strategy.

Performance assessment of a communication infrastructure with redundant topology: A complex network approach

The physical assets within a critical infrastructure system are pivotal to its efficient performance and protection and that of other dependent systems. This is particularly the case for communication systems where network protection strategies usually involve asset redundancy. Although such redundancy is well-modelled in the literature, there is a gap in knowledge from a network science perspective in terms of its implications for network modelling and performance assessment. This paper presents a multilayer complex network framework that takes into account the heterogeneity of the redundant infrastructure for realistic network modelling and further analysis, a step change from using a single network model. Key performance indicators (KPIs) for communication networks (i.e., latency and jitter, bandwidth and throughput, queue depth and packet drops) are redefined to evaluate key important features of a long-haul backbone network such as network capacity and average use. In addition, these KPIs are adapted to deal with the aforementioned redundancy and so inform network managers with values defined over a model closer to the real system. The paper analyses the use case of a nationwide core and metro network infrastructure of one of the main UK internet service providers. The results of the analysis of KPIs showcase the advantage of the proposed multilayer complex network framework over the traditional single network model. Critical network elements within different dimensions of a communication network are identified based on their performance for prioritising network management measures.

Application-driven level-of-detail modeling framework for occupant air-conditioning behavior in district cooling

Occupant behavior (OB) contributes significantly to uncertainties in the results of building performance simulation (BPS). However, a consensus regarding the appropriate level of detail (LoD) for OB modeling in BPS is yet to be reached. Hence, this study focuses on district cooling simulation applications. A systematic technical framework for determining the most appropriate LoD for modeling occupant air-conditioning (AC) use behavior is proposed herein. The framework includes three steps: defining applications and the key performance indicators (KPIs), defining comparable LoDs for AC use behavior modeling, and selecting LoDs based on KPI analysis. Appropriate LoDs for different applications are concluded. For the application related to total cooling demand evaluation, LoD O-1, representing average occupant with stochastic models, is recommended. For the design (sizing) of cooling equipment, LoD O-2, considering the diversity behaviors of occupants, is recommended. For the design of district thermal energy storage (TES) system, LoD O-2 is appropriate. For electricity pricing strategy-making, the most detailed LoD O-3 is recommended. The proposed analytics framework of modelling different LoDs of AC behavior can inspire researchers and modelers on understanding and determination of OB modeling LoDs for various future projects.

Модель объектных отношений для интеллектуального управления на основе производственных данных

<p>A field of Industry 4.0 is one of the most perspective with respect to research and optimization of production and industrial problems. The main problems in this field are connected with necessary analysis and processing of a huge data, which have a different native and sources. Particularly, the data from various automatic sources, as well as getting due to human management, become far away from each other both from the structure point of view and the native meaning. And there often occur, that such a different data in integrated form could contain a significant information for analysis, and moreover for a transformation of the technological process. At the same time, it is rather difficult to provide an analysis in frame of a significant asynchrony, and sometimes it becomes to a practical unsolvable problem. In this regard, the problem on developing of specialized methods for collecting, storing and processing big data of various structures are becoming fundamentally relevant. This is the purpose of the present work, which proposes a new method for organizing data based on the concept of object relations as a universal structure for production modeling. The proposed method is based on the concept of an "object", which is any entity of the production chain (plant, workshop, machine, production operation, unit of production, etc.) The key difference between the method of object relations and agent modeling is the fact that no behavioral scenarios are imposed on objects. Thus, the "object" structure turns out to be authorized to enter into any relationship with other "objects" within the framework of the model under consideration, which in turn allows to accumulate various kinds of data into a single hierarchy and guarantees the reliability of analysis at any level. The proposed method of object relations has been applied at several full-scale production sites, thereby confirming its stability and operability. The paper provides an analysis of key performance indicators of the application of the method of object relations to solve the problem of forming a technological passport of a product at the steel production, and also discusses ways of further development.</p>

Comparative Statistical Analysis of Key Performance Indicators in the Health System.

In this paper, a comparative statistical analysis of some performance indicators from the health system at SCJU Craiova and SJU Slatina is made in the period 2010-2021. Also, the correlations between the average duration of hospitalization, the bed utilization rate, the number of cases and the case complexity index for each hospital are studied. It is found that there are similarities, but also statistically significant differences between the two analyzed hospitals. Thus, it turns out that there are no significant differences between the bed utilization rate and the complexity index between the two hospitals, but there are statistically significant differences at a significance threshold of 5% between the average duration of hospitalization and the number of cases registered at the two hospitals analyzed. Moreover, the case complexity index is strongly negatively correlated with the bed utilization rate and with the number of cases in both hospitals, but positively correlated with the average duration of hospitalization at SCJU Craiova and weakly negatively correlated at SJU Slatina.

CO2 electrolysis towards large scale operation: rational catalyst and electrolyte design for efficient flow-cell.

The electrochemical CO2 reduction reaction (CO2RR) to renewable fuels/chemicals is a potential approach towards addressing the carbon neutral economy. To date, a comprehensive analysis of key performance indicators, such as an intrinsic property of catalyst, reaction environment and technological advancement in the flow cell, is limited. In this study, we discuss how the design of catalyst material, electrolyte and engineering gas diffusion electrode (GDE) could affect the CO2RR in a gas-fed flow cell. Significant emphasis is given to scale-up requirements, such as promising catalysts with a partial current density of ≥100 mA cm-2 and high faradaic efficiency. Additional experimental hurdles and their potential solutions, as well as the best available protocols for data acquisition for catalyst activity evaluation, are listed. We believe this manuscript provides some insights into the making of catalysts and electrolytes in a rational manner along with the engineering of GDEs towards CO2RR.

Analyzing Effective Digital Marketing Strategies for Online Merchants

In today's extremely competitive business environment, digital marketing has evolved into an essential component that must be present for an online retailer to achieve success and sustain development. The purpose of this research is to investigate successful digital marketing methods for online retailers, with a particular emphasis on gaining an understanding of the main components that contribute to the accomplishment of a digital marketing campaign. In the beginning of the paper, we discuss the significance of digital marketing in the context of online retailers. More specifically, we focus on the necessity of efficiently reaching and engaging with one's target audience while they are in the digital arena. The article then looks into a variety of approaches that online retailers take in order to make the most of their digital marketing efforts. The investigation covers a comprehensive variety of digital marketing tactics, such as search engine optimization (SEO), content marketing, social media marketing, email marketing, influencer marketing, and paid advertising. Each tactic is analyzed in terms of the overall marketing objectives of online retailers, the ways in which it might be applied, and the possible impact it can have on those objectives. The significance of making decisions regarding digital marketing initiatives based on analysis of data is investigated in this study. It places an emphasis on the significance of monitoring and conducting an analysis of key performance indicators (KPIs) as a means of determining the degree to which particular marketing tactics are successful. In addition, the abstract emphasizes the significance of personalization and targeting in digital marketing, drawing attention to the fact that marketing communications should be tailored to the specific demographics of target audiences. This research is exploring the key components of effective digital marketing strategies for online merchants & also provided insights and practical recommendations for online merchants to optimize their digital marketing efforts.

Omogućavanje digitalnog rasta kroz kontinuiranu edukaciju menadžera projekata - okvir za kolaborativno, komplementarno, održivo i istovremeno učenje u organizacijama za softversko inženjerstvo

Introduction/purpose: This paper introduces a novel PMO EDUCT framework that encompasses Collaborative, Complementary, Sustained, and Simultaneous learning explicitly tailored for the dynamic landscape of software engineering. This paper contributes to the ongoing discourse on education and professional development in the digital era by illuminating the challenges faced, the framework developed, and the measurable outcomes achieved. The presented framework underscores the need for agility, adaptability, and a relentless pursuit of knowledge as fundamental tenets for success in an ever-evolving landscape. Methods: Focusing on a large software engineering organization, this study explores the multifaceted aspects of project management education, methodology enhancement, and team optimization. The proposed methodology combines qualitative and quantitative approaches to explore the educational process area in a global organization and generate a flexible and measurable framework to improve corporate knowledge growth. The framework aims to provide learners the most flexibility about learning paths, schedules, collaboration, and best practice exchange while guaranteeing proper alignment with frequent market changes and emerging PM skills. Results: Findings indicate that personalised, continuous learning, facilitated through collaborative environments and custom-tailored content, yields significant benefits. Through analysis of key performance indicators (KPIs), this study showcases improved project onboarding, enhanced team collaboration, and the cultivation of a culture of innovation. Conclusion: This paper presents the PMO EDUCT framework that organizations can use to create a learning culture and empower their employees to succeed in the constantly evolving field of software development. By adopting collaborative, complementary, sustained, and simultaneous learning principles, organizations can develop a workforce with the essential skills of critical thinking, collaboration, and adaptability necessary for success in the digital era.

Analysis of Key Performance Indicators to Study the Growth and Development of Selected Software Companies in India

The Indian software industry plays a significant role in developing the national economy, from an inward looking economy into a dynamic digitally empowered society. Nearly 95% of the foreign exchange inflows in the service sector are contributed by IT and Buisness Process Outsourcing (BPO) industries. Indian government policy was introduced in 1986 and modified in 1988 in relation with the world market policy, Software Technology Parks of India scheme support to attract Foreign Direct Investment. Recent advancement in the field of information and communication has significantly modified the role of IT in all organizations. Enormous growth in IT industry has changed the outsourcing strategy and buying behavior. Organizations can realize more benefits by investing more funds in IT. India is considered a pioneer in software development and a favourite destination for software and IT enabled services. IT industry has produced a revolutionary variation in the economic scenario and a huge number of personnel are working with higher productivity and association with Multi National Corporations (MNCs).

KEY PERFORMANCE INDICATORS OF INDUSTRIAL SAFETY OF ENTERPRISES

This article discusses the issues of assessing the level of industrial safety of enterprises in terms of the efficiency of industrial enterprises, requiring an increase in production efficiency, ensuring the efficiency of products and services by mastering the ways of effective production management, the achievements of scientific and technological progress.
 Purpose: The article discusses key performance indicators as methods of industrial safety of an enterprise and a tool for analyzing and evaluating the level of a company’s performance.
 Method, methodology of the work: The article used theoretical materials, economic and mathematical methods, statistical methods of analysis.
 Results: The most informative parameters were obtained, showing some aspects of the analysis of key performance indicators of industrial enterprises.
 Scope of the results: The results obtained can be successfully applied in different areas of the economy for different economic entities, it is possible to use both for young firms and for organizations with sufficient experience.

Analyzing the key performance indicators of circular supply chains by hybrid fuzzy cognitive mapping and Fuzzy DEMATEL: evidence from healthcare sector.

This study presents a multi-layer fuzzy-based decision-making approach to enhance the hospital Circular Supply Chain (CSC) performance by focusing on intensive care units (ICU) via key performance indicators analysis. In this regard, a Systematic Literature Review (SLR) and Institution Fuzzy Delphi (IFD) are employed to extract the relevant and prominent KPIs. After, a hybrid Fuzzy Cognitive Mapping (FCM) and Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) have been applied to illustrate a conceptual framework for the CSC performance management of the healthcare sector in the emerging economy of Iran. As a result, eight critical indicators emanated from the SLR-IFD approach. Furthermore, sixteen relationships amongst the performance indicators were identified via hybrid FCM-FDEMATEL. Inventory availability, information availability, innovation, and technology were selected as the most influential indicators. Besides, changing the information technology category, including information availability and Innovation and technology, had the most impact on the performance of the entire CSC. This study attempts to evaluate hospitals’ circular supply chain performance, by designing the circular evaluation framework. Hospital managers can use the results of this research to improve their internal circular supply chain performances in the intensive care units by understanding the different scenarios.

PERFORMANCE EVALUATION OF REGIONAL RURAL BANKS IN INDIA

Regional rural banks play an important role in the development of agriculture and rural areas in India. RRBS has reached more into the agricultural areas of India through its extensive network. The performance of a rural credit score in India is highly dependent on their monetary strength. RRBs are key financing organization at the agricultural degree which shoulders obligation of assembly credit score desires of various forms of agriculture credit score in rural areas. At gift, most of the local rural banks are going through the troubles of overdue, recovery, nonperforming belongings and different troubles. Therefore, it's miles vital to look at monetary overall performance of RRBs in India. This paper tries to investigate the monetary overall performance of RRBs in India in the course of the duration 2006-07 to 2010- 2011. The look at is primarily based totally on secondary information accumulated shape annual reviews of NABARD and RBI. An analytical studies layout of Key Performance Indicators Analysis which include range of banks and branches, deposits, loans, loans, investments and growth rate index is followed withinside the present study. The look at is diagnostic and exploratory in nature and makes use of secondary information. The look at unearths and concludes that overall performance of RRBs has considerably improved. Keywords: Performance, RRBs, Growth Rate, NABARD.

Framework and Analysis of Key Performance Indicators in Cuban Higher Education

This article aims to examine how Cuban higher education has implemented and created frameworks for key performance indicators (KPIs) to enhance its higher education accountability and quality. Referring to the past 15 years of available data on the United Nations Educational, Scientific, and Cultural Organization’s website (2005–2020), this study shows that Cuba’s higher education system has improved, as indicated by the increasing rate of the gross graduation ratio (both sexes) as well as national and inbound student mobility. Resumen Este manuscrito examinó como la educación superior cubana ha implementado y creado marcos de referencia de Indicadores de Ejecución Clave para mejorar su responsabilidad y calidad de educación superior. Refiriéndose a los últimos 15 años de información disponible en la red mundial (2005–2020) de la página de las Naciones Unidas sobre Enseñanza, Organizaciones Científicas y Culturales, este estudio demuestra que el sistema de educación superior ha mejorado, indicado por el incremento en la tasa de graduación bruta (ambos géneros) nacional, y de movilidad estudiantil interna

Time Series Anomaly Detection for KPIs Based on Correlation Analysis and HMM

KPIs (Key Performance Indicators) in distributed systems may involve a variety of anomalies, which will lead to system failure and huge losses. Detecting KPI anomalies in the system is very important. This paper presents a time series anomaly detection method based on correlation analysis and HMM. Correlation analysis is used to obtain the correlation between abnormal KPIs in the system, thereby reducing the false alarm rate of anomaly detection. The HMM (Hidden Markov Model) is used for anomaly detection by finding the close relationship between abnormal KPIs. In our correlation analysis of abnormal KPIs, firstly, the time series prediction model (1D-CNN-TCN) is proposed. The residual sequence is obtained by calculating the residual between the predicted value and the actual value. The residual sequence can highlight the abnormal segment in each data point and improve the accuracy of anomaly screening. According to the obtained residual sequence, these abnormal KPIs are preliminarily screened out from the historical data. Next, KPI correlation analysis is performed, and the correlation score is obtained by adding a sliding window onto the obtained anomaly index residual sequence. The correlation analysis based on the residual sequence can eliminate the interference of the original data fluctuation itself. Then, a correlation matrix of abnormal KPIs is constructed using the obtained correlation scores. In anomaly detection, the constructed correlation matrix is processed to obtain the adaptive parameters of the HMM model, and the trained HMM is used to quickly discover the abnormal KPI that may cause a KPI anomaly. Experiments on public data sets show that the method obtains good results.

Aged Care Energy Use and Peak Demand Change in the COVID-19 Year: Empirical Evidence from Australia

Aged care communities have been under the spotlight since the beginning of 2020. Energy is essential to ensure reliable operation and quality care provision in residential aged care communities (RAC). The aim of this study is to determine how RAC’s yearly energy use and peak demand changed in Australia and what this might mean for RAC design, operation and energy asset investment and ultimately in the healthcare plan for elderly residents. Five years of electricity demand data from four case study RACs in the same climate zone are analyzed. Statistical tools are used to analyze the data, and a clustering algorithm is used to identify typical demand profiles. A number of energy key performance indicators (KPIs) are evaluated, highlighting their respective benefits and limitations. The results show an average 8% reduction for yearly energy use and 7% reduction for yearly peak demands in the COVID-19 year compared with the average of the previous four years. Typical demand profiles for the four communities were mostly lower in the pandemic year. Despite these results, the KPI analysis shows that, for these four communities, outdoor ambient temperature remains a very significant correlation factor for energy use.

A domain-specific language for modeling and analyzing solution spaces for technology roadmapping

The introduction of major innovations in industry requires a collaboration across the whole value chain. A common way to organize such a collaboration is the use of technology roadmaps, which act as an industry-wide long-term planning tool. Technology roadmaps are used to identify industry needs, estimate the availability of technological solutions, and identify the need for innovation in the future. Roadmaps are inherently both time-dependent and based on uncertain values, i.e., properties and structural components can change over time. Furthermore, roadmaps have to reason about alternative solutions as well as their key performance indicators. Current approaches for model-based engineering do not inherently support these aspects.We present a novel model-based approach treating those aspects as first-class citizens. To address the problem of missing support for time in the context of roadmap modeling, we introduce the concepts of a common global time, time-dependent properties, and time-dependent availability. This includes requirements, properties, and the structure of the model or its components as well. Furthermore, we support the specification and analysis of key performance indicators for alternative solutions. These concepts result in a continuous range of various valid models over time instead of a single valid model at a certain point of time. We present a graphical user interface to enable the user to efficiently create and analyze those models. We further show the semantics of the resulting model by a translation into a set of global constraints as well as how we solve the resulting constraint system. We report on the evaluation of these concepts and the Iris tool with domain experts from different companies in the automotive value chain based on the industrial case of a smart sensing electrical fuse.

INFORMATION TECHNOLOGY FOR INTERNET RESOURCES PROMOTION IN SEARCH SYSTEMS BASED ON CONTENT ANALYSIS OF WEB-PAGE KEYWORDS

Context. Timely and correct analysis of the process of visiting Internet resources, which led to the overall conversion of e-business, is fundamental and relevant for successfully managing the website. Appropriate, accurate traffic analysis, which brings both successful and unsuccessful conversions, will identify the cause of the impact on conversion metrics and criteria and will measure the effectiveness of changes made to the site to increase traffic conversions. It is necessary to collect information on the activities of system users on the website and determine specific performance indicators of the website to improve e-business strategy further to solve these problems and achieve the relevant goals of e-commerce. Thus, it is necessary to develop and implement an analytical method of text content support for e-commerce Internet resources based on the analysis of key performance indicators of the website, paying particular attention to determining the set of relevant and relevant keywords used by regular users and led to an increase in e-business conversions.
 Objective of the study is to develop a technology for promoting Internet resources of e-commerce based on the results of Web-analytics of critical indicators of pages as KPI and KSI through forming a relevant set of keywords as feedback activity of a regular audience.
 Method. An analytical method for promoting Internet resources based on the analysis of key performance indicators of the website, which is based on three main algorithms аlgorithm for identifying problem areas of the site structure for further optimization, аlgorithm for optimizing search engine marketing activities (SEM), аlgorithm for site promotion and calculation of its efficiency.
 General recommendations for the design of information resources processing systems have been developed, different from the existing ones, by the presence of additional modules that significantly affect promoting the website on the Internet to further the success of ecommerce or improve the values of these indicators. Among them is the module of online shopping, marketing, module-copywriter and Web-master. For each of them, calculate their own KRI. It will allow you to effectively implement the processing of information resources at the level of system developers (reducing resources and time for development, improving the quality of information processing systems).
 Results. The paper develops and describes in detail, based on the results of Web-analytics, the parameters and criteria for assessing the level of success of e-business. Software tools for monitoring the textual content of Internet resources based on the analysis of key performance indicators of the website have also been developed. For a detailed analysis of the functioning and promotion of Internet ecommerce systems such as Internet newspaper and Internet magazine, 12 different methods have been developed and implemented, respectively, with support for each of them with a different number of stages of the content life cycle. A computer experiment of analysis of key performance indicators of the website was conducted. The service of keeping statistics of visits to the Web resource allows you to estimate the increase in sales of textual content in direct proportion to the rise in the number of visits to the Web resource, the number of regular users, the prospects of marketing activities.
 Conclusions. It was found that the presence of appropriate modules in the systems of information resources processing increases the sales of textual content to the regular user by 9%, active involvement of unique visitors, potential users and expanding the target and regional audience by 11%, viewed pages by 12%, resources by 7%.

Analysis of the effectiveness of financing projects using crowdfunding

Purpose – analysis of key performance indicators (KPIs) for the success of innovative projects that try to raise funds indirectly through crowdfunding platforms. Research Methodology. The interdisciplinary method of discourse analysis and systematic approach were used in the context of this work; the comparative method allowed to determine the optimal approach to the problem. Scientific novelty. The field of financial support lacks tools to encourage market participants to provide them with ideas and projects that can be financed through crowdfunding. Conclusions. The following indicators influence the creation of a viable crowdfunding mechanism and the growth of fundraising: narrative (or previous history), a clear goal and planned duration of the project; investment in communication schemes and visualization of advertising, and third-party support (positive feedback) focus on the pledge process rather than on the financial goal; distribution of crowdfunding into structured categories. At the same time, the success of crowdfunding is not tied to the size of the reward and any location. Key words: crowdfunding; key performing factors; alternative financin

Analysis of Key Performance Indicators in Health Building Construction in Nepal

Key Performance Indicators (KPI) in a construction project show how successfully the project has been executed. The information from the KPI measurement guides the implementer to collect the feedback which can be fed in for the new projects to be implemented. This study aim was to assess key performance indicators for health building construction, its ranking, the most important affecting factor for each KPI, and how to improving KPIs in a health building construction in Nepal. The data were collected from project stakeholders through a questionnaire survey. The project stakeholders were the contractors and health building section personnel of DUDBC. Data were summarized, analyzed, and presented in tables using Microsoft Excel. The study found that the stakeholders working in health building construction projects thought quality factor as the most important KPI with the first rank. The cost factor and time factor are correspondingly second and third-ranked, whereas, client satisfaction is the least important KPI. The study also showed the Relative Importance Index (RII) for the various factors affecting each KPI in the health building construction. For KPI-cost most important affecting factor is price escalation. For KPI-time it is the approved project schedule. The possible ways to improve the KPIs in health building construction are listed as conducting regular management meeting, implementing the provisions of the contract agreement, establishment of the proper communication system, timely monitoring of the progress, establishment of quality assurance and control system, adaptation of the cost and schedule control system, ensure the proper health and safety provisions to the workers, an early warning system for changes, regular updates of the work plan and program, regular training on project management, proper site management, proper management of manpower involved in the construction and better inventory management of contractors.