Effective Utilization of Historical Data to Increase Organizational Performance: Focus on Sales/ Tendering and Projects

Master's thesis in Offshore technologyIn Oil and Gas industry there was not enough focus on this topic as cost was not a big factor in good olden days. But the sensational drop in oil prices below US$40 per barrel at the end of 2015 made the price more than 60 percent down compared to the one in previous years. It’s clear that the sector is going through one of the most transformative periods in its history. This situation has created more challenges to all O&G company leaders by forcing them to change their business strategies. The operating companies in the Oil and Gas industry have been focusing to reduce costs and increase organizational performance. Accordingly suppliers companies need to acknowledge their focus on the efficiency and optimization of resources to be able to sustain and grow in a competitive market. It demands better control of estimates and cost on future sales/tendering process. As quoted by one of the Operations Managers “An informed organization saves cost and wins faster”. The only way to get reliable information for any organization is by analyzing ‘what happened in the past’ and what we learned from it. In other words this is achieved through utilization of historical data from previous projects and by developing benchmarking metrics. Further, usage of the historical data can improve estimation and scheduling, support strategic planning, and improve the organizational processes. The historical project data or information can help in making strategic business decisions in any Organization. It can play a significant role in providing very distinct advantage over the competitors. Historical data can help the management to decide what projects are right for the future of the company and which projects can be avoided. Further, it can help to learn from past mistakes and win future bids by not repeating them. Most of the top management understands the importance of having and using historical project information or data. The problem is that very few companies have the methodologies, procedures, and systems in place to effectively use this information to improve their project processes and to support the estimation, scheduling, and control of future projects (opportunities). The present work focuses on historical data, estimation process and lessons learned for enhancing organizational performance. Further, the work includes a case study and number of expert interviews conducted at ABB. The work discusses how to collect, normalize, and analyze historical project data to develop practical information. Three models have been developed for project estimation process with a feedback loop, Lessons learned process model and Historical data utilization process. The recommendations have been made to use the historical data for establishing references for the sales/tendering department for future estimates, which can reduce the dependency on manual or a single person’s judgment and improve the estimation process. Some suggestions have also been made for establishing lessons learned process which can improve organizational performance. The results from analysis show that by applying the recommended processes, organizations can achieve efficiency through easy access and storage of historical database, easy access to lessons learned, measurable KPIs. Also use of key variables like project complexity and severity of requirements for estimation process and historical data process can form a better relation for data analysis and utilization.AB

A Case Study Of E-Supply Chain & Business Process Reengineering Of A Semiconductor Company In Malaysia

Penglibatan e-perniagaan dalam rantaian bekalan telah mewujudkan e-rantaian bekalan yang baru (e-SC) di firma-firma tempatan dan global. Due to globalization and advancement in information technology (IT), companies adopt best practices in e-business and supply chain management to be globally competitive as both are realities and prospects in 21st century

Project Cost Estimation : Promoting quality of cost estimation to reduce project cost variance

One of the dimensions of evaluating project success is assessing whether the project has been completed within the assigned budget. However, it is unlikely that the actual costs will be exactly as planned, and historically, industrial projects are prone to cost overruns. Careful planning and a reasonable cost baseline are key to achieving project success. The cost baseline consists of the aggregated cost estimate and contingency reserve. Literature identifies various methods for increasing the reliability of the cost baseline via setting appropriate contingencies. However, there is a gap in the literature regarding the other of the two components of the project cost baseline – the cost estimate. The objective of this thesis is to investigate and develop a method for reducing project cost variance by improving the quality of the cost estimation process in industrial project-based firms. The objective was achieved by observing the sales organization and the cost estimation procedure in the case company and identifying the underlying issue that results in the project cost variance. The method was developed by surveying the best available practices of cost estimation techniques and processes employed by industrial project organizations and synthesizing a holistic method for improving the quality of cost estimation and promoting knowledge management within an organization. From a practical perspective, the research offered the case company a new point of view on cost variances in terms of element-specific variances. This analysis revealed the need to update the cost estimation tools for specific elements in the company’s product portfolio. From a managerial perspective, the work emphasizes the information and procedural requirements of the cost estimation process. Furthermore, the work provides advice on employing alternative cost estimation techniques to balance resource utilization as well as making the process more lean. A new risk category that roots from within the organization was identified and the findings of the thesis suggest that this category should not be a part of the contingency reserve. The internal foreseen risks can be managed with procedural changes. The thesis proposes a stage-gate standardized model for cost estimation, that guides the organization to select an appropriate cost estimation technique corresponding to the stage of project preparation. The findings suggest that the cost estimation process should be followed systematically, and to proceed with the process, all milestone requirements should be met. In addition, the role of the historical information database was deemed central to the quality of the cost estimate, making it imperative to accentuate diligent high-quality reporting and knowledge management practices

Creation of a Project Portfolio for a Construction Company by Using Lean Six Sigma Principles : Change Management, as part of Clarifying the Case Company’s Strategy

Project Portfolio Management (PPM) is an important tool for an industrial companies to achieve a competitive advantage. Companies in the Construction Industry, especially in Infrastructure construction, where the majority of companies are small or medium-sized, generally do not have the capacity or knowledge for the strategic selection of projects as part of the company's future strategy, as there is a dearth of knowledge on project level PPM and Lean Six Sigma. This causes companies to blindly bid on different projects, hoping for a good outcome, as the selection of projects is not based on knowledge or facts. This causes companies to offer projects, that are negatively correlated to their own strategy, which in the long run will worsen the company's ability to generate prof-it, as projects do not create synergies between the companies' different business areas. In the ever-tightening competition in the market, where the cheapest offer invariably wins, the company must consider the Lean Six Sigma -mentality in its production, where it strives to optimize its own processes to achieve a situation, where it produces more added value with its processes, more efficiently and at lower costs. Only by learning from its own production can company achieve a competitive edge in a market. The methodology of the research has been based on the Case Company's interviews and internal docu-ments, on which the analysis has been formed by using the literature of the field. This study focuses on analyzing the production processes of an influential infrastructure construction company in Finland, aiming to optimize the company's strategy-, production-, and bidding processes, by developing a Project Portfolio Management -tool, so that the company has a better competitive position in future.Project Portfolio Management (PPM) on tärkeä työkalu teollisuusyrityksille kilpailuedun saavuttamisessa. Erityisesti infra-alaan erikoistuneista rakennusalan yrityksistä suurin osa on pieniä tai keskisuuria. Tämän takia yrityksillä ei yleisesti ottaen ole kapasiteettia, tietoa tai projektitason PPM- ja Lean Six Sigma -osaamista, strategisesta projektien valinnasta osana yhtiön strategisia tavoitteita. Infrarakentamisen parissa toimivat yritykset perustavat tarjouslaskentansa eri rakennusprojekteissa arvioihin, toivoen hyvää lopputulosta. Hankkeiden tarjouslaskenta perustuu tällöin arvailuun, eikä tietoon tai tosiasioihin. Tämä saa yritykset tarjoamaan omaan strategiaansa negatiivisesti vaikuttavia projekteja, jotka eivät luo synergiaetuja yritysten eri liiketoiminta-alueiden välille ja pitkällä aikavälillä heikentävät yrityksen kannattavuutta. Alalla vallitsevan kilpailun jatkuvasti kiristyessä, jossa halvin tarjous poikkeuksetta voittaa, tulee yrityksen huomioida Lean Six Sigma -mentaliteetti tuotannossaan. Yrityksen tulee pyrkiä optimoimaan omia prosessejaan saavuttaakseen tilanteen, jossa se tuottaa enemmän lisäarvoa resursseillaan tehokkaammin ja edullisemmin. Vain omasta tuotannostaan oppimalla yritys voi saavuttaa merkittävää kilpailuetua markkinoilla. Tämä tutkimus keskittyy Suomessa toimivan infrarakentamiseen erikoistuneen yrityksen tuotantoprosessien analysointiin; tavoitteena optimoida yrityksen strategia-, tuotanto- ja tarjousprosesseja. Tutkimuksen lopputuotteena kehitettiin Project Portfolio Management -työkalu, jota hyödyntämällä yrityksellä on mahdollisuus parempaan kilpailuasemaan tulevaisuudessa. Tutkimuksen metodologia on perustunut Case Yrityksen haastatteluihin sekä sisäisiin asiakirjoihin, joiden perusteella analyysi on muodostettu alan kirjallisuutta hyödyntäen

Engineering Trust - Reciprocity in the Production of Reputation Information

Reciprocity in feedback giving distorts the production and content of reputation information in a market, hampering trust and trade efficiency. Guided by feedback patterns observed on eBay and other platforms we run laboratory experiments to investigate how reciprocity can be managed by changes in the way feedback information flows through the system, leading to more accurate reputation information, more trust and more efficient trade. We discuss the implications for theory building and for managing the redesign of market trust systems.market design, reputation, trust, reciprocity, eBay

Competency-Based Education: Implications for Curricular Development of the Allied Dental Science Program at the Jordan University of Science and Technology

Preface: The content of this document represents a review of the best practices and principles in competency-based dental and allied dental education. This information is offered in the spirit of collegiality with the intent of improving the allied dental education in general and the dental hygiene education in particular in Jordan. Recommendations presented should serve as a basis for discussion and decision-making by all involved in the Allied Dental Science Program education and administration at the Jordan University of Science and Technology, including the Dean of the Applied Medical Sciences Department and the Allied Dental Science Program Director and Faculty

2009-2010 Graduate Catalog

2009-2010 graduate catalog for Morehead State University

AN INTEGRATED MULTIPLE STATISTICAL TECHNIQUE FOR PREDICTING POST-SECONDARY EDUCATIONAL DEGREE OUTCOMES BASED PRIMARILY ON VARIABLES AVAILABLE IN THE 8TH GRADE

There is a class of complex problems that may be too complicated to solve by any single analytical technique. Such problems involve so many measurements of interconnected factors that analysis with a single dimension technique may improve one aspect of the problem while overall achieving little or no improvement. This research examines the utility of modeling a complex problem with multiple statistical techniques integrated to analyze different types of data. The goal was to determine if this integrated approach was feasible and provided significantly better results than a single statistical technique. An application in engineering education was chosen because of the availability and comprehensiveness of the NELS:88 longitudinal dataset. This dataset provided a huge number of variables and 12,144 records of actual students progressing from 8th grade to their final educational outcomes 12 years later. The probability of earning a Science, Technology, Engineering, or Mathematics (STEM) degree is modeled using variables available in the 8th grade as well as standardized test scores. The variables include demographic, academic performance, and experiential measures. Extensive manipulation of the NELS:88 dataset was conducted to identify the student outcomes, prepare the set of covariates for modeling, and determine when the students' final outcome status occurred. The integrated models combined logistic regression, survival analysis, and Receiver Operating Characteristics (ROC) Curve analysis to predict obtaining a STEM degree vs. other outcomes. The results of the integrated models were compared to actual outcomes and the results of separate logistic regression models. Both sets of models provided good predictive accuracy. The feasibility of integrated models for complex problems was confirmed. The integrated approach provided less variability in incorrect STEM predictions, but the improvement was not statistically significant. The main contribution of this research is designing the integrated model approach and confirming its feasibility. Additional contributions include designing a process to create large multivariate logistic regression models; developing methods for extensive manipulation of a large dataset to adapt it for new analytical purposes; extending the application of logistic regression, survival analysis, and ROC Curve analysis within educational research; and creating a formal definition for STEM that can be statistically verified

2021 - 2022, Gardner-Webb Academic Catalog

2021 - 2022, Gardner-Webb University Academic Catalog. William Downs, president.https://digitalcommons.gardner-webb.edu/academic-catalogs-graduate-undergraduate-combined/1006/thumbnail.jp