scholarly journals Elevate Project Success Rate with Right Judgement of Complexity and Skill Competency Gap

2019 ◽  
Vol 8 (4) ◽  
pp. 12898-12906
Keyword(s):  
Project Management ◽  
Phase I ◽  
Phase Ii ◽  
Project Success ◽  
False Positive Rate ◽  
Maturity Model ◽  
Dimensional Solution ◽  
Capability Maturity ◽  
Project Complexity ◽  
Unique Approach

Software project management constantly keep fighting triple constraint of Quality, Schedule and Time. Failures are due to poor visibility of Project complexity and incorrectly estimating right skilled team. The project success rates are constantly falling in spite of implementing various project management principles involving waterfall, Scrum, Scaled Agile framework (SAFe), etc. The approach taken to estimate the team composition are based on non-contextual, unscientific methodology based on previous project experiences by the team. As our study found that, every organization had its unique approach to derive root cause of their failures and had custom-built estimation templates. A deep-rooted empirical research is under taken here addressed around three Capability Maturity Model (CMM) level 5 organizations. Often complexity is under-estimated and this is the enemy of software estimation. If this hypothesis is right, complexity metric can forecast the depth of estimation challenges and can help in prioritizing task and various intricate efforts needed and thereby deduce the appropriate team to navigate toward project success. Our Research was under taken in below two phases: Phase I - To investigate and address poor project complexity definition through quantification of project complexity Phase II - To derive metric around skill-capability Index in conjunction with project complexity. In Phase I, interviews and deliberation techniques were leveraged involving senior software practitioners. In Phase II, evaluation of the unsuccessful projects from the initiation until operational stage was carried out. Combining the phase I and II results, overall reasons contributing to incorrect mapping of skilled staffing was found. This paper presents two research contributions, firstly an approach to uncover poor estimation of skilled staff for a project with correct complexity mapping, secondly skill-competence index in line with project complexity quantification as a multi-dimensional solution to overcome project failures. Proposed model was found to be productive in real projects; in addition, the results showed that complexity metric estimated with this unique approach had low false positive rate and minimal deviations in project outcomes.

scholarly journals A Conceptual Framework on The Successful Adoption of Project Management Methodologies in Ghana

2020 ◽  
Vol 10 ◽  
pp. 409-422
Author(s):  
Ivy Hawah Taana
Keyword(s):  
Project Management ◽  
Conceptual Framework ◽  
Success Factors ◽  
Project Success ◽  
Primary Concern ◽  
Maturity Model ◽  
Successful Completion ◽  
Factors Affecting ◽  
Capability Maturity ◽  
Private Organization

The successful completion of every project whether undertaken by a public or private organization is of primary concern to many institutions. However, literature has confirmed that most project success depends on adhering to good practices and are keenly documented in Project Management Methodologies (PMMs). It is a fact that many projects do not see successful completion as most of them are long overdue, faced with budget overruns and even some are abandoned. The purpose of this study is to explore the factors that influence the Adoption of Project Management Methodology in Ghana. This is motivated by the dearth of academic literature concerning the successful adoption of Project Management Methodologies in Ghana. The study will also examine if the Adoption of Project Management Methodologies leads to project success. To achieve these aims, a conceptual framework was developed grounded on the Critical Success Factors (CSFs), the Capability Maturity Model (CMM) theory, and the Stakeholder theory. Four independent variables, a mediator and a moderator were hypothesized for the establishment of the success factors affecting Project Management Methodologies adoption and if the Project Management Methodology adoption leads to project success.  

scholarly journals An Evolutionary Software Project Management Maturity Model for Mauritius

10.28945/3158 ◽  
2007 ◽  
Author(s):  
Aneerav Sukhoo ◽  
Andries Barnard ◽  
Mariki Eloff ◽  
John Andrew van der Poll
Keyword(s):  
Project Management ◽  
European Countries ◽  
Software Project ◽  
Maturity Model ◽  
Software Project Management ◽  
Maturity Models ◽  
Management Framework ◽  
Capability Maturity ◽  
Software Professionals ◽  
Western European

Software project management is a relatively recent discipline that emerged during the second half of the 20th century (Kwak, 2003). Many of the software project management methodologies available today were developed in Western/European countries and research showed that there was a need to formalise a software project management framework for developing countries, in particular Africa (Muriithi & Crawford, 2003). Based on surveys and discussions with software professionals, a methodology for software project management is being proposed. The methodology is based on a maturity model as Mauritius is faced with a shortage in skilled professionals. So far, few organisations in Mauritius have been found to be using software project management methodologies developed in Western/European countries. Most maturity models, for example Capability Maturity Model Integration (CMMI) and Kerzner’s maturity model, have five maturity levels. The trend is towards the development of maturity models that have fewer maturity levels. For example, the Organisational Project Management Maturity Model (OPM3) and Prince 2 Maturity Model have been developed with three maturity levels.

scholarly journals Are project managers informally following capability maturity model integration practices for project management?

2018 ◽  
Vol 8 (3) ◽  
pp. 86-94
Author(s):  
Javed Iqbal ◽  
Muzafar Khan ◽  
Nasir Mehmood Minhas
Keyword(s):  
Project Management ◽  
Software Development ◽  
Process Improvement ◽  
Software Process ◽  
Software Process Improvement ◽  
Project Planning ◽  
Model Integration ◽  
Capability Maturity Model ◽  
Maturity Model ◽  
Capability Maturity

Project planning is crucial for fruitful completion of a software development project. In case of a certified software development organisation, one can guess whether the software development projects are planned properly or not. But, what to do for a non-certified organisation? The objective of this study is to address this problem. For this purpose, a questionnaire survey has been conducted by involving experienced practitioners. The results show that several software development organisations follow Capability Maturity Model Integration) Project Planning-Process Area practices unofficially. Such organisations are potential candidate organisations for software process improvement initiatives, and would be cheap and safe for successful completion of a project. Keywords: CMMI, software project management, software process improvement, specific goals, specific practices, subpractices.

COMPARISON OF OPEN SOURCE TOOLS FOR PROJECT MANAGEMENT

2013 ◽  
Vol 23 (02) ◽  
pp. 189-209 ◽  
Author(s):  
ANDRÉ MARQUES PEREIRA ◽  
RAFAEL QUEIROZ GONÇALVES ◽  
CHRISTIANE GRESSE VON WANGENHEIM ◽  
LUIGI BUGLIONE
Keyword(s):  
Project Management ◽  
Open Source ◽  
Best Practice ◽  
Management Practices ◽  
Small And Medium Enterprises ◽  
Low Cost ◽  
Software Tools ◽  
Tool Support ◽  
Maturity Model ◽  
Capability Maturity

Software projects often fail, because they are not adequately managed. The establishment of effective and efficient project management practices still remains a key challenge to software organizations. Striving to address these needs, "best practice" models, such as, the Capability Maturity Model Integration (CMMI) or the Project Management Body of Knowledge (PMBOK), are being developed to assist organizations in improving project management. Although not required, software tools can help implement the project management process in practice. In order to provide comprehensive, low-cost tool support for project management, specifically, for small and medium enterprises (SMEs), in this paper we compare the most popular free/open-source web-based project management tools with respect to their compliance to PMBOK and CMMI for Development (CMMI-DEV). The results of this research can be used by organizations to make decisions on tool adoptions as well as a basis for evolving software tools in alignment with best practices models.

Managing Software Development Projects for Success: Aligning Plan- and Agility-Based Approaches to Project Complexity and Project Dynamism

2019 ◽  
Vol 51 (3) ◽  
pp. 262-277 ◽  
Author(s):  
Charles W. Butler ◽  
Leo R. Vijayasarathy ◽  
Nicholas Roberts
Keyword(s):  
Project Management ◽  
Software Development ◽  
Project Success ◽  
Management Approach ◽  
Development Projects ◽  
Negative Effects ◽  
Project Approach ◽  
Project Outcomes ◽  
Project Complexity ◽  
Management Approaches

In general, project complexity and project dynamism are recognized as potent characteristics that influence, usually in a negative way, the outcome of software development projects. However, with respect to the two dominant paradigms for managing software development projects (i.e., plan-based project approach and agility-based project approach), there is less agreement as to which one is better. Emerging research suggests that the preeminence of one approach over another is a matter of fit between the project management approach and the project context, including its complexity and dynamism. We contribute to this line of research by studying the moderating influence of the two project management approaches on the relationship between project complexity and project dynamism on project outcomes. Our analysis of data gathered from a survey of software development professionals shows that managing dynamism is critical for realizing project success, and an agility-based project approach is best suited for mitigating dynamism’s negative effects on project success.

scholarly journals Prevention of Crypto-Ransomware Using a Pre-Encryption Detection Algorithm

Computers ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 79 ◽  
Author(s):  
S. Kok ◽  
Azween Abdullah ◽  
NZ Jhanjhi ◽  
Mahadevan Supramaniam
Keyword(s):  
Machine Learning ◽  
Phase I ◽  
Phase Ii ◽  
Learning Algorithm ◽  
False Positive Rate ◽  
Application Programming Interface ◽  
Detection Algorithm ◽  
Positive Rate ◽  
New Type ◽  
Two Phases

Ransomware is a relatively new type of intrusion attack, and is made with the objective of extorting a ransom from its victim. There are several types of ransomware attacks, but the present paper focuses only upon the crypto-ransomware, because it makes data unrecoverable once the victim’s files have been encrypted. Therefore, in this research, it was proposed that machine learning is used to detect crypto-ransomware before it starts its encryption function, or at the pre-encryption stage. Successful detection at this stage is crucial to enable the attack to be stopped from achieving its objective. Once the victim was aware of the presence of crypto-ransomware, valuable data and files can be backed up to another location, and then an attempt can be made to clean the ransomware with minimum risk. Therefore we proposed a pre-encryption detection algorithm (PEDA) that consisted of two phases. In, PEDA-Phase-I, a Windows application programming interface (API) generated by a suspicious program would be captured and analyzed using the learning algorithm (LA). The LA can determine whether the suspicious program was a crypto-ransomware or not, through API pattern recognition. This approach was used to ensure the most comprehensive detection of both known and unknown crypto-ransomware, but it may have a high false positive rate (FPR). If the prediction was a crypto-ransomware, PEDA would generate a signature of the suspicious program, and store it in the signature repository, which was in Phase-II. In PEDA-Phase-II, the signature repository allows the detection of crypto-ransomware at a much earlier stage, which was at the pre-execution stage through the signature matching method. This method can only detect known crypto-ransomware, and although very rigid, it was accurate and fast. The two phases in PEDA formed two layers of early detection for crypto-ransomware to ensure zero files lost to the user. However in this research, we focused upon Phase-I, which was the LA. Based on our results, the LA had the lowest FPR of 1.56% compared to Naive Bayes (NB), Random Forest (RF), Ensemble (NB and RF) and EldeRan (a machine learning approach to analyze and classify ransomware). Low FPR indicates that LA has a low probability of predicting goodware wrongly.

scholarly journals Assessing the Association between Agile Maturity Model Levels and Perceived Project Success

10.28945/4519 ◽  
2020 ◽  
Author(s):  
Vaughan Henriques ◽  
Maureen Tanner
Keyword(s):  
Performance Management ◽  
Conceptual Model ◽  
Online Survey ◽  
Project Success ◽  
Future Research ◽  
Maturity Model ◽  
Capability Maturity ◽  
Continuous Delivery ◽  
The Individual ◽  
Constant Improvement

Aim/Purpose: Given the underlying philosophy of the agile manifesto, this study investigates whether an increase in agile maturity is associated with improved perceived project success. Background: The underlying philosophy of the agile manifesto is embodied in principle one which promotes the continuous delivery of software that is deemed valuable by the customer, while principle twelve encourages continual improvement of the delivery process. This constant improvement, or maturity, is not a concept unique to agile methods and is commonly referred to as a maturity model. The most common of maturity model is the Capability Maturity Model Integrated (CMMI). However, research consensus indicates CMMI might not fully be compatible with agile implementation, specifically at higher levels of maturity without sacrificing agility. Agile maturity models (AMM), which are aligned to agile principles encourage continuous improvement while maintaining agility. Methodology: The study employs a conceptual model based on an existing agile maturity model that is related to perceived project success. Using an objectivist perspective, a quantitative method was employed to analyze the results of an online survey of agile practitioners. Contribution: The significant contribution from this research is the validation of the conceptual model relating the activities and maturity levels of the AMM as the independent variables to the dependent variable of perceived project success. Findings: The data analysis found that a significant positive correlation exists between maturity levels and perceived project success. The strongest correlation was found at the highest maturity level, with relatively weaker correlation at the lower levels of maturity. It can thus be concluded that a higher level of maturity in the AMM is positively associated with perceived project success. Recommendations for Practitioners: The study has practical implications in highlighting that performance management, requirements management, regular delivery and customer availability are key areas to focus on to establish and continually improve the success of agile implementations. This study further assists practitioners in systematically identifying the critical agile activities, such as the use of story cards, continuous delivery and the presence of a knowledgeable customer. Recommendation for Researchers: The contributions of this study for academics is the confirmation of the maturity model developed by Patel and Ramachandran (2009a). This study also shows the association between the individual activities within the maturity levels as well as the maturity levels and the perceived project success, addressing a gap in literature relating these concepts. Future Research: It would be useful to replicate this study whilst following a qualitative approach. The study could also be replicated with a sample consisting of agile project customers.

scholarly journals TGANs with Machine Learning Models in Automobile Insurance Fraud Detection and Comparative Study with Other Data Imbalance Techniques

2021 ◽  
Vol 9 (5) ◽  
pp. 236-244
Author(s):  
Rohan Yashraj Gupta ◽  
Satya Sai Mudigonda ◽  
Pallav Kumar Baruah
Keyword(s):  
Machine Learning ◽  
Phase I ◽  
Phase Ii ◽  
False Positive Rate ◽  
Fraud Detection ◽  
Insurance Fraud ◽  
Learning Models ◽  
Data Imbalance ◽  
Positive Rate ◽  
Machine Learning Models

A data-driven Fraud detection model for insurance business can be seen as a two-phase method. Phase I is data-preprocessing of a given dataset, in which, handling class imbalance is a major challenge. Phase II is that of classification using Machine Learning models. It is important to comprehend if there is any influence of the technique used in Phase I on the efficiency of the model used for Phase II. A natural query that intrigues one is whether there is a golden combination of a technique in Phase I and a specific model in Phase II for assured best performance of a Fraud Detection Model.In this work, we study a few techniques for handling data imbalance issue namely, SMOTE, MWMOTE, ADASYN and TGAN in combination with various classifier models like Random Forest (RF), Decision Trees (DT), Support Vector Machines (SVM), LightGBM, XGBoost and Gradient Boosting Machines (GBM). The study is conducted on a dataset for motor vehicle insurance fraud detection.We present a comparison of various combinations of data imbalance technique and classifier models. It is observed that the combination of TGAN in Phase I and GBM in Phase II gives the best performance. This combination performs best in terms of important metrics such as false positive rate, precision and specificity. We obtained the lowest false positive rate of 0.0011 and precision of 0.9988 which minimizes the most critical risk for the insurance company of falsely classifying a non-fraud claim as a fraud. Finally, the specificity of 0.9989 indicates that the model was also very good at predicting the non-fraudulent claim.

Agile and Defined Project Development

2011 ◽  
pp. 134-157
Author(s):  
Fabrizio Fioravanti
Keyword(s):  
Project Management ◽  
Product Quality ◽  
Capability Maturity Model ◽  
Agile Development ◽  
Maturity Model ◽  
Project Development ◽  
Capability Maturity ◽  
Agile Methodology ◽  
Agile Methodologies ◽  
Level 3

In this chapter, the ADPD methodology will be presented and discussed. The name and the consequent acronym are due to the fact that I would like to create a methodology that is agile and, therefore, compliant to the Agile Manifesto, but that at the same time can be widely accepted and then also deployed in organizations that are not inclined to accept Agile development. The ADPD’s main aim is to eliminate the criticisms that often bound Agile methodologies with hacking or unstructured development. To obtain such results, the methodology must be compliant at least with the Software Capability Maturity Model, commonly known as CMM-SW (Paulk, 1993, 1993a) Level 3: the defined level. It also explains the second term of the acronym. Third and fourth terms are quite obvious and do not necessitate any further investigation. The compliance with CMM-SW Level 3 allows me to successfully apply this methodology in an environment where a standardization in terms of software or product quality is a must, since the Defined Level of CMM-SW allows you to match the requirements of most of the companies that usually do not agree with Agile methodologies and management. These are the main reasons for which I started to define a new methodology, mainly based on the concept of the first Agile methodology I have applied in real projects; that is, XP (Beck, 1999, 2000). I have inserted in ADPD all the positive aspects and techniques that are part of XP and that I was able to apply successfully in daily project management. I modified all the improvable aspects, inserting some new hints to the project manager and guaranteeing at least the compliance with CMM-SW Level 3.

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