An approach for software effort estimation using fuzzy numbers and genetic al...csandit
One of the most critical tasks during the software development life cycle is that of estimating the
effort and time involved in the development of the software product. Estimation may be
performed by many ways such as: Expert judgments, Algorithmic effort estimation, Machine
learning and Analogy-based estimation. In which Analogy-based software effort estimation is
the process of identifying one or more historical projects that are similar to the project being
developed and then using the estimates from them. Analogy-based estimation is integrated with
Fuzzy numbers in order to improve the performance of software project effort estimation during
the early stages of a software development lifecycle. Because of uncertainty associated with
attribute measurement and data availability, fuzzy logic is introduced in the proposed model.
But hardly a historical project is exactly same as the project being estimated due to some
distance associated in similarity distance. This means that the most similar project still has a
similarity distance with the project being estimated in most of the cases. Therefore, the effort
needs to be adjusted when the most similar project has a similarity distance with the project
being estimated. To adjust the reused effort, we build an adjustment mechanism whose
algorithm can derive the optimal adjustment on the reused effort using Genetic Algorithm. The
proposed model Combine the fuzzy logic to estimate software effort in early stages with Genetic
algorithm based adjustment mechanism may result to near the correct effort estimation.
AN APPROACH FOR SOFTWARE EFFORT ESTIMATION USING FUZZY NUMBERS AND GENETIC AL...csandit
One of the most critical tasks during the software development life cycle is that of estimating the effort and time involved in the development of the software product. Estimation may be performed by many ways such as: Expert judgments, Algorithmic effort estimation, Machine
learning and Analogy-based estimation. In which Analogy-based software effort estimation is the process of identifying one or more historical projects that are similar to the project being developed and then using the estimates from them. Analogy-based estimation is integrated with Fuzzy numbers in order to improve the performance of software project effort estimation during
the early stages of a software development lifecycle. Because of uncertainty associated with attribute measurement and data availability, fuzzy logic is introduced in the proposed model.But hardly a historical project is exactly same as the project being estimated due to some distance associated in similarity distance. This means that the most similar project still has a
similarity distance with the project being estimated in most of the cases. Therefore, the effort needs to be adjusted when the most similar project has a similarity distance with the project being estimated. To adjust the reused effort, we build an adjustment mechanism whose
algorithm can derive the optimal adjustment on the reused effort using Genetic Algorithm. The proposed model Combine the fuzzy logic to estimate software effort in early stages with Genetic algorithm based adjustment mechanism may result to near the correct effort estimation.
An approach for software effort estimation using fuzzy numbers and genetic al...csandit
One of the most critical tasks during the software development life cycle is that of estimating the
effort and time involved in the development of the software product. Estimation may be
performed by many ways such as: Expert judgments, Algorithmic effort estimation, Machine
learning and Analogy-based estimation. In which Analogy-based software effort estimation is
the process of identifying one or more historical projects that are similar to the project being
developed and then using the estimates from them. Analogy-based estimation is integrated with
Fuzzy numbers in order to improve the performance of software project effort estimation during
the early stages of a software development lifecycle. Because of uncertainty associated with
attribute measurement and data availability, fuzzy logic is introduced in the proposed model.
But hardly a historical project is exactly same as the project being estimated due to some
distance associated in similarity distance. This means that the most similar project still has a
similarity distance with the project being estimated in most of the cases. Therefore, the effort
needs to be adjusted when the most similar project has a similarity distance with the project
being estimated. To adjust the reused effort, we build an adjustment mechanism whose
algorithm can derive the optimal adjustment on the reused effort using Genetic Algorithm. The
proposed model Combine the fuzzy logic to estimate software effort in early stages with Genetic
algorithm based adjustment mechanism may result to near the correct effort estimation.
AN APPROACH FOR SOFTWARE EFFORT ESTIMATION USING FUZZY NUMBERS AND GENETIC AL...csandit
One of the most critical tasks during the software development life cycle is that of estimating the effort and time involved in the development of the software product. Estimation may be performed by many ways such as: Expert judgments, Algorithmic effort estimation, Machine
learning and Analogy-based estimation. In which Analogy-based software effort estimation is the process of identifying one or more historical projects that are similar to the project being developed and then using the estimates from them. Analogy-based estimation is integrated with Fuzzy numbers in order to improve the performance of software project effort estimation during
the early stages of a software development lifecycle. Because of uncertainty associated with attribute measurement and data availability, fuzzy logic is introduced in the proposed model.But hardly a historical project is exactly same as the project being estimated due to some distance associated in similarity distance. This means that the most similar project still has a
similarity distance with the project being estimated in most of the cases. Therefore, the effort needs to be adjusted when the most similar project has a similarity distance with the project being estimated. To adjust the reused effort, we build an adjustment mechanism whose
algorithm can derive the optimal adjustment on the reused effort using Genetic Algorithm. The proposed model Combine the fuzzy logic to estimate software effort in early stages with Genetic algorithm based adjustment mechanism may result to near the correct effort estimation.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
A NEW MATHEMATICAL RISK MANAGEMENT MODEL FOR AGILE SOFTWARE DEVELOPMENT METHO...ijseajournal
This paper proposes a new mathematical model for estimating the cost of explicit Agile software
development risk management with its Impact Benefit s (savings/profits). This is necessitated by the fact
that despite the increase in the need for managing risks explicitly in medium-to-large scale agile software
development projects presently, there are no known ways to estimate explicit risk management
costs/benefits. With the proposed model, explicit risk management procedures alongside with risk
management estimation techniques is made known to Stakeholders who will be able to make the right
decisions on risk management costs and its impacts as well as when to utilise implicit or explicit risk
management. The proposed system proves to be feasible and dependable and is evidently capable of
enhancing the agile methods for use for all sizes of software projects while still maintaining the swiftness of
the agile process.
Evaluation method for strategic investmentsazhar901
Typically, valuation has been conducted using traditional methods such as the discounted payback method (DPM) which uses discounted cash flows to determine the time it takes to recoup the original investment; the internal rate of return (IRR) which uses the condition of when the present value is equal to zero to yield the corresponding discount factor or IRR; and the profitability index (PI), also known as the benefit-cost ratio (BCR), which determines the ratio of discounted benefit cash flows to the project‟s costs. Perhaps the most widely used traditional valuation method is NPV (NPV). The NPV method takes expected future cash flows and discounts them to the current time period. Another valuation method known as decision tree analysis (DTA) uses NPV in its valuation, but also accounts for the details of events in a valuation period such a decisions that include cash flow scenarios. The DTA method determines the expected values of outcomes based on their probability of occurrence given that certain decisions are made over time.
A Software Measurement Using Artificial Neural Network and Support Vector Mac...ijseajournal
Today, Software measurement are based on various techniques such that neural network, Genetic
algorithm, Fuzzy Logic etc. This study involves the efficiency of applying support vector machine using
Gaussian Radial Basis kernel function to software measurement problem to increase the performance and
accuracy. Support vector machines (SVM) are innovative approach to constructing learning machines that
Minimize generalization error. There is a close relationship between SVMs and the Radial Basis Function
(RBF) classifiers. Both have found numerous applications such as in optical character recognition, object
detection, face verification, text categorization, and so on. The result demonstrated that the accuracy and
generalization performance of SVM Gaussian Radial Basis kernel function is better than RBFN. We also
examine and summarize the several superior points of the SVM compared with RBFN.
Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems. DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization. It has apparently outperformed a number of Evolutionary Algorithms and further search heuristics in the vein of Particle Swarm Optimization at what time of testing over both yardstick and actual world problems. Nevertheless, DE, like other probabilistic optimization algorithms, from time to time exhibits precipitate convergence and stagnates at suboptimal position. In order to stay away from stagnation behavior while maintaining an excellent convergence speed, an innovative search strategy is introduced, named memetic search in DE. In the planned strategy, positions update equation customized as per a memetic search stratagem. In this strategy a better solution participates more times in the position modernize procedure. The position update equation is inspired from the memetic search in artificial bee colony algorithm. The proposed strategy is named as Memetic Search in Differential Evolution (MSDE). To prove efficiency and efficacy of MSDE, it is tested over 8 benchmark optimization problems and three real world optimization problems. A comparative analysis has also been carried out among proposed MSDE and original DE. Results show that the anticipated algorithm go one better than the basic DE and its recent deviations in a good number of the experiments.
EARLY STAGE SOFTWARE DEVELOPMENT EFFORT ESTIMATIONS – MAMDANI FIS VS NEURAL N...cscpconf
Accurately estimating the software size, cost, effort and schedule is probably the biggest
challenge facing software developers today. It has major implications for the management of
software development because both the overestimates and underestimates have direct impact for
causing damage to software companies. Lot of models have been proposed over the years by
various researchers for carrying out effort estimations. Also some of the studies for early stage
effort estimations suggest the importance of early estimations. New paradigms offer alternatives
to estimate the software development effort, in particular the Computational Intelligence (CI)
that exploits mechanisms of interaction between humans and processes domain
knowledge with the intention of building intelligent systems (IS). Among IS,
Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques
for software development effort estimation. In this paper neural network models and Mamdani
FIS model have been used to predict the early stage effort estimations using the student dataset.
It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in
comparison to the neural network models based models.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
A NEW MATHEMATICAL RISK MANAGEMENT MODEL FOR AGILE SOFTWARE DEVELOPMENT METHO...ijseajournal
This paper proposes a new mathematical model for estimating the cost of explicit Agile software
development risk management with its Impact Benefit s (savings/profits). This is necessitated by the fact
that despite the increase in the need for managing risks explicitly in medium-to-large scale agile software
development projects presently, there are no known ways to estimate explicit risk management
costs/benefits. With the proposed model, explicit risk management procedures alongside with risk
management estimation techniques is made known to Stakeholders who will be able to make the right
decisions on risk management costs and its impacts as well as when to utilise implicit or explicit risk
management. The proposed system proves to be feasible and dependable and is evidently capable of
enhancing the agile methods for use for all sizes of software projects while still maintaining the swiftness of
the agile process.
Evaluation method for strategic investmentsazhar901
Typically, valuation has been conducted using traditional methods such as the discounted payback method (DPM) which uses discounted cash flows to determine the time it takes to recoup the original investment; the internal rate of return (IRR) which uses the condition of when the present value is equal to zero to yield the corresponding discount factor or IRR; and the profitability index (PI), also known as the benefit-cost ratio (BCR), which determines the ratio of discounted benefit cash flows to the project‟s costs. Perhaps the most widely used traditional valuation method is NPV (NPV). The NPV method takes expected future cash flows and discounts them to the current time period. Another valuation method known as decision tree analysis (DTA) uses NPV in its valuation, but also accounts for the details of events in a valuation period such a decisions that include cash flow scenarios. The DTA method determines the expected values of outcomes based on their probability of occurrence given that certain decisions are made over time.
A Software Measurement Using Artificial Neural Network and Support Vector Mac...ijseajournal
Today, Software measurement are based on various techniques such that neural network, Genetic
algorithm, Fuzzy Logic etc. This study involves the efficiency of applying support vector machine using
Gaussian Radial Basis kernel function to software measurement problem to increase the performance and
accuracy. Support vector machines (SVM) are innovative approach to constructing learning machines that
Minimize generalization error. There is a close relationship between SVMs and the Radial Basis Function
(RBF) classifiers. Both have found numerous applications such as in optical character recognition, object
detection, face verification, text categorization, and so on. The result demonstrated that the accuracy and
generalization performance of SVM Gaussian Radial Basis kernel function is better than RBFN. We also
examine and summarize the several superior points of the SVM compared with RBFN.
Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems. DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization. It has apparently outperformed a number of Evolutionary Algorithms and further search heuristics in the vein of Particle Swarm Optimization at what time of testing over both yardstick and actual world problems. Nevertheless, DE, like other probabilistic optimization algorithms, from time to time exhibits precipitate convergence and stagnates at suboptimal position. In order to stay away from stagnation behavior while maintaining an excellent convergence speed, an innovative search strategy is introduced, named memetic search in DE. In the planned strategy, positions update equation customized as per a memetic search stratagem. In this strategy a better solution participates more times in the position modernize procedure. The position update equation is inspired from the memetic search in artificial bee colony algorithm. The proposed strategy is named as Memetic Search in Differential Evolution (MSDE). To prove efficiency and efficacy of MSDE, it is tested over 8 benchmark optimization problems and three real world optimization problems. A comparative analysis has also been carried out among proposed MSDE and original DE. Results show that the anticipated algorithm go one better than the basic DE and its recent deviations in a good number of the experiments.
EARLY STAGE SOFTWARE DEVELOPMENT EFFORT ESTIMATIONS – MAMDANI FIS VS NEURAL N...cscpconf
Accurately estimating the software size, cost, effort and schedule is probably the biggest
challenge facing software developers today. It has major implications for the management of
software development because both the overestimates and underestimates have direct impact for
causing damage to software companies. Lot of models have been proposed over the years by
various researchers for carrying out effort estimations. Also some of the studies for early stage
effort estimations suggest the importance of early estimations. New paradigms offer alternatives
to estimate the software development effort, in particular the Computational Intelligence (CI)
that exploits mechanisms of interaction between humans and processes domain
knowledge with the intention of building intelligent systems (IS). Among IS,
Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques
for software development effort estimation. In this paper neural network models and Mamdani
FIS model have been used to predict the early stage effort estimations using the student dataset.
It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in
comparison to the neural network models based models.
As mentioned on the ISBSG workshop in El Segundo and the MAIN track in the IWSM in Assisi, the Basis of Estimate - Software Services is ready for review.
The document is intended to set a best practice for structuring an Estimate for Software Services.
You are invited to review it.
If interested you're allowed to forward the attached document to reviewers.
Comment by the reviewers can be mailed directly to me: Ton Dekkers ton.dekkers@nesma.nl
The due date for comments is set to Sunday, December 16 2012.
Next step will be incorporating the useful suggestions and preparing a version for the 3rd and final review within AACE.
THE UNIFIED APPROACH FOR ORGANIZATIONAL NETWORK VULNERABILITY ASSESSMENTijseajournal
The present business network infrastructure is quickly varying with latest servers, services, connections,
and ports added often, at times day by day, and with a uncontrollably inflow of laptops, storage media and
wireless networks. With the increasing amount of vulnerabilities and exploits coupled with the recurrent
evolution of IT infrastructure, organizations at present require more numerous vulnerability assessments.
In this paper new approach the Unified process for Network vulnerability Assessments hereafter called as
a unified NVA is proposed for network vulnerability assessment derived from Unified Software
Development Process or Unified Process, it is a popular iterative and incremental software development
process framework.
Assignment 1/AgileProjectCharterTemplateExample.pdf
C Example Project/Program Charter
Template
THIS APPENDIX CONTAINS AN EXAMPLE of a project charter template that can be used to define the
macro layer in a hybrid, managed agile development approach. This template is provided as an
example and is intended to be customized to fit the project and business environment that it is
used in.
Project overview
Background
Provide a brief description of the background behind the problem that the project or program is
intended to address to a sufficient level to allow the reader to understand the context of the problem.
Problem Statement
Provide a brief description of the problem that the project or program is intended to address from a
business or operational management perspective.
Project Vision
Write a concise vision statement that summarizes the purpose and intent of the project and describes
what the world will be like when the project is completed. The vision statement should reflect a bal-
anced view that will satisfy the needs of diverse customers as well as those of the developing organiza-
tion. It may be somewhat idealistic, but it should be grounded in the realities of existing or anticipated
387
388 E X A M P L E P R O J E C T / P R O G R A M C H A R T E R T E M P L AT E
customer markets, enterprise architectures, organizational strategic directions, and cost and resource
limitations. Consider using the following template:
◾ For (target customer)
◾ Who (statement of the need or opportunity)
◾ The (product name)
◾ Is a (product category)
◾ That (key benefit, compelling reason to buy or use)
Success Criteria
What are the success criteria for the project? How do you know if the project has been successful?
Project Approach/Development Process
Identify the development process and/or any deviations from the standard methodology that will be
used for this project or program.
Project plan
This section outlines the plan for managing the project.
Scope
The project scope defines the range of the proposed products and services the project will deliver.
Scope can be represented using a context diagram, an event list, and/or a feature table. Scope might
be subdivided into the scope of the initial product release and planned growth strategies for subse-
quent releases. It is also important to define what the project will not include, so describe limitations
and exclusions, such as product features or characteristics that a stakeholder might anticipate, but
which are not planned to be included in the project.
In Scope
The project scope provides an overview of the user stories that the project will deliver. Scope might be
subdivided into the scope of the initial product release and planned growth strategies for subsequent
releases.
Release Priority Story # Story Name Description
E X A M P L E P R O J E C T /P R O G R A M C H A R T E R T E M P L AT E 389
Out of Scope
It’s also important to define what the ...
Proceedings of the 2015 Industrial and Systems Engineering Res.docxwkyra78
Proceedings of the 2015 Industrial and Systems Engineering Research Conference
S. Cetinkaya and J. K. Ryan, eds.
Use of Symbolic Regression for Lean Six Sigma Projects
Daniel Moreno-Sanchez, MSc.
Jacobo Tijerina-Aguilera, MSc.
Universidad de Monterrey
San Pedro Garza Garcia, NL 66238, Mexico
Arlethe Yari Aguilar-Villarreal, MEng.
Universidad Autonoma de Nuevo Leon
San Nicolas de los Garza, NL 66451, Mexico
Abstract
Lean Six Sigma projects and the quality engineering profession have to deal with an extensive selection of tools
most of them requiring specialized training. The increased availability of standard statistical software motivates the
use of advanced data science techniques to identify relationships between potential causes and project metrics. In
these circumstances, Symbolic Regression has received increased attention from researchers and practitioners to
uncover the intrinsic relationships hidden within complex data without requiring specialized training for its
implementation. The objective of this paper is to evaluate the advantages and drawbacks of using computer assisted
Symbolic Regression within the Analyze phase of a Lean Six Sigma project. An application of this approach in a
service industry project is also presented.
Keywords
Symbolic Regression, Data Science, Lean Six Sigma
1. Introduction
Lean Six Sigma (LSS) has become a well-known hybrid methodology for quality and productivity improvement in
organizations. Its wide adoption in several industries has shaped Process Innovation and Operational Excellence
initiatives, enabling LSS to become a main topic in quality practitioner sites of interest [1], recognized Six Sigma
(SS) certification body of knowledge contents [2], and professional society conferences [3].
However LSS projects and the quality engineering profession have to deal with an extensive selection of tools most
of them requiring specialized training. To assist LSS practitioners it is common to categorize tools based on the
traditional DMAIC model which stands for Define, Measure, Analyze, Improve, and Control phases. Table 1
presents an overview of the main tools that are commonly used in each phase of a LSS project, allowing team
members to progressively develop an understanding between realizing each phase’s intent and how the selected
tools can contribute to that purpose.
This paper focuses on the Analyze phase where tools for statistical model building are most likely to be selected.
The increased availability of standard statistical software motivates the use of advanced data science techniques to
identify relationships between potential causes and project metrics. In these circumstances Symbolic Regression
(SR) has received increased attention from researchers and practitioners even though SR is still in an early stage of
commercial availability.
The objective of this paper is to evaluate the advantages and drawbacks o ...
Analyzing the solutions of DEA through information visualization and data min...Gurdal Ertek
Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, Smart DEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for bench marking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework.
http://research.sabanciuniv.edu.
En la “Sección Escuelas” trabajamos con alumnos, padres de familia, docentes y personal administrativo, desarrollando habilidades que van de acorde a su función y trato con los diferentes segmentos.
Nos interesa complementar la educación humanista y emocional de los centros educativos para contribuir a una sociedad mas incluyente y tolerante.
O B J E T I V O G E N E R A L
Identificar y reproducir los elementos de un discurso efectivo, técnicas de manejo del escenario y herramientas de lenguaje corporal para transmitir seguridad así como reflexionar sobre las creencias limitantes que les puedan impedir hablar efectivamente en público.
H A B I L I D A D E S A D E S A R R O L L A R
Desarrollo de un discurso para cualquier contexto
Control de voz, gesticulación y movimientos
Comunicación persuasiva
Tablas que muestran los votos en datos duros, partidos y nombres de candidatos en todas las elecciones a gobernador en Sonora de 1949 a 2009. MCS Lizette Sandoval Meneses
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
We will dig deeper into:
1. How to capture video testimonials that convert from your audience 🎥
2. How to leverage your testimonials to boost your sales 💲
3. How you can capture more CRM data to understand your audience better through video testimonials. 📊
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
An introduction to the cryptocurrency investment platform Binance Savings.Any kyc Account
Learn how to use Binance Savings to expand your bitcoin holdings. Discover how to maximize your earnings on one of the most reliable cryptocurrency exchange platforms, as well as how to earn interest on your cryptocurrency holdings and the various savings choices available.
1. Page 1 of 6
ProblemTree&Objectives TreeTemplate
TOOL
Problem Tree
Purpose The ProblemTree isa methodforconductinga problemanalysis.Itisthe thoroughstudyof one or more problems(identifiedduringthe
assessmentstage),to identifytheircausesanddecide whetherandhowto addressthem. The aimof problemtree istostructure,
summarize andorganize the initial findingsof anassessment inthe formof a tree inorderto arrive at a clearerunderstandingof the
situationunderanalysis.
Merelylistingandrankingproblemsdoesnotprovide forasufficientlydeepanalysisof the situation.
Information Sources 1. IFRC ProjectPlanningManual: 4.1.4: Problemanalysisusingthe “problemtree”tool (P.21-22)
2. IFRC ProjectPlanningManual:Annex1:How to create a problemtree (P.51-53)
3. Initial situation/needsassessment
4. Otherneedsassessmentdata
5. Projectteamexperience
Who The problemanalysisusingthe ProblemTree methodshouldbe coordinated/facilitatedbyone personwholeadsthe entire process.For
EDF projects thiswill oftenbe the LWRProgram Manager, butcan be a representative fromthe partneroreventhe LWR Country
Director.The factors to considerwhendeterminingthe leadforthisprocessishis/herfamiliaritywithtargetpopulation,familiaritywith
the resultsfromthe needsassessment,andexperience inusingthe ProblemTree method.
For restrictedprojects the personresponsible forthe completionof the ProblemTree aswell asthe remainingaspectsof the project
designisthe Technical DesignCoordinator,whoisselectedduringthe Proposal Kickoff Meeting.The TechnicalDesignCoordinator:
Leadsthe technical designworkshop,includingproblemanalysisandlogical frameworkdevelopmentwithLWR,partnersand
technical experts.
Writessectionsincluding: ProjectDesign Workbook,whichmayinclude ResultsFramework,LogFrame,ImplementationPlan
and/orPerformance MonitoringPlan(PMP) dependingondonorguidance.
For proposalsunderthe threshold ($500,000),the DecisionMakerwill identifythe Technical DesignFacilitator.Forproposalsoverthe
threshold,the DecisionMakerandthe DeputyDirectorfor NBDwill selectthe Technical DesignFacilitator.
* For furtherguidance onthe grantsacquisitionprocessplease refertothe LWR Grants AcquisitionManual.
When The ProblemTree analysiscomesafterthe needsassessmentandbefore startingworkonthe ObjectivesTree.
Recommendations The ProblemTree methodisnotrequired,butaproblemanalysisshouldbe completedforall projectswhere applicable.
o The ProblemTree methodis a veryeffective tool andLWRrecommendsthatitbe usedas the primaryproblemanalysis
method.Nevertheless, LWR’spastproblemanalysismethodthattookthe formof a ProblemAnalysisbox canalsobe
used.
For some restrictedfundingproposalsthe donormayspecifythe problemstatementorthe causes,orboth.
o In caseswhere the problemstatementisprovided,thenthe problemanalysisshouldfocusondeterminingonlythe
causesto that problem,basedonwhatisknownaboutthe target area/populationasa resultof the needsassessment.
o If both the problemstatementandthe causesare specifiedbythe donor,the problemanalysis isnotrequired. The
2. Page 2 of 6
ProblemTree&Objectives TreeTemplate
TOOL
designteamcan move directlytocompletingthe ObjectivesTree.
It isrecommendedthatthe problemstatementandeachcause identifiedbe linkedtodatathat verifiesitsexistence inthe
target populationandthe degree towhichitaffectsthe targetpopulation.
o For example,if the projectgoal is"improvedagricultural productivity",the correspondingdescriptionof the cause
wouldbe "pooragricultural productivityinthe targetarea."The degree towhichthe cause affectsthe targetpopulation
wouldbe representedbyspecificdatawouldverifythe “howpoor”the agricultural productivityisinthe area(i.e.50%
reductionfromaverage inthe pastyear).
o The documentedsource maybe a LWR needsassessment,peeragencyneedsassessment,governmentreport,agency
report,or otherpublisheddocument
o This documentedsource is documentedinthe Project DesignWorkbookin the “Evidence forCause” tab.
The processis as importantasthe product.The exercise shouldbe treatedasalearningexperience andanopportunityfor
differentviewsandintereststobe expressed.
If necessary,the differentaspectsof aproblemareacan be furtherelaboratedthroughfocusgroupsorinterviews.
The Word template providedisatypical graphical presentationof aproblemtree.The graphiccanbe manipulated(size and
numberof boxes) toreflectthe resultsof the ProblemTree analysis,whichisoftencompletedwithstickynotesand flipchart.
o If the Word template isuseditmustbe transferredtothe ProjectDesignWorkbook once completed.Todoso,copy the
whole graphicandpaste it intothe ProjectDesignWorkbook usingthe “Paste Special”functionandpaste itas a
“Picture (EnhancedMeta-file)”
o An alternative optionistotake a photoof the resultsandpaste itinto the ProjectDesignWorkbook.
KEY: Any methodorprogram can be usedto documentthe resultsof the ProblemTree inthe ProjectDesignWorkbook.Whatis
importantisthat the resultsare documented.
Tips Completingthe problemanalysiscanbe complex therefore experience infacilitatingaproblemanalysisandfamiliaritywiththe
local contextisof utmostimportance whenselectingaleadcoordinator/facilitator.
Whenthe problemtree iscreatedwiththe targetpopulation’sparticipation,the analysisof the problemisenrichedandjoint
learningamongall concernedismade possible.
Doeseach cause-effectlink(illustratedbyarrows) make sense?Iseachlinkplausible?Whyorwhynot?
How well have the causesgone downtothe roots?Are there anyunidentified rootcauses?
What appearsto be the relative contributionof eachcausal stream(causeslinkedbyarrowsleadingtothe core problem
statement) tothe problem?
Do some causesappearmore than once?Why isthis?
Whichcausesshowsignificantinfluence?
3. Page 3 of 6
ProblemTree&Objectives TreeTemplate
TOOL
Problem
Effects
Cause:
Level 1
Cause:
Level 2
Effect2: Effect3:
ProblemStatement:
Cause 1.b:
Effect1: Effect4:
Cause 1: Cause 3:
Cause 2.a:
Cause 2:
Cause 1.a:
Cause 3.a:
Cause 3.c:
Cause 3.b:
LWR PROBLEM TREE TEMPLATE
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ProblemTree&Objectives TreeTemplate
TOOL
Objectives Tree
Purpose The ObjectivesTree isthe intermediate stepbetweenthe ProblemTree andthe ResultsFramework.The difference betweenthe
Objective Tree andthe ResultsFramework isthatthe Objective Tree showsALLpossible objectivesthatthe projectcouldchoose to
solve the problemidentifiedinthe ProblemTree analysis.The ResultsFramework showsthe final objectivesof the project,leavingout
those objectivesthatare not relevantorare too resource intensive.
It isa tool to aidanalysisandthe presentationof ideas.Itsmain strengthisthatitkeepsthe analysisof potential projectobjectives
firmlyrootedinaddressing arange of clearlyidentifiedpriorityproblems. Whereasproblemsanalysisseektoidentifycurrentnegative
conditions,objectivesanalysisaimstodisplayall possible solutionsandwill formthe foundationforthe project’sspecificstrategies. It
will helpto:
Demonstrate anddescribe the situationinthe future if all the identifiedproblems were remedied
Identifypossibleobjectives(intendedresults) andverifythe hierarchybetween them
Illustrate andverifythe causal (means-ends)relationshipsthroughadiagram
Establishprioritiesby:
o assessinghowrealisticthe achievementof some objectivesmaybe and
o identifyingadditional meansthatmaybe requiredtoachieve the intendedresults
Information Sources 1. IFRC ProjectPlanningManual: 4.2Developmentof objectives(P.22-24)
2. IFRC ProjectPlanningManual: Annex2:How to create and use an objectivestree (P.54-56)
3. ProblemTree results
Who The completionof the ObjectiveTree shouldbe coordinated/facilitatedbyone personwholeadsthe entire projectdesignprocess.For
EDF projects thiswill oftenbe the LWRProgram Manager, butcan be a representative fromthe partneroreventhe LWR Country
Director.The factors to considerwhendeterminingthe leadforthisprocessishis/herfamiliaritywithtargetpopulation,familiaritywith
the resultsfromthe needsassessment,andexperience in usingthe ObjectiveTree Method.
For restrictedprojects the personresponsible forthe completionof all aspectsof the projectdesignisthe TechnicalDesignCoordinator,
whois selectedduringthe Proposal Kickoff Meeting.The Technical DesignCoordinator:
Leadsthe technical designworkshop,includingproblemanalysisandlogical frameworkdevelopmentwithLWR,partnersand
technical experts.
Writessectionsincluding:ProjectDesignBook,whichmayincludeResultsFramework,LogFrame,ImplementationPlanand/or
Performance MonitoringPlan(PMP) dependingondonorguidance.
For proposalsunderthe threshold($500,000),the DecisionMakerwill identifythe Technical DesignFacilitator.Forproposalsoverthe
threshold,the Decision Makerandthe DeputyDirectorfor NBDwill selectthe Technical DesignFacilitator.
* For furtherguidance onthe grantsacquisitionprocessplease refertothe LWR Grants AcquisitionManual.
When The Objective Tree tool isusedafterthe ProblemTree iscompleted.The objectiveanalysisusingthe ObjectiveTree isthe intermediate
5. Page 5 of 6
ProblemTree&Objectives TreeTemplate
TOOL
stepbetweenthe creationof the ProblemTree andthe creationof the ResultsFramework.
Recommendations 1. There may be some causesnearthe bottomof the tree that are very general.They cannotbe turnedintoobjectivesthatcaneasily
be addressedbyan intervention. Instead,theyactas external factorsthatneedtobe consideredandassessedtoverify the
feasibilityof the intervention
2. As withthe ProblemTree the Wordtemplate providedisatypical graphical presentationof anobjective tree. The graphiccanbe
manipulated (size andnumberof boxes)toreflectthe resultsof the Objective Tree analysis,whichisoftencompletedwithsticky
notesandflipchart.
a. If the Word template isuseditmustbe transferredtothe ProjectDesignWorkbook once completed.Todoso,copy the
whole graphicandpaste it intothe ZeroDraft usingthe “Paste Special”functionandpaste itas a “Picture (Enhanced
Meta-file)”
b. An alternative optionistotake a photoof the resultsandpaste itinto the ProjectDesignWorkbook.
KEY: Any methodorprogram can be usedto documentthe resultsof the Objective Tree inthe ProjectDesignWorkbook.Whatis
importantisthat the resultsare documented.
Tips Are the positive statementsandobjectivesclear?
Have theybeenputintoa logical andreasonable orderthatshowsmeans-to-endslogic?
Is there a needtoadd otherobjectives?
How dothese objectivesdifferfromthe initialassessmentof howthe interventionshouldbe designed?