Room to Breathe: The BA's role in project estimationufunctional
What's the Business Analyst's role in project estimation?
According to this presentation, it's "Getting the project through the Hot Zone, with Room to Breathe."
Room to Breathe means enough time for the team and project manager to deal with the remaining uncertainty as it comes up.
The Hot Zone starts when up-front requirements and planning are yielding diminishing returns, the pressure to commit to a plan is mounting, and there's still more than about 25% uncertainty in the estimate.
The difference between a requirements gatherer and a Business Analyst is that a BA provides great decision support, and the estimation problem is at the heart of that.
This document discusses estimating IT projects. It begins by defining estimation and explaining why IT project estimation can be difficult due to uncertainties. It then covers estimating methodologies like functional size measurement and function point analysis to objectively measure a project's size based on elements like user stories, interfaces, and data movements. The document stresses that the only certainty in projects is uncertainty and discusses techniques for translating a project's estimated size into an effort estimate while managing risks and changes. The goal is to provide reliable cost and schedule estimates for IT projects.
The document provides tips and techniques for software estimation. It discusses defining estimates, factors that influence accuracy such as probability statements and the cone of uncertainty. The primary purpose of estimation is to determine if targets are realistic rather than perfectly predicting outcomes. Techniques covered include counting elements to estimate, using historical data for calibration, individual expert judgement breaking tasks into appropriate levels of detail, analogy to past projects, and group expert judgement. Accuracy improves with proper technique selection, assumptions documentation, and incorporating lessons learned.
Everyone has been given a 2 paragraph document listing the "scope of services" for a potential project. The client would like an estimate in 48 hours and there are no more details to help you deliver that required fixed bid contract. At the same time, many teams have also been given (or created) a detailed PRD or backlog document and still had a project budget balloon out of control. In this session I would like to discuss the not only the problems associated with estimation and how to avoid them, but more importantly how we can plan for them, turning our estimation process into not only an art, but a science. Well cover how to sell your estimate internally, and arm you with the methodologies to support your numbers. The problem with software estimation The morale The metrics The reality - an estimation metaphor Avoiding Risk Project entry point of sale At what point of the project lifecycle is your first sale? Risk association with point of sale Products in the front, estimations in the back The Elusive Discovery phase How to estimate a discovery How to sell a discovery How to include discovery in a full fixed bid RFP Planning for Risk Estimation types Gut - An art form Comparables - An art/science Factors/formula - A science Contingency Rating systems Formulas Granularity
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.
This document provides a draft proposal for a graduation project that aims to determine a quantitative definition for "significantly more" in the context of comparisons made using the Analytic Hierarchy Process (AHP) method. The proposal outlines that AHP uses a 1-9 scale to compare criteria, but this can sometimes lead to inconsistent results. The project will conduct surveys to understand if inconsistencies are due to the scale itself or individuals' judgments. Based on survey results, the team will develop an algorithm to customize the scale for each individual, reducing inconsistencies. The proposal describes the project tasks, methods, constraints, risks and schedule.
This document discusses the application of sensitivity analysis for investment project evaluation. Sensitivity analysis is used to determine how changes in input values impact final output values. It examines the maximum and minimum values an input can have while still allowing a project to be profitable. An example analysis is shown for a metal processing industry project. Input values for net income, discount rate, and costs are varied to observe their impact on net present value. Sensitivity analysis allows improvements to investment decisions by showing how outputs change with inputs when future conditions are uncertain.
Room to Breathe: The BA's role in project estimationufunctional
What's the Business Analyst's role in project estimation?
According to this presentation, it's "Getting the project through the Hot Zone, with Room to Breathe."
Room to Breathe means enough time for the team and project manager to deal with the remaining uncertainty as it comes up.
The Hot Zone starts when up-front requirements and planning are yielding diminishing returns, the pressure to commit to a plan is mounting, and there's still more than about 25% uncertainty in the estimate.
The difference between a requirements gatherer and a Business Analyst is that a BA provides great decision support, and the estimation problem is at the heart of that.
This document discusses estimating IT projects. It begins by defining estimation and explaining why IT project estimation can be difficult due to uncertainties. It then covers estimating methodologies like functional size measurement and function point analysis to objectively measure a project's size based on elements like user stories, interfaces, and data movements. The document stresses that the only certainty in projects is uncertainty and discusses techniques for translating a project's estimated size into an effort estimate while managing risks and changes. The goal is to provide reliable cost and schedule estimates for IT projects.
The document provides tips and techniques for software estimation. It discusses defining estimates, factors that influence accuracy such as probability statements and the cone of uncertainty. The primary purpose of estimation is to determine if targets are realistic rather than perfectly predicting outcomes. Techniques covered include counting elements to estimate, using historical data for calibration, individual expert judgement breaking tasks into appropriate levels of detail, analogy to past projects, and group expert judgement. Accuracy improves with proper technique selection, assumptions documentation, and incorporating lessons learned.
Everyone has been given a 2 paragraph document listing the "scope of services" for a potential project. The client would like an estimate in 48 hours and there are no more details to help you deliver that required fixed bid contract. At the same time, many teams have also been given (or created) a detailed PRD or backlog document and still had a project budget balloon out of control. In this session I would like to discuss the not only the problems associated with estimation and how to avoid them, but more importantly how we can plan for them, turning our estimation process into not only an art, but a science. Well cover how to sell your estimate internally, and arm you with the methodologies to support your numbers. The problem with software estimation The morale The metrics The reality - an estimation metaphor Avoiding Risk Project entry point of sale At what point of the project lifecycle is your first sale? Risk association with point of sale Products in the front, estimations in the back The Elusive Discovery phase How to estimate a discovery How to sell a discovery How to include discovery in a full fixed bid RFP Planning for Risk Estimation types Gut - An art form Comparables - An art/science Factors/formula - A science Contingency Rating systems Formulas Granularity
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.
This document provides a draft proposal for a graduation project that aims to determine a quantitative definition for "significantly more" in the context of comparisons made using the Analytic Hierarchy Process (AHP) method. The proposal outlines that AHP uses a 1-9 scale to compare criteria, but this can sometimes lead to inconsistent results. The project will conduct surveys to understand if inconsistencies are due to the scale itself or individuals' judgments. Based on survey results, the team will develop an algorithm to customize the scale for each individual, reducing inconsistencies. The proposal describes the project tasks, methods, constraints, risks and schedule.
This document discusses the application of sensitivity analysis for investment project evaluation. Sensitivity analysis is used to determine how changes in input values impact final output values. It examines the maximum and minimum values an input can have while still allowing a project to be profitable. An example analysis is shown for a metal processing industry project. Input values for net income, discount rate, and costs are varied to observe their impact on net present value. Sensitivity analysis allows improvements to investment decisions by showing how outputs change with inputs when future conditions are uncertain.
2008 SMEF - Scope management - Sail the seas of changeFrank Vogelezang
Scope management has a lot of parallels with Columbus journey to discover America. He did not know what he was going to find, but he went with all knowledge available.
Bij een aantal opdrachtgevers leeft het beeld dat leveranciers, met name die op het gebied van IT dienstverlening, ratten zijn. Alleen maar uit op eigen gewin en zonder oog voor de belangen van de opdrachtgever. Ik begrijp dat beeld wel, maar ik ben het er niet mee eens. En dat komt niet omdat ik voor een IT dienstverlener werk. Het gedrag dat door opdrachtgevers soms als ratten-gedrag betiteld wordt is namelijk vooral een gevolg van wat de opdrachtgever vraagt. Het is tijd om dat even recht te zetten.
Frank Vogelezang presented a method for estimating the functional size of 400 applications in an Oracle eBS portfolio in 3 months with limited resources. The method involved estimating sizes based on application characteristics rather than documentation, allowing for imprecise results within 30% deviation. This functional size estimation approach was 50% cheaper than a traditional function point analysis and allowed sizing the entire portfolio in 5,300 hours compared to over 10 person-years for a traditional count. The results provided a functional size of 316,720 function points across 363 applications to help manage and control the portfolio.
- Frank Vogelezang presented on estimating and pricing application management at the 2011 Galorath International Conference in Eindhoven.
- He discussed Ordina's approach to separating estimating, which focuses on engineering costs, from pricing, which is a commercial process.
- Their estimating model for application management breaks work down into components with different cost drivers like functional size, age, and service levels. It is designed for outsourced application management.
Estimating & Control - Reliable Estimates for Realistic Projects - PMI NL cha...Frank Vogelezang
IT projects have a large rate of failure. This is partly due to the unstable environment an IT project has to operate in, partly due to bad management, but mainly due to the fact that projects start with an unrealistic estimate and has to live up to impossible expectations. The “Basis of Estimate” is a good framework to establish the completeness of an estimate and to control the progress. To create a reliable estimate for a realistic project the right basis must be selected for design, sizing, effort, planning and cost. How can we select the right experience data to make realistic predictions for a new IT project.
Presentatie die ik op 31 oktober 2012 gegeven heb voor de OV benchmark. Deze groep van (semi)overheden komt twee keer per jaar bij elkaar om ideeën rondom het meetbaar en inzichtelijk maken van kosten en inspanning in het ICT te bespreken.
This document discusses using a real-life case study to help explain the COSMIC measurement method. It describes the Web Advice Module case study, which measures a small banking application. Developing the case study aims to provide practical examples for novice and experienced users. Real-life cases have advantages like relevance but also challenges like complexity that require more documentation. The working group is finalizing version 0.8 and inviting further input to publish a final version in January 2013.
The use of FPA is on the rise again, at least in Requests for Proposal for new contracts. But what is a function point and what can you do with it or should better not be done. I gave my colleagues a brief introduction, that appeared to be interesting to a much wider audience, so I translated the original Dutch presentation to English.
Simplify Estimating & Pricing of Application ManagementFrank Vogelezang
Estimating Application Management is not simple because the scope of Application Management is more diffuse than the scope of a project. (Application Management is software that manages and monitors the availability and components of network-centered applications within an organization, such as e-mail, intranets and client/server).
When Application Management is outsourced to an IT service provider, both parties need to have a clear understanding what activities will be outsourced and what activities will remain with the outsourcing organization.
To make that easier, Ordina has developed Dynamic Delivery, which selects the best IT service model for Application Management.
When you have defined what activities are in scope for an Application Management service offering, you are able to use this model as a basis to estimate the related effort and cost. In this webinar, you will learn how Ordina was able to do this in a transparent way, based on experience data by:
- Combining the vision of their Service Component Model with the estimating power and references of SEER-IT.
- Translating the Service Component Model to WBS elements that are predominantly based on the knowledge bases within SEER-IT.
- Configuring the WBS elements to be able to estimate Application Management for Oracle EBS.
It shows how we converted our model for estimating application management into a working model using SEER for IT and SEER for Software knowledge bases.
You can find the webinar on: http://www.galorath.com/flash_presentations/appl_mgt_webinar040312_final/
Parametric Estimation for Reliable Project EstimatesFrank Vogelezang
Frank Vogelezang is a manager at Ordina who gives presentations on parametric estimation for reliable IT project estimates. The presentation covers estimating IT projects, translating requirements to a functional size measured in function points, and using proven reference data through parametric analysis to build reliable cost and schedule estimates. Keeping track of actual project performance allows re-estimating and incorporating experience to improve future parametric estimates.
Application Portfolio Management, the Basics - How much Software do I haveFrank Vogelezang
After two external benchmarks, the Software Application Support division decided that the only way to quantitatively manage application support was by establishing a sufficient estimate of the size of the application portfolio. Based on criteria from Gartner’s Application Benchmark a selection was made regarding which applications made up the application portfolio. Five different methods were used to size approximately three hundred applications, each with its own precision and cost efficiency: Gartner Fast FPA estimation, Backfiring from LoC for some older PL/1 and Assembler applications, detailed counts with NESMA FPA and COSMIC for newly developed systems and backtracking from budget for less important smaller applications. The size estimations were made by regular support personnel with little training in functional size measurement. A sample selection was reviewed by an experienced consultant, in order to detect possible pitfalls and ambiguities. The results from the review led to a re-evaluation of most of the FPA-estimations, with a higher precision and greater consistency. The results of these size estimates can now be used to compare parts of the portfolio and to quantitatively manage the (support of the) portfolio.
Scope master introduction presentation feb 2020 w vidColin Hammond
This document discusses automated analysis of software requirements using ScopeMaster. It provides an overview of ScopeMaster, describing it as a tool that analyzes user stories and requirements documents to find problems, help fix issues before coding, and provide better estimates. It highlights benefits like reduced costs, fewer defects, and faster delivery. Examples are given showing ScopeMaster finding 150 defects in requirements in 2 days and identifying potential savings of $100k or more in just a few hours of analysis.
Estimating for projects and programmes is a core project management competence. Estimating uncertainty is generally the largest single risk to project delivery. Here, estimating best practice is described along with a few hints and tips.
Advanced Project Data Analytics for Improved Project DeliveryMark Constable
Data Analytics is already beginning to impact how projects are delivered. We can now automate minute taking and capturing actions, we can use Flow to progress chase, Power BI reduces the burden of reporting.
But we are just scratching the surface. It won’t be long before we can leverage the rich dataset of experience to predict what risks are likely to occur, understand which WBS elements will be susceptible to variance, deduce what the optimum resource profile looks like, define a schedule by leveraging data from those projects that have gone before.
The role of a project professional is about to change dramatically. In this webinar we will explore the challenges and opportunities, and how we should respond. It’s a call-to-action for the community to mobilise, help to reshape project delivery and understand the implications for you and your organisation.
Presenter Martin Paver is a Chartered Project Professional, APM Fellow and Chartered Engineer. In December 2017 he established the London Project Data Analytics meetup which has quickly spread across the UK and expanded to 3000+ members. Martin has major project experience including leading a $billion projects with a team of 220 and a multi-billion PMO with a team of 50. He has a detailed grasp of project management and combines this with a broad understanding of recent developments in the field of data science. He is on a mission to ensure that the project management profession readies itself for a transformed future.
Learning outcomes:
- Understand the implications of advanced data analytics on project delivery
- Understand the scope of which functions it is likely to impact
- Help you to develop a strategy for how you engage with it
- Understand how to leverage the benefits and opportunities that will emerge from it
Presenter:
Martin Paver, CEO & Founder, Projecting Success Ltd
2008 SMEF - Scope management - Sail the seas of changeFrank Vogelezang
Scope management has a lot of parallels with Columbus journey to discover America. He did not know what he was going to find, but he went with all knowledge available.
Bij een aantal opdrachtgevers leeft het beeld dat leveranciers, met name die op het gebied van IT dienstverlening, ratten zijn. Alleen maar uit op eigen gewin en zonder oog voor de belangen van de opdrachtgever. Ik begrijp dat beeld wel, maar ik ben het er niet mee eens. En dat komt niet omdat ik voor een IT dienstverlener werk. Het gedrag dat door opdrachtgevers soms als ratten-gedrag betiteld wordt is namelijk vooral een gevolg van wat de opdrachtgever vraagt. Het is tijd om dat even recht te zetten.
Frank Vogelezang presented a method for estimating the functional size of 400 applications in an Oracle eBS portfolio in 3 months with limited resources. The method involved estimating sizes based on application characteristics rather than documentation, allowing for imprecise results within 30% deviation. This functional size estimation approach was 50% cheaper than a traditional function point analysis and allowed sizing the entire portfolio in 5,300 hours compared to over 10 person-years for a traditional count. The results provided a functional size of 316,720 function points across 363 applications to help manage and control the portfolio.
- Frank Vogelezang presented on estimating and pricing application management at the 2011 Galorath International Conference in Eindhoven.
- He discussed Ordina's approach to separating estimating, which focuses on engineering costs, from pricing, which is a commercial process.
- Their estimating model for application management breaks work down into components with different cost drivers like functional size, age, and service levels. It is designed for outsourced application management.
Estimating & Control - Reliable Estimates for Realistic Projects - PMI NL cha...Frank Vogelezang
IT projects have a large rate of failure. This is partly due to the unstable environment an IT project has to operate in, partly due to bad management, but mainly due to the fact that projects start with an unrealistic estimate and has to live up to impossible expectations. The “Basis of Estimate” is a good framework to establish the completeness of an estimate and to control the progress. To create a reliable estimate for a realistic project the right basis must be selected for design, sizing, effort, planning and cost. How can we select the right experience data to make realistic predictions for a new IT project.
Presentatie die ik op 31 oktober 2012 gegeven heb voor de OV benchmark. Deze groep van (semi)overheden komt twee keer per jaar bij elkaar om ideeën rondom het meetbaar en inzichtelijk maken van kosten en inspanning in het ICT te bespreken.
This document discusses using a real-life case study to help explain the COSMIC measurement method. It describes the Web Advice Module case study, which measures a small banking application. Developing the case study aims to provide practical examples for novice and experienced users. Real-life cases have advantages like relevance but also challenges like complexity that require more documentation. The working group is finalizing version 0.8 and inviting further input to publish a final version in January 2013.
The use of FPA is on the rise again, at least in Requests for Proposal for new contracts. But what is a function point and what can you do with it or should better not be done. I gave my colleagues a brief introduction, that appeared to be interesting to a much wider audience, so I translated the original Dutch presentation to English.
Simplify Estimating & Pricing of Application ManagementFrank Vogelezang
Estimating Application Management is not simple because the scope of Application Management is more diffuse than the scope of a project. (Application Management is software that manages and monitors the availability and components of network-centered applications within an organization, such as e-mail, intranets and client/server).
When Application Management is outsourced to an IT service provider, both parties need to have a clear understanding what activities will be outsourced and what activities will remain with the outsourcing organization.
To make that easier, Ordina has developed Dynamic Delivery, which selects the best IT service model for Application Management.
When you have defined what activities are in scope for an Application Management service offering, you are able to use this model as a basis to estimate the related effort and cost. In this webinar, you will learn how Ordina was able to do this in a transparent way, based on experience data by:
- Combining the vision of their Service Component Model with the estimating power and references of SEER-IT.
- Translating the Service Component Model to WBS elements that are predominantly based on the knowledge bases within SEER-IT.
- Configuring the WBS elements to be able to estimate Application Management for Oracle EBS.
It shows how we converted our model for estimating application management into a working model using SEER for IT and SEER for Software knowledge bases.
You can find the webinar on: http://www.galorath.com/flash_presentations/appl_mgt_webinar040312_final/
Parametric Estimation for Reliable Project EstimatesFrank Vogelezang
Frank Vogelezang is a manager at Ordina who gives presentations on parametric estimation for reliable IT project estimates. The presentation covers estimating IT projects, translating requirements to a functional size measured in function points, and using proven reference data through parametric analysis to build reliable cost and schedule estimates. Keeping track of actual project performance allows re-estimating and incorporating experience to improve future parametric estimates.
Application Portfolio Management, the Basics - How much Software do I haveFrank Vogelezang
After two external benchmarks, the Software Application Support division decided that the only way to quantitatively manage application support was by establishing a sufficient estimate of the size of the application portfolio. Based on criteria from Gartner’s Application Benchmark a selection was made regarding which applications made up the application portfolio. Five different methods were used to size approximately three hundred applications, each with its own precision and cost efficiency: Gartner Fast FPA estimation, Backfiring from LoC for some older PL/1 and Assembler applications, detailed counts with NESMA FPA and COSMIC for newly developed systems and backtracking from budget for less important smaller applications. The size estimations were made by regular support personnel with little training in functional size measurement. A sample selection was reviewed by an experienced consultant, in order to detect possible pitfalls and ambiguities. The results from the review led to a re-evaluation of most of the FPA-estimations, with a higher precision and greater consistency. The results of these size estimates can now be used to compare parts of the portfolio and to quantitatively manage the (support of the) portfolio.
Scope master introduction presentation feb 2020 w vidColin Hammond
This document discusses automated analysis of software requirements using ScopeMaster. It provides an overview of ScopeMaster, describing it as a tool that analyzes user stories and requirements documents to find problems, help fix issues before coding, and provide better estimates. It highlights benefits like reduced costs, fewer defects, and faster delivery. Examples are given showing ScopeMaster finding 150 defects in requirements in 2 days and identifying potential savings of $100k or more in just a few hours of analysis.
Estimating for projects and programmes is a core project management competence. Estimating uncertainty is generally the largest single risk to project delivery. Here, estimating best practice is described along with a few hints and tips.
Advanced Project Data Analytics for Improved Project DeliveryMark Constable
Data Analytics is already beginning to impact how projects are delivered. We can now automate minute taking and capturing actions, we can use Flow to progress chase, Power BI reduces the burden of reporting.
But we are just scratching the surface. It won’t be long before we can leverage the rich dataset of experience to predict what risks are likely to occur, understand which WBS elements will be susceptible to variance, deduce what the optimum resource profile looks like, define a schedule by leveraging data from those projects that have gone before.
The role of a project professional is about to change dramatically. In this webinar we will explore the challenges and opportunities, and how we should respond. It’s a call-to-action for the community to mobilise, help to reshape project delivery and understand the implications for you and your organisation.
Presenter Martin Paver is a Chartered Project Professional, APM Fellow and Chartered Engineer. In December 2017 he established the London Project Data Analytics meetup which has quickly spread across the UK and expanded to 3000+ members. Martin has major project experience including leading a $billion projects with a team of 220 and a multi-billion PMO with a team of 50. He has a detailed grasp of project management and combines this with a broad understanding of recent developments in the field of data science. He is on a mission to ensure that the project management profession readies itself for a transformed future.
Learning outcomes:
- Understand the implications of advanced data analytics on project delivery
- Understand the scope of which functions it is likely to impact
- Help you to develop a strategy for how you engage with it
- Understand how to leverage the benefits and opportunities that will emerge from it
Presenter:
Martin Paver, CEO & Founder, Projecting Success Ltd
Software Metrics: Taking the Guesswork Out of Software ProjectsTechWell
Why bother with measurement and metrics? If you never use the data you collect, this is a valid question—and the answer is “Don’t bother, it’s a waste of time.” In that case, you’ll manage with opinions, personalities, and guesses—or even worse, misconceptions and misunderstandings. Based on his more than forty years of software and systems development experience, Ed Weller describes reasons for measurement, key measures in both traditional and agile environments, decisions enabled by measurement, and lessons learned from successful—and not so successful—measurement programs. Find out how to develop and maintain consistent data and valid measures so you can estimate reliably, deliver products with known quality, and have happy users and customers—the ultimate trailing indicator. Learn to manage projects dynamically with the support of current metrics and data from past projects to guide your management planning and control. Join Ed to explore how to invest in measurements that provide leading indicators to help you meet your company and customer goals.
'Metrics That Matter': Gabrielle Benefield @ Colombo Agile Con 2014ColomboCampsCommunity
The document discusses different types of metrics that can be used to measure success, including activity-based, output-based, and outcome-based metrics. It also provides examples of metrics that could be used to measure different phases of a project such as planning, development, design, testing, and maintenance. Finally, it discusses challenges with measuring success, including differences between plans and actual outcomes.
Harold van Heeringen discusses software estimation and performance measurement. He notes that most software projects have low estimation maturity and experience cost and schedule overruns. Functional size measurement and historical project data can be used to create more objective, repeatable estimates. Estimates should include scenarios for different durations, team sizes, and non-functional requirements. Performance measurement involves collecting project data and comparing actual metrics like productivity and defects to estimates. Benchmarking against industry data provides opportunities for improvement. Accurate estimation and performance measurement processes help create defendable estimates and manage projects based on actual performance.
This document describes a project and portfolio simulation capability that provides predictive and prescriptive analytics. It allows users to easily create multiple scenarios considering portfolio data, resources, and financials. It also provides a competing objectives optimizer that evaluates objectives like project priorities, throughput, resource capacity, costs, and revenues. The simulation generates predictions and recommendations by considering all risks and simulating numerous potential futures to optimize portfolio performance. It enables rapid interactive scenario planning and visualization of project schedules and their impacts on constrained resources and costs.
Presentation given by Richard Corderoy from the Oakland Group on 29 July 2020.
Link to the news story:
https://www.apm.org.uk/news/cutting-through-the-hype-how-to-use-advanced-analytics-to-do-practical-things-today-webinar/
Link to YouTube recording: https://youtu.be/OIsvCrFR5Uw
This document discusses using machine learning and data to drive proactive assurance activities. It proposes developing a quantitative project health score based on metrics and signals from project data to remove subjectivity. Machine learning models would be trained on historical project performance data to predict when a project's health score is deteriorating so that assurance interventions can be performed earlier. This approach aims to move from infrequent, subjective assessments to more objective, data-driven proactive assurance.
Accurate estimates are important for software projects. While it may be tempting to underestimate to avoid issues like Parkinson's Law, underestimating causes more severe problems like reduced project planning effectiveness and a lower chance of on-time completion. The software industry has a poor track record, with only 28% of projects being delivered on time and on budget according to one study. Having accurate estimates improves visibility, quality, coordination, budgeting, and credibility. Overall, predictability of cost, schedule and functionality is valued more by project managers than flexibility or development speed alone.
[DSC Europe 22] The Making of a Data Organization - Denys HolovatyiDataScienceConferenc1
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2. 2
Agenda
Estimating IT projects
What is estimating
How good is your estimate
The only certainty is uncertainty
Cost drivers for IT projects
Reliable estimation
4. IT has a bad track-record in project estimating
What is estimating
4
For a critical analysis of the Chaos reports see: www.cs.vu.nl/~x/chaos
5. IT has a bad track-record in project estimating
What is estimating
Any idea where this bad track-record comes from?
5
6. IT has a bad track-record in project estimating
What is estimating
Any idea where this bad track-record comes from?
No clear project objective
Start with an inadequate budget
Too little time and/or resources
No use of benchmarking
No idea what an estimate is
6
We can double
the estimate . . . . but then it will
ultimately be four
times as expensive!
on estimating
7. Definition of an estimate
What is estimation
How would you define an estimate?
An estimate is
an analytical and unbiased prediction
of how long it takes
and what it will cost
The bias comes from the interplay with targets, commitments and plans
7
8. Target, estimate, commitment and plan
What is estimation
Target
Desirable business objective
When and what
Estimate
Analytical prediction
With an uncertainty range
How and what
Commitment
Promise to deliver
Defined functionality and quality
What and when
Plan
Bridging the gap between estimate and commitment and mitigating the risk involved
When and how
8
9. A typical estimate
What is estimation
9
Probability
Schedule / Cost
50/50 median result
First likely option
10. A good estimate
What is estimation
A good estimate is
a prediction
that provides a clear enough view
of the project reality
to allow the project leadership to make informed decisions
about how to control the project
to hit its targets.
Know where you come from, where you are and where you are going
10
Software Estimation: Demystifying the black art: www.SteveMcConnell.com
11. Basis of Estimate
New standard practice by NESMA and AACEi
11
RECOMMENDEDPRACTICE
Estimation
purpose
Engagement
Scope
Description
Estimating
methodology
(FP, expert,
etc.)
Estimate
Classification
(1,2,3,4,5)
Design Basis
(Components
lists, units, etc.)
Sizing Basis
Requirements
Functional
technical
Effort Basis
delivery
constraints,
service levels
Planning Basis
Working time
standby
Cost Basis
methods and
sources , units
Assumptions
internal,
external
Allowances
Not in the Basis
Exclusions
No costs
included for…
Exceptions
anomalies or
variances on
standard
Risks and
Opportunities
assumptions
Containments
cost elements
for mitigation
Contingencies
Uncertainty,
unforeseeable
elements
Management
Reserve
changes in
scope, effort
Reconciliation
Changes to
previous
estimation
Benchmarking
Comparisons to
similar
engagements
Level of detail
Stage, Deal
size/type, fixed
price/TM
Estimate
Quality
Assurance
Reviews
Attachments Attachments Attachments Attachments
12. How good is your estimate
A simple quiz with unexpected questions
13. A simple quiz
How good is your estimate
The rules
You get 10 questions, about anything but IT
Answer each question with an upper and a lower boundary
The answer should be within these bounds with a 90% chance
The objective
To finish the quiz with 90% correct answers
So 9 answers to the questions are within the boundaries
13
14. A simple quiz
How good is your estimate
1. What is the surface temperature of the sun in ºC
2. What was the total throughput of the Port of Rotterdam in 2012 in metric tons
3. World-wide box office receipts of the Lord of the Rings trilogy in US$
4. What is the total area of the Asian continent in km2
5. What is the year of birth of Alexander the Great according to Christian calender
6. The number of book titles in the Library of the Congress since 1776 in millions
7. How heavy was the heaviest blue whale ever recorded in metric tons
8. How many Euro bills were in circulation at the end of 2009 in billions
9. What is the highest point in the kingdom of the Netherlands in m
10.What is the total length of the coastline of the Pacific Ocean in km
14
15. Estimating psychology
How good is your estimate
How well did you do this quiz?
The average score is around 3, in line with the CHAOS reports
We are conditioned to believe that narrow ranges are more accurate
We feel that wide ranges make us appear ignorant or incompetent
In real projects estimates are often biased by knowledge about the targets
15
16. Beating the estimating psychology
How good is your estimate
If the objective is unclear, the answer cannot be precise
IT suppliers want to do customers a favour by promising they can deliver,
although they have no idea whether it is realistic. Is that a favour?
There are no bad suppliers, but enough substandard customers*
16
* Joep Bröcker (KPN) : www.sogeti.nl/evenementen/2010/succesvol-aanbesteden-van-ict
17. The only certainty is uncertainty
Most IT projects deliver something else than initially intended
18. Managing the devil’s triangle
Balancing between cost, time and scope
Cost
18
Time
Scope or Quality
Risk
19. Managing the devil’s triangle
Balancing between cost and time for a given size
19
Paul Masson’s
Law
Parkinson’s
Law
Brooks’
Law
Minimal time
Optimal effort
Time
Effort/Cost
Realistic
Productivity
20. The devil is in change
Traditional fixed price, fixed date projects
Cost
20
Time
Scope or Quality
Risk
Risk
Risk
Risk
21. Let’s make room for change
The uncertainty in agile projects
Cost
21
Time
Scope or Quality
Risk
Doubt
25. 25
Effort estimation
Estimating IT projects
Ask the experts to estimate using Delphi techniques
Original Delphi:
Individual estimates | Distributed by a facilitator | Several rounds
Wideband Delphi:
Group discussion | Individual estimates | Consensus on large variation
Delphi – PERT:
Use Delphi to establish lower bound, higher bound and most likely value
Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
26. 26
Effort estimation
Estimating IT projects
Ask the experts to estimate using Delphi techniques
Original Delphi:
Individual estimates | Distributed by a facilitator | Several rounds
Wideband Delphi:
Group discussion | Individual estimates | Consensus on large variation
Delphi – PERT:
Use Delphi to establish lower bound, higher bound and most likely value
Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
Planning Poker:
Estimate effort to produce a work item, related to a standard work item
Use cards with a Fibonacci (like) scale to reflect uncertainty for larger items
28. 28
Size estimation
Estimating IT projects
Sizing by proxy
Define repeatable elements
Experience data per proxy element
Technical elements: Lines of Code
Programs / Modules
Screens
Data files / Views
Interfaces
Logical elements: User Stories / Use Cases
Processes in the Data Flow Diagram
Functional Size Measurement
29. 29
Size estimation
Lines of Code
What does the number of lines tell me about size?
13 LoC – 1 statement
Backfiring
Translation to Functional Size
Uncertainty range over 300%
20 LoC – 3 statements
30. 30
Size estimation
Functional Size Measurement – Function Point Analysis
FPA stands for Function
Point
Analysis
What the software should be able to do (functionality) Function
expressed in a number Point
based on an objectively described method Analysis
Something intangible like functionality becomes a physical number that can
be used for calculations
31. 31
Size estimation
Functional Size Measurement – Function Point Analysis
External Input
External Output
External Inquiry
External input files
Internallogical files
Data oriented
32. Size estimation
Functional Size Measurement – Function Point Analysis
Counting function points
Based on established criteria each element is
classified:
Each classification has its own scores
Internal files 7 10 15
External interfaces 5 7 10
External input 3 4 6
External output 4 5 7
External inquiry 3 4 6
A function point never travels alone
32
Simple
Complex
34. Size estimation
Functional Size Measurement – COSMIC
Counting COSMIC function points
Establish Functional Processes
Determine the data movements
# Entries
# Writes
# Reads
# eXits
Each data movement is scored
Entry 1 CFP
Write 1 CFP
Read 1 CFP
eXit 1 CFP
A data movement can be identified alone
34
38. Translating size into effort
Team size as a cost driver
38
Paul Masson’s
Law
Parkinson’s
Law
Brooks’
Law
Minimal time
Optimal effort
Time
Effort/Cost
Realistic
Productivity
39. Translating size into effort
What can you do with Functional Size
39
Translate functionality into a physical number that can be used to calculate:
Required amount of hours / cost
Schedule time
Basis for a fixed price (per unit) that is still variable
The calculation depends on the technology used (Java, eBS, . . .)
But it is not a linear calculation!
Twice the size in function points is not twice as much hours / cost / time
42. Reliable estimation
Case – Rebuild of Investment Fund Application
Case (1 page)
5 expert estimates (2 pages)
Estimation approach (1 page)
1. Are the estimates complete?
2. Are the assumptions correct?
3. How relevant and reliable are the estimates?
4. Question the experts!
5. Are the estimates comparable? By accident or by design?
6. Can approaches be used to reinforce other estimates?
Present the results of these steps
Present the results of the final estimate
42