This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Please find below a transcription of the audio portion of Fletcher Hearn’s session, Project PerformanceMeasurement – Part 1: Overview Of Project PerformanceMeasurements, being provided by MPUG for the convenience of our members. Kyle: Hello, and welcome to part one of MPUGs Project PerformanceMeasurement course.
Please find below a transcription of the audio portion of Fletcher Hearn’s session, Project PerformanceMeasurement – Part 2: What to Measure and How to Report, being provided by MPUG for the convenience of our members. Kyle: And welcome to Part 2 of MPUG’s Project PerformanceMeasurement course.
If we look at the discipline of softwareengineering, we see that the microeconomics branch of economics deals more with the types of decisions we need to make as softwareengineers or managers. Softwareengineering economics." IEEE Transactions of SoftwareEngineering, 1 (1984): 4-21.
I work in a domain where the CoU is baked into the Integrated Program PerformanceManagement (IPPM) processes flowed down from the buyer, in this case, the Federal Government. The CoU paradigm defines the needed reduction in uncertainty is some performance metric. IEEE Transactions on EngineeringManagement , 57 (4), pp.
There is always lots of complaining about the biases introduced into managing projects and making the estimates needed to make project decisions. Optimism bias - a cognitive bias that causes a person to believe that they are at a lesser risk of experiencing a negative event compared to others. These principles originate in: .
The Cone of Uncertainty as a Technical PerformanceMeasure. Uncertainty creates Risk. Riskmanagement requires active reduction of risk. Active reduction requires we have a desired reduction goal, perform the work, and measure progress toward the rduction goal. Measure of Effectiveness.
Barry Boehm's work in “SoftwareEngineering Economics”. The Cone is a project management framework describing the uncertainty aspects of estimates (cost and schedule) and other project attributes (cost, schedule, and technical performance parameters). The notion of the Cone of Uncertainty has been around for awhile.
After having worked for outsourcing, consultancy and product companies I believe that creating a place where people really trust each other is easier when softwareengineers and stakeholders are both part of the same organization. This is standard Product Management. Done by every Product Manager for every Product Company.
Barry Boehm's work in “SoftwareEngineering Economics”. The Cone is a project management framework describing the uncertainty aspects of estimates (cost and schedule) and other project attributes (cost, schedule, and technical performance parameters). The notion of the Cone of Uncertainty has been around for awhile.
Barry Boehm's work in “SoftwareEngineering Economics”. The Cone is a project management framework describing the uncertainty aspects of estimates or any other project attribute (in this post, cost, schedule, and technical performance parameters). A critical success factor for all project work is RiskManagement.
Here's an extract from "Chapter 8: Human Behavior and Complexity," Terry Cooke-Davies, in Aspects of Complexity: Managing Projects in a Complex World. This is a cautionary tale for those listening to the #NoEstimates advocates, where anecdotes of bad management are used in an attempt to replace established principles of business management.
Barry Boehm's work in “SoftwareEngineering Economics”. The Cone is a project management framework describing the uncertainty aspects of estimates (cost and schedule) and other project attributes (cost, schedule, and technical performance parameters). The notion of the Cone of Uncertainty has been around for awhile.
We're writing two chapters in an upcoming Project Management Book, with a working title, The Gower Handbook of Project Performance for Agile, Waterfall and Everything in Between , edited by Mark Phillips. One chapter on the Principles of RiskManagement and the second chapter on the Practices of RiskManagement.
It is wrong to suppose that if you can’t measure it, you can’t manage it – a costly myth. This community of program controls, cost analyst, earned value managers and program managers is accountable for providing information to decision makers on enterprise and complex projects and programs. Technical PerformanceMeasures.
There is always lots of complaining about the biases introduced into managing projects and making the estimates needed to make project decisions. Optimism bias - a cognitive bias that causes a person to believe that they are at a lesser risk of experiencing a negative event compared to others. These principles originate in: .
Risk interaction within systems and subsystems, between functional and physical elements, can also be modeled with DSM. DSM models interacting risks in a graphical representation produce numerical simulations of the risk and impacts on the probability of program success. Traditional risk models cannot model loops.
Let's say you're the project or program manager of a large complex system. We cannot escape these two uncertainties - reducible and irreducible - and must learn how to manage in the presence of these uncertainties. Is each of these measures being met for the planned cost at the planned time? . Abstracted from [3].
Risk interaction within systems and subsystems, between functional and physical elements, can also be modeled with DSM. DSM models interacting risks in a graphical representation produce numerical simulations of the risk and impacts on the probability of program success. Traditional risk models cannot model loops.
In a recent exchange in social media, it was clear the notion of risk and the sources of risk, the consequences or risks and managing in the presence of risk was in very unclear, when it was conjectured , we can simply slice the work into small bits and REDUCE risk. . SoftwareRiskManagement , Barry W.
We organize all of the trending information in your field so you don't have to. Join 100,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content