The venerable Cost Estimating and Assessment Guide (Cost Guide) has been updated for the first time since 2009! Published in March, the 2020 version of the Cost Guide has been significantly improved.
Some of the changes include:
Better alignment of best practices, cost estimate characteristics, and cost estimating steps
Clarification of some of the best practices and their related criteria
Additional content in technical appendixes and revision or deletion of others
Update case studies and references to USA government legislation and rules
Modernization of the Cost Guide’s format and graphics.
The Cost Guide defines the four characteristics of a good estimate: comprehensive, well documented, accurate, and credible. It also incorporates 18 best practices and shows how the best practices align to the four characteristics. Additionally, it introduces the 12 steps of the cost estimating process that produce reliable estimates, and shows how the best practices align with the 12 steps.
Earned Value Management (EVM) remains central to the Cost Guide’s approach to managing the delivery of a project once the estimate is approved.
Based on a successful day at the races, 5 winners and one place from 8 bets, this article looks at the balance between luck and process in achieving the result. Our conclusion is that you should not confuse luck with skill. Good processes will help build success, persistence will generate more opportunities for you to be lucky, and skill or capability will shift the odds in your favour, but randomness rules!
To quote Coleman Cox: I am a great believer in Luck. The harder I work, the more of it I seem to have.
Any output from a planning process is a consequence of the approach applied by the planner to develop their plan. Different people will develop different plans to achieve the same objectives based on their knowledge, experience and attitudes. This influence can be ignored or, if better understood, exploited!
Current mythology is that the Work Breakdown Structure (WBS) was developed as part of the PERT program within the US Navy in 1957/58. I’m not so sure…….. Similar types of chart were around for up to 100 year before the PERT program started:
Organization Charts were developed in 1854 but not too widely used (the example shown is from 1917).
Cost breakdown charts were in use from 1909 at least (if not sooner).
Process diagrams and flow charts were publicized by the Gilbreth’s in 1921.
What I’m looking for is evidence that this type of hierarchical chart focused on work to be accomplished was developed prior to 1957; or alternatively confirmation that the PERT team initiated the idea and the NASA/DoD/PERT-COST people standardized the idea.
This paper brings together a number of published articles and other research we’ve undertaken in the last decade or so to present a coherent view of the evolution of project scheduling in a format that can be used by other Academics. It is also aimed at correcting many of the commonly held misconceptions around this topic.
The concepts used for project schedule management have very deep roots; getting the right people in the right place at the right time to accomplish an objective has been a major organizational challenge for at least 3000 years! In ancient times this process seems to have been based on the scheme of arrangements being contained in the leader’s mind and instructions communicated verbally. Modern approaches to solving the twin challenges of first thinking through the ‘plan’ and then communicating the plan to the people who need to do ‘the right work, at the right time, in the right place’ use sophisticated graphics, charts, diagrams, and computations, but the problem and challenges are the same.
This paper traces the development of the concepts most project managers take for granted including bar charts and critical path schedules from their origins (which are far earlier than most people think) through to the modern day. The first section of the paper looks at the development of concepts that allow the visualization of time and other data. The second looks at the shift from static representations to dynamic modelling through the emergence of computers, dynamic calculations and integrated data from the 1950s to the present time.