The Dynamic Progress Method

Using Advanced Simulation to Improve Project Planning and Management

J. Chris White, Robert M. Sholtes

• Publisher: CRC Press
• Year: 2016
• eBook ISBN: 9781498788090
• Topic: Business
• Subtopic: Operations
• Index: Business

Recent computer-based tools for project planning and management focus on user-friendliness and interconnectivity. However, these programs function on the Critical Path Method, or CPM, which was created in the 1950s. These programs, which involve simplistic models and methods, ignore the fact that the underlying computations on which they function h

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Introduction

There are some great project managers out there who are using the wrong tools.

J. Chris White

This book is written for project managers who have

• Been involved with large and complex projects (e.g., lasting many months or years, involving many resources, involving large budgets);
• Managed several projects that have been late, over budget, or both, even with the best intentions and best efforts of the project manager and the project team;
• Been given a start date and end date by upper management and told to make a project plan that fits in that timeline, no matter what;
• Established initial baseline project plans that became obsolete immediately after they were launched;
• Experienced frustration with current project planning and management tools that do not easily incorporate real-world variables;
• Had difficulty using the data within their project planning tools to defend and/or validate their assumptions and estimates; or
• Are looking for a better way to manage their projects and tell the story of how their project is progressing.

The motivation and rationale for the research and development work contained in this book can be summarized with the following:

• Problem: Despite good intentions, many large and complex projects are over budget, late, or a combination of both.
• Hypothesis: The planning tools used by project managers are based on simplistic methods and algorithms that inadvertently provide unrealistic estimates for costs and schedules, which can set up unachievable expectations and cause a domino effect of replanning and re-estimating and, ultimately, result in a project failure.
• Proposed solution: Harness the power of modern computers to more accurately and operationally simulate the allocation of resources to accomplish project work to provide more realistic, achievable, and defendable estimates for cost and schedule.

Background of Research

The work described in this book was developed through two Small Business Innovation Research (SBIR) contracts that were awarded to ViaSim Solutions by the Defense Advanced Research Project Agency (DARPA). The Phase I contract (W31P4Q-08-C-0044) was awarded in late 2007, and the Phase II contract was awarded in 2009 (W31P4Q-09-C-0169). The Phase II final report was submitted in early 2011. At the time of the publication of this book, pmBLOX^®, Inc., the company launched from this SBIR project, is seeking Phase III commercialization funding through an equity crowdfunding website.

(If the readers are unfamiliar with the SBIR program, please visit http://www.sbir.gov. The objective of the SBIR program, which is overseen by the Small Business Administration [SBA], is to help small businesses develop commercially viable products and services while also perhaps fulfilling a specific need at a government agency. ViaSim Solutions has participated in multiple SBIR projects and is extremely supportive of the program. The authors highly recommend that every small business check out the SBIR program to see if there are suitable opportunities.)

The original solicitation from DARPA (topic SB072-006) called for the “application and development of advanced mathematics for Department of Defense (DoD) applications (DARPA, FY2007.2 SBIR proposal submission, p. 10).” This cast a very wide net for the types of proposals that might be submitted to DARPA. Business partners at ViaSim Solutions (the authors of this book) had experience using advanced simulation techniques in several different domains. The authors chose to submit a proposal that applied some of these simulation techniques to large-scale projects (e.g., DoD projects). The research hypothesis was that many project performance issues, such as cost overruns and late schedules, are due to the fact that the currently available project planning tools employ an overly simplistic approach to estimating the cost and schedule for a project. This estimating approach provides unrealistic and sometimes unachievable baseline project plans. Although there are plenty of poor project managers out there, our belief was that well-intentioned, skilled project managers would still have project performance issues simply because of their choice in the software that is used for planning the project. Consequently, the authors hypothesized that the cost and schedule performance for projects could be improved through the use of a new and improved approach for project planning and estimating.

Through the SBIR Phase I and Phase II contracts, research confirmed this hypothesis about current approaches, and ViaSim Solutions developed a prototype simulation-based project planning tool, called pmBLOX, that eliminated many of the issues that are found in current tools. We have named the resource-based simulation approach used in pmBLOX as the Dynamic Progress Method (DPM), and it will be explained in later chapters.

Getting Good Projects for the Research

For the research for this effort, ViaSim Solutions solicited real-world projects from many different organizations. It was actually quite difficult to get a good set of example projects against which we could have consistent comparisons. There were several issues with some of the example project plans that were submitted. As a result, many plans were eliminated from consideration. However, because one of the goals of this book is to improve the readers’ overall ability to plan and manage projects, two of the major issues will be discussed in this section for educational purposes. Project planners and managers should avoid these two problems if they want to have legitimate, defendable project plans.

The first and most common issue for why an example project was removed from consideration was the exclusion of resources (e.g., labor, equipment, materials). In these example project plans, the only information provided for tasks was the durations. With no resources in the plans, it is difficult to gage the adequacy of the estimates. Should a particular task take 4 or 10 days? Who knows? There is no information on which to base the estimate. This is actually a very huge risk: building a plan with no formal consideration of resources at all. In this type of situation, how can the project manager have any confidence at all with regards to the estimate? And, if there is any doubt in his or her mind, what information does he or she have to compare, validate, or refute with?

The second issue for why an example project was removed from consideration was the exclusion of dependencies between and among tasks. For many of the example project plans received by ViaSim Solutions, the project plan simply consisted of a list of tasks with start dates and finish dates (with a stated duration between those dates). For these plans, it was impossible to know how to order or prioritize the tasks if resource constraints occurred. Just because one task ended on March 31, and another task started on April 1, it was impossible to know if there was a connection between these two tasks. Was the second task waiting for the first task to finish? Or, was there some other constraint that required the second task to start on April 1 (e.g., resources not available, waiting for material from a supplier)? In extreme cases, not only were there no dependencies among tasks in these example plans, but also most (if not all) of the tasks were expected to be worked in parallel. The plan was just a list of tasks. Of course, this is unrealistic with the application of resources. As soon as they are incorporated, the project schedule would slip significantly to the right (i.e., longer). In one particular example from the defense industry (which was not used in the final data set), one project was moved from 5 to 26 months, representing a 420% increase in schedule when the resources were incorporated.

Results of the DARPA SBIR Effort

After reviewing 40 real-world project plans submitted for the research on this effort, ViaSim Solutions created a data set of 16 projects that included those from the fields of construction, information technology, defense, and product distribution. The smallest project was 3 months long, and the largest project was 3.5 years long. All statistics shown in this research are weighted values so that larger projects have more influence on results than smaller projects. This data set was used to determine the current state of project management for the purposes of this research.

Note: Only 16 of 40 example plans were viable for the purpose of this study. This is a strong indication of the poor state of current project planning. The fact indicates that potentially more than half of the plans that are currently used in organizations have insufficient information even to be able to judge their reasonableness. The 16 projects analyzed for this research project at least had enough information to pass this level of evaluation.

Based on the issues cited in the “Getting Good Projects for the Research” section in this chapter, several criteria had to be met for these plans to be used as the initial research data set:

• The project plans must be in Microsoft Project^® (MPP format). To be consistent, a single tool had to be chosen...

Table of contents

• Cover
• Title Page
• Copyright Page
• Table of Contents
• Foreword
• Acknowledgments
• Overview Summary
• Authors
• Chapter 1 Introduction
• Chapter 2 Why “Dynamic Progress Method?”
• Chapter 3 The Current Status of Project Management
• Chapter 4 Critical Path Method and Earned Value Management
• Chapter 5 The New Approach of Dynamic Progress Method
• Chapter 6 Overview of the Dynamic Progress Method Simulation Model
• Chapter 7 Overview of pmBLOX
• Chapter 8 Advanced Capabilities of Dynamic Progress Method
• Index