Below are summaries of the research studies presented at the Cost Engineering Committee (CEC) 2015.
Diagnosing Risks: Approaches to Cost and Schedule Risk Analysis
Managing project risk is a complicated practice. There are risks that are known, but unmanageable, like hurricanes. There are also the “unknown unknowns,” the black swans, such as geopolitical events that cannot be foreseen or mitigated. It is impossible to identify all project risks, let alone manage them. Nevertheless, we must endeavor to understand project risk and put measures in place to manage them.
This study identifies actual risks—risks that came to fruition—and demonstrates how these risks manifested into risks. Using IPA’s database of over 17,000 projects, IPA developed a probabilistic model that measures the likelihood that a particular risk will occur and its effect should it occur. The output of this model enables CEC users to calibrate their own risk modeling using actual risk probabilities and effects.
What Do the Best Change Management Processes Look Like?
At IBC 2015, IPA determined that project systems that employ a change management process as part of their estimate planning achieve better cost effectiveness (all things being equal) than companies that do not. This is useful at a high level, but leads to further questions: What is it about these processes that drive costs down and how are these processes employed? Using our historical company work process database as well as the results from a change management survey, we were able to dissect Industry’s change management processes to uncover the mechanics of a thorough change management system.
Accurate Estimates at FEL 2: Is it Luck or Is There a Better Way to Estimate?
IPA has observed that projects are developing more accurate estimates by the end of concept selection (Front-End Loading [FEL] 2). Many of these estimates are within ±15 percent of the project’s actual cost. The immediate question was: What has changed in estimate development that has enabled this shift in accuracy? Further, we wanted to know whether companies today are using better tools for their more early estimates. Do they have new estimate validation processes in place?
The answers to these questions were surprising. In general, many companies have begun to blur the lines between classes of estimates, using more detailed methods and, most importantly, detailed data on less defined scopes. As would be expected, the estimates were more predictable. The study digs deeper to learn more about these FEL 2 estimating practices.
Accurate Estimates for Indirect Costs
Estimating indirect costs is a challenge for Industry. Indirect costs span a host of accounts that are highly variable due, in part, to their opacity as well as the lack of accepted industry standards around their definition. Moreover, the link between indirect costs and direct costs is often convoluted. IPA has found that companies have difficulties estimating indirect costs in early estimates and even more trouble validating them, and these difficulties are only getting worse.
To help shed light on the estimating practices and the norms for addressing indirect costs, this study focused on the common components that comprise indirect costs. The study looked at estimating methodologies and their accuracy and found that more detailed data and methodologies yield better and more competitive estimates, which is not surprising. Given this finding, IPA prepared new metrics to help companies better quantify indirect costs.
Drivers of Construction Labor Productivity
Productivity is an outcome, not an input or driver of performance. Project cost, particularly major equipment, bulk materials, and construction labor wages, are not areas to realize capital efficiency gains. Instead, capital project efficiency opportunities can be in the level of hours required to complete the project; in other words, it is all about productivity. However, is it always fair to blame construction worker skill levels for poor productivity outcomes?
In this study, we presented our new focus on productivity and highlighted the many contributing factors that influence productivity. IPA has observed how project practices have a direct result on field labor productivity. Areas such as engineering quality, vendor information timeliness, construction supervision quality, and site management were all linked to a project’s productivity. In many cases, these areas were the main contributors to project outcomes. As such, construction labor should not be blamed for poor productivity in all instances. From this research, our path forward is to begin benchmarking individual company productivities to help identify where companies need to focus.