Reference class forecasting

Revision as of 22:10, 21 February 2021

Abstract

The definition of project success according to the standard published by the project management institute is meeting customers' expectations without exceeding the desired requirement such as cost, duration, and scope. ^[1] However, executing projects on time following a planned framework and budget is a challenging aspect of project management. Reference class forecasting is a method that studies the overall view of certain projects by forecasting similar projects rather than focusing solely on the considered project. This method allows a project manager to avoid errors by basing the forecast on similar projects. It also assists to take decisions under uncertainties through assessing the risk of the planned project. ^[1] In this article, the RCFM method developed by Kahneman and Tversky will be presented. That will be followed with clear guidance on how to use the method. Then its application and limitations.

Big Idea

Optimism bias is a term coined by Daniel Kahnemann means that people tend to see the world in a more positive light. Optimism bias is the foundation of the RCF method, the method states that human judgment is biased, as it tends to be more optimistic than realistic due to overconfidence which leads to underestimating cost, completion times, and risks of planned actions. Furthermore, humans also tend to overestimate the benefits of those same actions. Research made on a sample of 250 large projects executed over the last 7 decades shows that 90% of these projects exceeded the original budget and duration planes. According to re-searcher, almost all projects do not deliver the intended promises ^[2]. The potential causes of the poor performance for projects have been categorized into three areas: Technical, political and economic, and psychological. Bent Flyvbjerg has found that basing forecasts on similar projects to the one on hand gives an estimate free from psychological biases. ^[3]

One method that is being used in infrastructure projects is Reference Class forecasting. ^[4]

RCFM aims to reduce inaccuracy and bias, it takes a so called (outside view) on the project in hand. This view has to be basied on information taken from a class of similar projects. ^[5] RCFM is recommended by the American Planning Association which “encourages planners to use reference class forecasting in addition to traditional methods as a way to improve accuracy“. ^[5]

The RCF attempts to fit a certain event into a probability of distribution of comparable class reference. Furthermore, this method of enhancing decision-making in light of un-certainties has proved to be effective. It allows for adjustments to be made in the original cost-benefit analysis (CBA) so the plan includes margin errors. ^[6] "https://www.sciencedirect.com/science/article/pii/S1364032116301162/Managing the cost overrun risks of hydroelectric dams: An application of reference class forecasting techniques" </ref>

The reference class forecast provided an external point of view and act as an enabler of better planning based on historical data of projects that have similar attributes.  By doing so, the project managers can reduce bias that is caused due to assessing available information “inside views” and neglecting unknown unknowns or other considerations “outside views”.

Implementation

RCFM requires a large amount of work The RCFM consists of three steps approach. Then based on the degree of tolerance for the risk we decide what quantity of uplift would be needed to account for bias in cost and time estimates

• Identify a reference class that has similar attributes to the project on hand. There is no role of thumbs when choosing a reference class. However, the reference class can not be narrow to get a reliable result if the categories were too small. The reference class can not be too wide either. Furthermore, an analysis of the risk of overrun project cost and duration should be revealed.

• Determine a probability of distribution for the chosen reference classes. This requires trustful historical data from several projects within the reference class. The result of the probability distribution of the historical data will be used to estimate the level of uncertainty. From a statistical perspective, regression models are an essential tool in deriving the probability distribution

• Comparing the project on hand with the reference class distribution in order to determine the desired outcome such as budget and project duration

The RCF should be implemented prior to initiating the project to get a unique opportunity on reflecting on the budget before completion and planned duration.

Limitation

The RCF method is more useful in cases where errors are due to non-random events such as cognitive/human bias in decision making with uncertain future events’ RCF is not a new tool within the decision-making framework for large infrastructure investments. However, its application to energy projects is rare RCF does not assess the risk factors, it indicates the overall financial risk Asses the influence of various reference classes with respect to similarity levels Acquiring data The ability of th RCD method to provide an accurate information for decision making depends on the sample size of the reference classes and the relevance of the reference class.

Annotated Bibliography

References

1. ↑ ^{1.0 1.1} "https://app-knovel-com.proxy.findit.dtu.dk/web/toc.v/cid:kpGPMBKP02/viewerType:toc/root_slug:viewerType%3Atoc/url_slug:root_slug%3Aguide-project-management?kpromoter=federation/A Guide to the PROJECT MANAGEMENT BODY OF KNOWLEDGE"
2. ↑ "https://doi.org/10.1080/0144164032000080494a /What Causes Cost Overrun in Transport Infrastructure Projects?"
3. ↑ "https://www.apm.org.uk/news/de-risking-the-programme-portfolio-with-reference-class-forecasting//De-risking the programme portfolio with reference class forecasting"
4. ↑ "https://www.researchgate.net/publication/324337008_Implementation_of_the_Reference_Class_Forecasting_Method_for_Projects_Implemented_in_a_Chemical_Industry_Company/Implementation of the Reference Class Forecasting Method for Projects Implemented in a Chemical Industry Company"
5. ↑ ^{5.0 5.1} "http://documents1.worldbank.org/curated/en/968761468141298118/pdf/wps3781.pdf/Policy and Planning for Large Infrastructure Projects: Problems, Causes, Cures"
6. ↑ Cite error: Invalid <ref> tag; no text was provided for refs named sciencedirect_-hydroelectric