Learning curves: Accuracy in predicting future performance

Farghal, S H and Everett, J G (1997) Learning curves: Accuracy in predicting future performance. Journal of Construction Engineering and Management, 123(1), pp. 41-45. ISSN 0733-9364

Abstract

Many repetitive construction field operations exhibit a phenomenon known as the learning or experience effect. A learning curve is generated when the time or cost required to complete one cycle of an activity is plotted as a function of the cycle number. For practicing construction engineers and managers, the greatest potential value of learning curves lies in their ability to predict future performance, instead of fitting historical data. This paper presents a new method for using learning curves to predict the time or cost to complete the remaining cycles of an activity in progress, to assess the accuracy of this method, and to compare the accuracy of this method with the standard forecasting technique used in construction cost reporting. Using the proposed method, the accuracy of predicting the time or cost required to complete an ongoing activity improves dramatically for about the first 25-30% of the activity and then levels off to within 15-20% of the actual value. Compared to the standard method using the cumulative average, the new learning curve method is shown to be more accurate. The analysis quantifies the trade-off between accuracy of predicting future performance and the timeliness and potential value of such a prediction.

Item Type: Article
Index terms: manager, construction cost, engineer, forecasting, repetitive construction, accuracy
Subjects: building construction, prediction and forecasting, profession, financial and cost management, professional development, practitioner
Topics: Roles and Professions, Construction Technology, Research Practice, Cost Management, Information Management
Descriptive scope: 3 PCA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here