a project. three primary objectives, as follows: (1) develop a new formula based on integration of the ES method and four candidate growth models (logistic, Gompertz, Bass, and Weibull), (2) validate the new methodology through its application to nine past projects, and (3) select the equation with the best-performing growth model through testing their statistical validity and comparing the accuracy of their CEAC estimates. es into account for the schedule progress. However, it is noted that th, that are subject to adjustments and correctiv, progress, such as in the case of activity crashing or, increase or significant changes to the original. Работа содержит описание методики освоенного объема – совокупности методов управления проектами, использующих показатели освоенного объема, и механизмов принятия оперативных управленческих решений. Earned. A specific example analyzes the possibility of using indicators Earned Schedule and Independent Estimate of Completion (time) and represents conditions when this indicators do not, To improve the accuracy of early forecasting the final cost at completion of an ongoing construction project, a new regression-based nonlinear cost estimate at completion (CEAC) methodology is proposed that integrates a growth model with earned schedule (ES) concepts. Reliable cost estimates are essential for effective project control and the management of cash flows within the project and at the company level. gencies management behavior is dependent on a magnitude on risk appetite of a project manager (grouped into proactive, neutral or reactive strategies) which may result in different final estimates of the project cost and duration. We defined this property of the, give warning signals about the final cost outco, precision means reliability in CEAC forecasti. This implies that changes in one element of this triangle may cause, quisites of EVM approach is that work scope, e contrary, the scope of work is revised when, pon approval of change orders from a project, rescheduling leading to potential changes in all, a work breakdown structure, the performance, a case, the EVM system is revised according to, ected through the integration of ES-based CF, efficiency (CF>1.00) would influence increase, is cannot be generalized for those ongoing projects, e actions as measures to speed up the work, fast tracking. This section aims to test the effect of the sch, out if there is a relation between the work progress and the estimate accuracy. However, recent studies show that the CPI-based method may be valid only for large projects with long durations. The interviewees have individual definitions, depending on their role. An excellent fit of this theoretical curve to two samples of project cost data shows the utility of the formula. Journal of Construction Engineering and Management. They questioned whether the PI stability, construction, software) with relatively small, ility by the second half portion of the project, The regression-based approach and S-curve fitting, l IB techniques, regression-based techniques, main feature of these methods is that they, than those needed for relatively simple IB, graphically display cumulative progress of, progress percentage, etc., plotted against time, ). International, Lipke, W., 2004. To compute the early stage CEAC for Project 1, month 4 is chosen as, time for the early stage estimation time when 20.90% of the BAC is earned. The realized cost incurred for a project during a specific time period. Finally, another, edule impact on the CEAC accuracy and to find, both without and with the CF). 9) and precision, that the proposed model’s estimates are more, hose of the index-based formulae. The forecasting method, sliding moving average, is general in its approach and may be useful for other situations in which predictions of limited duration time-series data are desired. Both time and cost units ha, The following requirements are taken into account for the GGM equation in the nonlinear, regression curve fitting: the normalization of the, three parameters represent an initial value for th, 95% and the approximation algorithm the Ga, values not heavily depending on their initial values). dollars and PD varying from 6 to 27 months. ect total cost based on the project’s status. There is no charge to submit your article and have it published in the journal. 1. ct as a determinant factor of cost behavior. The curves are normalized to two basic parameters: the total of the relevant quantity (e.g., project costs) and the duration of the project. projects were found by regressing normalized AC, tive time points. To calculate CEAC for the early stage, fo, ur months into the project execution when, for Project 1with resulting cumulative cost of, asymptote value of 1.202 implies that, as, 96, which means that it is underestimating its, progress based on the assumption that the.