Project Duration Forecasting Using Earned Duration Management with Exponential Smoothing Techniques

Khamooshi, Homayoun; Abdi, Abdollah

doi:10.1061/(asce)me.1943-5479.0000475

Cited by 47 publications

(35 citation statements)

References 36 publications

(46 reference statements)

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“…These studies show that, the same orders, which are characterized with for example the purpose of the object, have an impact on their delivery time. A different approach to production monitoring has been proposed in the study [24] in the EDM (Earned Duration Management) method. The role of this technique is to replace one of the tools of the EVM method, the schedule performance index (SPI) with its own EDI (Earned Duration Index) index in the form of an exponential function with a time argument.…”

Section: Figure 2 Graphic Interpretation Of Simple Parameters Of Thementioning

confidence: 99%

Monitoring of Time and Cost Variances of Schedule Using Simple Earned Value Method Indicators

Przywara¹,

Rak²

2020

Preprint

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The Planning and implementation of construction projects are difficult processes and are burdened with many risk elements. The budget spread over time, which is developed on the basis of the schedule, presents the expected distribution of costs throughout the duration of the works, which during the implementation of the project is subject to constant changes resulting from time, cost and organizational factors. Managing construction contracts requires managers to be able to analyze on an ongoing basis the variances of production costs - from the values calculated in the offer cost estimate and assumed in the Budgeted Cost of Work Scheduled. The article attempts to analyze the emerging time and cost deviations using proprietary T/S and T/C monitoring, based on simple indicators of the EVM method. An example of construction of a multi-family housing development was used to study the variances of planned and incurred costs.

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Section: Figure 2 Graphic Interpretation Of Simple Parameters Of Thementioning

confidence: 99%

Monitoring of Time and Cost Variances of Schedule Using Simple Earned Value Method Indicators

Przywara¹,

Rak²

2020

Preprint

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“…Numerous recent works show the viability of exponential smoothing for prediction purposes. In the project management area, [3] and [13] propose improvements to well-known Earned Value Management (EVM) project control methodology and Earned Duration Index (EDI) parameter by enhancing it with exponential smoothing to predict project progress and calculate project completion time and cost. In both cases, application of exponential smoothing was easy to incorporate to the traditional forecasting methodologies, raised their accuracy and reduced errors.…”

Section: Time Series Analysismentioning

confidence: 99%

Software Development Metrics Prediction Using Time Series Methods

Choraś

Kozik

Pawlicki

et al. 2019

Lecture Notes in Computer Science

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The software development process is an intricate task, with the growing complexity of software solutions and inflating code-line count being part of the reason for the fall of software code coherence and readability thus being one of the causes for software faults and it's declining quality. Debugging software during development is significantly less expensive than attempting damage control after the software's release. An automated quality-related analysis of developed code, which includes code analysis and correlation of development data like an ideal solution. In this paper the ability to predict software faults and software quality is scrutinized. Hereby we investigate four models that can be used to analyze time-based data series for prediction of trends observed in the software development process are investigated. Those models are Exponential Smoothing, the Holt-Winters Model, Autoregressive Integrated Moving Average (ARIMA) and Recurrent Neural Networks (RNN). Time-series analysis methods prove a good fit for software related data prediction. Such methods and tools can lend a helping hand for Product Owners in their daily decision-making process as related to e.g. assignment of tasks, time predictions, bugs predictions, time to release etc. Results of the research are presented.

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“…To overcome this issue, Earned Duration Management (EDM, Khamooshi and Golafshani (2014)) has been introduced as a completely time-based adaptation of EVM. Recently, several studies have used EDM rather than EVM as a basis for project time forecasting (Khamooshi and Abdi 2016;de Andrade et al 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Further, exponential smoothing, a time series forecasting technique that assigns greater weights to recent observations, has been applied for project time forecasting by Khamooshi and Abdi (2016) and Batselier and Vanhoucke (2017) to account for these effects.…”

Section: Introductionmentioning

confidence: 99%

Integrating Corrective Actions in Project Time Forecasting Using Exponential Smoothing

Martens

Vanhoucke

2020

J. Manage. Eng.

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Earned Value Management (EVM) and Earned Duration Management (EDM) are established methodologies to monitor the project performance during execution. These methods serve as a basis to forecast the final project duration and/or project cost. The aim of this paper is to improve the accuracy of project time forecasting by extending exponential smoothing for project time forecasting using EVM and EDM with the integration of corrective actions that are taken during project progress. In order to evaluate the forecasting accuracy of this approach, eight projects conducted in recent years have been followed up in real-time. Based on the nature of the observed corrective actions, six distinct categories of corrective actions are identified. The empirical experiment showed that explicitly integrating the occurrence of corrective actions into the forecasting process improves the forecasting accuracy of traditional forecasting methods and forecasting methods using standard exponential smoothing, especially for the middle and late phases of projects. Consequently, by including corrective actions in the forecasting process, project managers can predict the final project duration more accurately.

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Project Duration Forecasting Using Earned Duration Management with Exponential Smoothing Techniques

Cited by 47 publications

References 36 publications

Monitoring of Time and Cost Variances of Schedule Using Simple Earned Value Method Indicators

Monitoring of Time and Cost Variances of Schedule Using Simple Earned Value Method Indicators

Software Development Metrics Prediction Using Time Series Methods

Integrating Corrective Actions in Project Time Forecasting Using Exponential Smoothing

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